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A package of business related risk measures : development and empirical study 1973

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c.l A PACKAGE OF BUSINESS RELATED RISK MEASURES: DEVELOPMENT AND EMPIRICAL STUDY ALFRED CHU KWONG B.Sc.B.A., U n i v e r s i t y of P h i l i p p i n e s , 1971 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS OF THE DEGREE OF MASTER OF BUSINESS ADMINISTRATION i n the Department of Commerce and Business A d m i n i s t r a t i o n We accept t h i s t h e s i s as conforming to -the r e q u i r e d standard THE UNIVERSITY OF BRITISH COLUMBIA A p r i l , 1973 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make i t freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the Head of my Department or by his representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of Commerce & Business A d m i n i s t r a t i o n The University of British Columbia Vancouver 8, Canada Date A p r i l 1973 i ABSTRACT Risk t a k i n g propensity i s defined as the w i l l i n g n e s s of an i n d i v i d u a l to take r i s k s . Although previous research has suggested t h a t t h i s construct i s m u l t i d i m e n s i o n a l , the primary purpose of t h i s t h e s i s i s to develop a package of measures r e l e v a n t to one dimension of r i s k t "business r i s k . The package inc l u d e s measures adopted and r e v i s e d from ones used p r e v i o u s l y and measures constructed f o r t h i s study. T h i r t y - f i v e Masters Students i n Business A d m i n i s t r a t i o n were administered the f o l l o w i n g package of measures i Choice Dilemma, Extremity Confidence i n Judgment, In-Basket, U t i l i t y Items,.Stock P r i c e Wagers, a Personal Record Questionnaire, and a p e r s o n a l i t y q u e s t i o n n a i r e concerning I n t e r n a l E x t e r n a l Con- t r o l and Sensation Seeking. The r e s u l t s of the study show th a t some of the i n t e r c o r r e - l a t i o n s among measures are i n s i g n i f i c a n t . Several f a c t o r ana- l y t i c a l methods were t r i e d but the e x t r a c t e d f a c t o r s were n e i t h e r i d e n t i f i a b l e nor expected. The study examined the r e l a t i o n s h i p between r i s k t a k i n g and some s e l e c t e d v a r i a b l e s l i k e S a l a r y , amount of a s s e t , amount of l i a b i l i t y , years of working e x p e r i - ence, and number of dependents. Choice Dilemma was found to be a f u n c t i o n of a g r e a t e r number of v a r i a b l e s , namely average age of the dependents, working years, s a l a r y , face value of insurance and l i a b i l i t i e s . Extremity confidence i n judgment i s r e l a t e d to number of working years and s a l a r y . The In-Basket Memo i i score i s r e l a t e d to IE C o n t r o l , average age of dependents, working years and s a l a r y . The t h e s i s has been able t o p i n p o i n t areas of weakness i n the items themselves and i n d i c a t e which measures should be subject t o r e v i s i o n or e l i m i n a t i o n . I t has a l s o been able to narrow down the d e f i n i t i o n of business r i s k t a k i n g . In t h i s regard, i t has provided i n s i g h t s i n t o what a f i n a l package of Bu s i n e s s - r e l a t e d r i s k measures should c o n t a i n . The study suggests more i n t e r e s t i n g areas to look at and serves as a p i v o t f o r f u t u r e research of t h i s k i n d . ACKNOWLEDGMENT The Author wishes t o express h i s thanks and g r a t i t u d e to the f o l l o w i n g i n d i v i d u a l s , without whose cooperation t h i s t h e s i s would not have been p o s s i b l e i - Prof. Kenneth R. MacCrimmon f o r p e r m i t t i n g me to work under h i s guidance, g i v i n g me the encouragement I needed, prac- t i c a l l y f i n a n c i n g my l a s t year of M.B.A. w i t h stipends and funds f o r the t h e s i s and p r o v i d i n g me w i t h h i s 596 c l a s s as su b j e c t s ; - Prof. Ronald Tay l o r , f o r h i s w i l l i n g n e s s to serve as a member of the t h e s i s committee, h i s numerous suggestions which brought me back to earth from the f i r s t t h e s i s p r o p o s a l , and h i s help i n convincing h i s c l a s s to p a r t i c i p a t e i n the study; - Prof. John F. B a s s l e r , f o r h e l p i n g me conduct the stock p r i c e wagers and f o r t e l l i n g me everything I wanted to know about U t i l i t y but was a f r a i d to ask; - Prof. C a r l Sarndal f o r h i s p a r t i c i p a t i o n as a member of the t h e s i s committee and h i s i n s i g h t f u l advice on s t a t i s t i c a l methodology; - Davida Morrow f o r her patience i n coding the responses of the s u b j e c t s ; - U.B.C. Committee on Human Subjects f o r approval of the va r i o u s instruments used; - Dr. W i l l i a m Stanbury, f o r p r o v i d i n g me w i t h the computer money I needed f o r running the programs; i v - Dr. J. W. C. Tomlinson f o r h i s generous help i n a l l o w i n g me to s o l i c i t v o l u n t e e r s from h i s c l a s s ; - S h i r l e y Freeman f o r t y p i n g the f i n a l d r a f t and deciphering my handwritings and - Hazel Ramsey f o r her help w i t h grammar, e d i t i n g , and understanding. V TABLE OF CONTENTS Page ABSTRACT i ACKNOWLEDGEMENT i i i 1 INTRODUCTION 1 Risk and Uncertainty 2 Components of Risk 6 Purpose of the Thesis 7 Organization of the Thesis 7 2 THE ECONOMIC BACKGROUND OF RISK TAKING PROPENSITY MEASUREMENT 9 I n t r o d u c t i o n 9 U t i l i t y Theory and the Measurement of Risk Taking 10 E m p i r i c a l Studies of U t i l i t y Curves 12 U t i l i t y i Problems and D i f f i c u l t i e s 17 Dis c u s s i o n 22 3 THE PSYCHOLOGICAL BACKGROUND OF RISK TAKING PROPENSITY MEASUREMENT 24 An Overview 24 Judgmental Measure 29 Dilemma of Choice Questionnaire 31 Actu a l B e t t i n g Instruments 32 Other P o s s i b i l i t i e s 33 Discussion 35 4 A PACKAGE OF RT INSTRUMENTS AND RELATED MEASURES 37 The Package 44 In-Basket E x e r c i s e 44 Choice Dilemma Items 47 Extremity Confidence i n Judgment 49 Event Occurrence and A c t i v i t y I n t e r e s t 49 Personal Records 50 U t i l i t y Type Questions 51 Stock P r i c e Wagers 52 Method of Scoring the Items 53 Discussion 56 v i TABLE OF CONTENTS (Continued) Page 5 THE DESIGN OF THE STUDY 58 Subjects Used 58 Procedure Used 58 I n s t r u c t i o n s to the Subjects 61 Conclusion 66 6 AN ANALYSIS OF THE MEASURES AND ITEMS IN THE PACKAGE 68 In-Basket 69 Choice Dilemma 82 U t i l i t y Items 89 Scale of Wager 98 Stock P r i c e Wagers 103 Extremity Confidence i n Judgment 110 Event Occurrence and A c t i v i t y I n t e r e s t 120 D i s c u s s i o n 126 7 OVERALL ANALYSIS OF RISK MEASURES 128 Overview 128 C o r r e l a t i o n Matrix of Risk Measures 128 Factor A n a l y s i s 132 Risk Taking as a Function of other V a r i a b l e s 140 Discussion 146 8 CONCLUSIONS 148 Recommendation f o r Future Research 150 BIBLIOGRAPHY 153 APPENDIX A - LIST OF RAW DATA 162 APPENDIX B - EXAMPLE OF A SUBJECT PRINTOUT 175 v i i LIST OF TABLES Table Number Page I Memo Scores by Item, Frequency and Median 75 I I C o r r e l a t i o n M a t r i x , Memo Scores by Item 77 I I I C o r r e l a t i o n M a t r i x , Minimum Odds by Item 77 IV C o r r e l a t i o n M a t r i x , Semantic D i f f e r e n t i a l Scores 78 V Choice Dilemma Item I n t e r c o r r e l a t i o n s 86 VI Mode Rank, Mean Odd, Median Ranks by Item 88 V I I C o r r e l a t i o n Matrix, Compensation U t i l i t y Deviations and Scores 93 V I I I C o r r e l a t i o n M a t r i x , Rate of Return U t i l i t y Scores 93 IX C o r r e l a t i o n M a t r i x , Net P r o f i t U t i l i t y Scores 93 X C o r r e l a t i o n s of U t i l i t y Items 97 XI Buying P r i c e s , Item 4, Frequency D i s t r i b u t i o n 101 X I I Buying P r i c e s , Item 5, Frequency D i s t r i b u t i o n 101 X I I I C o r r e l a t i o n M a t r i x , Scale of Wager Premiums 102 XIV O v e r a l l Set Rankings D i s t r i b u t i o n 105 XV Set D, D i s t r i b u t i o n of Ranks 106 XVI Set C, D i s t r i b u t i o n of Ranks 106 XVII C o r r e l a t i o n M a t r i x , Stock P r i c e Wager Scores 107 XVIII Confidence Score, Item 13, Frequency D i s t r i b u t i o n 115 XIX Confidence Score, Item 6, Frequency D i s t r i b u t i o n 116 v i i i Table Number XX XXI XXII XXIII XXIV XXV XXVI XXVII XXVIII XXIX LIST OF TABLES (Continued) C o r r e l a t i o n M a t r i x , Extremity Scores C o r r e l a t i o n M a t r i x , Confidence Scores IE Scale w i t h C o r r e l a t i o n s of Each Item w i t h T o t a l Score SS Scale w i t h C o r r e l a t i o n s of Each Item w i t h T o t a l Score Spearman Rho's of Risk Measures Oblique Rotated Factor Matrices Using Pearson's as Input Orthogonal Factor Matrix and Trans- formation Matrix (Pearson) Oblique Factor M a t r i c e s , Using Spearman's as Input Orthogonal Factor Matrices Using Spearman's P a r t i a l C o r r e l a t i o n s of Risk Measures w i t h Selected V a r i a b l e s Page 117 118 125 125 130 133 135 138 139 145 I X LIST OF FIGURES Figure Number Page 2 - 1 Example of a U t i l i t y Curve 20 4 - 1 Risk Taking Model i n Decision Making Context 40 6 - 1 Aggregate Memo Scores, Histogram 71 6 - 2 Minimum Odds Scores, Histogram 7 2 6 - 3 S.D. Scores, Histogram 7 3 6 - 4 Average Grade Assigned to the Items, Histogram 7 4 6 - 5 Choice Dilemma Odds Score, Histogram 82 6 - 6 Choice Dilemma Rank, Item 3 , Histogram 84 6 - 7 Choice Dilemma Odd, Item 3 , Histogram 84 6-8 Compensation U t i l i t y Scores, Histogram 8 9 6 - 9 Net P r o f i t U t i l i t y Scores, Histogram 90 6-10 Rate of Return U t i l i t y Scores, Histogram 9 0 6 - 1 1 One Subject's Three U t i l i t y Curves 9 5 - 9 6 6-12 Scale of Wager Scores, Histogram 9 9 6 - 1 3 Number of No Responses, Histogram 100 6-14 Stock P r i c e Wager Scores, Histogram 104 6 - 1 5 Extremity Scores, Histogram 1 1 1 6-16 Confidence Scores, Histogram 112 6 - 1 7 Chance Assignment D i s t r i b u t i o n , Item 1 3 , Histogram 1 1 3 6-18 Extremity Scores, Item 1 3 » Histogram 114 6-19 Chance Assignments, Item 6 , Histogram 1 1 5 6-20 I n t e r n a l C o n t r o l Scores, Histogram 120 LIST OF FIGURES (Continued) Figure Number Page 6-21 Sensation Seeking Scores, Histogram 121 6-22 Responses f o r Each Item, Histogram 122 6-23 SSS Responses f o r Each Item, Histogram 123 To Rolando San Luis Perez My F r a t e r n i t y Brother Who Died f o r Peace, Brotherhood and the U p s i l o n Sigma Phi CHAPTER 1 INTRODUCTION I f you can make a heap of a l l your winnings And r i s k i t on one t u r n of p i t c h and toss and l o s e and s t a r t again at your "beginnings and never breathe a word about your l o s s . . . Rudyard K i p l i n g , IF Although we may not agree fundamentally w i t h K i p l i n g ' s d e f i n i t i o n of a man i n h i s poem IF, we can be q u i t e sure t h a t he's t a l k i n g about a s p e c i a l k i n d of man—the r i s k - t a k e r — a much admired prototype t h a t has been perceived to be endowed w i t h a l l the proper s u p e r l a t i v e s of m a s c u l i n i t y — t h e best of courage, dar i n g and st r e n g t h of charac t e r . Yet, r i s k - t a k i n g i s not r e a l l y a phenomenon—or a t a l e n t common only to h i s t o r i c a l f i g u r e s who have performed mighty deeds. Any a c t i v i t y having an u n c e r t a i n outcome i n v o l v e s an element of r i s k . Who i s to say tha t a man c r o s s i n g the s t r e e t or accepting a b l i n d date i s not t a k i n g any r i s k s ? The funda- mental d i f f e r e n c e i s , of course, i n terms of degree. K i p l i n g ' s man i s d e f i n i t e l y a great r i s k - t a k e r , w h i l e the ordin a r y man attempting to win at chess may be l e s s of a r i s k - t a k e r . A t h e i s t s , according to the C a t h o l i c dogmatists, are t a k i n g the g r e a t e s t r i s k s — t h e chance of e t e r n a l damnation. Decisions i n the r e a l world i n v o l v e u n c e r t a i n t y . In f a c t , the d e f i n i t i o n of d e c i s i o n , according to Shackle (1961), imposes a c o n d i t i o n of "bounded u n c e r t a i n t y . " "To have p e r f e c t f o r e s i g h t 2 i s to render a l l d e c i s i o n s empty" (Shackle, 1961). The n o t i o n of bounded u n c e r t a i n t y may be deduced from Shackle's quote, "Decision i s choice but not choice i n face of p e r f e c t f o r e - knowledge, nor choice i n face of complete ignorance." This d e f i n i t i o n we have to accept as we must accept Shackle's i d e a that "the u l t i m a t e nature of the cosmos i s not one whose h i s - t o r y i s p r e d e s t i n a t e ^ o r one "behaving i n every d e t a i l i n a manner s e t t l e d and determined from the s t a r t . " ( I t a l s o means the Maker makes empty d e c i s i o n s w h i l e we mortals do not because we are not k n o w - i t - a l l — a s an aside to Shackle.) "Chance i s but an expression of man's ignoranqe," Laplace once declared. Not being p e r f e c t ( n e i t h e r p e r f e c t l y ignorant nor p e r f e c t l y knowledgeable), man i s condemned to face r i s k s — though he t r i e s , w i t h some amount of e f f o r t , to c o n t a i n un- c e r t a i n t y by i n c r e a s i n g h i s s t o r e of knowledge or reduce h i s environment i n t o something t h a t he could c o n t r o l . A f t e r a l l , prophets are so r a r e . But then, what i s r i s k ? And what i s u n c e r t a i n t y ? When are the two terms s i m i l a r and where l i e s the d i f f e r e n c e of the two? Without going i n t o the semantics (and the v a r i o u s images tha t s p r i n g up by mentioning the terms), we have the f o l l o w i n g d e f i n i t i o n s and explanations from Science. Risk and Uncertainty t Doubt and u n c e r t a i n t y seem to be synonymous i n most p h i l o - s o p h i c a l essays. Jeremy Bentham (Keynes 1921) once suggested 3 t h a t witnesses should i n d i c a t e t h e i r s t a t e of mind on a s c a l e of c e r t a i n t y , something l i k e Gibbon's T h e o l o g i c a l Barometer of doubt (Cohen i960). In K i p l i n g ' s l i n e s , " r i s k " i s " i n one t u r n of p i t c h and t o s s , " suggesting the ' u n c e r t a i n t y ' inherent i n gambling. Hertz (1964) and Grayson (i960) i m p l i c i t l y place the two terms as s u b s t i t u t e s f o r one another. Uncertainty i s d e f i n e d as the s t a t e of mind t h a t e x i s t s when more than one outcome i s judged p o s s i b l e on the b a s i s of e x i s t i n g i n f o r m a t i o n when an i n d i v i d u a l i s c o n s i d e r i n g the out- come of a given a c t . The o r i g i n of u n c e r t a i n t y i s u n p r e d i c t a - b i l i t y . In the case of an investment d e c i s i o n , u n c e r t a i n t y e x i s t s when an attempt i s being made to p r e d i c t the outcomes of accepting or r e j e c t i n g a given proposal. Risk i s defined as "the chanee of . . . l o s s " i n The Con- c i s e Oxford D i c t i o n a r y . The l o s s i s p o s s i b l y an opportunity l o s s , d e f i n e d by S c h l a i f f e r (1959) as "the d i f f e r e n c e between the cost or p r o f i t a c t u a l l y r e a l i z e d under that d e c i s i o n and the cost or p r o f i t which would have been r e a l i z e d i f the d e c i - s i o n had been the best one p o s s i b l e f o r the event which a c t u a l l y occurred." In investment d e c i s i o n s , t h i s connotation recognizes t h a t a l o s s may be i n c u r r e d by e i t h e r r e j e c t i n g or accepting an investment p r o p o s a l — t w o r i s k s being i n c u r r e d t t h a t the pro- j e c t may not r e a l i z e the minimum r e t u r n r e q u i r e d by the f i r m and t h a t i f the r e t u r n i s l e s s than was p r o j e c t e d t h e , d e c i s i o n may not be optimal i n t h a t other a l t e r n a t i v e s or proposals would have gr e a t e r b e n e f i t i n a c t u a l f a c t . 4 Another d e f i n i t i o n of r i s k runs as follows» take the framework of a c e r t a i n t y continuum th a t extends from a "believed absolute c e r t a i n t y of the fu t u r e outcome of a present d e c i s i o n or act where the p r o b a b i l i t y d i s t r i b u t i o n c o l l a p s e s i n t o one s i n g l e outcome wi t h a p r o b a b i l i t y of u n i t y to the other extreme of complete u n c e r t a i n t y as to both outcomes and to the proba- b i l i t i e s of these outcomes. In the case of complete u n c e r t a i n t y , i t i s p o s s i b l e t h a t d e c i s i o n theory might d i c t a t e the use of the p r i n c i p l e of i n s u f f i c i e n t reason (equi-probable s t a t e s of na- t u r e ) (Savage* 1954, 4.9) but i t i s a l s o p o s s i b l e that we per- mit s u f f i c i e n t knowledge to come up w i t h ex-ante s u b j e c t i v e p r o b a b i l i t i e s . Between the two extremes of complete c e r t a i n t y and complete ignorance l i e s the area i n which we have some b a s i s f o r b e l i e f i n some f i n i t e range of m u l t i p l e mutually e x c l u s i v e p o s s i b l e outcomes w i t h some p r o b a b i l i t y d i s t r i b u t i o n over i t . This i s the case of r i s k (Knight, 1921), which could be termed the case of s i g n i f i c a n t knowledge or b e l i e f . The Knight d i s t i n c t i o n i s that r i s k i s "measurable uncer- t a i n t y " which may be represented by numerical p r o b a b i l i t i e s and t h a t u n c e r t a i n t y i s "unmeasurable u n c e r t a i n t y , where the decision-maker i s ignorant of the s t a t i s t i c a l frequencies of events r e l e v a n t t o h i s d e c i s i o n , " or where "a p r i o r i c a l c u l a - t i o n s are imp o s s i b l e , or when an important, once and f o r a l l d e c i s i o n i s concerned" _ (Knight., 1921). However, some econo- mists have come to question the usefulness of such a d i s t i n c - t i o n . Arrow (1951) s a i d , "In b r i e f , Knight's u n c e r t a i n t i e s 5 seem to have s u r p r i s i n g l y manyof the p r o p e r t i e s of o r d i n a r y p r o b a b i l i t i e s , and i t i s not c l e a r as to how much i s gained by the d i s t i n c t i o n . ...... A c t u a l l y , h i s u n c e r t a i n t i e s produce about.the same r e a c t i o n s i n i n d i v i d u a l s as other w r i t e r s a s c r i b e t o r i s k s . " Shackle (1955) concluded that i n the r e a l w o r l d , most d e c i - sions were i n s i t u a t i o n s of u n c e r t a i n t y . But, he not only r e - j e c t e d numerical p r o b a b i l i t i e s f o r r e p r e s e n t i n g the u n c e r t a i n t y i n s i t u a t i o n s but maintained th a t i n s i t u a t i o n s where a l l poten- t i a l outcomes seemed p e r f e c t l y p o s s i b l e , i t was impossible to d i s t i n g u i s h meaningfully between the r e l a t i v e l i k e l i h o o d s of these outcomes. This was forwarded as the n o t i o n of " p o t e n t i a l s u r p r i s e . " This n o t i o n seems questionable, however, when i t i s i n t e r p r e t e d to mean t h a t people would be i n d i f f e r e n t between t o s s i n g a c o i n and drawing a p a r t i c u l a r k i n d from a deck of cards I In h i s i n t r o d u c t i o n t o the IEA Conference on Risk and U n c e r t a i n t y , Borch ( I 9 6 8 ) s a i d t h a t the Knight d i s t i n c t i o n "no longer serves any u s e f u l purpose." Ramsey ( 1 9 2 6 ) i m p l i e d t h a t f o r a " r a t i o n a l " man a l l u n c e r t a i n t i e s can be reduced to r i s k s . (We s h a l l not go any f u r t h e r i n t o what i s meant by "rational".) In t h i s t h e s i s , r i s k i s t r e a t e d as a s i t u a t i o n where •ambi- g u i t y * does not e x i s t and where a p r o b a b i l i t y d i s t r i b u t i o n — whether o b j e c t i v e , s u b j e c t i v e , or n e c e s s a r y — I s provided ( f o r the d e f i n i t i o n s of these terms, please see Savage 1 9 5 4 ) . 6 Components of Risk Risk i s composed of the f o l l o w i n g elements : 1. Outcomes - existence of at l e a s t two mutually e x c l u s i v e outcomes a r i s i n g from an act and from events outside the a c t . 2. Actions - existence of at l e a s t two independent courses of a c t i o n , at l e a s t one of which must be u n c e r t a i n as t o outcome. 3. Meaningfulness - existence of values t h a t the d e c i s i o n maker attaches to the consequences of the outcomes. Also the amount of r i s k i n v o l v e d depends upon the d e c i s i o n m a k e r * s _ p e r c e p t i o n — i . e . , he must be able to r e a l i z e t h a t some- t h i n g of value to him i s at stake i n the d e c i s i o n process. In a d d i t i o n , degrees of b e l i e f may vary among decision-makers. Thus, faced w i t h the same s i t u a t i o n , i t i s p o s s i b l e t h a t two decision-makers perceive d i f f e r e n t l e v e l s of r i s k . Because of t h i s d i f f e r e n t i a l p e r c e p t i o n , r i s k i s r e a l l y s u b j e c t i v e — i . e . , r i s k to one i n d i v i d u a l may not be r i s k to another. In order to examine r i s k - t a k i n g among i n d i v i d u a l s , the s i t u a t i o n s i n which d e c i s i o n s by these i n d i v i d u a l s are t o be made should be perceived s i m i l a r l y by these p e r s o n s — i . e . , the value at stake and t h e i r degrees of b e l i e f must be s i m i l a r ( i . e . , p r o v i s i o n of o b j e c t i v e p r o b a b i l i t i e s ) , and other v a r i a b l e s must a l s o be m i t i g a t e d i n t h e i r e f f e c t s . 7 Purpose of the Thesis The primary o b j e c t i v e of the t h e s i s i s to develop a package of r i s k - t a k i n g propensity measures whose main emphasis i s on •business-economic r i s k - t a k i n g and monetary r i s k t a k i n g . The development w i l l i n v o l v e a review of some of the more well-known measures t h a t e x i s t f o r assessing r i s k t a k i n g a t t i t u d e s , subse- quent refinements or m o d i f i c a t i o n s of past measures th a t have been found t o be appropriate f o r our purpose, and o r i g i n a l con- s t r u c t i o n of measures. The package of measures w i l l be given t o volunteers from the graduate programme of the U.B.C. Fac u l t y of Commerce. A s t a t i s t i c a l a n a l y s i s of t h e i r responses w i l l be presented i n the t h e s i s , The r a t i o n a l e behind the package of measures w i l l be discussed i n the c o n c l u s i o n of t h i s t h e s i s . Organization of the t h e s i s The study i s d i v i d e d i n t o e i g h t chapters. Chapter 1 i s an i n t r o d u c t o r y chapter concerning the d e f i n i t i o n of r i s k and u n c e r t a i n t y and the components of r i s k . Chapter 2 deals w i t h the economic foundation of r i s k - t a k i n g researches w i t h a b r i e f background on some aspects of the t h e o r i e s of r i s k bearing and a study of the use of u t i l i t y f u n c t i o n s . Chapter 3 presents the p s y c h o l o g i c a l background of the r i s k - t a k i n g measures deve- loped or adopted by t h i s t h e s i s . Chapter 4 provides a b r i e f d e s c r i p t i o n of the package developed i n t h i s study and the va r i o u s a l t e r n a t i v e s considered i n the process. Chapter 5 deals w i t h the design f o r us i n g the package on our s e l e c t e d group. 8 Chapter 6 presents the analyses of the measures and the items co n t a i n e d . i n the package. Chapter ? discusses the o v e r a l l a n a l y s i s of the measures, t h e i r c o r r e l a t i o n s w i t h one another and the f a c t o r analyses of these measures. Chapter 8 contains a summary and c o n c l u s i o n of the study. 9 CHAPTER 2 THE ECONOMIC BACKGROUND OF RISK TAKING PROPENSITY MEASUREMENT Int r o d u c t i o n Theories, both d e s c r i p t i v e and p r e s c r i p t i v e , have "been formulated by economists to e x p l a i n and d i c t a t e behavior under u n c e r t a i n t y . Decision-making models have been proposed and claimed to be p r e d i c t i v e l y adequate and normatively s u p e r i o r . The assumption that i n d i v i d u a l s act w i t h s u b j e c t i v e cer- t a i n t y has long ceased to e x p l a i n the existence of c e r t a i n observed phenomena, l i k e insurance (Arrow, p. 11, 1965). For a w h i l e , economists i m p l i e d that i n d i v i d u a l s maximized expected value (mathematical expectation) among choices. D. B e r n o u l l i , i n I738, i n h i s r e s o l u t i o n of the St..Petersburg paradox, s a i d the contrary ( B e r n o u l l i 1954). The problem was equivalent to the f o l l o w i n g 1 John tosses a c o i n i n the a i r repeatedly u n t i l i t f a l l s head up. I f t h i s occurs on the f i r s t throw, he pays Paul $1.00; i f t h i s occurs f i r s t on the second throw, he pays Paul $2.00; on the t h i r d throw, $4.00; on the f o u r t h throw, $8.00 and on the nth throw, $ 2 . 0 0 n - l . What i s the maximum amount that Paul should pay f o r t h i s game? It s p a r a d o x i c a l nature i s e a s i l y explained 1 The p r o b a b i l i t y of a head on the f i r s t throw i s 1/2, so the expected winning from the f i r s t throw i s 1/2 times $1.00 or $0.50. The proba- b i l i t y of a f i r s t head on the second throw i s 1/4 (1/2 of t a i l s on the f i r s t throw times 1/2 of heads on the second) so the expected winning i s 1/4 times $2.00 or $0.50. The p r o b a b i l i t y 10 of a f i r s t head on the nth throw i s ( 1 /2) n so the expected winnings are ( 1 /2) n times $ 2 . 0 0 n _ 1 , or $0.50. Since these p r o b a b i l i t i e s are mutually e x c l u s i v e , we add them to o b t a i n the expected winnings from the game, which are $0.50 times the i n - f i n i t e p o s s i b l e number of throws. The expected winnings of Paul are i n f i n i t e . But i t would seem in c o n c e i v a b l e that anyone would pay an i n f i n i t e amount f o r the s a i d game. In B e r n o u l l i ' s s o l u t i o n , the d i m i n i s h i n g marginal u t i l i t y of money was taken i n t o account. A d i s t i n c t i o n was made between mathematical ex- p e c t a t i o n and "moral e x p e c t a t i o n " — " m o r a l e x p e c t a t i o n " defined as the sum of the products of the v a r i o u s advantages a c c r u i n g from v a r i o u s sums of money times t h e i r r e s p e c t i v e p r o b a b i l i t i e s . Here was the expected u t i l i t y hypothesis s t a t e d i n a d i f f e r e n t way. In Von Neumann and Morgenstern's terms (1953)» MD» Ber- n o u l l i ' s well-known suggestion to 'solve' the St. Petersburg Paradox by the use of the s o - c a l l e d 'moral expectation* means d e f i n i n g the u t i l i t y n u m e r i c a l l y or the l o g a r i t h m of one's monetary possessions." K a r l Menger (193*0 s a i d that i t r e q u i r e d the boundedness of the u t i l i t y f u n c t i o n , not the mere presence of r i s k a v e r s i o n , t o re s o l v e the paradox. Savage (195*0 l a t e r completed the demonstration of the expected u t i l i t y theorem. U t i l i t y Theory and the Measurement of Risk Taking According t o F i s h e r (1918), the term " u t i l i t y " i s a h e r i t a g e of Bentham and h i s p r i n c i p l e of morals and l e g i s l a t i o n . The concept of u t i l i t y i n economics may be tr a c e d even to Adam Smith i n h i s quote "Value i n use cannot be measured by any known stan- dard; i t i s d i f f e r e n t l y estimated by d i f f e r e n t persons" ( S t i g l e r , 11 1950). This i d e a of u t i l i t y , considered as a q u a n t i t a t i v e expression of the amount of s a t i s f a c t i o n derived from consump- t i o n , i s thus a very b a s i c n o t i o n i n economics. Pareto, Jevons, and Marshall had incorporated u t i l i t y i n t h e i r work ( S t i g l e r , 1950). The i d e a that the curvature of a u t i l i t y f u n c t i o n r e f l e c t s i t s owner's a t t i t u d e towards r i s k arose out of Von Neumann and Morgenstern*s monumental work, The Theory of Games and Economic Behavior (1953). In i t , axioms r e l a t i n g to u t i l i t y curves were discussed; a l s o , Von Neumann and Morgenstern s t a t e d t h a t the u t i l i t y s c a l e , which must be c o n s i s t e n t , d i d not have any n a t u r a l o r i g i n . Priedmann and Savage (19^8) followed up on Von Neumann and Morgenstern w i t h t h e i r hypothesis of a consumer u n i t behaving as i f i t maximizes u t i l i t y . From the observation t h a t people both buy insurance and l o t t e r y t i c k e t s ( l o t t e r i e s having mul- t i p l e p r i z e s ) they derived a double i n f l e c t e d u t i l i t y f u n c t i o n , convex f o r low wealth l e v e l s , concave f o r intermediate l e v e l s and convex f o r higher values of wealth. Concavity of the u t i l i t y f u n c t i o n over an i n t e r v a l i m p l i e s r i s k a v e r s i o n of the d e c i s i o n - m a k e r — i . e . , he would not pay as much as the l o t t e r y ' s expected monetary value f o r the t i c k e t . Markowitz l a t e r (1952 b) sug- gested t h a t another concave segment be added t o the l e f t end of the u t i l i t y f u n c t i o n . M o s t e l l e r and Nogee (1951) t e s t e d the d e s c r i p t i v e v a l i d i t y of the expected u t i l i t y theorem i n experimental s e t t i n g s , and concluded that expected u t i l i t y theory i s not d e s c r i p t i v e ( i . e . , 12 people do not behave as i f they maximize u t i l i t y ) . P r a t t (1964) and Arrow (1965) independently formulated the most s p e c i f i c d e f i n i t i o n to date of r i s k a t t i t u d e i n terms of the shape of the u t i l i t y f u n c t i o n . They defined r a ( x ) = u " (x)/u'cx) as absolute r i s k a v e r s i o n and r r ( x ) = xu (x)/u'<5x) as r e l a t i v e r i s k a v e r s i o n — b o t h measures are l o c a l i n t h a t they may vary as x (income, wealth, etc.) v a r i e s . E m p i r i c a l Studies of U t i l i t y Curves Grayson's (i960) Decisions Under Uncertainty i s perhaps one of the e a r l i e r a p p l i c a t i o n s of u t i l i t y theory t o s i t u a t i o n s of u n c e r t a i n t y . Based on Von Neumann and Morgenstern, he devised a method of d e r i v i n g u t i l i t y curves. O i l and gas operators, as w e l l as members of t h e i r o r g a n i z a t i o n , were given a s e r i e s of h y p o t h e t i c a l ventures. The subjects were asked to e i t h e r accept or r e j e c t a venture on the b a s i s of i n f o r m a t i o n concerning the investment, i t s pay-offs and i t s p r o b a b i l i t y of success. A t a b l e of i n d i f f e r e n c e p r o b a b i l i t i e s was derived f o r each i n d i - v i d u a l . By s e t t i n g zero $ amount as zero i n u t i l i t y and -$10,000 as -1.00 i n u t i l i t y , he constructed u t i l i t y curves f o r h i s sub- j e c t s . From the shape and slope of these curves, he deduced the r i s k preferences of the i n d i v i d u a l s . Some d i f f i c u l t i e s were encountered w i t h the experiment. One was the p r o b a b i l i t i e s i n v o l v e d . Some operators (Grayson, i960, pp. 313-314) d i d not always t h i n k of p r o b a b i l i t i e s as being o b j e c t i v e . Thus, there was the danger of i n t r o d u c i n g a s u b j e c t i v e "correction'* ( s i m i l a r to what F e l l n e r (1961) has 13 observed as the s l a n t i n g tendency) i n t o the p r o b a b i l i t i e s . However, when the p r o b a b i l i t i e s used i n the experiment dropped i n t o ranges w i t h which the operators had experience, these odds were c r e d i b l e and found to be s a t i s f a c t o r y . Thus, the curves can only be s a i d to be very c l o s e Happroximations' 1 of t r u e u t i l i t y f u n c t i o n s . However, Grayson b e l i e v e d that the subjec- t i v e p r o b a b i l i t y element was sma l l and w h i l e t h i s d i d not f i t w e l l w i t h the d e s c r i p t i v e p a r t of u t i l i t y theory, i t s t i l l can be very u s e f u l , i n a normative sense, as a guide t o a c t i o n . His suggestion was t o t r y to remove any p o s s i b i l i t y of i n t r o - ducing s u b j e c t i v e p r o b a b i l i t i e s by i (1) h o l d i n g p r o b a b i l i t i e s constant (say at 50-50) and (2) a l l o w i n g the pay-offs to f l u c - t u a t e . The experiment has i n d i c a t e d t h a t more time should be spent w i t h the subjects i n e x p l a i n i n g the use of o b j e c t i v e pro- b a b i l i t i e s and moreover, the pay-offs should be constructed so that they were i n the realm of experience of the s u b j e c t s . Swalm (1966) conducted another u t i l i t y study. He defined u t i l i t y as "a measurable preference among va r i o u s choices a v a i l a b l e i n r i s k s i t u a t i o n s . " R e l a t i v e u t i l i t i e s were measur- able w h i l e absolute u t i l i t i e s were not. Following the p r o p o s i - t i o n t h a t i f a person was i n d i f f e r e n t between two a l t e r n a t i v e s , the expected u t i l i t y of the a l t e r n a t i v e was the same, he set up a s e r i e s of questions, each o f f e r i n g two a l t e r n a t i v e s — o n e cer- t a i n and one u n c e r t a i n (with 50-50 odds f o r the two outcomes). His research approach was as f o l l o w s 1 he introduced u t i l i t y theory to the businessmen (one to two hours per man) and v a r i e d the c o n s t r u c t i o n of the questions based on the experience of 14 the person i n v o l v e d . Because of the p o s s i b l e confounding of u t i l i t y and s u b j e c t i v e p r o b a b i l i t i e s , r i s k was l i m i t e d to 50-50 s i n c e they understood t h i s to be a f l i p of a c o i n . The maximum s i n g l e amount tha t the subject might recommend be spent i n any one year was used as a ba s i s f o r s e t t i n g what Swalm c a l l e d the "planning h o r i z o n , " which was twice t h i s amount. He b e l i e v e d t h a t u t i l i t y was a f u n c t i o n of the corporate planning h o r i z o n . Thus the s e r i e s of questions that ensued i n the i n t e r v i e w was based on t h i s "planning h o r i z o n . " The method of g e t t i n g p o i n t s on the u t i l i t y curve was as follows i Suppose a person s a i d h i s "maximum amount" (mentioned above) was $20,000. $40,000 would be h i s planning h o r i z o n . The u t i l i t y of 0 d o l l a r s would be set at zero and the u t i l i t y of the planning h o r i z o n set at 1. The f i r s t question asked would be something l i k e this» "Suppose you are faced w i t h two a l t e r n a - t i v e s . One i s to go i n t o an investment where there i s a 50-50 chance at g e t t i n g $40,000 (net present value of p r o f i t ) and a 50-50 chance a t g e t t i n g zero. The other a l t e r n a t i v e i s to use the same amount of money f o r c o s t - s a v i n g investment which w i l l net you some c e r t a i n amount. How sma l l w i l l the c e r t a i n amount have to be before you are i n d i f f e r e n t between the two a l t e r n a - t i v e s ? " Once the subject answered t h i s , he would be g e t t i n g three i n i t i a l p o i n t s on the curve. Suppose X was the answer. Thus we would have the f o l l o w i n g c a l c u l a t i o n 1 .50 ( u t i l i t y of 40,000) + .50 ( u t i l i t y of zero) = u t i l i t y (X) .50 (1) + .50(0) = u t i l i t y X. u t i l i t y of X = .5 , 15 The next question would be based on the f i r s t one where we could have two a l t e r n a t i v e s i "one i s an investment where there i s a 50-50 chance at g e t t i n g X amount and 50-50 chance at g e t t i n g $40,000; another i s a c e r t a i n investment t h a t w i l l net you Y amount." Once Y was determined, the c a l c u l a t i o n would be as follows« .50 ( u t i l . of $40,000) + .50 ( u t i l i t y of X) = u t i l i t y (Y) .50 (1) + .50(.5) = u t i l i t y (Y) u t i l i t y of Y = .75 In t h i s manner a s e r i e s of questions was constructed. A consistency check could be b u i l t i n as a l a s t question so that i n c o n s i s t e n c y could be weeded out. Swalm's r e s u l t was th a t sharp slopes were found i n the negative quadrants. By l o o k i n g at the shape of the curve, he i n f e r r e d whether the person i s a r i s k - t a k e r or not. Swalm's conclusions were 1 (1) businessmen do not attempt to optimize the expected d o l l a r outcome i n r i s k s i t u a t i o n s i n - v o l v i n g what to them are l a r g e amounts; (2) C a r d i n a l u t i l i t y theory o f f e r s a reasonable b a s i s f o r judging the i n t e r n a l con- s i s t e n c y of a s e r i e s of d e c i s i o n s made by an executive d e a l i n g w i t h r i s k s and can be an a i d i n i n c r e a s i n g the consistency of such d e c i s i o n ; (3) the theory o f f e r s a r e l a t i v e l y simple way of c l a s s i f y i n g many types of i n d u s t r i a l d e c i s i o n makers; and (4) u t i l i t y i s a f u n c t i o n of the i n d i v i d u a l ' s "planning h o r i z o n . " S p e t z l e r (1968) interviewed 36 corporate executives by asking them to make d e c i s i o n s i n each of 40 h y p o t h e t i c a l i n - vestment s i t u a t i o n s . The 40 s i t u a t i o n s i n c l u d e d 20 questions 16 at e i t h e r of two investment l e v e l s , $3 m i l l i o n and $50 m i l l i o n . L i k e Grayson, a number of i n d i f f e r e n c e p r o b a b i l i t i e s were se- cured. To help the interviewees i n understanding p r o b a b i l i t y statements, a reference c h a r t , which was a c i r c u l a r chart so designed t h a t a simple t w i s t increased the red area w h i l e r e - ducing the green area, was used, where the respondents v i s u a l i z e d the chart s p i n n i n g r a p i d l y w i t h the throw of a s i n g l e dart deter- mining the outcome. The next t h i n g S p e t z l e r undertook was t o f i n d a mathematical form f o r u t i l i t y f u n c t i o n s . E s s e n t i a l l y , he was l o o k i n g f o r a f u n c t i o n whose parameters could be deter- mined by minimizing the sum of the squares of the d e v i a t i o n s , i.e . i [U($0) - (P STJ(X S) + (1-P S) 13 ( X f ) ) ] 2 = minimum, where U(X) = the u t i l i t y of $X present v a l u e , s stands f o r success and f stands f o r f a i l u r e and P g stands f o r the proba- b i l i t y of success and (1-P S) = p r o b a b i l i t y of f a i l u r e . Seventeen Scandinavian shipowners were used i n a u t i l i t y experiment by Lorange and Norman (1971). C e r t a i n t y equivalences were d e r i v e d f o r each respondent i n a s e r i e s of 11 independent h y p o t h e t i c a l c h o i c e s , each one i n v o l v i n g a new b u i l d i n g con- t r a c t , but w i t h v a r y i n g outcomes and/or p r o b a b i l i t i e s of success. Seven of the 11 choices i n v o l v e d 50-50 odds v a r i e t y w h i l e the r e s t concerned changing p r o b a b i l i t i e s where the pay-offs were he l d constant. They responded t o these 11 h y p o t h e t i c a l choices under two l i q u i d i t y p o s i t i o n s — a s a t i s f a c t o r y and an u n s a t i s - f a c t o r y l i q u i d i t y p o s i t i o n . A lso, two normative questions were asked i one concerning the time h o r i z o n of the respondents* 17 c h a r t e r i n g p o l i c y and changes over time, and two, whether t h e i r r i s k a t t i t u d e s would he d i f f e r e n t or not assuming that they were 15 years younger. From the s u b j e c t s ' responses, Lorange and Norman t r i e d f i t t i n g the u t i l i t y curves u s i n g s e v e r a l f u n c t i o n s — i . e . , l o g a r i t h m i c , exponential and quadratic f u n c t i o n s . As p a r t of the package f o r elementary d e c i s i o n a n a l y s i s , a s e r i e s of programs th a t enable the respondent to i n t e r a c t w i t h the computer i n order to derive r i s k a v e r s i o n index has been developed by S c h l a i f f e r (1971). The complete package i s c a l l e d Manecon and i s a v a i l a b l e at a p r i c e from Harvard. These r i s k - a v e r s i o n - i n d i c e s programs are the r e s u l t s of S c h l a i f f e r ' s s t u d i e s on u t i l i t y f u n c t i o n s . E s s e n t i a l l y , these programs p r i n t out the Arrow-Pratt i n d i c e s depending upon how the user s p e c i f i e s h i s r i s k a v e rsion ( i . e . , whether i t i s constant, c o n s t a n t l y p r o p o r t i o n a l , decreasing, e t c . ) . U t i l i t y 1 Problems and D i f f i c u l t i e s U t i l i t y - t y p e questions are easy to c o n s t r u c t . Swalm's approach, being q u i t e s t r a i g h t forward and simple, may be used i n c o n s t r u c t i n g u t i l i t y questions. Some d i f f i c u l t i e s , however, may be encountered. F i r s t l y , one must be able to determine what equivalents one i s a f t e r . A mistake one could commit i s to confound the v a r i o u s types of equivalent i n the u t i l i t y questions. Toda and MacCrimmon, i n an unpublished paper, c l a s s i f i e d c e r t a i n t y equivalents as e i t h e r s e l l i n g , g i f t , or buying equi- v a l e n t s . They b e l i e v e d t h a t , i f the u t i l i t y questions were to 18 be v a l i d as r i s k - t a k i n g measure questions, one must be c o n s i s t e n t w i t h the equivalents s o u g h t — i . e . , the d i f f e r e n t types of equi- v a l e n t s should not be mixed up i n the same q u e s t i o n n a i r e . For i n s t a n c e , a u t i l i t y - t y p e question might run as f o l l o w s i "Suppose you are faced w i t h a s i t u a t i o n where, i f s u c c e s s f u l , you w i l l net K d o l l a r s and i f not s u c c e s s f u l , you w i l l net X d o l l a r s . The p r o b a b i l i t y of success i s .50. How much would you pay i n order to get t h i s investment?" This i s a buying e q u i v a l e n t . Whereas, i f a question i s as f o l l o w s , "Suppose you are faced w i t h two a l t e r n a t i v e s — o n e c e r t a i n , one u n c e r t a i n . The u n c e r t a i n a l t e r n a t i v e i s as f o l l o w s — i f you took i t and you were s u c c e s s f u l , you gai n K d o l l a r s , b u t i f you took i t and f a i l e d , you stand to l o s e X d o l l a r s . The p r o b a b i l i t y of suc- cess i s .50. The second a l t e r n a t i v e i s c e r t a i n — i f you take i t , you are sure to net Y amount. How s m a l l would Y have to be be- fo r e you are i n d i f f e r e n t between the two a l t e r n a t i v e s ? " This i s a g i f t e q u i v a l e n t . An example of a s e l l i n g e quivalent runs as f o l l o w s 1 "Suppose you have an investment i n a venture t h a t i s u n c e r t a i n as to outcomes. I f the venture was s u c c e s s f u l , you gain K d o l l a r s but i f i t f a i l e d , you stand to l o s e X d o l l a r s . Your p o s s i b l e investment i s about M d o l l a r s . The p r o b a b i l i t y of success i s .50. I f you could s e l l t h i s e n t i r e investment to someone e l s e , how much would you ask f o r i t ? " Toda and MacCrimmon presented a mathematic proof t h a t these equi v a l e n t s were not the same. Thus, i f we are i n t e r e s t e d i n g e t t i n g u t i l i t y responses under net t e r m i n a l wealth s i t u a t i o n s , we must have the same net 19 t e r m i n a l wealth s i t u a t i o n throughout the q u e s t i o n n a i r e . Or, i f the u t i l i t y responses we seek concern increments t o wealth, the questions i n the e n t i r e q u e s t i o n n a i r e should he concerned w i t h increments to wealth. The c h a i n i n g method of e l i c i t i n g e quivalents i s e a s i e r i n c o n s t r u c t i o n terms than the i n d i f f e r e n c e p r o b a b i l i t y method used by Grayson and S p e t z l e r . In the p l o t t i n g of the u t i l i t y curves, c h a i n i n g can help the experimenter by making the time f o r p l o t t i n g s h o r t e r . We s h a l l i l l u s t r a t e here how cha i n i n g works. Suppose we have determined the planning h o r i z o n as X and we use 5 0 - 5 0 f o r p r o b a b i l i t y assignment, the s e r i e s of questions may be d i a - grammed t h i s way t Question 11 Y t o be determined ( I f we l e t u(X) = u t i l l a n d u ( 0 ) = 0 u t i l , u(Y) = . 5 ) Question 2 j Z to be determined (thus, u(Z) = . 7 5 ) Question 3 i R to be determined (thus, u(R) = . 2 5 ) . 5 (0) Question k i to be determined . 5 (Z) (thus, u(V) = . 5 ) 20 Question 4 i s supposed to be a consistency check question. I f the person f o l l o w s the Von-Neumann-Morgenstera axioms, he ought to have V = Y. Before we go i n t o the consistency i s s u e , we w i l l present here the p l o t of the sample e q u i v a l e n t s . FIGURE 2.1 > Example of a U t i l i t y Curve P r o b a b i l i t y l e a r n i n g i s perhaps the gre a t e s t d i f f i c u l t y encountered by past researchers (Grayson, S p e t z l e r , e t c . ) . The f a i l u r e to see the p r o b a b i l i t i e s as o b j e c t i v e ones causes " i n c o r r e c t " or untrue responses. S p e t z l e r * s reference chart aims at g i v i n g the subjects a f e e l of what the un d e r l y i n g pro- b a b i l i t i e s mean. Even Swalm, who thought that h i s 50-50 was able to remove a l l s u b j e c t i v e p e r c e p t i o n , had some subjects who s a i d 50-50 to them was not r e a l . A l s o , the pay-offs i n v o l v e d are o f t e n summarized pay-offs i n monetary terms. I t i s p o s s i b l e t h a t the su b j e c t s might f a i l to grasp the "consequences" of the pa y - o f f s , because some of them t h i n k i n percentage terms. Net Present Value i s o f t e n used as an expression of the pay-offs 21 but t h i s i s a condensed f i g u r e whose meaning some subjects may not r e a d i l y grasp. U s u a l l y , investment-type questions are employed but the question as t o how the pay-offs should be phrased i s sometimes not asked of the s u b j e c t s . The o b j e c t i v e of the u t i l i t y questions i s to make the s i t u a t i o n s as r e a l as p o s s i b l e i n order to e l i c i t responses t h a t are meaningful. How-̂ ever, because of the s i m p l i c i t y of the p a y - o f f s , r e a l i s m i s sac- r i f i c e d . Net present value i n c l u d e s i n i t s c a l c u l a t i o n the d i s - counting r a t e but the sub j e c t s sometimes have d i f f i c u l t y evalu- a t i n g the c o n s t r a i n t s t h a t the investment (and commitment) might mean t o f u t u r e o p p o r t u n i t i e s . The experimenter wants the ques- t i o n s t o be responded to as i f they were "independent" questions- i . e . , the response to Question 1 should not i n any way be taken i n t o account by the respondent i n answering subsequent questions. A l s o , there i s the danger of respondents g i v i n g expected value as c e r t a i n t y equivalents (even i f , i n r e a l i t y , they do not use expected value as a d e c i s i o n r u l e ) . M o t i v a t i o n a l elements thus must be incorporated together w i t h the questions so tha t the responses given are " t r u e " responses r a t h e r than what the r e s - pondents t h i n k they ought to g i v e . As to consistency, Grayson, S p e t z l e r , and Swalm found t h a t there were i n f a c t answers that d i d not conform to the axioms of Von Neumann and Morgenstern. The responses by the subjects t o the consistency check question should thus be examined. I f the responses are outside a s p e c i f i e d range ( i . e . , the range being +10$ of the amounts on which the check i s a p p l i e d ) , we must conclude that the axioms 22 are not followed and the s u b j e c t s ' responses are considered dubious. The Arrow-Pratt index of r i s k a v e r s i o n assumes th a t one could derive a u t i l i t y f u n c t i o n f o r each u t i l i t y curve. However, the form of the f u n c t i o n i s d i f f i c u l t to determine. Researchers i n the past, l i k e S p e t z l e r , Norman and Lorange, suggested what the form of the u t i l i t y f u n c t i o n was. The v a r i o u s f u n c t i o n a l forms suggested were d i f f e r e n t from one researcher t o the next ( i . e . , S p e t z l e r ' s f u n c t i o n s were not the same as those of Norman and Lorange). Also, i f the fu n c t i o n s are to be determined, much c u r v e - f i t t i n g work would have to be done and the parameters of the f u n c t i o n s would a l s o have to be deri v e d . This i s d e f i n i t e l y a d i f f i c u l t a c t i v i t y to undertake. A si m p l e r way, from an experimenter's computational p o i n t of view, i s to measure the h o r i z o n t a l d e v i a t i o n s from the r i s k n e u t r a l l i n e (see Figure 2 .1 ) and average these d e v i a t i o n s . B a s s l e r (1972) employed t h i s method f o r computing r i s k a v e r s i o n i n d i c e s . D i s c u s s i o n U t i l i t y theory, as we have s a i d , has i t s p o s s i b i l i t i e s i n measuring an i n d i v i d u a l ' s r i s k t a k i n g a t t i t u d e . D i f f i c u l t i e s w i t h o p e r a t i o n a l u t i l i t y measurement have been pointed out. Normatively, u t i l i t y theory o f f e r s the economic man an approach i n making d e c i s i o n s under u n c e r t a i n t y . A corporate r i s k p o l i c y can be derived by the a p p l i c a t i o n of u t i l i t y ( S p e t z l e r ) . With the u t i l i t y f u n c t i o n s of the key managers p l o t t e d out, d e l e g a t i o n 23 of decision-making can be f a c i l i t a t e d (Grayson). Howard (1968) l i k e w i s e suggested the c o n s t r u c t i o n of v a r i o u s u t i l i t y f u n c t i o n s based on independent v a r i a b l e s l i k e market shares, p r o f i t , e t c . to be incorporated i n s t a t i s t i c a l d e c i s i o n theory to maximize u t i l i t y . Another economic-based instrument t h a t could be used f o r the assessment of r i s k - t a k i n g p ropensity i s the Indifference^ Curve approach. MacCrimmon and Toda (1969) g i v e a method of p l o t t i n g the i n d i v i d u a l ' s i n d i f f e r e n c e curves i n s i t u a t i o n s of t r a d e - o f f s (between two commodities). The slope of the i n d i f f e r - ence curve at any p o i n t shows the marginal r a t e at which one a t t r i b u t e i s s u b s t i t u t e d f o r another. A polynomial u t i l i t y f u n c t i o n of each object considered has been der i v e d from the i n d i f f e r e n c e curves obtained by MacCrimmon and Toda. Thus, questions concerning u t i l i t y f u n c t i o n s may a l s o be r a i s e d against the i n d i f f e r e n c e curve method, which can be considered the i n d i r e c t way of a r r i v i n g at u t i l i t y f u n c t i o n s . D i s c u s s i o n on the methods of determining i n d i f f e r e n c e curves and the d e r i - v a t i o n of u t i l i t y f u n c t i o n s from these w i l l not be undertaken here. However, a l t e r n a t i v e s to r i s k - t a k i n g measurement are con- f i n e d not only to economics but may be extended t o the f i e l d of psychology. In the next chapter, we w i l l present some of the p s y c h o l o g i c a l measures that have been found to. have v a l i d i t y f o r our purposes. 24 - CHAPTER 3 THE PSYCHOLOGICAL BACKGROUND OF RISK TAKING PROPENSITY MEASUREMENT An Overview Risk t a k i n g propensity has "been hypothesized to be a general p e r s o n a l i t y d i s p o s i t i o n . Many devices have been pro- posed by p s y c h o l o g i s t s f o r use i n i t s assessment. However, previous s t u d i e s revealed t h a t there was a considerable l a c k of agreement among measures t h a t were supposed t o be i n v e s t i g a t i n g the same general c h a r a c t e r i s t i c . The controversy surrounding a l l these r i s k - t a k i n g propensity measures surfaces p a r t i a l l y w i t h the f o l l o w i n g questions i (1) Is r i s k t a k i n g propensity a general p e r s o n a l i t y d i s p o s i t i o n ? ( 2 ) What are the p e r s o n a l i t y c o r r e l a t e s of r i s k - t a k i n g a t t i t u d e s ? ( 3 ) Can we i d e n t i f y the dimensions of the broader construct c a l l e d r i s k - t a k i n g ? (4) How reasonable are these measures ( i . e . i n terms of face v a l i - d i t y ) ? and (5) What about the convergent v a l i d i t y of these instruments? „ S l o y i c (1962) attempted to provide evidence about the con- vergent v a l i d i t y by determining whether i n t e r c o r r e l a t i o n s among s e v e r a l r i s k - t a k i n g measures were s i g n i f i c a n t l y d i f f e r e n t from zero and s u f f i c i e n t l y l a r g e to encourage f u r t h e r examination. Eighty-two subjects were administered a b a t t e r y of Response Set (Dot E s t i m a t i o n Test, Word Meanings Test f o r Category Width and Test Risk f o r gambling on guesses), Questionnaire ( L i f e E x p e r i - ence Inventory of Torrance and Z i l l e r and a Job Preference 25 Inventory), experimental gambling (Bet Preference Test and S e l f C r e d i t i n g Test) and peer r a t i n g measures of r i s k t a k i n g tenden- c i e s , The i n t e r c o r r e l a t i o n s among these measures were g e n e r a l l y not s i g n i f i c a n t (ranging from - . 3 5 to . 3 4 ) . B a s s l e r ( 1 9 7 2 ) , i n h i s d o c t o r a l d i s s e r t a t i o n t e s t e d v a r i o u s measures (e.g., v a r i a n c e , negative semi-variance, skewness, K t s r - t o s i s , e t c . ) derived from an e x e r c i s e on s t o c k , d e c i s i o n s i t u a t i o n s ( c a l l e d the Investment Experiment as a Group) i n a consistency check w i t h t h e c h o i c e dilemma ques t i o n n a i r e of Kogan and Wallach ( 1 9 6 4 ) a n d u t i l i t y f u n c t i o n s , The highest c o r r e l a t i o n he found e x i s t e d only between two s i t u a t i o n s which had money pay-offs (p <.005 and r = - . 5 5 ) . Kogan and Wallach, i n t h e i r 19.64 study, i n t e r c o r r e l a t e d the f o l l o w i n g measuresi Choice Dilemmas.Pure Chance B e t t i n g (Actual) S i t u a t i o n s ; Brim and Hoff Extremity i n Judgment and Confidence; Category Width; Choices among d i f f e r e n t l o t t e r i e s based on motor s k i l l t asks w i t h monetary p a y - o f f s ; Number-guessing games w i t h monetary pay-offs and in f o r m a t i o n a v a i l a b l e f o r purchase; Problem-Solving Tasks w i t h up t o . e i g h t clues a v a i l a b l e , each at the cost of a decrement i n . t h e monetary reward f o r a c o r r e c t s o l u t i o n ; and a f i n a l a l l or nothing chance l o t t e r y . They found no evidence of g e n e r a l i t y based on t h e i r r e s u l t s , i . e . , no p a t t e r n of high c o r r e l a t i o n s among measures. The published r e s u l t s of other s i m i l a r s t u d i e s (Maehr and Videbeck ( 1 9 6 8 ) , Weinstein and Martin ( 1 9 6 9 ) ) i n d i c a t e d poor convergent v a l i d i t y . A l d e r f e r and Bierman ( 1 9 7 0 ) , u s i n g a three outcome l o t t e r y , showed t h a t opposite patterns of r e l a t i o n s h i p e x i s t e d between 26 choice dilemma and investment r i s k - t a k i n g . S l o v i c (1971) found t h a t under two d i f f e r e n t e v a l u a t i o n modes (preference or s e l l i n g p r i c e ) , there was.a l a c k of consistency "between the two gambling measures employed. S l o v i c (1964) s a i d t h a t "What i s needed, t h e r e f o r e , i s a systematic i n v e s t i g a t i o n of the f a c t o r s r e s p o n s i b l e f o r t h i s l a c k of convergent v a l i d i t y . " The expla n a t i o n f o r t h i s l a c k could be found i n the f o l l o w i n g i m u l t i d i m e n s i o n a l i t y of r i s k . s u b j e c t i v i t y of r i s k , and emotional a r o u s a l i n v o l v e d i n r i s k . Kogan and Wallach (1967) summarized the var i o u s determin- ants of r i s k t a k i n g , an i n t e r e s t i n g part being the s i t u a t i o n a l i n f l u e n c e s on r i s k t a k i n g , which can be i n t e r p r e t e d to agree w i t h S l o v i c * s m u l t i d i m e n s i o n a l i t y - s u b j e c t i v i t y i s s u e . A l s o , s e v e r a l p e r s o n a l i t y v a r i a b l e s are l i k e l y to a f f e c t one's emotional a r o u s a l and thus i n f l u e n c e r i s k - t a k i n g . The f o l l o w i n g have been maintained to be of major.importance t (1) I-E Cont r o l (from Rotter 1966) (e.g., L i v e r a n t and Scodel I960, Lefcourt and S t e f f y 1970). (2) Defensiveness (using the Marlowe-Crowne S o c i a l D e s i r a b i l i t y Scale) (e.g., Martuza 1970). (3) F i e l d Dependence-Independence (Kogan and Wallach 1964) (4) Need Achievement-Fear of F a i l u r e (as measured by TAT or the "French Test f o r I n s i g h t " ) (Atkinson, B a s t i a n , E a r l and L i t w i n 1960s Scodel, Minas and Ratoosh 1959; McClelland 1958; Morris 1966;.Weinstein 1969). (5) Test Anxiety (Kogan and Wallach 1964). (6) I n t e l l i g e n c e and S k i l l (Kogan and Wallach 1964; J e l l i s o n and R i s k i n d 1970). (7) Autonomy (using the EPPS) (Cameron and Myers 1966).* 2? (8) Sensation Seeking (of Zuckermann, et a l . 1964) (suggested by S l o v i c ) . (9) Suspiciousness vs. Trust (Shure and Meeker 1967). (10) Cautiousness (using Gordon P I Scale) (Phelan 1962). Other types of s t u d i e s i n the i n v e s t i g a t i o n of the person- a l i t y c o r r e l a t e s of r i s k - t a k i n g are i n existence (e.g., Rim 1964; Cameron and Myers 1966). The Sensation Seeking, mentioned above, i s what psycholo- g i s t s r e f e r r e d to as the con s t r u c t "optimal s t i m u l a t i o n l e v e l . " One school of thought proposes th a t the i n d i v i d u a l i s c o n s t a n t l y seeking some optimal l e v e l of i n t e r n a l excitement. Risk i s courted i n . o r d e r to r a i s e the amount of e x c i t a t i o n when.it drops below the optimal l e v e l and avoided when the e x c i t a t i o n l e v e l becomes excessive. Thus, the i n i t i a l hypothesis i s tha t a per- son w i t h a higher s e n s a t i o n seeking tendency would e x h i b i t h i gher r i s k - t a k i n g . I n t e r n a l - E x t e r n a l C o n t r o l r e f e r s to "the extent to which an i n d i v i d u a l i n a s p e c i f i c s i t u a t i o n or c l a s s of s i t u a t i o n s b e l i e v e s t h a t what has happened, i s happening or w i l l happen i s d i r e c t l y r e l a t e d to what he has done." L i v e r a n t and Scodel (I960) demonstrated a r e l a t i o n s h i p between r i s k - t a k i n g and I-E where the r i s k s i t u a t i o n i n v o l v e d gambling ch o i c e s , w i t h t h e i r a s s e r t i o n that "a penchant f o r ' i n t e r n a l c o n t r o l e v i d e n t l y con- t r i b u t e d to lower l e v e l s of r i s k - t a k i n g and to l e s s v a r i a b i l i t y i n the choice of d e c i s i o n a l t e r n a t i v e s where the s e t t i n g i n - v olved c h a n c e — i n other words, when i n f a c t no i n t e r n a l c o n t r o l was p o s s i b l e . " 27& Both of these measures are L i k e r t - t y p e (to remove s o c i a l d e s i r a b i l i t y b i a s ) measures, each item c o n s i s t i n g of p a i r of a l t e r n a t i v e s f o r the subject to s e l e c t . The s c o r i n g method employed f o r these measures i s s i m p l i f i e d and " o b j e c t i v e " ( i . e . , there i s no requirement f o r v a l i d a t e d judges to review the r e s - ponses, as i n TAT). Atkinson (1957) was one of those who pioneered the expec- tancy theory. Atkinson et a l . (I960) found support f o r t h e i r model of Resultant M o t i v a t i o n w i t h the s h u f f l e b o a r d game (as a r i s k d e v i c e ) . The r e s u l t a n t m o t i v a t i o n f u n c t i o n d e r i v e d from e m p i r i c a l t e s t i n g demonstrated t h a t a person w i t h high Mg (Motivation t o succeed) p r e f e r r e d moderate r i s k w h i l e a person w i t h high Mf (motivation to avoid f a i l u r e ) p r e f e r r e d extremely r i s k y or extremely c o n s e r v a t i v e a l t e r n a t i v e s or choices. How- ever, Weinstein (1969), u s i n g the French Test of I n s i g h t (a t e s t f o r need achievement) and other (n Ach) need Achievement t e s t s (e.g., TAT) t r i e d to determine the r e l a t i o n s h i p between l e v e l of need achievement and 12 measures of r i s k preferences and found low n o n - s i g n i f i c a n t c o r r e l a t i o n among t r a d i t i o n a l n Ach measures and low convergence across r i s k preferences. From the numerous s t u d i e s reported i n the l i t e r a t u r e , i t seems t h a t researches i n t o the p e r s o n a l i t y c o r r e l a t e s of r i s k - t a k i n g have not been f r u i t f u l . Two things may have been wrong w i t h the studies» (1) the measurement of the other p e r s o n a l i t y v a r i a b l e s has not been accurate because of the nature of the instruments used; 28 (2) the r i s k - t a k i n g measurement has been based on instrument(s) whose c o n s t r u c t i o n has been f a u l t y . C r i t i c i s m of the past researches i n t o r i s k - t a k i n g i s d i - r e c t e d towards two major areas i (1) the instrument i t s e l f i s w e a k — i n terms of the i n a b i l i t y to d i s t i n g u i s h f a c t o r s , percep- t u a l d i f f e r e n c e s , and (2) the way the s t u d i e s have been con- ducted- - f a i l u r e to e l i m i n a t e v a r i a b l e s t h a t tend to i n v a l i d a t e the r e s u l t s (boredom-inducing effects); i n a b i l i t y t o separate chance and s k i l l e f f e c t s , l a c k of meaningfulness of the conse- quences of the d e c i s i o n s made i n response to the measures, and i n s i g n i f i c a n t value of p o t e n t i a l l o s s (dime-nickel chance s i t u - a t i o n s , f o r example). A l s o , d i f f e r e n t procedures designed to assess the same a t t i t u d e s may l e a d to q u i t e d i f f e r e n t placement of the i n d i v i d u a l s (Cook and S e l l t i z 1964). Moreover, the asser- t i o n of non-convergence of the v a r i o u s measures i s somewhat weakened by the questionable measures of r i s k - t a k i n g used ( e i g . , S l o v i c 1962). Search i s always a s e r i e s of generation and e l i m i n a t i o n . C r i t e r i a must be set up by which we s e l e c t our instruments. In Chapter 4, we w i l l present these c r i t e r i a together w i t h the d e s c r i p t i o n of the f i n a l package. Instruments considered weak (by our set of c r i t e r i a ) w i l l be omitted from f u r t h e r c o n s i d e r a t i o n . For i n s t a n c e , the i n - struments t h a t have been constructed based on examination ques- t i o n s . f o r high school students ( l a b e l l e d as the "Gambling Set" by S l o v i c ) where a gambling index (Swineford 1938» 1941) i s used as a measure of r i s k - t a k i n g tendency are c l e a r l y out of 29 the question f o r business r i s k - t a k i n g p r o p ensity research. Moreover, instruments w i t h inadequate c o n t r o l of extraneous v a r i a b l e s (e.g., b e t t i n g choices where subjects are provided w i t h money to pl a y w i t h , i g n o r i n g e f f e c t s of gains and l o s s e s on subsequent b e t t i n g behavior) are h i g h l y u n d e s i r a b l e . What w i l l be presented here are measures th a t have been found t o possess c e r t a i n p r o p e r t i e s compatible w i t h our c r i t e r i a . For a complete l i s t i n g of the v a r i o u s measures employed i n ear- l i e r r e s e a r c h , r e f e r to S l o v i c (1964). Judgmental Measure Brim and Hoff (1957) designed the Desire f o r C e r t a i n t y Test (renamed Extremity-Confidence i n Judgment by Kogan and Wallach 1964), an instrument based on the n o t i o n that g r e a t e r extremity i n judgment a f f o r d s the p o s s i b i l i t y of a g r e a t e r magnitude of e r r o r and judgmental confidence, which might i n d i c a t e an i n d i - v i d u a l ' s c h a r a c t e r i s t i c b i a s e s i n p e r c e i v i n g p r o b a b i l i t i e s of success and f a i l u r e . Subjects are asked to complete sentences of the form "The Chances t h a t such and such an event w i l l occur are about i n 100." A f t e r making h i s p r o b a b i l i t y estimate, the subject i s asked to r a t e h i s confidence i n th a t e s t i m a t e — ranging from very sure to not sure at a l l . Scores obtained are the mean confidence r a t i n g and mean d e v i a t i o n from the most con- s e r v a t i v e p r o b a b i l i t y estimate (which i s 50%), An example of the items given runs as f o l l o w s t "The chances t h a t a U.S. household w i l l have an extension phone t o a r e g u l a r phone are about i n 100. Very Quite Moderately S l i g h t l y Not Sure Sure Sure Sure Sure At A l l " 30 The Confidence Score d e r i v e d i s based on the f o l l o w i n g code I 1 f o r Very Sure, 2 f o r Quite Sure, 3_ f o r Moderately Sure, 4 f o r S l i g h t l y Sure and 5 f o r Not Sure at A l l . The b a s i c c r i t i c i s m t h a t has come out so f a r i s the accu- racy of the assumption behind i t s c o n s t r u c t i o n . I t i s assumed tha t the i n d i v i d u a l s answering the items do not know the answers and are t h e r e f o r e making guesses. The existence of s t a t i s t i c a l data, which can be used as b a s i s f o r a s s i g n i n g estimates (or p r o b a b i l i t y ) , i f known to the i n d i v i d u a l s , may confound the i n t e r p r e t a t i o n — e . g . , . . a n i n d i v i d u a l a s s i g n i n g an extreme number or p r o p o r t i o n may be expressing h i s knowledge of the matter r a t h e r than being extreme i n h i s judgments. Thus, one would not be able to d i s t i n g u i s h between extremity of judgment and the amount of knowledge the person possesses. However, the way to get around t h i s i s t o make sure t h a t the questions asked are general questions whose answers are.not known t o the s u b j e c t s . The Confidence Score r e v e a l s how sure the subjects are of t h e i r answers. I t i s hypothesized t h a t i n d i v i d u a l s w i l l be more extreme i n t h e i r judgment when they are h i g h l y c o n f i d e n t , and l e s s extreme when they have low confidence. Kogan and Wallach (1964).employed t h i s instrument as p a r t of t h e i r study on r i s k - t a k i n g . Sex d i f f e r e n c e s were found i n t h e i r a n a l y s i s , confirming t h e i r previous study (Wallach and Kogan 1 9 5 9 ) i n i t s c o n c l u s i o n t h a t women were h i g h l y c e r t a i n l e s s f r e q u e n t l y than men but. t h a t when they were c e r t a i n , they were more w i l l i n g to take l a r g e r i s k s . 31 Dilemma of Choice Questionnaire Wallach and Kogan (1959) developed a questionnaire t o o b t a i n p r o b a b i l i t y preferences i n everyday l i f e s i t u a t i o n s . On t h i s t e s t , a subject i s presented w i t h 12 h y p o t h e t i c a l s i t u - a t i o n s , each r e q u i r i n g a choice between a safe a l t e r n a t i v e and a more a t t r a c t i v e but r i s k y one. The s u b j e c t , a c t i n g as a d v i s o r to the p r o t a g o n i s t i n each s i t u a t i o n , i s to i n d i c a t e the proba- b i l i t y of success which would be s u f f i c i e n t f o r him to s e l e c t the r i s k y a l t e r n a t i v e . A b r i e f d e s c r i p t i o n of three of these s i t u a t i o n s follows i 1. Mr. A., an e l e c t r i c a l engineer, has the choice of s t a y i n g w i t h h i s present job at a modest, though adequate s a l a r y or of moving on to another job o f f e r i n g more money but no long-term s e c u r i t y . 2. Mr. B., who has developed a severe heart ailment, has the choice of changing many of h i s strongest l i f e h a b i t s or of undergoing a d e l i c a t e medical operation which might succeed or might prove f a t a l . 3. Mr. C., a man of moderate means, has the choice of i n v e s t i n g a sum of r e c e n t l y i n h e r i t e d money i n secure "blue-chip" stocks and bonds or i n more r i s k y s e c u r i t i e s o f f e r i n g the p o s s i b i l i t y of l a r g e g a i n s . Response ca t e g o r i e s and i n s t r u c t i o n s f o r t h e i r use f o r item 2 are as f o l l o w s t Imagine that you are a d v i s i n g Mr. B. L i s t e d below are s e v e r a l p r o b a b i l i t i e s or odds that the o p e r a t i o n w i l l prove s u c c e s s f u l . Please check the lower p r o b a b i l i t y t h a t you would consider acceptable f o r the operation to be performed. .....Place a check, here i f you t h i n k Mr. B. should not have the o p e r a t i o n , no matter what the p r o b a b i l i t i e s . The chances are 9 i n 10 t h a t the operation w i l l be a success. The chances are 7 i n 10 t h a t the operation w i l l be a success. 32 The chances are 5 i n 10 that the operation w i l l be a success. The chances are 3 i n 10 t h a t the operation w i l l be a success. The chances are 1 i n 10 that the operation w i l l be a success. The response c a t e g o r i e s were reversed i n order f o r every other item; t h a t i s , they were arrayed from 1 i n 10 upward f o r the odd items and from high l e v e l s down to 1 i n 10 f o r the even items. A c t u a l B e t t i n g Instruments Various researchers b e l i e v e t h a t r i s k - t a k i n g may be more a c c u r a t e l y measured i n s i t u a t i o n s where the outcomes are r e a l r a t h e r than h y p o t h e t i c a l . M o s t e l l e r and Nogee (1951) presented s u b j e c t s w i t h s e t s of wagers and then a c t u a l l y played out the s u b j e c t ' s c h o i c e s , w i t h r e a l money changing hands. Edwards.(1953, 1954a, 1954b) employed b e t t i n g instruments i n studying p r o b a b i l i t y preferences. He a l s o found t h a t r i s k t a k i n g a t t i t u d e s under r e a l gambling s i t u a t i o n s were s i g n i f i - c a n t l y d i f f e r e n t from those under imaginary gambling s i t u a t i o n s . Coombs and P r u i t t (I960) used gambles of zero expected value i n studying v a r i a n c e preferences among students. Suydam and Myer(1962) o f f e r e d t h e i r s u bjects choices of e i t h e r gambles or sure amounts, the sure amounts being sometimes l o s s e s and sometimes wins. Scodel, Minas andRatoosh (1959) a l s o used r e a l gambling i n t h e i r attempt t o r e l a t e p r o b a b i l i t y preferences to achieve- ment m o t i v a t i o n and other s e l e c t e d p e r s o n a l i t y v a r i a b l e s such as i n t e l l i g e n c e . 3 3 C r i t i c i s m s of the b e t t i n g s t u d i e s are u s u a l l y d i r e c t e d t o - wards the way the experiments were c a r r i e d out. Subjects were g e n e r a l l y provided w i t h the i n i t i a l stakes f o r gambling. The Coombs and P r u i t t study (i960) has been c r i t i c i z e d on the zero expected value and the t r i v i a l stakes i n v o l v e d ( A l d e r f e r and Bierman 1970). C e r t a i n amendments must be made i n the c o n s t r u c t i o n or design of the b e t t i n g instrument. One would be t o make the stakes s i g n i f i c a n t enough f o r the s u b j e c t s . A l s o , the subjects should not be given the o r i g i n a l amount to p l a y w i t h . The e f f e c t s of g a i n and l o s s on subsequent b e t t i n g behavior should a l s o be c o n t r o l l e d . Other P o s s i b i l i t i e s ...... The Semantic D i f f e r e n t i a l technique, a method developed by Osgood and Succi (1969) f o r the e v a l u a t i o n of meanings, may be a p p l i e d i n r i s k - t a k i n g measurement.In the past, the Semantic D i f f e r e n t i a l technique (Kogan and Wallach 1964) has been employed f o r the study of people's views of r i s k - l a d e n concepts l i k e earthquakes, quicksand, and the stock market. But these s t u d i e s have not been q u i t e s u c c e s s f u l because they have been unable t o take m u l t i d i m e n s i o n a l i t y of r i s k i n t o account. One p o s s i b i l i t y i s to employ a semantic d i f f e r e n t i a l s c a l e to which the su b j e c t s respond i n t h e i r r a t i n g of h y p o t h e t i c a l r i s k - t a k e r s i n the d i - mension of r i s k we so s p e c i f i e d . An example of a subset o f d i f f e r e n t i a l i s 1 " Independent Dependent w where independent i s a fa v o r a b l e a d j e c t i v e and dependent, the 3 4 unfavorable. Relying on the n o t i o n t h a t persons would adhere to the i d e a of r a t i n g someone f a v o r a b l y i f t h i s someone had c h a r a c t e r i s t i c s s i m i l a r to t h e i r own, the Semantic D i f f e r e n t i a l Technique would give us an i n d i c a t i o n of a person's r i s k - t a k i n g a t t i t u d e by the way he perceives r i s k - t a k e r s . One c a u t i o n that should be taken i n mind i s t h a t the Seman- t i c D i f f e r e n t i a l i s not unidimensional and what we should only employ i s the "evaluative".dimension. Osgood and Succi ( 1 9 6 9 ) have a good d i s c u s s i o n of the dimensions of Semantic D i f f e r e n t i a l . This d i s c u s s i o n w i l l not be repeated here. The i n t e r v i e w technique employed i n most s o c i a l psychology s t u d i e s or as p a r t of the " p r o j e c t i v e " technique i n psycho- a n a l y s i s o f f e r s another p o s s i b i l i t y from which one could d e r i v e a r i s k - t a k i n g measure. This would i n v o l v e questions about how the s u b j e c t s handle s i t u a t i o n s of r i s k i n h i s r e a l l i f e — i . e . , the kinds of a c t i v i t i e s they undertake, which g i v e one an i n d i - c a t i o n of the amount of r i s k they.are w i l l i n g to take. I f r i s k i s s u b j e c t i v e (according to S l o v i c 1 9 6 4 ) , what then i s considered r i s k y and why i s i t considered r i s k y by the i n d i v i d u a l ? I n t e r - views provide the answers to these questions. Of course, the d i f f i c u l t y w i t h the interview.method, as w i t h other " p r o j e c t i v e " techniques, used r a t h e r l o o s e l y , occurs when one wants to score the responses. Some amount of "personal judgment" comes i n t o p l a y during the i n t e r p r e t a t i o n of responses. A v a r i a n t of the i n t e r v i e w method i s the r a t i n g method. This.has been used by S l o v i c ( c a l l e d the r i s k r a t i n g scheme) i n 1 9 6 2 ; The s u b j e c t s were asked to r a t e t h e i r f e l l o w f r a t e r n i t y 35 brothers on a b i p o l a r t r a i t of general w i l l i n g n e s s t o take r i s k s . This k i n d of a r a t i n g system r e s t s on the assumption t h a t a per- son c l o s e t o the i n d i v i d u a l being r a t e d knows enough about the l a t t e r * s r i s k - t a k i n g d i s p o s i t i o n to make a judgment. The danger here i s t h a t i t i s h i g h l y p o s s i b l e t h a t the r a t e r employs h i s own value on r i s k as a gauge through which he measures other people. Thus, we must know something about the a t t r i b u t e s and weights he uses i n the judging. The s i m p l i f i e d r a t i n g method employed by S l o v i c (1962) must be extended to i n c l u d e questions on the subjects* reasons behind the r a t i n g (e.g., what d e c i s i o n s d i d he (the person being rated) r e c e n t l y take t h a t seem to i n d i - cate h i s r i s k - t a k i n g d i s p o s i t i o n ? or why do you suppose he i s t h a t k i n d of a r i s k - t a k e r ? ) . D i s c u s s i o n There are other a l t e r n a t i v e s f o r measuring r i s k - t a k i n g p r o p e n s i t i e s , which may be considered as outgrowths of psycho- logy or which may be l a b e l l e d i n t e r - d i s c i p l i n a r y . Some of these are games which are dynamic enough to i n c l u d e some amount of complexity and r e a l i s m . Management games may be modified to serve as r i s k - t a k i n g propensity measures. Although nowadays these are considered l a r g e l y p a r t of Management, a d i s t i n c t d i s c i p l i n e , they may be c o n s i d e r e d d e r i v a t i o n s of games employed by p s y c h o l o g i s t s (e.g. P r i s o n e r Dilemma Game,. War Strategy Games of S t r e u f f e r t (1965) c a l l e d . A T a c t i c a l Negotiations.Game). The In-Basket. f o r instance, (from.Frederiksen 1962; Hemphill, et al.. 1962), may be modified to become a r i s k - t a k i n g propensity measure. 36 Personnel S e l e c t i o n Games, where the a t t r i b u t e s considered are l a r g e l y those r e l a t e d t o r i s k - t a k i n g , are another example, A cumulative body of m a t e r i a l s can be derived by studying some instruments and designs used by others. However, m o d i f i - c a t i o n s must be made on instruments used i n the past. A f a l l a c y can be committed i n research by merely l i f t i n g an instrument from the past and a p p l y i n g i t based on a design s p e c i f i e d by other researchers without c o n s i d e r i n g the circumstances of the resear c h . I f a " s u p e r i o r " measure of RT propensity can be const r u c t e d , i n q u i r y i n t o the p e r s o n a l i t y c o r r e l a t e s of r i s k - t a k i n g may be done w i t h a g r e a t e r amount of success. Chapter 4 w i l l s t a r t w i t h a b r i e f d i s c u s s i o n of the d e c i - s i o n making environment as an overview, and then w i l l describe the f i n a l package by d i v i d i n g i t i n t o i t s subsets of instruments w i t h explanations and i l l u s t r a t i o n s . 37 CHAPTER 4 A PACKAGE OF RT INSTRUMENTS AND RELATED MEASURES An Overview Dec i s i o n making i s defined as p r i m a r i l y d e a l i n g w i t h evalu- a t i o n and choice from a set of a l t e r n a t i v e s . Both thought and a c t i o n are i m p l i e d i n such a d e f i n i t i o n . The main elements of d e c i s i o n making are a decision-maker and h i s d e c i s i o n environ- ment. The main a t t r i b u t e s of a decision-maker are h i s v a l u e s , h i s b e l i e f s , and h i s resources (MacCrimmon 1970). Judgment, being an important part of decision-making, derives i t s s t r e n g t h from the i n t e r a c t i o n of a decision-maker's a t t r i b u t e s and the i n f o r m a t i o n on hand. C l e a r l y , the decision-maker's r i s k t a k i n g propensity i s part of h i s a t t r i b u t e s and t h e r e f o r e i n f l u e n c e s d e c i s i o n making. Though the r i s k t a k i n g propensity of a d e c i s i o n maker i s r e l e v a n t only i n s i t u a t i o n s of r i s k or u n c e r t a i n t y , most p r a c t i c a l management d e c i s i o n s i t u a t i o n s however are charac- t e r i z e d by considerable u n c e r t a i n t y — i . e . , where only p a r t i a l knowledge of r e l e v a n t v a r i a b l e s comes i n t o p l a y . A d e c i s i o n maker who uses expected value as h i s d e c i s i o n r u l e i m p l i e s t h a t he i s r i s k - n e u t r a l . This however may be con- s i d e r e d as a s p e c i a l case of a r i s k t a k i n g a t t i t u d e . Outcomes and a c t i o n s are two d i f f e r e n t t h i n g s . Sometimes, a d e c i s i o n maker b e l i e v e s t h a t the course of a c t i o n he takes i n f l u e n c e s the outcomes of h i s d e c i s i o n ; but the extent of such i n f l u e n c e i s , by and l a r g e , u n c e r t a i n . The l a r g e r h i s pool of r e l e v a n t i n f o r m a t i o n the b e t t e r h i s e v a l u a t i v e c a p a b i l i t i e s . 38 However, he knows t h a t , d e s p i t e h i s knowledge, there i s s t i l l such a t h i n g as unexplained v a r i a t i o n or area of doubt. The whole t o p i c of r i s k - t a k i n g r e a l l y belongs to the domain of "Decision-making under u n c e r t a i n t y . " The amount of r i s k one i s w i l l i n g to take i s indeed a d e c i s i o n by i t s e l f . Because a decision-maker b e l i e v e s t h a t i t i s r e s u l t s t h a t count, he has to evaluate the l i k e l i h o o d of such r e s u l t s . Sometimes, the d e c i s i o n maker faces an a l t e r n a t i v e which i s s t o c h a s t i c a l l y dominant; here, there i s no question as to which a l t e r n a t i v e he i s going t o take. However when s t o c h a s t i c dominance i s not c l e a r - c u t , he gets i n t o a bin d . He t r i e s t o estimate what r i s k s he i s w i l l i n g to take. Since there i s no c l e a r cut way of e s t i - mating h i s a t t i t u d e towards r i s k , he does t h i s e s t i m a t i o n i n t u i - t i v e l y . I f a way i s provided f o r the d e c i s i o n maker t o measure h i s r i s k t a k i n g a t t i t u d e , decision-making may be f a c i l i t a t e d . Rather than e s t i m a t i n g t h i s r i s k - t a k i n g propensity every time he faces a d e c i s i o n problem, the measurement of h i s r i s k a t t i - tude i s done only a few times. A l s o , by q u a n t i f y i n g h i s r i s k a t t i t u d e s , he can t e l l h i s subordinate what r i s k s he i s w i l l i n g to take. Oftentimes, decision-making i s delegated, depending upon the degree of d e c e n t r a l i z a t i o n . Here, we are t a l k i n g about h i g h e r - l e v e l d e c i s i o n s (or "de c i s i o n s of higher q u a l i t y " ) — e.g., investment d e c i s i o n s . Here, the d e l e g a t i o n i s o f t e n the g r a n t i n g of choice-making powers. However, there a r i s e s a b a s i c question of whose r i s k t a k i n g propensity should be taken i n t o c o n s i d e r a t i o n . Grayson (i960) suggested t h a t the s e n i o r manager's 39 u t i l i t y f u n c t i o n should be used i n d e c i d i n g on the l e v e l of r i s k t h a t the subordinate decision-maker should take i n s i t u a t i o n s concerning the a l l o c a t i o n of company resources f o r investment. Also, i f decision-making i s to be delegated, who we want most depends upon, other t h i n g s being equal, the r i s k t a k i n g a t t i t u d e of our s u b o r d i n a t e — o n c e we are able to a s c e r t a i n such an a t t i t u d e . In t h i s way, a person could delegate h i s d e c i s i o n - making a u t h o r i t y to someone whose r i s k - t a k i n g propensity i s s i m i l a r t o h i s own—other q u a l i f i c a t i o n s being equal to the r e s t of the candidates. Prom the business o r g a n i z a t i o n ' s point of view, a high r i s k - t a k e r i s not n e c e s s a r i l y good, nor i s he bad; i t i s more a question of acceptance or w i l l i n g n e s s on the part of the o r g a n i z a t i o n to accept the l e v e l of r i s k t h a t he might choose i n the f u t u r e . Also, there i s a question of the s t a b i l i t y of h i s r i s k - t a k i n g a t t i t u d e over time. Thus, knowing something about the r i s k - t a k i n g a t t i t u d e s of people i n the o r g a n i z a t i o n or of those who are to be considered soon as members of the or- g a n i z a t i o n helps c l a r i f y c e r t a i n i s s u e s . Of course, there are s i t u a t i o n s where an extremely r i s k - a v e r s e * i n d i v i d u a l becomes a somewhat poor d e c i s i o n - m a k e r — e s p e c i a l l y when he has continued seeking i n f o r m a t i o n even though the cost of information-gathering i s much, much gre a t e r than the "expected value of p e r f e c t i n f o r - mation. " The ide a of r i s k t a k i n g propensity as i t r e l a t e s to d e c i s i o n making i s not new. In h i s classroom d i s c u s s i o n , Dr. MacCrimmon has i l l u s t r a t e d how r i s k t a k i n g propensity i n t e r a c t s w i t h the v a r i o u s v a r i a b l e s i n the d e c i s i o n making process. 40 In order to c l a r i f y what we have s a i d , we have constructed a diagram showing the r e l a t i o n s h i p of r i s k t a k i n g propensity w i t h other decision-making v a r i a b l e s . This i s i l l u s t r a t e d as a schema i n Figure 4.1. Some explanation concerning t h i s schema must be gi v e n . The Person b r i n g s w i t h him at the post-problem d e f i n i t i o n stage s e v e r a l t h i n g s t h i s p e r s o n a l i t y c h a r a c t e r i s t i c s (e.g. I-E Con- t r o l ) and h i s demographic c h a r a c t e r i s t i c s ? wealth i s defined here as the resources he or the o r g a n i z a t i o n has. Moreover, h i s l e v e l of aspiration,among other t h i n g s , i n t e r a c t s w i t h c e r t a i n s i t u a t i o n a l e f f e c t s to produce a c e r t a i n l e v e l of emotional a r o u s a l . His previous r i s k experiences would a f f e c t h i s "wealth M and t h e r e f o r e h i m s e l f . S u b j e c t i v e p r o b a b i l i t y , l o o s e l y phrased here, would mean h i s tendency to i n j e c t c e r t a i n s u b j e c t i v e e l e - ments i n p r o b a b i l i t y assignment. A l s o , i n f o r m a t i o n (as shown by the double-arrowed l i n e ) i s sought and may be possessed by the i n d i v i d u a l , which w i l l i n f l u e n c e h i s perception of the a l - t e r n a t i v e environment—which could be defined as the set of f e a s i b l e a l t e r n a t i v e s t h a t e x i s t (with or without the i n d i v i d u a l ' s knowledge of t h e i r e x i s t e n c e ) . Perception, thus, i s a b i t broad to i n c l u d e search b e h a v i o r — i . e . , r e c o g n i t i o n , whether a given p o s s i b l e a c t i o n i s an a l t e r n a t i v e or not. Associated w i t h each a l t e r n a t i v e , there are p o s s i b l e consequences th a t could a r i s e . The s e v e r i t y of the consequences d e f i n i t e l y depends upon how h i s p e r c e p t i o n i s a f f e c t e d by the i n f l u e n c e s we so c i t e d . Ob- j e c t i v e p r o b a b i l i t y , i n t h i s case, may be " e x i s t e n t " or "non- e x i s t e n t " — d e p e n d i n g upon the problem. However, l e t us make ' i n t e r n a l - E x t e r n a l C o n t r o l 1 Defensiveness e t c . 6 S i t u a t i o n a l E f f e c t s (emotional arousal), pers Vcharacterist onality \ ^ ^ d e m o g r a p h i c \ t e r i s t i c s j Vcharacterist icsj Peer e f f e c t s EERSON C wealth FIGURE 4.1 The Risk Environment i n Decision Making f o r an I n d i v i d u a l 42 the assumption that o b j e c t i v e p r o b a b i l i t i e s e x i s t ; whether he knows them to e x i s t or not i s another matter. A f t e r he has gathered the set of a l t e r n a t i v e s he thought f e a s i b l e , h i s next move i s choice. He looks back at the s e v e r i t y of consequences of each a l t e r n a t i v e , and the l i k e l i h o o d s of these consequences. Now h i s r i s k t a k i n g propensity focuses i t s e l f i n t o major import- ance, and a c t i o n f o l l o w s — t h e s e l e c t i o n of a course of a c t i o n . The a c t i o n w i l l have c e r t a i n consequences or outcomes and, de- pending upon the extent of the odds f o r or against favorable outcomes, the outcomes w i l l be perceived and such perception w i l l be added on to h i s pool of previous r i s k experiences. D e f i n i t e l y , the schema we have constructed i s too s i m p l i s - t i c and needs f u r t h e r refinement. But we f e e l that r e l a t i o n - ships may be c l a r i f i e d by such p r e s e n t a t i o n . I f we are i n t e r e s t e d i n studying r i s k t a k i n g i n business s i t u a t i o n s i n v o l v i n g t h i n g s l i k e t e c h n o l o g i c a l change, innova- t i o n , ownership and the l i k e , we should u t i l i z e items that bear a c l o s e r e l a t i o n s h i p to these s i t u a t i o n s (MacCrimmon and Kwong 1972). Because r i s k t a k i n g a t t i t u d e i s not unidimensional, the search should be focused on what we're i n t e r e s t e d i n . The f o l l o w i n g c r i t e r i a have been set up as g u i d e l i n e s i n search and development i 1. Appropriateness - The instrument must focus on business d e c i s i o n problems and top dimensions of r i s k r e l e v a n t to the i n d i v i d u a l i n business. 2. M o t i v a t i o n - One has t o assume that there i s a " t r u e " a t t i t u d e towards the o b j e c t . I t i s be- l i e v e d that i f the instrument possesses c e r t a i n c h a r a c t e r i s t i c s that s u s t a i n emotional a r o u s a l , " t r u e " a t t i t u d e has a g r e a t e r l i k e l i h o o d of 4 3 s u r f a c i n g . Part of t h i s property i s the a b i l i t y of the instrument to e l i c i t responses which apply to the i n d i v i d u a l s r a t h e r than responses which are merely s o c i a l l y accept- able a l t e r n a t i v e s (Gordon 1951)• The items must be c r e d i b l e , i n t e r e s t i n g , d i v e r s i f i e d , i n v o l v i n g and not too long ( i . e . , t h a t i t must not be boredom-inducing). 3 . D i s c r i m i n a t i o n - I t must be able to place i n d i - v i d u a l s i n t o c a t e g o r i e s , i . e . , i d e n t i f y the i n d i v i d u a l s on the ba s i s of h i s responses and c l a s s i f y them i n t o groups. S u f f i c i e n t v a r i a - b i l i t y and consistency are part of t h i s pro- p e r t y . 4 . C o n t r o l - I t must possess the a b i l i t y to con- t r o l the d i f f e r e n t i a l perceptions of the same r i s k to d i s t i n g u i s h v a r i o u s s i t u a t i o n a l e f f e c t s . 5. Ease of A d m i n i s t r a t i o n - I t must be able t o be administered w i t h low s u p e r v i s i o n and the m i n i - mum of i n s t r u c t i o n s , i n s t r u c t i o n s which are h i g h l y understandable. 6. A n a l y s i s Ease - We r e f e r here t o s c o r i n g ease, ease of d i r e c t i n t e r p r e t a t i o n and the compati- b i l i t y of the instrument w i t h research design. To f a c i l i t a t e c l a s s i f i c a t i o n of the instruments, the r o l e s i t u a t i o n s i n these may be broken down i n t o » - What would you advise X to do i f he were confronted w i t h s i t u a t i o n s S? - What would you do i f you were Z and were confronted w i t h s i t u a t i o n s S? - What would you do i f you were confronted w i t h s i t u - a t i o n s S? The measures presented i n t h i s chapter are t e i t h e r com- p l e t e l y new or past measures r e f i n e d to s u i t pur needs. The o r i g i n a l package i s contained i n a working paper by MacCrimmon and Kwong (1972). What w i l l be presented here i s the f i n a l package. In order to f a c i l i t a t e s e l e c t i o n and c o n s t r u c t i o n , the t h e s i s has a " p i l o t " group i n m i n d — a s e l e c t e d group of kk U.B.C. Graduate Students i n Business—who w i l l he given the package as a p r e l i m i n a r y study on r i s k t a k i n g a t t i t u d e s . In p r e s e n t i n g these measures, we would l i k e to p o i n t out that although the complete p r e s e n t a t i o n of the instruments (item by item) w i l l not be made, i l l u s t r a t i o n s and d e s c r i p t i o n s are a v a i l a b l e f o r the b e n e f i t of those who would want to pursue f u r t h e r research i n t o t h i s f i e l d . The t h e s i s w r i t e r f e e l s that i t i s h i s pr e r o g a t i v e to wit h h o l d p u b l i c a t i o n of h i s instruments i f he so d e s i r e s . The Package B r i e f l y , we can d i v i d e the package i n t o two s e t s i one which r e q u i r e s the presence of the experimenter (stock p r i c e wagers, u t i l i t y questions on s e v e r a l dimensions) and one which i s s e l f - e x p l a n a t o r y , r e q u i r i n g no a s s i s t a n c e or presence of ex- perimenters (In-Basket; Choice Dilemma items; Extremity-Confidence i n Judgment; Event Occurrence and A c t i v i t y I n t e r e s t Questionnaire; and the Personal Record Questionnaire). Also, the questionnaire c a l l e d Event Occurrence and A c t i v i t y I n t e r e s t i s not a standard RT propensity measure but a que s t i o n n a i r e c o n s i s t i n g of I n t e r n a l - E x t e r n a l C o n t r o l and Sensation-seeking items. We w i l l commence the d i s c u s s i o n on the second set f i r s t . In-Basket Exercise In i t s past form, the instrument i s a c o l l e c t i o n of l e t t e r s , memoranda, records of in-coming telephone c a l l s and other m a t e r i - a l s t hat have supposedly c o l l e c t e d i n the in-basket of an admin- i s t r a t i v e o f f i c e r . The form of the In-Basket i s a t t r a c t i v e due 45 to i t s p r o x i m i t y w i t h the r e a l world. The f a c t o r s experimenters looked at i n the past werei imaginativeness, o r g a n i z a t i o n a l change, concern w i t h p u b l i c r e l a t i o n s , e t c . The In-Basket con- t a i n e d i n the package aims at measuring r i s k t a k i n g propensity by examining the responses to the v a r i o u s items i t contains. I t i s composed of s i x l e t t e r s and one memo, each of which con- t a i n s two courses of a c t i o n — o n e c e r t a i n and another u n c e r t a i n . Memo sheets are provided f o r the subjects to respond w i t h . The subject assumes the r o l e of B i l l Bickner, a d i v i s i o n a l V.P. f o r M u l t i n a t i o n a l Products, I n t e r n a t i o n a l , who j u s t a r r i v e d at h i s job due to the untimely death of a former V.P. A l l i n f o r - mation concerning the l e t t e r s and memos are i n the e x e r c i s e i t - s e l f and the subject i s not supposed to ask f o r c o n s u l t a t i o n . He i s to go through the l e t t e r s and memo, responding to them on memo sheets provided i n o u t l i n e form. Because Bickner must leave promptly to catch a plane f o r an important meeting and w i l l not be back i n one week's time, he must respond t o the items w i t h a s p e c i f i e d time l i m i t . A f t e r responding on the memo sheets, the subject i s asked to answer a number of questions at the end of the e x e r c i s e — a Semantic D i f f e r e n t i a l s e t , where a d j e c t i v e p a i r s are provided f o r the subject to r a t e f o u r c o r r e s - pondents, and a set of questions which asks him the p r o b a b i l i t y of success he would accept before t a k i n g the u n c e r t a i n a l t e r n a - t i v e contained i n each l e t t e r and memo. The business l e t t e r s have been created from s i t u a t i o n s recorded i n case s t u d i e s from I n t e r n a t i o n a l Business and Tech- n o l o g i c a l Change. Both i m p l i e d and s t a t e d consequences have 46 been b u i l t i n t o the items f o r the examinee to weigh. The l e t t e r s and memos may be described b r i e f l y as f o l l o w s t (1) L e t t e r from Donald Moore of t h e i r Canadian sub- s i d i a r y concerning a p o s s i b l e s u i t : by another company on charges of patent v i o l a t i o n , where the a l t e r n a t i v e s are i go t o court (the uncer- t a i n one), and s e t t l e out of court (the c e r t a i n a l t e r n a t i v e ) . The recommendation by the w r i t e r of the l e t t e r i s to pay the settlement amount. (2) L e t t e r from Frank Bickner, son of B i l l , s t a t i n g h i s i n t e n t i o n to take up music (the u n c e r t a i n a l t e r n a t i v e ) and leave engineering (the c e r t a i n a l t e r n a t i v e ) . This i s a personal l e t t e r . (3) L e t t e r from Paul Royce, a c l o s e f r i e n d of B i l l , asking B i l l to j o i n him i n a venture i n the P h i l i p p i n e s concerning coconut o i l e x t r a c t i o n (uncertain) and leave M u l t i n a t i o n a l Products (the c e r t a i n a l t e r n a t i v e ) . (4) L e t t e r from Johnny Kaye, P r o j e c t team d i r e c t o r f o r A r izona, who recommends th a t investment i n Arizona i s a t t r a c t i v e . Two courses of a c t i o n are open to the company; go i n alone (the un- c e r t a i n a l t e r n a t i v e ) or j o i n f orces ( j o i n t ven- t u r e ) w i t h competitors (the c e r t a i n a l t e r n a t i v e ) . Recommendation was to go i t alone. (5) L e t t e r from John White of t h e i r A t l a n t a s u b s i d i - ary where the c o n t i n u a t i o n of a time and motion study (with a p o s s i b l e b e n e f i t of improving pro- d u c t i v i t y by at l e a s t 25$) might s t a r t a general s t r i k e among.the workers. White's recommendation was to have Anderson, the Time and Motion r e - searcher, r e c a l l e d to New York o f f i c e . (6) A memo from Annabel Johnson, the s e c r e t a r y , t e l l i n g Bickner about Domier, a l a r g e buyer of t h e i r Quebec company's products, who sought to ban the Quebec company from s e l l i n g to h i s com- p e t i t o r . (7) A l e t t e r from Peter Taylor, the marketing manager of t h e i r New Jersey s u b s i d i a r y , informing Bickner of h i s i n t e n t i o n to r e s i g n i f the l o c a l p r e s i - dent i n s i s t e d i n marketing a new product, T-32, i n s t e a d of c o n t i n u i n g an o l d , e s t a b l i s h e d product. The c e r t a i n a l t e r n a t i v e was t o continue the o l d product w h i l e the u n c e r t a i n a l t e r n a t i v e was to market the T-32. 47 An o r g a n i z a t i o n a l chart o u t l i n i n g the l i n e - s t a f f r e l a t i o n - s h i p s i s i n c l u d e d i n the package to c l a r i f y Bickner's area of r e s p o n s i b i l i t y . Choice Dilemma Items The instrument c o n s i s t s of 10 i t e m s — 5 from Kogan and Wallach and 5 constructed i n the same format. In order to determine the s e v e r i t y of the consequences on the l i v e s of the c e n t r a l persons i n v o l v e d , i n s t r u c t i o n s are given to the sub- j e c t s to rank the items i n the order of g r e a t e r impact. We have mentioned the format of the choice Dilemma questions i n Chapter Three and w i l l enumerate the ten items contained i n our instrument» (1) Mr. A., an e l e c t r i c a l engineer, has the choice of s t a y i n g w i t h h i s job at a modest, though adequate s a l a r y or moving on t o another job o f f e r i n g more money but no long-term s e c u r i t y (from K & W). (2) Mr. K., the marketing manager of a f i r m , faces the choice of e i t h e r i n v e s t i n g $3 m i l l i o n i n a new product which could mean 20% ROI or f a i l u r e or i n v e s t i n g the same amount to market an o l d , w e l l - e s t a b l i s h e d product but w i t h no r e t u r n higher than 10% ROI ( o r i g i n a l ) . (3) Mr. B., an accountant, w i t h a severe heart ailment, has the choice of going through a d e l i c a t e medical operation which could cure him completely or could be f a t a l , or to l i v e out h i s days by changing many of h i s strongest l i f e h a b i t s , reducing h i s work l o a d , changing h i s d i e t and g i v i n g up f a v o r i t e l e i s u r e - t i m e p u r s u i t s (K & W). (4) Mr. J . , production s u p e r v i s o r , faces a dilemmai to go ahead or not t o go ahead w i t h some d r a s t i c changes to improve the company, which, i f success- f u l , would mean J's promotion as general manager and, i f a f a i l u r e , would mean J's t e r m i n a t i o n . I f he recommended no change, however, he would remain i n h i s present job w i t h no prospects of promotion or more than minor s a l a r y increases ( o r i g i n a l ) . 48 (5) Mr. C., man of moderate means, has the choice of i n v e s t i n g a sum of r e c e n t l y i n h e r i t e d money i n secure ""blue-chip M stocks and bonds or i n more r i s k y s e c u r i t i e s o f f e r i n g the p o s s i b i l i t y of l a r g e gains (K & W). (6) Mr. B.C., president of a s u b s i d i a r y , has been a r - r e s t e d f o r a l l e g e d treason. MIK, the parent com- pany, faces the choice of s e l l i n g out at a reason- a b l e , but low p r i c e or hanging on w i t h the p o s s i - b i l i t y of B.C. being convicted w i t h the s u b s i d i a r y being expropriated ( o r i g i n a l ) . (7) Mr. E., president of an American c o r p o r a t i o n con- templating expansion, has the choice of b u i l d i n g an a d d i t i o n a l p l a n t i n the U.S. w i t h the expecta- t i o n of a moderate r e t u r n on the investment or of b u i l d i n g i n a f o r e i g n country w i t h an unstable p o l i t i c a l h i s t o r y , where, however, r e t u r n s would be considerably higher (K & W). (8) Mr. T.D., s a l e s manager of a U.S. s u b s i d i a r y , has the choice of s e l l i n g $500,000 worth of goods to a l o c a l p o l i t i c i a n who i s d e f i n i t e l y not going t o pay or not s e l l i n g the goods to him w i t h the p o s s i - b i l i t y t h a t such r e f u s a l could i n c i t e anger and t r o u b l e from the p o l i t i c i a n ( o r i g i n a l ) . (9) Mr. K., a s u c c e s s f u l businessman w i t h a strong f e e l i n g of c i v i c r e s p o n s i b i l i t y , has the choice o f seeking or not seeking e l e c t i o n to congress as a candidate of a m i n o r i t y p a r t y w i t h l i m i t e d funds (K & W). (10) Mr. L., area manager of a U.S. f i r m i n Southeast A s i a , faces the choice of c o n t i n u i n g production or not i n the midst of a s t r i k e i n the U.S. West Coast Docks which could l a s t f o r 3 months or be s e t t l e d immediately ( o r i g i n a l ) . In the same v e i n as Kogan and Wallach, the response cate- g o r i e s are reversed i n order f o r every other i t e m — i . e . , they are arrayed from 1 i n 10 upward f o r the odd items and from high l e v e l s down to 1 i n 10 f o r the even items. 49 Extremity-Confidence i n Judgment F i f t e e n items f o l l o w i n g the Brim and Hoff format have been constructed based on the same assumptions forwarded by s t u d i e s u s i n g t h i s instrument. In order to remove the e f f e c t of know- ledge t h a t may contaminate the r e s u l t s , the items constructed here are mostly about f a c t s which we f e e l the subjects have no knowledge of. For example, "The chances t h a t an a d u l t Japanese i n Japan w i l l know how to speak E n g l i s h are about i n 100," i s an item whose exact answer may not be known or remembered by the s u b j e c t . Although t h i s i s not the standard r i s k measurement, i t does r e f l e c t the " w i l l i n g n e s s of a person to take the r i s k of e r r o r s i n judgments" and h i s confidence l e v e l . The s u b j e c t s are asked to i n d i c a t e the chances that the event w i l l occur and g i v e t h e i r confidence by e n c i r c l i n g the phrase t h a t describes t h i s confidence ( i . e . , Very Sure, Quite Sure, Moderately Sure, Not Sure at A l l ) . Event Occurrence and A c t i v i t y I n t e r e s t Questionnaire Following the b e l i e f t h a t e x t e r n a l - i n t e r n a l c o n t r o l and sensation seeking are two p e r s o n a l i t y c o r r e l a t e s of r i s k - t a k i n g , t h i s instrument has been constructed by t a k i n g ten items from Rotter's I-E s c a l e and ten from the Zuckerman, et a l . Sensation Seeking Scale. The instrument has been renamed to d i s g u i s e i t s i n t e n t i o n . The I-E items are i n t e r s p e r s e d w i t h the Sensation Seeking items u s i n g the format of the o r i g i n a l s . Two examples of items 50 contained i n t h i s instrument f o l l o w t (1) a. Many of the unhappy t h i n g s i n people's l i v e s are p a r t l y due t o bad l u c k , b. People's misfortunes r e s u l t from the mistakes they make. (2) a. I would l i k e a job which would r e q u i r e a l o t of t r a v e l l i n g , b. I would p r e f e r a job i n one l o c a t i o n . A l l the odd items are Ro t t e r I-E type w h i l e a l l even items are sensation-seeking type. A l s o , the order of the i n t e r n a l c o n t r o l choice and the e x t e r n a l c o n t r o l choice i s reversed f o r every other odd item. The same i s t r u e of the sensation seeking items, i n the case of even items. Personal Records In order to secure i n f o r m a t i o n on the demographic ch a r a c t e r - i s t i c s of the s u b j e c t , t h i s instrument, i n the us u a l survey f o r - mat, c o n s i s t s of questions concerning age (expressed i n terms of year of b i r t h ) , education l e v e l of the subject and h i s previous background, h i s assets and l i a b i l i t i e s ; h i s l e i s u r e h a b i t s (e.g., p l a y i n g poker, e t c . ) , h i s working experience, how he finances h i s education and the l i k e . The s u b j e c t s ' responses are values of v a r i o u s demographic v a r i a b l e s t h a t may be r e l a t e d to t h e i r r i s k t a k i n g a t t i t u d e s . Some of these v a r i a b l e s were suggested by Kogan and Wallach (1967) i n t h e i r essay on the determinants of r i s k t a k i n g be- h a v i o r . We in t e n d to examine the r i s k t a k i n g measures and the su b j e c t s ' responses on these q u e s t i o n n a i r e s by r e l a t i n g the scores generated to the v a r i o u s demographic v a r i a b l e s sought by the Personal Record. 51 U t i l i t y Type Questions Each subject i s asked four s e t s of questions by t h i s instrument. Two of the s e t s concern questions to be answered by the subject i n h i s business or p r o f e s s i o n a l r o l e , which i s provided f o r by a short s c e n a r i o . Except f o r the Scale of Wager s e t , the questions seek t o e l i c i t c e r t a i n t y equivalences by usi n g the method of ch a i n i n g (see Chapter 2). The sets are composed of the f o l l o w i n g i a. Personal U t i l i t y sets - .two sets of items are given. The f i r s t i s the Scale of Wager where the subject i s asked questions about wagers i n terms of t h e i r cash equivalences (buying) and of the d e c i s i o n to accept or r e j e c t the l o t t e r i e s o f f e r e d . The second i s c a l l e d the Compensation U t i l i t y Questionnaire where the f i r s t question i s used as a basis f o r a "planning h o r i z o n " — i . e . , h i s annual compensation i n h i s f i r s t year of work (expected). The proba- b i l i t i e s i n v o l v e d here are .80 and .20 f o r chances of success and f a i l u r e r e s p e c t i v e l y as contrasted w i t h the 50-50 odds of the f i r s t s e t . Here, we are a f t e r the amount of the biggest pay-off i n the case of the u n c e r t a i n a l t e r n a t i v e , that would make him i n d i f f e r e n t between the c e r t a i n and u n c e r t a i n a l t e r n a t i v e s . b. Business U t i l i t y s e t s - two scenarios are given f o r the two sets contained i n t h i s s e c t i o n . One con- cerns the assumption by the subject of the r o l e of a general manager of a sma l l company and another t e l l s the subject to assume the r o l e of a d i v i s i o n manager of a l a r g e i n t e r n a t i o n a l business. He i s to answer the set p e r t a i n i n g to the scenario w i t h the s p e c i f i e d r o l e i n mind... - Two typ.es. .of u t i l i t y questions, are asked, h e r e — N e t P r o f i t U t i l i t y Questions and Rate of Return Questions. E q u i l i - b r a t i n g p r o b a b i l i t y , i s s o l i c i t e d by each item i n the .case of. Net P r o f i t U. Questions w h i l e i n the Rate of Return, the cash equivalents (or the Cer- t a i n t y Monetary E q u i v a l e n t s ) of the u n c e r t a i n a l - t e r n a t i v e s are s o l i c i t e d , where the p r o b a b i l i t i e s i n v o l v e d are 50-50. In order to reduce the contamination of r e s u l t s t h a t may be caused by l e a r n i n g e f f e c t s , the personal u t i l i t y and the Business 52 U t i l i t y s e t s are interchanged randomly. Also, f o r purposes of i n t e r p e r s o n a l comparison, the net p r o f i t and the r a t e - o f - r e t u r n u t i l i t y q u e s t i o n n a i r e s are interchanged randomly between scenario of the f i r s t type and of the second type. The i n c l u s i o n of the u t i l i t y items i n the i n t e r a c t i v e s et stems from convenience. In order to f a c i l i t a t e the s u b j e c t s , the e n t i r e package i s d i v i d e d i n t o s m a l l e r l o t s . The u t i l i t y items are thus i n c l u d e d as part of the i n t e r a c t i v e s e t . A l s o , we f e e l the u t i l i t y items may need more v e r b a l c l a r i f i c a t i o n s — i . e . , how to f i l l i n the blanks, what v a r i a b l e s should be con-r s i d e r e d constant, e t c . Stock P r i c e Wagers The subjects are presented w i t h f i v e s e t s of wagers i n which the pay-offs are r e a l r a t h e r than h y p o t h e t i c a l as compared to the other measures. Although the subjects have a chance of g a i n i n g a c t u a l money, only one of the chosen wagers, s e l e c t e d randomly, w i l l be played out. In each s e t , one of the options i s not a wager at a l l s i n c e i f s e l e c t e d , the subject i s e n t i t l e d to $2.00 f o r sure. The r e s t of the wagers d i f f e r i n the amount of win or l o s s , the p r o b a b i l i t i e s i n v o l v e d and, i n two s e t s , v the expected winnings. Information concerning the amount of win or l o s s , the p r o b a b i l i t y of winning and the expected winnings i s provided. These wagers are based on the f r a c t i o n a l p a r t of the p r i c e s of f i v e stocks s e l e c t e d randomly from a l i s t of 100 stocks h e a v i l y traded on the New York Stock Exchange. Set A and B contain options whose expected winnings are $2.00 w h i l e 53 Set C s t a r t s out w i t h a $ 2 . 0 0 sure amount o p t i o n , followed by items whose expected winnings increase "by 1 0 $ of the previous item's EV as the variance of the wager in c r e a s e s . Set D i s the reverse of Set C where the expected winnings decrease as the v a r i a n c e i n c r e a s e s . In Set E, the p r o b a b i l i t y of winning i s f i x e d at 62% w i t h the amounts of win and l o s s v a r y i n g , a l l w i t h expected winnings of $ 2 . 0 0 . A l i s t of 100 stocks under $50 i s attached t o the i n s t r u - ment. The subject wins i f the f r a c t i o n a l amount of a stock's p r i c e i s 1 / 8 , 3 / 8 or 5 / 8 ; he l o s e s i f the f r a c t i o n a l amount i s 1 / 4 , 1 / 2 , 3 / 4 , 7/8 or a whole number. Generally, the options of wagers are of the form i "You w i l l r e c e i v e $ (amount of win) i f at l e a s t (number) of the 5 stocks has (have) a f r a c t i o n a l p r i c e ( s ) of 1 / 8 , 3 / 8 , or 5 / 8 . However, you must pay $ (amount of l o s s ) i f only (number) of the f i v e stocks has/have one of these f r a c - t i o n a l p r i c e s . Chance of winning Expected winning " Method of Scoring the Items The f o l l o w i n g scores w i l l be used as input to a n a l y s i s t 1 . Choice Dilemma Scores - each item w i l l have as a r e s - ponse a number out of 10 t h a t the subject accepts as the odds of success. The ten numbers from the ten items w i l l be averaged f o r each subject and w i l l c o n s t i t u t e a t o t a l score on t h i s s e t . In a d d i t i o n , rank responses (ranking by subjects i n order of the g r a v i t y of the consequences of the items on the l i v e s of the c e n t r a l persons involved) w i l l be used f o r studying the 54 rank c o r r e l a t i o n s of high r i s k t a k e r s and low r i s k t a k e r s as determined by t h e i r t o t a l score f o r the s e t . 2. In-Basket Scores - Several scores w i l l be d e r i v e d from the e x e r c i s e . (a) Note/Wire Response Set - the v e r b a l responses w i l l be given ranks (of r i s k a v ersion) by the examiner based on the s t r a t e g i e s the subjects have adopted. Rank 1 w i l l imply the g r e a t e s t r i s k - t a k i n g . (b) Ranks - each item w i l l be ranked by the subject i n the order of importance. (c) Grades - the subject i s asked to a s s i g n grades based on h i s p e r c e p t i o n of the importance of the consequences to him as a businessman. There w i l l be 7 grades f o r each sub- j e c t w i t h the item he deemed as most important graded as 100 ( i . e . , maximum i s 1 0 0 ) . (d) Score f o r Part A ( a f t e r - E x e r c i s e Questionnaire) An average i s derived from the odds the subject assigned to each item. (e) Semantic D i f f e r e n t i a l Score - the subject i s asked to r a t e the persons named by the questionnaire w i t h the a d j e c t i v e - p a i r s (10 i n a l l ) provided. The a d j e c t i v e s are iden- t i f i e d as f a v o r a b l e or unfavorable and the s c a l e s run from +5t +3, 0 to - 3 and - 5 . These are added f o r the ten a d j e c t i v e p a i r s and represent h i s score f o r the Semantic D i f f e r e n t i a l on that p a r t i c u l a r person. A t o t a l score can be derived by adding these i n d i v i d u a l scores together. 55 3. Event Occurrence and A c t i v i t y I n t e r e s t Scores - two scores are d e r i v e d — o n e , the number of i n t e r n a l c o n t r o l a l t e r - n a t i v e s the subject s e l e c t e d and two, the number of se n s a t i o n - seeking a l t e r n a t i v e s he chose. 4. Extremity-Confidence Scores - The confidence score f o r each item w i l l be added up to derive a confidence r a t i n g (with Very Sure as 1, Quite Sure as 2, Moderately Sure as 3» S l i g h t l y Sure as 4 and Not Sure at A l l as 5). The extremity score i s d e r i v e d by averaging the 15 squared d e v i a t i o n s of the subject's chance assignments from .50 (considered as "conserva- t i v e " ) . 5. Personal Record "Scores" - The subject's age, amount of a s s e t s , amount of insurance, and l i a b i l i t i e s are derived from the Personal Record Questionnaire. These are used as values f o r the demographic v a r i a b l e s we are i n t e r e s t e d i n . From the sec- t i o n on hobbies and l e i s u r e , we attempt to deduce the s u b j e c t ' s r i s k t a k i n g a t t i t u d e . Using a s c a l e of 5—where 1 i n d i c a t e s high r i s k - t a k i n g , 2 moderate r i s k - t a k i n g , 3 r e l a t i v e l y r i s k - n e u t r a l , k moderately r i s k averse and 5 h i g h l y r i s k averse . 6. Stock P r i c e Wager Score - For each set the formula i s the rank (derived by ordering the wagers from lowest to highest v a r i a n c e , where variance i s ( l - p ) p ( a - b ) ^ w i t h p as the proba- b i l i t y of l o s i n g (-b amount).of the choice minus the product of the rank and the p r o p o r t i o n of the variance of the choice to the variance l a r g e s t i n the s e t . A t o t a l score i s derived by adding up these i n d i v i d u a l scores. In mathematical termsi 56 where r c ^ represents the rank of the o p t i o n chosen i n set i; V c i , the v a r i a n c e of the option chosen; and V^, the l a r g e s t variance of set i . 7. U t i l i t y Scores - The s c o r i n g method employed essen- t i a l l y i s s i m i l a r to the one B a s s l e r used i n h i s d i s s e r t a t i o n (1972). The h o r i z o n t a l d e v i a t i o n between the c e r t a i n t y equiva- l e n t s and the expected value i s d e r i v e d f o r each item. Then, t h i s value i s converted i n t o percentage terms ( i . e . , as a per- centage of Expected Value). The percentage d e v i a t i o n s are summed and averaged. This s c o r i n g method i s done f o r r a t e of r e t u r n u t i l i t y questions, net p r o f i t and compensation. As f o r the s c a l e of wager, we have e s s e n t i a l l y the f o l l o w i n g to express the aggregate score 1 Score = n \ h d j , 1=1 where n i s the number of no answers to the wagers ( i . e . , t h a t the subject w i l l not take the wager), and hd^ i s the h o r i z o n t a l d e v i a t i o n of the amount he would pay f o r the wager ( i ) from the expected value of wager ( i ) . Discussion We have presented here the nature of the items used. The s c o r i n g convention, except i n the case of Extremity score, i s t h a t higher scores r e f l e c t higher r i s k a v e r s i o n . In the next chapter, we w i l l d i s c u s s the methodology i n - volved i n a d m i n i s t e r i n g these instruments and the nature of the subjects i n v o l v e d . 57 Far from p e r f e c t , we f e e l t h a t c e r t a i n improvements may he made on the instruments. Some amount of a t t e n t i o n has "been taken i n the c o n s t r u c t i o n of the package. We a l s o hope th a t we have learned from the mistakes of the past researchers to come up w i t h a reasonable package. We are not a s s e r t i n g t h a t t h i s package contains a l l the a l t e r n a t i v e s to studying business-monetary r i s k t a k i n g . We are however confident t h a t the instruments are u s e f u l i n r e - search of t h i s nature. The e m p i r i c a l study c a r r i e d out i s not f o r v a l i d a t i n g the package but i s f o r an in-depth a n a l y s i s of a p a r t i c u l a r group of i n d i v i d u a l s whose r i s k - t a k i n g tendencies we are i n t e r e s t e d i n . Some attempts at item analyses w i l l be made. But, con- s i d e r i n g the nature of our sample, these analyses must be read w i t h care. A l s o , we would l i k e t o determine whether or not some of the conclusions concerning r i s k t a k i n g , drawn by past r e - searchers, s t i l l hold f o r our group. 58 CHAPTER 5 THE DESIGN OF THE STUDY Subjects Used T h i r t y - f i v e Graduate Students i n Business A d m i n i s t r a t i o n of the U n i v e r s i t y of B r i t i s h Columbia completed the sets of instruments we have o u t l i n e d i n Chapter f o u r . These subjects were s o l i c i t e d s t r i c t l y on a vo l u n t a r y b a s i s w i t h guarantee of anonymity. They were a l l Master's students w i t h d i f f e r e n t options. The o r i g i n a l i n t e n t i o n had been to secure at l e a s t f o r t y s u b j e c t s . F i f t y copies of the f i r s t s e t , c o n s i s t i n g of the choice dilemma, extremity-confidence and A c t i v i t y I n t e r e s t were handed out, and at l e a s t f o r t y In-Basket questionnaires and personal records sheets were d i s t r i b u t e d . But because of the amount of time i n v o l v e d , only 3 5 completed the e n t i r e s e t s . The subjects were drawn from three M.B.A. cl a s s e s w i t h the cooperation of the p r o f e s s o r s i n v o l v e d and from students who frequent the U.B.C. Commerce Graduate Reading Room. The three M.B.A. courses were i O r g a n i z a t i o n a l Behavior, P o l i c y , and Dec i s i o n Making. Procedure Used Because there i s a p o s s i b i l i t y of subjects b e l i e v i n g t h a t r i s k t a k i n g i s a value and th e r e f o r e responding to the items i n order to appear as r i s k t a k e r s , the design has been to d i s - guise the v a r i o u s measures as some s o r t of a package of d e c i s i o n - making e x e r c i s e s . 59 The f o l l o w i n g i n f o r m a t i o n sheet accompanied the f i r s t set of instrumentsi INFORMATION SHEET A STUDY OF INDIVIDUAL DECISION MAKING BY A l f r e d C. Kwong Graduate student, Faculty of Commerce and Business A d m i n i s t r a t i o n , U n i v e r s i t y of B.C. As p a r t of a Master's Thesis on the development of a D e s c r i p t i v e D ecision Making Theory, we are attempting to o b t a i n volunteers f o r the study. P a r t i c i p a t i o n w i l l i n v o l v e responses to a s e r i e s of decision-making exer- c i s e s and questionnaires and a l l responses w i l l be kept ANONYMOUS. The v a r i o u s research instruments have been approved by the U n i v e r s i t y Screening Committee and we have obtained a C e r t i f i c a t e of Approval f o r Procedures i n Research and Other Studies I n v o l v i n g Human Subjects. The e n t i r e study i n v o l v e s the development of a package of Business Decision Making measures intended f o r r e - search i n t o Decision Making s t y l e s , p a t t e r n r e c o g n i t i o n , i m p l i c i t h e u r i s t i c s , s t r a t e g y a v a i l a b i l i t y , and D e c i s i o n Making p e r s o n a l i t y c o r r e l a t e s , and a p r e l i m i n a r y a p p l i - c a t i o n of these instruments on a smaller sample. The package contains the f o l l o w i n g i 1. An i n d i v i d u a l q u e s t i o n n a i r e 2. A choice of wagers problem 3. An event occurrence and a c t i v i t y i n t e r e s t q u e s t i o n n a i r e . 4. Extremity-Confidence i n Judgment Questions 5. An In-Basket E x e r c i s e 6. "Choice Dilemma" Questions ?. U t i l i t y Functions on a number of dimensions. A l l i n d i v i d u a l r e s u l t s w i l l be CONFIDENTIAL, although your own p r o f i l e w i l l be made a v a i l a b l e to you i f you wish i t . Since research instruments may be administered at d i f f e r e n t times, p a r t i c i p a n t s w i l l be asked to s e l e c t t h e i r own s i x d i g i t code number and use t h i s on a l l of the q u e s t i o n n a i r e s , e t c . , so t h a t we can assemble a l l m a t e r i a l s f o r each r e s - pondent. From the p o i n t of view of p a r t i c i p a n t s , going through the s e r i e s of e x e r c i s e s and questionnaires w i l l enable them to increase t h e i r understanding of t h e i r own d e c i s i o n making s t y l e s and. p r o f i l e s i n s i t u a t i o n s of u n c e r t a i n t y and com- p l e x i t y . A l s o , as a l e s s e r inducement, p a r t i c i p a n t s w i l l 60 be given the opportunity to engage i n an a c t u a l choice of wagers s i t u a t i o n s where expected winnings w i l l be provided. Thank you. We hope you f i n d the s e r i e s of ques t i o n n a i r e s and e x e r c i s e s i n t e r e s t i n g . We f e l t t hat the e n t i r e package, i f given out a l l at once, could be viewed by our subjects as extremely time-consuming and d i f f i c u l t . Guided by t h i s c o n jecture, the package was d i v i d e d i n t o three s e t s i two "take-home" packages and one " i n t e r a c t i v e " package. These are of the f o l l o w i n g i Take Home Set 1 i 1. Choice Dilemma Questionnaire 2. A c t i v i t y I n t e r e s t and Event Occurrence Q. 3 . Extremity-Confidence i n Judgment Take Home Set 21 1. In-Basket 2. Personal Records I n t e r a c t i v e Set 3» 1. U t i l i t y Measures 2. Stock P r i c e Wagers The v e r b a l i n s t r u c t i o n was tha t they could f i l l out the quest i o n n a i r e s anytime they were f r e e , not n e c e s s a r i l y at one s i t t i n g . The i n t e r v a l between set s i s at l e a s t one week, making sure that the subject has f i n i s h e d the p r i o r set before going on to the next. The i n t e r a c t i v e set i s administered w i t h the experimenter present because the stock p r i c e wagers must be played out. Be- cause the l a s t set r e q u i r e s both experimenter and su b j e c t , s e v e r a l sessions were held depending upon the a v a i l a b i l i t y of the s u b j e c t s . The u t i l i t y items are in c l u d e d i n t h i s set by convenience, as mentioned before. 61 Data-gathering had been d i f f i c u l t on the personal records ques t i o n n a i r e "because some of the questions, as viewed by the s u b j e c t s , were "too p e r s o n a l " and many feared that t h e i r anony- mity was i n jeopardy. I n s t r u c t i o n s to the Subjects Presented below are the i n s t r u c t i o n s to the questionnaires we handed out (except f o r the u t i l i t y items which were b a s i c a l l y question-and-answer form w i t h the heading U t i l i t y Questionnaire and the Personal Record Questionnaire). 1. Choice Dilemma Items I.D. No. On the f o l l o w i n g pages you w i l l f i n d a s e r i e s of s i t u a t i o n s t h a t can occur i n business. The c e n t r a l per- son i n each s i t u a t i o n i s faced w i t h a choice between a l t e r n a t i v e courses of a c t i o n . In these ten s i t u a t i o n s , the c e n t r a l person has two a l t e r n a t i v e s . The outcomes of one of the a l t e r n a t i v e s may be more a t t r a c t i v e than those of the second} however, the r e a l i z a t i o n of these outcomes i s u n c e r t a i n . For each of the ten s i t u a t i o n s you are asked to i n d i c a t e the m i n i - mum chance of success you would demand before recommending t h a t the u n c e r t a i n a l t e r n a t i v e be chosen. Read each s i t u a t i o n c a r e f u l l y before g i v i n g your answer or judgment. Try to place y o u r s e l f i n the p o s i - t i o n of the c e n t r a l person i n each s i t u a t i o n . There are ten s i t u a t i o n s i n a l l ; please make your recommendations i n a l l of them. Als o , please do the f o l l o w i n g t a s k J Rank the items according to the impact of the consequences on the l i v e s of the c e n t r a l persons i n v o l v e d (which means t h a t , given a l i m i t e d time schedule f o r a d v i s i n g , you would want to order your appointments f o r these persons i n accordance w i t h the e f f e c t s of the d e c i s i o n s on t h e i r l i v e s ) . 62 ITEM RANK* 1. 2. 3 . 4 . 5. 6. 7. 8. 9. 10. * G i v i n g the one t h a t would have the g r e a t e s t impact 1, the next 2 and so f o r t h down to the one having the l e a s t impact r e c e i v i n g a rank of 10. I I . Extremity Confidence i n Judgment This q u e s t i o n n a i r e w i l l help us f i n d out about people's opinions about v a r i o u s t h i n g s . Each item i n the q u e s t i o n n a i r e w i l l decide a s p e c i f i c event. We want your op i n i o n as to how l i k e l y each event i s . A l l of the items i n the t e s t w i l l be of the form i n which you e s t i - mate the number of chances out of 100 t h a t a s p e c i f i c event occurs. Thus, i f you judge an event to be u n l i k e l y , you'd w r i t e a number c l o s t to 0; i f you judge an event to be l i k e l y , you would w r i t e a number clo s e to 100; and i f you judge an event to be about e q u a l l y l i k e l y or u n l i k e l y , you would w r i t e a number clo s e to 50. We a l s o want you to i n d i c a t e how sure you are of your opinions. So, a f t e r you have decided how l i k e l y an event i s we want you to i n d i c a t e how confident you are of t h i s judgment by c i r c l i n g one of the 5 c a t e g o r i e s below each question. i Please do not s k i p any questions. I I I . Event Occurrence and A c t i v i t y I n t e r e s t Questionnaire t This i s a q u e s t i o n n a i r e to f i n d out the way i n which c e r t a i n important events i n our s o c i e t y a f f e c t d i f f e r e n t people. Each item c o n s i s t s of a p a i r of a l t e r n a t i v e s l e t t e r e d a or b. Please s e l e c t the one statement of each p a i r (and only one) which you more s t r o n g l y b e l i e v e to be t r u e r a t h e r than one you think, you should choose or the one you would l i k e to be t r u e . This i s a measure of personal b e l i e f s i o b v i o u s l y , there are no r i g h t or wrong answers. 63 Please answer these items on t h i s inventory care- f u l l y hut do not spend too much time on any one item. Be sure t o f i n d an answer to every item. In some cases, you may di s c o v e r t h a t you b e l i e v e both statements or n e i t h e r one to be t r u e . In such cases, be sure to s e l e c t the one you more s t r o n g l y b e l i e v e to be the case as f a r as you are concerned. A l s o , t r y to respond t o each item independently when making your choice; do not be i n f l u e n c e d by pre- vious choices. IV. In Basket E x e r c i s e ; Please do t h i s work i n your room which w i l l become your " p r i v a t e o f f i c e " f o r f o r t y minutes. You w i l l work as i f you were B i l l B i c k n e r , V i c e - P r e s i d e n t , North American Operations of the M u l t i n a t i o n a l Products I n t e r - n a t i o n a l Co. You j u s t a r r i v e d i n t h i s new job, having come from the Connecticut s u b s i d i a r y where you were i t s p r e s i d e n t . Your predecessor, Mr. James Norton, died of a heart attack l a s t week. You were n o t i f i e d very r e c e n t l y of t h i s new assignment and have had l i t t l e time t o become acquainted w i t h the job. Today i s Wednesday, May 14, 1972. You have j u s t a r r i v e d i n the o f f i c e at 7»45 p.m. and must leave promptly at 8t25 p.m. t o catch the 9»30 plane to Mexico C i t y f o r an important meeting. You w i l l not be back u n t i l Thurs- day, May 23, 1972. The m a t e r i a l s i n the package were l e f t i n your i n - basket on your desk by your s e c r e t a r y . You are to go through the e n t i r e packet of m a t e r i a l s by reading them and t a k i n g whatever a c t i o n you deem appropriate on each item. Since your a s s i s t a n t w i l l take charge of the a c t u a l d r a f t i n g of the l e t t e r s and as there i s l i t t l e time f o r you t o w r i t e these f o r m a l l y , every a c t i o n you wish to take should be w r i t t e n down i n note form or i n w i r e s , where a p p r o p r i a t e , e i t h e r to y o u r s e l f , to your a s s i s t a n t or to the person concerned. Be sure to i n d i - cate i n the notes and/or wires to whom they are addressed. Please w r i t e the note and/or wires on the enclosed Memo sheets. You are to use your own experience as the ba s i s of your a c t i o n i n assuming the r o l e of B i l l Bickner. NOTE'. .. THE DAY IS WEDNESDAY, MAY 15, 1972. TIME» 7>45 P.M. THE TELEPHONE SWITCHBOARD IS CLOSED. 64 WRITE DOWN EVERY ACTION YOU TAKE ON ANY ITEM. YOU CANNOT CALL ON ANYONE FOR ASSISTANCE. YOU MUST WORK WITH THE MATERIALS AT HAND. YOU WILL BE OUT OF OFFICE FROM 8t25 UNTIL NEXT THURSDAY MAY 23, 19?2. YOU CANNOT TAKE ANY OF THE MATERIALS WITH YOU ON THE TRIP. BE SURE TO RECORD EVERY ACTION Please do your work i n the f o l l o w i n g order given below. You w i l l have 40 minutes f o r question 1 and 10 minutes f o r questions 2, 3, and 4. 1. Please c a r e f u l l y read the correspondence and w r i t e your response to each of the 7 items on the enclosed Memo sheets. 2. A f t e r you have w r i t t e n a response t o a l l 7 items, please t u r n to the Questionnaire formCblue cover page). The f i r s t q uestion asks you to f i r s t rank the 7 items i n terms of importance ( i . e . , the seriousness of the p o s s i b l e consequences). This can be done by s o r t i n g your w r i t t e n memos i n order of importance. Next you are asked t o r a t e each of the items. This should be done by g i v i n g the most important item 100 po i n t s and then g i v i n g the other 6 items p o i n t s on the b a s i s of how they stand i n r e l a t i o n to t h i s . Please place t h i s r a t i n g number on the top right-hand corner of each of the 7 memos. 3. A f t e r you have r a t e d the 7 items, read Part B of the Questionnaire. This asks f o r the switch-over chance between a l t e r n a t i v e s f o r f o u r of the items. 4. A f t e r Part B, read and complete Part C of the Questionnaire which asks f o r a d e s c r i p t i o n of some of the correspondents. V. Wagers on Stock P r i c e s The p r i n t e d i n s t r u c t i o n s were as f o l l o w s i On the next few pages you w i l l be presented w i t h sets of opt i o n s . The sets are l a b e l l e d A, B, C, D and E. In each set. there are 5 options and you w i l l be asked to s e l e c t the one option you most p r e f e r i n each s e t . In each set one of the options i s r e c e i v i n g $2 f o r sure, w h i l e the other f o u r options are wagers and i n - v o l v e a.chance of winning more than $2, but u s u a l l y a chance of l o s i n g money too. The chance of winning i s shown f o r each wager. In set A, B, and E each of the 65 options has expected winnings of $2. (This means that i f any one was played a l a r g e number of times the winnings would average out to $2 per time.) In s e t s G and D, the expected winnings are d i f f e r e n t f o r each o p t i o n and are shown there. We want you t o t h i n k through the options i n each set and to s e l e c t the one you most p r e f e r . A f t e r you have done t h i s f o r a l l the s e t s , we s h a l l s e l e c t a set at random and then p l a y out the o p t i o n you chose i n that s e t . I f the r e s u l t i s t h a t you win money, we w i l l pay you immediately, w h i l e i f the r e s u l t i n d i c a t e s t h a t you l o s e money we expect immediate payment from you. A l l the wagers are based on the f r a c t i o n a l p a r t of the p r i c e s of f i v e stocks on the New York Stock Ex- change. You win i f the f r a c t i o n a l amount of a stock's p r i c e i s 1/8, 3/8 or 5/8 w h i l e you l o s e i f the f r a c - t i o n a l amount i s 1/4, 1/2, 3/4, 7/8 or a whole number. Studies of the stock market have shown t h a t no one ending amount i s more l i k e l y than any other f o r stocks i n the p r i c e range we s h a l l c onsider. The wagers i n each set d i f f e r i n the number of stocks out of the f i v e t h a t must have the winning f r a c t i o n a l amounts. As the number increases from "at l e a s t 1 out of 5" "to "at l e a s t 4 out of 5", "the chances of winning get s m a l l e r w h i l e the payoffs get l a r g e r . We have a page l i s t i n g 100 stocks a c t i v e l y traded on the New York Stock Exchange. They were chosen ran- domly from stocks under $50. The f i v e stocks to be used i n determining the payoffs w i l l be s e l e c t e d ran- domly. The f r a c t i o n a l p r i c e we s h a l l use i s the one f o r these stocks at the c l o s e of t r a d i n g on September 8, 1972. Because there were c e r t a i n research questions we wanted to c l a r i f y , v e r b a l i n s t r u c t i o n s amended the p r i n t e d q u e s t i o n n a i r e i n s t r u c t i o n s and were as follows i "Instead of s e l e c t i n g j u s t one o p t i o n i n each s e t , please rank the options i n the s e t s according to your preference. Also a f t e r you've done t h a t f o r a l l the s e t s , rank the s e t s now according to your preference. The method of s e l e c t i n g the set and the o p t i o n w i l l be based on your preference." 66 The l a s t sentence had been l e f t vague because there i s a f e a r , on the experimenter's p a r t , t h a t once the subject made h i s f i r s t c h o i ce, he would rank the r e s t haphazardly. This l a s t sentence would make the subject b e l i e v e t h a t the way he ranked h i s preferences would a f f e c t the way the option was s e l e c t e d . In p l a y i n g out the o p t i o n , of course, the "top" choice would be used, except i n the case where Set C ( i n c r e a s i n g ex- pected winnings as p r o b a b i l i t y of winning i n c r e a s e s ) was chosen as the f i r s t c hoice. The reason given was t h a t "the experimenter stands to l o s e more i f set C i s played out." Because some of the subjects knew the experimenter person- a l l y , i t was f e l t t hat t h i s could a f f e c t the way they chose t h e i r b e t s — i . e . , t h a t "they wouldn't want to 'win* t h a t much from A l f r e d c o n s i d e r i n g t h a t he i s u s i n g money from h i s own pocket." The only method to get t h i s undesirable e f f e c t out of the way was to say t h a t the money came from the research funds of the Industry, Trade & Commerce Department (see Acknowledg- ment ). The money i n the denomination of two's was placed i n f r o n t of the subjects i n order to give the s e s s i o n more authen- t i c i t y . Conclusion The study was c a r r i e d out over a five-week p e r i o d . The a n a l y s i s t h a t i s to f o l l o w i s based on these 35 s u b j e c t s . On the whole, 35 i s not such a l a r g e sample nor can one c a l l the sampling random. However, given the amount of time needed to 67 read through the items and respond t o the q u e s t i o n n a i r e s , the sample of 35 subjects i s not considered bad. Even though "ran- dom" sampling design was o r i g i n a l l y conceived, under p r a c t i c a l circumstances, f r u i t i o n of our i d e a was not p o s s i b l e due to the "voluntary" aspects of the study. 68 CHAPTER 6 AN ANALYSIS OF THE MEASURES AND ITEMS IN THE PACKAGE Overview Because of the number of questionnaires administered, a voluminous amount of a n a l y s i s may be undertaken on the r e s - ponses. However, b r e v i t y d i c t a t e s t h a t only a n a l y s i s r e l a t i n g to c e n t r a l l y - i m p o r t a n t questions should be presented. For the i n d i v i d u a l measures, the a n a l y s i s i n t h i s chapter i s presented w i t h the f o l l o w i n g s u b s e c t i o n s i A. Score(s) - r e i t e r a t e s how the s c o r e ( s ) of the question- n a i r e i s / a r e d e r i v e d . B. D i s t r i b u t i o n ( s ) - shows the frequency, d i s t r i b u t i o n ( s ) of the s c o r e ( s ) computed i n A, and the i m p l i c a - t i o n s they c a r r y . C. Item D i s t r i b u t i o n ( s ) - presents the frequency d i s t r i b u - t i o n (s) of item(s) whose responses are d i s t r i - buted i n an i n t e r e s t i n g way. D. Item Analyses - discusses e i t h e r the i n t e r c o r r e l a t i o n s of items w i t h each other or c o r r e l a t i o n ( s ) of the items w i t h the aggregate sc o r e ( s ) and the reasons behind the r e s u l t s . E. Issues concerning measures - examines some of the research questions posed by past researchers and the issues r a i s e d by the t h e s i s . F. Q u a l i t a t i v e Analyses - presents some comments of the s u b j e c t s i n response to the measure. (Optional as t h i s may not be r e l e v a n t . ) Because of the uniqueness of the sample and the way the subjects were s e l e c t e d , g e n e r a l i z a t i o n from the r e s u l t s of t h i s study may not be p o s s i b l e . But, 'confirmation' and/or r e j e c t i o n s 69 of the v a r i o u s conclusions posed by past researchers as they stand w i t h our group are i n themselves i n t e r e s t i n g . In Basket A. Three scores are derived from the q u e s t i o n n a i r e . The Memo score, which i s the average of the 'str a t e g y ' score the subject r e c e i v e s i n each item, may be generated i n three ways. The minimum odds score, which i s the mean of the minimum odds subjects assigned to the items, may be generated i n two ways. The semantic d i f f e r e n t i a l score i s j u s t the sum of the four semantic d i f f e r e n t i a l sub-scores (see Chapter 4 ) . The codes f o r the s t r a t e g i e s i m p l i e d by the s u b j e c t s ' responses aret 1 f o r t a k i n g the r i s k y a l t e r n a t i v e u n c o n d i t i o n - a l l y , 2 f o r t a k i n g the r i s k y a l t e r n a t i v e under c e r t a i n circum- stances, 2 f o r t a k i n g the conservative a l t e r n a t i v e i f c e r t a i n c o n d i t i o n s were met, 4 f o r t a k i n g the conservative a l t e r n a t i v e u n c o n d i t i o n a l l y , _\ f o r gathering i n f o r m a t i o n and 6 f o r delay. A value of 9 i s assigned to responses t h a t are not r i s k r e l e v a n t — i . e . , o r g a n i z a t i o n a l c o n s i d e r a t i o n , happiness, e t c . In gener- a t i n g the three p o s s i b l e memo scores, a l l 9's are excluded. The d i f f e r e n c e of these three memo scores l i e s i n the treatment of the 5's and 6's. I f delay and gathering more inf o r m a t i o n are more r i s k - averse acts than t a k i n g the conservative a l t e r n a t i v e , then the memo score should i n c l u d e them as 5's and 6's. However, one can argue t h a t delay and gatheri n g i n f o r m a t i o n are more r i s k - prone s t r a t e g i e s , and t h a t they should l i e between 2 and 3 70 ( i . e . , more r i s k - a v e r s e : than t a k i n g the r i s k y a l t e r n a t i v e con- d i t i o n a l l y and more ri s k - p r o n e than t a k i n g the c o n d i t i o n a l con- s e r v a t i v e a l t e r n a t i v e ) . Another contention i s th a t s i n c e we do not know about delay and more i n f o r m a t i o n g a t h e r i n g , and t h e i r r i s k t a k i n g i m p l i c a t i o n s , these s t r a t e g i e s should be excluded from the c a l c u l a t i o n of the aggregate memo score. Since we are not sure of where the delay and inf o r m a t i o n g a t h e r i n g s t r a t e g i e s l i e i n the r i s k t a k i n g continuum, an aggre- gate score which excludes them i s r e l i e d upon as the memo score. However, as a d d i t i o n a l a n a l y s i s i n p u t s , two other memo scores are generated. One i s to in c l u d e these s t r a t e g i e s as 5's and 6's; another i s to t r e a t them as 2.5's. The minimum odds score may e i t h e r be generated as a simple average of the odds su b j e c t s assigned i n the items or an average of the odds u s i n g the grades assigned as weights. The former i s r e l i e d upon as the score because the grades may not t u r n out to be r e l i a b l e as weights. In the l a t e r subsections, we w i l l d i s - cuss what scores are r e t a i n e d . B. Figure 6-1 gives us a breakdown of the memo scores (5's and 6*s excluded) and t h e i r frequency. The mean of the memo scores i m p l i e s that the s u b j e c t s ' s t r a - tegy u s u a l l y i s between t a k i n g a r i s k y a l t e r n a t i v e provided c e r - t a i n c o n d i t i o n s are met and t a k i n g a conservative a l t e r n a t i v e i f c e r t a i n circumstances could be changed. However, the 2.35 r e s u l t can be enterpreted as u s u a l l y t a k i n g the c o n d i t i o n a l r i s k y a l t e r - n a t i v e i f one considers the d i s t a n c e . Only one subject p r e f e r s the conservative a l t e r n a t i v e u n c o n d i t i o n a l l y throughout the items as i n d i c a t e d by the f o l l o w i n g f i g u r e . 71 No. of Subjects 10 9 "7 £ 5 0 PIG. 6-1 Histogram, Aggregate Memo Scores 31.+% 2S.7% Z9% 2O.0% 1 7 2 % 2.9% i 1-33 Mean i - 2 . 3 5 8 Range* 2 . 3 3 Variance 1 0 . 2 0 1 Median 1 2 . 2 9 1.67 2.33 2.67 3.33 367 Memo S c o r e 4 monz risk aw-nse F i g . 6 - 2 i l l u s t r a t e s how the aggregate minimum odds scores are d i s t r i b u t e d . The group would on the average accept the r i s k y proposals i f the minimum odds f o r success were 6 out of 1 0 , a l i t t l e b e t t e r than the odds o f f e r e d i n a c o i n t o s s . 72 FIG. 6-2 Histogram, Minimum Odds Scores No. of Subjects 10 30.3% 30.3% 9.1% 6.1% • i 1.5 3.5 4.5 5.5 65 7.5 8.5 Meani 5-752 Mediant 5.9 Range i $,±k V a r i a n c e i 1.48 iflore. nsV?-averse. 9 ' 5 M i M . o d a (oof of 10) Figure 6-3 i l l u s t r a t e s how the semantic d i f f e r e n t i a l (S.D.) scores are d i s t r i b u t e d . I t should be noted that the S.D. score i s the value assigned to a su b j e c t ' s p e r c e p t i o n of the r i s k a v e r t e r s i n the items (where the r i s k t a k e r s are assigned as negative r i s k a v e r t e r s i f they happen to be the h y p o t h e t i c a l l e t t e r w r i t e r s ) . 73 FIG. 6-3 Histogram, S.D. Scores No. of Subjects 10 - I O O ¥ 33.394 2 4 . 1 % 6.1% 3% 90 -70 -50 Meani -12.441 Variance! 791.04 Range i . 152 Mediant -11.00 3% 36 -10 tO 3o 50 lO wore nafc averse •W- SD Scores The mean S.D. score i n d i c a t e s t h a t r i s k takers are per- ceived i n a p o s i t i v e manner, or r i s k a v e r t e r s i n a negative way. This i s a rough c o n f i r m a t i o n of the r i s k - t a k i n g - a s - a - v a l u e con- c l u s i o n of the past. However, the spread of the d i s t r i b u t i o n , i f taken i n t o aecount, i n d i c a t e s t h a t the degree of favorable or unfavorable assessment of r i s k t akers v a r i e s from one assessor to the other. 74 As i n d i c a t i o n of the seriousness of the consequences i m p l i e d by the r i s k y a l t e r n a t i v e i n each item, the sub j e c t s assigned "grades" (numbers out of 100) to the items. An aver- age grade assignment i s generated and the d i s t r i b u t i o n i s shown i n F i g . 6-4. FIG. 6-4 Histogram, Average Grade Assigned to the Items No. of Subjects to 32.2% 32.2.% 1*3% 3.5% 3.5% If* 4A * ^ m — > Meani 67.74 Median 1 69.8 Range 1 65.7 Variances 15«86 Average. Grade Assigned. The occurrence of one score at the 10-20 l e v e l suggests that t h i s subject f a i l e d to f o l l o w i n s t r u c t i o n s when a s s i g n i n g 75 grades. The t i g h t n e s s of the d i s t r i b u t i o n , excluding the extreme 10-20 one, i n d i c a t e s roughly that the subjects con- verge i n s e v e r i t y p e r c e p t i o n . C. Table I gives us a breakdown of s t r a t e g y scores by items and the frequency of these scores. TABLE I Memo Scores By Item, R e l a t i v e Frequency and Median Item ^ \ No. "1 2 3 4 5 6 - 7 Value \ ^ Rel. Freq. R.F. R.F. R.F. R.F. R.F. R.F. 1 2 3 4 5 6 . 9 45-7$ 17.1 0.0 22.9 11.4 2.9 0.0 26.5$ 14.7 0.0 17.6 2.9 0.0 38.2 48.6 11.4 5.7 20.0 5.7 5.7 2.9 17.1 28.6 17.1 17.1 11.4 0.0 8.6 5.7 2.9 5.7 74.3 8.6 0.0 2.9 51.4 8.6 0.0 5.7 20.0 0.0 14.3 37.1 2.9 5.7 34.3 8.6 0.0 11.4 Medians 1.875 3.750 1.625 2.75 3.9-81 1.472 3.625 I f we are to i n f e r r i s k t a k i n g a t t i t u d e s from the s t r a t e g i e s recommended, items t h a t e l i c i t non r i s k c o n s i d e r a t i o n should be subject to c o r r e c t i o n or e l i m i n a t i o n . Item 2, concerning the son's d e s i r e to enter i n t o a r i s k y c a reer, e l i c i t e d responses l i k e "Do what you're happy i n , " " I f t h a t ' s what you want, go ahead," e t c . , and has the l a r g e s t frequency of 9's among a l l the items. Item 6, concerning the p o s s i b i l i t y of marketing a new pro- duct, has the lowest median and the l a r g e s t frequency i n the 76 r i s k - t a k i n g s t r a t e g y score c l a s s . The i n c l i n a t i o n of the sub- j e c t s i s to open up markets f o r new products even though the r i s k i s gre a t . As f a r as delay i s concerned, only items 1 and 3 ("the f i r s t item concerning a p o s s i b l e court s u i t and the l a t t e r , the p o s s i b i l i t y of not supplying a steady customer i n preference of a new unstable buyer) e l i c i t e d the delay s t r a t e g y . Responses l i k e "wait u n t i l I r e t u r n " or " t e l l him I ' l l t a l k to him l a t e r " are coded as delay. Items 6 , 1, and 4 e l i c i t e d g a t h e r i n g - i n f o r m a t i o n s t r a t e g i e s . The t a b l e r e v e a l s t h i s c l e a r l y . As we s a i d before, item 6's median i s the lowest among the other items; but some students f e e l t h a t they should not t r y the new product out u n t i l more in f o r m a t i o n can be secured. Item 1 a l s o i s deemed by some students (11.4$) to r e q u i r e more in f o r m a t i o n before any a c t i o n i s taken. Eleven percent of the sub j e c t s a l s o recommend g e t t i n g more i n f o r m a t i o n before t a k i n g any a c t i o n — e i t h e r r e c a l l i n g the Time and Motion man who had offended the Union or c o n t i n u i n g the study. In item 5, Bickner i s being asked by h i s f r i e n d to q u i t h i s job and j o i n him i n a r i s k y venture. Here, the sub j e c t s f e e l t h a t Bickner, being already secure i n the company, should stay on. Thus, a m a j o r i t y of the s u b j e c t s favor the conserva- t i v e a l t e r n a t i v e . D. As revealed by Table I I , the i n t e r - i t e m c o r r e l a t i o n s of the memo scores are very poor. This suggests that the s t r a - tegy employed v a r i e s very much, and t h a t the conversion of 77 strategy recommendations into scores may be inconsistent. This suggestion implies that the method of judging the r i s k taking attitudes of the subjects might have been inadequate. Table III gives us an idea of the minimum odds assigned i n each item and t h e i r relationships with the aggregate score. A l l items are correlated with the aggregate score but the inter-item correlations are very poor. TABLE II Correlation Matrix, Item No. 1 Memo Scores by Item 2 3 4 5 6 7 Ag. Memo Sc. 1 (-.426) -0.067 - . 2 3 .22 - .27 -0.07 .254 2 -.08 .22 (- .44) .32 .15 .247 3 -.13 -.12 - . 2 9 .05 (.33) 4 (-.36) .08 .20 (.424) 5 .15 - . 2 9 .14 6 -.28 .08 7 (.51) Ag. Memo Sc. Coeffic i e n t s enclosed:' i n parenthesis are s i g n i f i c a n t ( p^ 0 . 0 5 ) . TABLE III Correlation Matrix Minimum Odds Scores by Item Item No. 1 2 3 4 5 6 7 Ag. Score 1 (.46) (.35) -0.019 .12 .08 -.14 (.429) 2 (.37) -.14 -.004 (.38) - . 2 0 (.471) 3 (.38) - .013 (.48) .12 (.758) 4 .05 (.33) .24 (.616) 5 .03 .17 (.29) 6 .02 (.63) 7 (.37) Coeffi c i e n t s e n e l o s e d i n parenthesis are s i g n i f i c a n t (p< 0 . 0 5 ) . 78 Item* 5 i s "by f a r the weakest i n c o r r e l a t i o n w i t h the aggre- gate score. Because i t a l s o f a i l e d t o d i s c r i m i n a t e i n the s t r a - tegy responses (with 74$ recommending t a k i n g the c o n s e r v a t i v e a c t i o n ) t h i s i s an item t h a t should be removed. Table IV gives us the i n t e r c o r r e l a t i o n s of the semantic d i f f e r e n t i a l scores. The Aggregate S.D. score c o r r e l a t e s h i g h l y w i t h each of the S.D. scores but the inter-number c o r r e l a t i o n s t u r n out to be weak. TABLE IV C o r r e l a t i o n Matrix Semantic D i f f e r e n t i a l Scores Number Moore Paul Taylor Kaye Ag. S.D. Score Moore -0.09 .17 (-.33) (.437) Paul -.182 -.004 (.789) Taylor (.32) (.615) Kaye ._. (.382) S.D. Score C o e f f i c i e n t s enclosed i n parenthesis are s i g n i f i c a n t at 0.05 l e v e l . The item analyses f o r the In-Basket r e v e a l t h a t the ques- t i o n n a i r e should somehow be r e v i s e d . The r e s u l t i n g weak i n t e r - item c o r r e l a t i o n s suggest t h a t the v a l i d i t y of the items i s questionable. This q u e s t i o n n a i r e , we have to remember, r e q u i r e s the l a r g e s t p r o p o r t i o n of response time. Although we have created i n t e r e s t i n g s i t u a t i o n s i n each of the items, the amount of time and e f f o r t i n v o l v e d might induce boredom. The s o l u t i o n i s to cut down the number of items and f u r t h e r systematize the s t r a t e g y s c o r i n g method. 79 The memo scores we have generated have not been s a t i s f a c - t o r y . I t s value as a r i s k measure i s thus minimal. However, we are not r e j e c t i n g the value of i n f e r r i n g r i s k t a k i n g a t t i - tudes from s t r a t e g y ; we are saying t h a t there could be some- t h i n g wrong i n our method of judging the memos. E. In order to a s c e r t a i n which of the memo scores ( i . e . , how the 5's and 6's should be t r e a t e d ) , should be r e t a i n e d , the r e l a t i o n s h i p of the three scores w i t h the minimum odds score i s examined. The memo score t h a t excludes the 5's and 6's has the highest c o r r e l a t i o n (r = 0.186) w i t h the minimum odd score (the r's of the second score which i n c l u d e s 5's and 6's and the t h i r d score which t r e a t s 5's and 6 fs as 2 . 5 's are, r e s p e c t i v e l y ! -0.126 and 0.176). However, the c o r r e l a t i o n i s not s i g n i f i c a n t at the 0;05 l e v e l . The weighted minimum odds score, which i s generated by using the grades students assigned as weights, i s delete d be- cause of i t s weak c o r r e l a t i o n w i t h the memo score (r = .103) and w i t h the Aggregate Semantic D i f f e r e n t i a l Score (r = .09). This score i s a l s o found to be u n r e l a t e d to the other r i s k measures l i k e Choice Dilemma (r = -0.015), Stock P r i c e Wager Score (r = 0.08), and Compensation U t i l i t y Score (r = 0.012). The Semantic D i f f e r e n t i a l Score has no s i g n i f i c a n t r e l a t i o n - s h i p w i t h the other In-Basket r i s k measures. I t has a 0.127 w i t h the memo score and a 0.0^7 w i t h the average odd score. Item-wise, the Semantic D i f f e r e n t i a l Score f o r Taylor (the marketing manager who didn't l i k e pushing new, u n t r i e d products) 80 i s the lowest i n mean (-0.206). This i m p l i e s t h a t the s u b j e c t s f i n d Taylor unfavorable and consider him weak, dependent, unsure and c a u t i o u s . Johnny Kaye i s viewed as independent, confident and s t r o n g . He i s thus perceived i n the most p o s i t i v e way (mean = 16.94). However, from the r e s u l t s of the c o r r e l a t i o n of Semantic D i f f e r e n t i a l Scores w i t h other r i s k measures, we have to con- clude that t h i s score may not be considered as a r i s k t a k i n g score. There i s no c l e a r - c u t i n d i c a t i o n t h a t an i n d i v i d u a l who views r i s k t a k e r s i n the most fav o r a b l e way i s h i m s e l f a r i s k t a k e r . For each s u b j e c t , the c o r r e l a t i o n between grade assignment and the average minimum odds i s derived as a p r e l i m i n a r y i n q u i r y i n t o the s e v e r i t y of consequences i s s u e . Because the subjects are asked to a s s i g n grades (out of a maximum of 100) t o the items as i n d i c a t i o n s of the g r a v i t y of the consequences, the hypothesis i s t h a t the higher the grade assigned, the higher would be the minimum acceptable chance be- f o r e the u n c e r t a i n a l t e r n a t i v e i s undertaken. Of the 28 s u b j e c t s who have complete grade assignments, 10 have negative c o r r e l a t i o n c o e f f i c i e n t s (ranging from -0.44 to -0.0?) and 18 have p o s i t i v e values (ranging from 0.85 to 0.056) but only 3 have s i g n i f i c a n t r*s (r > 0.722, df = 6, p"5^ 0.05). Thus, f o r most people, the s e v e r i t y of consequence hypothesis does not h o l d . The p o s s i b i l i t y that people a s s i g n i n g higher grades tend to r e q u i r e higher minimum odds i s examined as an adjunct to the 81 s e v e r i t y of consequence i s s u e . The c o r r e l a t i o n , although p o s i - t i v e , i s not s i g n i f i c a n t at the 0.05 l e v e l (r = 0.26). F. The comments subjects gave a f t e r the In-Basket was administered suggest that the l e n g t h of time i n d i c a t e d on the q u e s t i o n n a i r e i s not accurate. Some subjects mentioned t h a t i t took 2 hours to f i n i s h . Others f e l t t h a t the 45 minutes i n d i - cated time pressure and i f t h i s time l i m i t were complied w i t h , they would not be able to g i v e the q u e s t i o n n a i r e much thought. On the whole, the subjects found the In-Basket extremely i n t e r e s t i n g but f e l t t hat the f a c t s contained i n i t were too much to handle. According to the subjects the items should be trimmed. As f a r as the memo responses were concerned, many f e l t t h a t , although r i s k was taken i n t o c o n s i d e r a t i o n , the idea of an u l t i - matum i n item 3 compelled them to r e j e c t the conservative pro- p o s a l . Others brought i n a n t i t r u s t c o n s i d e r a t i o n and thus con- founded the r i s k - r e l e v a n t s t r a t e g y scores. I t i s a l s o d i f f i c u l t to decide how the s t r a t e g y of 'gathering i n f o r m a t i o n ' should be t r e a t e d . On the one hand, t h i s may be considered more r i s k averse than t a k i n g the conservative a l t e r n a - t i v e immediately, s i n c e g a t h e r i n g i n f o r m a t i o n may be considered an intermediate s t r a t e g y w i t h no commitment to e i t h e r r i s k y or conservative a l t e r n a t i v e . Rather than o u t r i g h t commitment, they are h e s i t a t i n g by g e t t i n g more inf o r m a t i o n ( p o s s i b l y i n order to 'reduce' the r i s k ) . On the other hand, gathering i n f o r m a t i o n i s a r i s k i e r s t r a t e g y than t a k i n g a c o n d i t i o n a l conservative a l t e r - n a t i v e and i s considered intermediate r i s k - t a k i n g i n t h a t the 82 su b j e c t s may perceive g r e a t e r r i s k by gathe r i n g i n f o r m a t i o n s i n c e there i s the p o s s i b i l i t y t h a t a f t e r g a t h e r i n g more i n f o r - mation both options ( i . e . , the r i s k y a l t e r n a t i v e or the conser- v a t i v e a l t e r n a t i v e ) may va n i s h or may not be open t o them. These two contentions concerning gathering i n f o r m a t i o n cannot be r e s o l v e d . The same may be s a i d of the delay s t r a t e g y . Choice Dilemma A. The response of the su b j e c t s i n each item i s a number out of ten. An aggregate score i s derived by averaging these responses. The rankings assigned by subjects t o the items are used f o r the a n a l y s i s i n E. B. The d i s t r i b u t i o n of the aggregate scores i s i l l u s t r a t e d below. 16 t o FIGURE 6 - 5 Choice Dilemma Odds Score Frequency D i s t r i b u t i o n (Histogram) 45.ft% n.5% 2.9% 31.8% 5.7% Z.9% O S 1.5 2 . S 3.5 +.S SS 6 . 5 7 .S 8 .5 9 - 5 Scares 83 The mean of the group i s 6.384 w i t h a s t d . d e v i a t i o n of 0 .886 . Thus, on the average, the group would accept the r i s k y a l t e r n a t i v e as posed "by the ques t i o n n a i r e only i f the minimum odds f o r success i s g r e a t e r than s i x out of t e n , or i f the odds are b e t t e r than those of a c o i n t o s s . A l s o , the shape of the d i s t r i b u t i o n suggests that the group i s f a i r l y homogeneous (the range i s 4 .6 w i t h the minimum value at 4 . 0 ) i n t h e i r responses. .. C. Figure 6-6 gives us a p i c t u r e of how item 3 i s ranked i n r e l a t i o n t o other items. Because i t i n v o l v e s a p o s s i b l y f a t a l o p e r a t i o n , the consequence of the u n c e r t a i n a l t e r n a t i v e i s p erceived to be most severe eighty-one percent of the time. Figure 6-7 i m p l i e s t h a t a m a j o r i t y of the s u b j e c t s , per- c e i v i n g t h i s item to be most severe, recommend t a k i n g the r i s k y a l t e r n a t i v e only when the minimum odd f o r success i s high. The mode odd i s set at 9.000 w h i l e the mean i s 8 . 0 3 . A l s o , no sub- j e c t responded below a minimum odd of 5» Thus the most severe item e l i c i t e d r i s k a v e r s i o n from a l l the s u b j e c t s . 84 FIGURE 6 - 6 Choice Dilemma Rank, Item 3 No. of Subjects 81-0% 2 0 • IO 3.Q% mo!* a 3 severe Mediani 1 . 1 1 1 Modei 1 . 0 0 Variance! 4 . 3 7 7 8 3Q% I I t « a S T Sevcre Frequency Absolute ro FIGURE 6 - 7 Choice Dilemma Odd, Item 3 4 - 0 . 0 % 25.7% 2 2 . 9 % 8 Mediani 8 . 0 5 4 Modei 9 . 0 0 0 more rrsfe-averse IO -> -Odds Cbu+ of 10; 85 D. The i n t e r e o r r e l a t i o r i s of the items w i t h one another are presented i n the t a b l e below. Item 3 i s the only one not s i g n i f i c a n t l y c o r r e l a t e d w i t h the aggregate score. This could be explained by the f a c t t h a t i t i s the only item i n the que s t i o n n a i r e that does not deal w i t h business r i s k . Since t h i s item concerns the p o s s i b i l i t y of a f a t a l o p e r a t i o n , i t may be t r e a t e d as d i f f e r e n t from the r e s t . Item 5 (concerning the p o s s i b i l i t y of i n v e s t i n g a low- income man's i n h e r i t a n c e i n r i s k y s t o c k s ) and item 6 (concerning the p o s s i b i l i t y of a man being convicted f o r treason) have the lowest s i g n i f i c a n t c o r r e l a t i o n s w i t h the Aggregate Score. These two items c o r r e l a t e h i g h l y w i t h one another. However, the mean s e v e r i t y ranks f o r these two are s i g n i f i c a n t l y d i f f e r - ent (9.8 f o r item 5 and 3.7 f o r item 6). The contents or s i t u - a t i o n s i n these two items are not s i m i l a r ; thus, there i s no reason to expect t h a t the two items should c o r r e l a t e only w i t h one another. Improving the measure as a 'business r i s k t a k i n g * measure w i l l e n t a i l the e l i m i n a t i o n of items 3» 5 and 6. The i n t e r - i t e m c o r r e l a t i o n s presented i n Table V show th a t items 8 and 9 (the f i r s t concerning a s a l e s manager's d e c i s i o n to s e l l to a p o l i t i c i a n who might not pay h i s b i l l s and the l a t t e r , a businessman's entry i n t o p o l i t i c s as a candidate) are p o o r l y c o r r e l a t e d w i t h the r e s t . These two items a l s o r e q u i r e m o d i f i c a t i o n and may a l s o be candidates f o r e l i m i n a t i o n . TABLE V Choice Dilemma Item I n t e r c o r r e l a t i o n s Item No. 1 2 3 4 5 6 7 8 9 10 Ag. Score 1 (0.489) -.236 (.483) -.006 .172 (.365) .07 .24 (.54) (.702) 2 (.29) (.29) -.08 (-0.3) .119 .05 -.26 (.36) (.422) 3 .26 -.04 -.27 0.02 .06 -.17 -.19 0.13 4 .03 .22 -."06 -.06 .008 .10 (.47) 5 (.358) .20 .03 .07 -.10 (.3*) 6 -.03 .16 .14 -.13 (.325) 7 .27 .23 (.36) (.57) 8 .07 -.08 (.42) 9 .15 (.39) 10 (.463) Ag. Score C o e f f i c i e n t s enclosed i n parenthesis are s i g n i f i c a n t at O.05 l e v e l . 00 O N 87 E. Kogan and Wallach (1967) asserted t h a t the g r e a t e r the s e v e r i t y of consequences, the more r i s k - a v e r s e the behavior. In order t o examine the r e l a t i o n s h i p between s e v e r i t y of con- sequences and r i s k t a k i n g , a Spearman rho between the sub j e c t ' s rankings of the ten items (as i n d i c a t i o n of the s e v e r i t y of item consequences—with 1 as the most s e r i o u s to 10 as the l e a s t s e r i o u s ) and odds (converted i n t o o r d i n a l s c a l e where rank 1 i s used f o r the lowest minimum odds, etc.) i s generated f o r each s u b j e c t . Because there are only ten items, f o r any c o r r e l a t i o n co- e f f i c i e n t to be s i g n i f i c a n t (at the 5$ l e v e l ) , the value must be l e s s than -0.648. The hypothesized c o r r e l a t i o n should be negative because of the way we order the odds and the ranks. Of the 33 subjects who have complete answers t o t h i s mea- sure, 30 have negative c o e f f i c i e n t s none of which are s i g n i f i - cant (the r's range from -.606 t o -0.042). The remaining three have p o s i t i v e c o e f f i c i e n t s ( r ' s t 0.164 to 0.025). Based on these r e s u l t s , one cannot say t h a t perceived s e v e r i t y of con- sequence i s r e l a t e d to r i s k t a k i n g . Another way of l o o k i n g at the s e v e r i t y of consequence i s s u e i s t o compare the median ranks f o r the items w i t h the mean odd. Table VI summarizes the mean odds of the group f o r each item, the mode rank, and the median rank. Again, there i s no s i g n i - f i c a n t i n d i c a t i o n t h a t the group assigns lower odds (or takes higher r i s k ) to higher ranked ( l e s s severe) items. 88 TABLE VI Mode Ranks of Items, Mean Odd of Items and Median Ranks! Mode Median Mean - Variance Item No. Rank Rank Odd Odd 1 4 4.11 5.34 4.87 2 4 3.85 5.24 4.84 3 1 1.11 7.42 3.35 4 2 3,5 6.78 3.18 5 10 8.86 5.7 5.17 6 2 4.85 7.63 4.4 7 8 6.37 7.79 3.03 8 6 5.81 5.54 5.9 9 7 7.38 5.63 6.11 .. 10 • 10 8.25 .4.26 . 4.11. A n a l y s i s of v a r i a n c e , u s i n g F - d i s t r i b u t i o n , r e v e a l s that the means.of the items are s i g n i f i c a n t l y d i f f e r e n t from one another (p <. .001). This i m p l i e s t h a t items are i n h e r e n t l y different... I f we consider item 3 and item 10, these two being the most extreme i n rankings, the mean odds are s i g n i f i c a n t l y d i f f e r - ent (p 0.05, pooled s t d . d e v i a t i o n = 2.03). The r e l a t i o n s h i p of s e v e r i t y and r i s k t a k i n g , based on the above statement, may r e a l l y be 'discontinuous' i n that the extreme items (the l e a s t and the most.severe) are s i g n i f i c a n t l y d i f f e r e n t from one another i n r i s k t a k i n g responses w h i l e the.ones i n the middle are not. There.is of course the p o s s i b i l i t y t h a t the ranking i n the l e s s extreme cases are not a c c u r a t e l y reported by the subjects because of t h e i r i n a b i l i t y to d i s t i n g u i s h meaningfully among items whose degrees of s e v e r i t y are q u i t e c l o s e . In t h i s case, the rankings of these items become questionable. 89 U t i l i t y Items A. There are e s s e n t i a l l y three scores d e r i v e d . The method of d e r i v i n g the score i s s i m i l a r to what B a s s l e r (1972) did_ i n t h a t the h o r i z o n t a l d e v i a t i o n of the equivalent from the expected value i s taken, converted i n t o percentage term ( i . e . , as a percentage of EV) and summed up. These three scores are t Compensation U t i l i t y score, Net P r o f i t , and Rate of Return. The f i r s t i s a gain equivalent score; the second i s a "buying equivalent score; the t h i r d i n v o l v e s e q u i l i b r a t i n g p r o b a b i l i t i e s and the f o u r t h , the u s u a l c e r t a i n t y equivalent (Swalm). B. The f i g u r e s below i l l u s t r a t e how these u t i l i t y scores are d i s t r i b u t e d . FIGURE 6-8 Histogram Compensation U t i l i t y Scores No. of Subjects t o 3.0% 24% 18.0% 6.1% -0* -O.b Mean; .327 Median: .421 9.a% -0.4- O- 0.2 0.4 o.fe 0-8 3 % 6% Va r i a n c e i .345 Range i 10.156 1 , 6 Utility Score more nsfe averse 90 FIGURE 6-9 Histogram, Net P r o f i t U t i l i t y Scores No. of Subjects to 9.\% 3 3 3 % 3.0% 3.0% * 4 . 3 % e.\% G.\% •ZS -15 0.5 15 25 3.5 4-5 3 0 % Meant .2.131 .Mediant 2.0 Variance! 15-923 Range 1 17.I6.5 sr.5 6.5 T S Net Profit Vrt-ili^ Scores more nsK averse FIGURE 6-10 Histogram, Rate of Return U t i l i t y Scores No. of Subjects. 10 4-% 0.2 OA 08 »0 «Z 1.4 1.6 1.8 J a.o "RR Scopes Mean 1 .202 Variance 1 .104 Range 1 1.965 Mediant .162 mow risK averse 91 The r e s u l t s of the Compensation U t i l i t y Score r e v e a l that one subject has a very extreme value (-12.927). This i m p l i e s t h a t h i s t o t a l d e v i a t i o n from the expected values i s -1200$. He has "been i n c o n s i s t e n t i n that h i s c e r t a i n t y equivalents are l a r g e r than the maximums of the EV's ranges. In other words, given an u n c e r t a i n a l t e r n a t i v e w i t h 50$ chance of g a i n i n g twice the amount of h i s current s a l a r y and 50$ chance of r e c e i v i n g only one h a l f of h i s current s a l a r y , he r e q u i r e s , i n l i e u of t h i s u n c e r t a i n a l t e r n a t i v e , a sure income g r e a t e r than twice the current s a l a r y . Thus, t h i s r a i s e s doubt on the accuracy of h i s answers. The r e s t of the responses seem reasonable i n tha t the most r i s k averse subject has a t o t a l d e v i a t i o n of 160$ from the expected v a l u e s . (On average, given three c e r t a i n t y e q u i v a l e n t s , h i s certainty.amount deviates from the expected value by 53$ approximately.) The Net P r o f i t U t i l i t y Score d i s t r i b u t i o n as presented i s not p e c u l i a r . However, there are two subjects whose t o t a l d e v i - a t i o n s are about 1200$ to 970$ of the expected v a l u e s . The s i z e of the vari a n c e r e v e a l s .this.... Four i n d i v i d u a l d e v i a t i o n s are derive d from the q u e s t i o n n a i r e , converted i n t o percentage terms, and summed. Based on t h i s c a l c u l a t i o n , the subjects w i t h ex- treme value have, on the average, negative d e v i a t i o n s of about 300$ to 240$. For these two s u b j e c t s , the p o s s i b i l i t y t h a t they haven't thought the problems out w e l l i s great. On the p o s i t i v e s i d e ( i n d i c a t i n g higher r i s k a v e r s i o n ) , there are a l s o two sub- j e c t s w i t h a 550$ to 650$ d e v i a t i o n from expected v a l u e . I f these t o t a l d e v i a t i o n s were d i v i d e d by f o u r , the r e s u l t of 140$ 92 to 1S0% r e v e a l s t h a t these two subjects r e q u i r e ( i n l i e u of the u n c e r t a i n a l t e r n a t i v e ) a sure amount th a t i s more than twice the expected value. These r e s u l t s are acceptable. As f o r the r a t e of r e t u r n u t i l i t y d i s t r i b u t i o n , only one subject seems to be extremely out of l i n e w i t h the r e s t . The r e s u l t s i n d i c a t e t h a t a m a j o r i t y of the subjects (68$) are r e l a - t i v e l y n e u t r a l (range i 0.0 to 0.2 t o t a l d e v i a t i o n s ) . A c t u a l l y , f i v e s u b j e c t s have zero t o t a l d e v i a t i o n s i n d i c a t i n g that t h e i r c e r t a i n t y equivalents are equal to the r e s p e c t i v e expected values (or r i s k n e u t r a l as d e f i n e d ) . Thus, none are r i s k t a k e r s i n t h e i r responses. In D, we w i l l examine how these u t i l i t y scores stand up i n terms of c r e d i b i l i t y . One would expect t h a t these four scores should c o r r e l a t e h i g h l y , C. The Net P r o f i t U t i l i t y Questionnaire asks f o r proba- b i l i t y of success as a.response. An examination of the answers (please see Appendix) r e v e a l s t h a t only three s u b j e c t s gave any extreme p r o b a b i l i t y assignments to any item (p = 1.) whi l e only two subjects are r i s k n e u t r a l ( i . e . , g i v i n g .33, «50, .50, and •33 as p r o b a b i l i t i e s to the 4 i t e m s ) . The question s t i l l r e - mains as t o whether one should accept p r o b a b i l i t y assignments of 1.0 as v a l i d responses. D. For each item, the subject's response i s used t o c a l - c u l a t e the d e v i a t i o n ("premium") from the expected valu e s . In t h i s s e c t i o n , these d e v i a t i o n s ( i n percentage terms) are used r a t h e r than the raw responses. Although the Compensation U t i l i t y Scores (aggregate) c o r r e l a t e s i g n i f i c a n t l y w i t h the i n d i v i d u a l 93 items d e v i a t i o n s , the de v i a t i o n s themselves are not s i g n i f i - c a n t l y r e l a t e d as revealed by Table V I I . TABLE V I I C o r r e l a t i o n Matrix (Pearson) Compensation U t i l i t y " D e v i a t i o n s " and Scores Item No. 1 2 3 Ag. Score 1 1.00 ,1?2 .162 2 1.00 -.123 3 1.00 Score (Ag.). (.397) (.741) (.573) 1.000 C o e f f i c i e n t s enclosed i n parenthesis are at 0.05 l e v e l . s i g n i f i c a n t TABLE-VIII C o r r e l a t i o n Matrix (Pearson) Rate of Return U t i l i t y Scores Item No. 1 2 3 RR 4 Score 1 (.81) (.46) 2 .14 3 4 .20 (.49) .17 (.43) -.072 .123} 1.95) ~RR Score C o e f f i c i e n t s enclosed i n parenthesis are s i g n i f i c a n t at .05 l e v e l . - TABLE IX C o r r e l a t i o n Matrix (Pearson) Net P r o f i t U t i l i t y Score Item No. 1 2 2 4 Ag. Score 1 (.33) .21 (.72) (.60) 2 .16 (.49) (.72) .15 (.74) (.64) Ag. Score C o e f f i c i e n t s enclosed i n parenthesis are s i g n i f i c a n t at .05 l e v e l . 9 4 From the t a b l e s above, we can look at the i n t e r c o r r e l a t i o n of the business r i s k premiums. The c o r r e l a t i o n of the c o n s i s - tency check d e v i a t i o n ( 4 ) and the one ( 1 ) f o r which t h i s check i s being done i s not s i g n i f i c a n t f o r the r a t e of r e t u r n u t i l i t y questions but i s h i g h l y s i g n i f i c a n t f o r the net p r o f i t one (items 1 and 4 ) . Moreover, item 4 of the r a t e of r e t u r n ques- t i o n n a i r e stands out p o o r l y . The r e t e n t i o n of the ROI check i n the f u t u r e i s not a d v i s a b l e due to these r e s u l t s . In f a c t , i t s negative c o r r e l a t i o n w i t h item 3 places the item i n much doubt. The r e s u l t s of the i n t e r c o r r e l a t i o n s of the Net P r o f i t U t i l i t y items suggest t h a t the items, except item 3 , are f a i r l y a cceptable. E. An examination of the computed r i s k premiums i s under- taken f o r each subject to a s c e r t a i n the nature of h i s marginal u t i l i t y . These r i s k premiums, by the way, are expressed i n per- centage terms (please see A of U t i l i t y Items). For Compensation U t i l i t y items, 1 0 subjects have decreasing r i s k premiums ( i . e . , percentage decreases as income in c r e a s e s ) w h i l e 4 have i n c r e a s i n g r i s k premiums. The r e s t change from de- c r e a s i n g r i s k premiums to i n c r e a s i n g r i s k premiums. Thus the n o t i o n of constant r i s k a v e r s i o n i s not confirmed. For the business u t i l i t y items, the marginal u t i l i t y nature i s a l s o h i g h l y i n d i v i d u a l i s t i c because of the mixture of i n c r e a s i n g , decreasing or constant r i s k a v e r s i o n . The r a t e of r e t u r n and net p r o f i t q u e stionnaires have i n each an item which serves as a consistency check (as discussed i n Chapter 2 ) . Using a "neighborhood" c r i t e r i o n of 10% ( i . e . , 95 t h a t the responses i n t h i s check item should not deviate more than 10% from the answers they gave i n the previous item f o r which check i s made), 25 subjects (71%) have i n c o n s i s t e n c y i n t h e i r r a t e of r e t u r n responses (10 i n the more r i s k - t a k i n g d i - r e c t i o n and the r e s t i n the more r i s k - a v e r s e d i r e c t i o n ) . In the net p r o f i t check item, 32 have i n c o n s i s t e n t responses (20 i n the more r i s k averse d i r e c t i o n and 12 i n the l e s s r i s k - averse' ). A few s u b j e c t s ' u t i l i t y curves are a c t u a l l y p l o t t e d out. Figure 6-11 g i v e s us one subject's three u t i l i t y curves. He i s considered the 'most extreme* person i n t h a t h i s u t i l i t y curves are extremely d i s s i m i l a r . I t i s conceivable t h a t compensation and the other two u t i l i t y curves are d i s s i m i l a r as they belong to d i f f e r e n t c a t e g o r i e s — o n e p e r t a i n i n g to personal and the other to business. But even the business u t i l i t y curves do not seem to be of the same k i n d f o r t h i s s u b j e c t . But, as we s a i d b efore, he i s an extreme case. U t i l i t y f o r i.o ^ Compensation J $6,0OO. Compensation $ \\jOOO $I'G,OOO. Figure 6-11(a) One subject's three U t i l i t y Curves 96 A l s o , r a t e of r e t u r n u t i l i t y scores are compared under two c o n d i t i o n s — u n d e r the l a r g e f i r m assumption and under the s m a l l f i r m assumption (t = 1.0994, df = 33» p ~ 0 . 3 0 ) . The same comparison method i s done f o r the net p r o f i t u t i l i t y scores (t = 1.98, p > 0.05). I t would not seem l i k e l y t h a t the group has d i f f e r e n t r i s k t a k i n g propensity under the two c o n d i t i o n s . This i m p l i e s t h a t the s i z e of the f i r m does not a f f e c t r e s u l t a n t r i s k t a k i n g p r o p e n s i t y . 97 We are p r i m a r i l y i n t e r e s t e d i n how the sub j e c t s are placed as r i s k t a k e r s by these u t i l i t y items. Ordinal s c a l e i n t h i s case i s as acceptable as the •absolute* or i n t e r v a l s c a l e . Thus, u s i n g the Kendall Tau r a t h e r than the Pearson's, the business u t i l i t y scores c o r r e l a t e s i g n i f i c a n t l y (net p r o f i t and r a t e of r e t u r n ) w i t h r = 0.215 (p = 0.039). However, the Pearson c o r r e l a t i o n i s not s i g n i f i c a n t at the 0.05 l e v e l . I f we are to consider only placement of i n d i v i d u a l s i n terms of rank, r a t h e r than l o o k i n g at magnitudes, the Kendall tau sug- gests that the u t i l i t y items i n the business s e c t i o n s v a l i d a t e one another as r i s k t a k i n g measures. Table X gives us an idea how these u t i l i t y items r e l a t e w i t h one another. The "personal" u t i l i t y score (compensation) does not c o r r e l a t e s i g n i f i c a n t l y w i t h the business u t i l i t y scores. TABLE X CORRELATIONS OP UTILITY ITEMS' 1 Compensation Rate of Return Net P r o f i t Compensation 1.000 Rate of Return 1.000 Net P r o f i t 0.2948 1.000 Missing means no s i g n i f i c a n t c o r r e l a t i o n s (p>0.05). A l l c o r r e l a t i o n c o e f f i c i e n t s , p<0.039. Thus, we can say tha t there i s no s i g n i f i c a n t r e l a t i o n s h i p ( o r d i n a l ) between personal u t i l i t y and business u t i l i t y scores. 98 F. As we mentioned i n previous chapters, the i n c l u s i o n of the u t i l i t y items as part of the face - t o - f a c e set i s due t o the f e a r t h a t the items i n the u t i l i t y set may not be as c l e a r as we i n i t i a l l y thought. Because of the p o s s i b i l i t y of sub- j e c t s * misunderstanding of the contents, these were presented i n the experimenter's presence. However, during a d m i n i s t r a t i o n , the subjects d i d not ask f o r any c l a r i f i c a t i o n . Thus, i n c l u s i o n i n the category set mentioned i s a f t e r a l l not necessary. There i s a l s o the i n i t i a l f e a r t h a t the s u b j e c t s , because of t h e i r MBA t r a i n i n g , w i l l use the EV maximization c r i t e r i o n and r e s u l t i n r i s k n e u t r a l assessments. However, only a few subjects turned out to use the s a i d c r i t e r i o n . Thus the f e a r i s not warranted. One of these subjects even wrote on the s i d e t h a t the quest i o n n a i r e was e a s i l y seen through (he thought t h i s was some s o r t of a t e s t on expected v a l u e ) . Scale of Wager Although we have in c l u d e d t h i s measure i n the u t i l i t y s et and have discussed t h i s q uestionnaire i n the previous chapters as a u t i l i t y one c l a s s i f i e d as personal u t i l i t y , t h i s i s not a u t i l i t y measure i n t h a t i t d i f f e r s from the u t i l i t y measures i n many re s p e c t s . The form of the questions contained i n i t i s d i f f e r e n t . A l s o , the score d e r i v e d does not f o l l o w the conven- t i o n of the u t i l i t y ones. By convenience, t h i s measure has been i n c l u d e d w i t h the u t i l i t y s e t . In the a n a l y s i s to f o l l o w , t h i s q u e s t i o n n a i r e i s considered d i s t i n c t from the u t i l i t y ones. 99 A. The Scale of Wager Score derived i s a product of the numher of no responses ('no' i n d i c a t i n g that the subject would not p l a y the game) and the d e v i a t i o n s of the responses from the expected v a l u e s . The d e v i a t i o n i s derived by g e t t i n g the d i f f e r - ence between zero and the expected value of the gamble i n each item ( i . e . , the buying p r i c e the subject o f f e r s i s added to the l o s s amount and the expected value i s computed). B. The frequency d i s t r i b u t i o n of the s c a l e of wager scores i s presented below. No. 10 of Subjects 5 FIGURE 6-12 Histogram, Scale of Wager Scores , 2 6 % Mean t 13.577 Mediant 16.65 1433% 14.33% is 18 14.34% more risk averse Variance! 90.702 Range 1 27.7 21 2 4 _ 2 .7 3 D .Scale, of .Uager • Scores . The apparent d i s c o n t i n u i t y of the frequency d i s t r i b u t i o n of the s c a l e of wager scores i s a r e s u l t of the method employed i n c a l c u l a t i n g the score. Because the number of no responses i s used as a weight, the m u l t i p l i c a t i o n of t h i s w i t h the t o t a l 100 d e v i a t i o n s r e s u l t s i n the p e c u l i a r i t y of the frequency d i s t r i - b u t i o n (the p o s s i b l e numbers of no responses are 0, 1, 2, 3, 4 and 5)» Seven s u b j e c t s have zero d e v i a t i o n s i n d i c a t i n g t h a t here they e i t h e r have zero no responses or use expected value as a c r i t e r i o n i n responding ( i n that t h e i r buying equivalents r e s u l t i n zero expected v a l u e s ) . Figure 6-13 c l a r i f i e s what the d i s t r i b u t i o n of no responses i s . Comparing t h i s w i t h Figure 6-12, we f i n d t h a t the frequen- c i e s f i t i n n i c e l y , i n that 21$, having zero s c a l e of wager score i n the. previous f i g u r e , i s a l s o the percentage of people w i t h zero no responses. A zero 'no responses* i n d i c a t e s t h a t a l l the games are acceptable. The maximum p o s s i b l e l o s s i f the f i v e games were played, by the way, i s $20,000. 9 NO. OP SUBJeCTS FIGURE 6-13 Histogram, Number of No Responses-*- ,. 2 6 % 1*33% 9% 1433% 1434% number of NO responses No i n d i c a t e s t h a t the subjects w i l l not p l a y the wager even though they might have put down buying e q u i v a l e n t s . Meani 2.32 Median i 3 Variance« 1.25 Ranget 5«0 101 Again, there i s some doubt as to whether the subjects who i n d i c a t e t h e i r w i l l i n g n e s s to p l a y are t e l l i n g the t r u t h . C. Table XI and X I I give us an idea of how subjects r e s - ponded to items 4 and 5 of "the Scale of Wager qu e s t i o n n a i r e . The former item r e f e r s to a gamble w i t h a 50-50 chance of winning $2,000 or l o s i n g $1,000; and the l a t t e r concerns a 50-50 chance of g a i n i n g $20,000 or l o s i n g $10,000. TABLE XI Frequency D i s t r i b u t i o n , Buying P r i c e s Item 4, Scale of Wager Buying P r i c e R e l a t i v e Frequency Absolute Frequency $ 0.00 71$ 25 100.00 6% 2 500.00 11% 4 1,000.00 6$ .. 2 above 1,000.00 6$ 2 100$ 35 Meani 206.00 TABLE X I I Frequency D i s t r i b u t i o n , Buying P r i c e s Item 5, Scale of Wager Buying P r i c e R e l a t i v e Frequency Absolute Frequency 0.00 80$ 28 500.00 2.9$ 1 3,000.00 2.9$ 1 5,000.00 5.6$ 2 10,000.00 2.9$ 1 above 10.000 5.7$ 2 100$ 3'5 Mean» 1,471.00 Even though the p o s s i b l e g a i n i s very high i n these two items, a m a j o r i t y of the sub j e c t s would not pay anything f o r 102 the game because of the s i z e of the p o s s i b l e l o s s . For sub- j e c t s who i n d i c a t e d t h a t they would buy the wager at a high p r i c e , t h e i r responses might be a b i t questionable because of the stake i n v o l v e d . Thus, the h y p o t h e t i c a l nature of the game might have induced inaccurate answers i n that the subjects at present do not have the amounts they i n d i c a t e d . The question- n a i r e assumes that the subjects take account of t h e i r present wealth l e v e l but does not e x p l i c i t l y t e l l the sub j e c t s t o assume such. For items 1, 2, and 3 "the mean buying p r i c e s are J $.45 f o r item 1, 3.15 f o r item 2 and 20.28 f o r item 3. Here i s a rough i n d i c a t i o n t h a t the buying p r i c e s do not increase i n the pro- p o r t i o n s i m i l a r to the p r o p o r t i o n at which expected value i n - creases. D. The Scale of Wager d e v i a t i o n s ( i f compared w i t h Com- pensation u t i l i t y items) shows much b e t t e r 'cohesion* i n tha t these are c o r r e l a t e d s i g n i f i c a n t l y w i t h one another. The aggre- gate score i s h i g h l y c o r r e l a t e d w i t h the i n d i v i d u a l d e v i a t i o n s . I f the v a l i d i t y i s based on item analyses alone, the Scale of Wager i s s u p e r i o r to the 'other u t i l i t y scores.' The t a b l e f o l l o w i n g f u l l y v e r i f i e s t h i s . TABLE X I I I C o r r e l a t i o n Matrix Scale of Wager Premiums and Scores Item No. 1 2 3 Ag. Score 1 2 3 4 5 (.82) (.69) (.81) (.69) (.72) (.86) (.64) (.80) (.93) (.87) (.69) (.65) (.57) Ag. Score 103 However, these high c o r r e l a t i o n s are not the only considera- t i o n . The d i s c u s s i o n i n (C) has given us an ide a of the dubious nature of the su b j e c t s ' responses. E. Each subject's buying p r i c e s are examined. Although the s i z e of the gambles increase from one item t o the next i n m u l t i p l e s of 10 ( i . e . , the p o s s i b l e win of item 2 i s $20.00 w h i l e f o r item 1 i t i s 2 .00) , the buying p r i c e s of the subjects do not increase i n the same p r o p o r t i o n . Stock P r i c e Wagers A. The sub j e c t ' s top choice (where he i n d i c a t e d rank one) i s converted i n t o the variance of the gamble chosen; t h i s i s made i n t o a p r o p o r t i o n a l form (as a p r o p o r t i o n of the l a r g e s t v a r i a n c e i n the set} which i s subtracted from one; and the pro- p o r t i o n i s m u l t i p l i e d by the rank of the item chosen (rank i n - d i c a t e s order by s i z e of va r i a n c e where the l a r g e s t v a r i a n c e i s given a rank of 0 ) . The Stock P r i c e Wager i s the sum of the "ranked p r o p o r t i o n s " from the f i v e s e t s . B. The d i s t r i b u t i o n of stock p r i c e wager scores i s i l l u s - t r a t e d i n Figure 6-14. We can see tha t there are no zeros as scores. This i m p l i e s t h a t no one chose the gamble w i t h the l a r g e s t v a r i a n c e i n a l l the s e t s . The mean of 2.?4 (by breaking t h i s down i n t o the ranks and p r o p o r t i o n s ) suggests t h a t on the average the subjects chose the t h i r d - s m a l l e s t - v a r i a n c e gamble. In a l l sets (except the one i n v o l v i n g the 62$ b e t s ) , t h i s r e f e r s to the wager w i t h a 62$ chance of winning. However, whether t h i s i s an i n d i c a t i o n of general p r o b a b i l i t y preference remains to 104 No. l o of Subjects FIGURE 6-14 Histogram, Stock P r i c e Wager Scores 22.9% I 7 A 5 S 15.3% 11.4% 2.9% 2-9% 1.33 1.67 11.4% 2.33 Z.67 3.33 Meani 2 . 7 4 Modei 4 . 0 0 0 Median i 2 . 5 7 Variance! 0 . 7 3 3 Range.t 2 . 7 5 more risk averse 3.67 Or 4-.33 stock price wager sc. be j u s t i f i e d ( i . e . , we cannot say that 62$ i s the " f a v o u r i t e " p r o b a b i l i t y of the s u b j e c t s ) . The mode of 4 . 0 0 0 (22.9$) sug- gests t h a t there are 8 subjects who p r e f e r r e d the sure $ 2 . 0 0 throughout. C. The subjects were asked to rank the f i v e s e t s according to t h e i r d e s i r a b i l i t y . Table XIV gives an idea of how the s u b j e c t s a s s i g n ranks to these f i v e s e t s . Set C i s chosen by the m a j o r i t y of the sub- j e c t s as number 1. This can be explained by the f a c t t h a t C i s the only s et i n the Stock P r i c e Wager q u e s t i o n n a i r e , which o f f e r s expected values g r e a t e r than $ 2 . 0 0 (the expected value f i x e d f o r three s e t s ) . 105 TABLE XIV Ov e r a l l Set Rankings D i s t r i b u t i o n Set RANK 1 2 3 4 5 Median Frequency R e l a t i v e ..... ...... . A B C D E 8 . 6 18 . 2 5 7 . 6 3 . 0 9 . 1 3 3 . 3 9 . 1 24 . 2 9 . 1 24 . 2 2 7 . 3 18 . 2 9 . 1 36.4 1 2 . 1 24 . 2 18 . 2 6 . 1 2 7 . 3 24 . 2 6 . 1 36.4 3 . 0 24 . 2 3 0 . 3 2 . 7 7 8 3 . 7 5 1 . 3 6 8 3 . 5 5 3 . 6 8 7 Based on the median, the l e a s t l i k e d set seems to be Set B which o f f e r s a f i x e d expected value and p o s s i b l e g a i n but has an o p t i o n w i t h a p o s s i b l e l o s s of $ 7 0 . 0 0 . On an o v e r a l l b a s i s , t h i s r e s u l t i s a rough i n d i c a t i o n of l o s s m i n i m i z a t i o n behavior. I f one looks at how the rank l ' s are d i s t r i b u t e d throughout the s e t , s et D has the l e a s t number of l ' s . This i n d i c a t e s t h a t f o r the m a j o r i t y of subjects set D i s not the top choice, i n that they do not p r e f e r the expected value to be l e s s than $ 2 . 0 0 even though i t increases as the p r o b a b i l i t y of success i n c r e a s e s . In u s u a l m u l t i a t t r i b u t e choice making, there i s a dominance r u l e which s t a t e s that the choice, which has a more d e s i r a b l e value i n one of i t s a t t r i b u t e s w h i l e the r e s t of the a t t r i b u t e s are s i m i l a r i n value to those of other choices, i s chosen. In Set D, i f the dominance r u l e f o l l o w s , the i n i t i a l hypothesis i s that item 5 (sure amount of $ 2 . 0 0 ) should be chosen as top choice i n the set because t h i s choice dominates. This i s drawn 106 from the n o t i o n that more c e r t a i n t y of g a i n i n g i s p r e f e r r e d to l e s s c e r t a i n t y of g a i n i n g ( a l l other t h i n g s being the same) and g r e a t e r expected value i s p r e f e r r e d over l e s s expected v a l u e . Table XV i n d i c a t e s t h a t the value of the median decreases from the f i r s t to the l a s t item. A l s o , the mode ranks are ' i n the reverse diagonal.' This confirms the b e l i e f t h a t the s u b j e c t s , i n g e n e r a l , f o l l o w e d the r u l e . This shows the subjects r e a l l y thought out t h e i r choices w e l l . TABLE XV Set D D i s t r i b u t i o n of Ranks R e l a t i v e Frequency —>__Value . ™ Median Item No. - — ' 1 2 3 5 1 8.6 8.6 2.9 11.4 68.6 4.229 2 8.6 14.3 11.4 65.7 — 3.33 3 14.3 11.4 65.7 5.7 2.9 2.714 4 1 4 51.4 11.4 14.3 11 4 2.63 5 58.8 14.7 8.8 2.9 14.7 2.000 TABLE XVI Set C D i s t r i b u t i o n of Ranks "TT—-Rank Item No. — - — 1 2 3 4 5 Median 1 28.6 20.0 20.0 8.6 22.9 2.771 2 14.3 20.0 14.3 22.9 28.6 3.31̂  3 20.0 14.3 40.0 25.7 — 2.714 4 17.1 20.0 22.9 37 1 2.9 2.88 5 20.0 25.7 2.9 5.7 45.7 3.314 R e l a t i v e Frequencies 10? Table XVI gives us an idea of how Set C, the ma j o r i t y ' s f a v o r i t e s e t , i s responded to by the s u b j e c t s . Only 20$ of the s u b j e c t s ranked the item(5) w i t h the highest expected value as 1. The r e s u l t s of the above d i s t r i b u t i o n r e v e a l t h a t the expected value c r i t e r i o n i s not the s o l e c r i t e r i o n . We s h a l l d i s c u s s the s t r a t e g i e s i n d i v i d u a l s u bjects employed i n E. D. Table XVII g i v e s us the r e s u l t s of the i n t e r c o r r e l a - t i o n s of the aggregate wager score and the f i v e s e t s ' top choice scores. TABLE XVII C o r r e l a t i o n Matrix Stock P r i c e Wager Scores Set A B C D E Ag. Score A (.37) (.43) (.55) .18 (.708) B .07 .25 (.34) (.551) C (.39) (.52) (.73) D .10 (.74) E (.53) Ag. Score C o e f f i c i e n t s enclosed i n parenthesis are s i g n i f i c a n t at .05 l e v e l . Set B and Set C do not seem to be as h i g h l y ' d e s i r a b l e ' as the r e s t i n terms of the number of s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s . The k i n d of a n a l y s i s we j u s t presented above i s d i f f e r e n t from the way we conducted the analyses on the r e s t of the mea- sures because i n s t e a d of items, we used s e t s . This may be j u s t i f i e d because the items i n the set are so i n t e r r e l a t e d w i t h one another t h a t i t would be senseless to t a l k about removing 108 items r a t h e r than s e t s . The low c o r r e l a t i o n of Set E w i t h the r e s t i s understand- able from the p o i n t of view t h a t the d i f f e r e n t format of E's items may have induced such a r e s u l t . This suggests t h a t the items i n Set E should be r e v i s e d i n such a way tha t i t conforms w i t h the format of the r e s t of the s e t s . As f o r Set B, the low c o r r e l a t i o n w i t h Set C and D i s unexpected. This suggests th a t some other c o n s i d e r a t i o n s were incorporated i n t h e i r responses to B as compared to the r e s t of the s e t s . These c o n s i d e r a t i o n s cannot be i s o l a t e d . The major d i f f e r e n c e of Set B w i t h the r e s t of the sets l i e s i n the s i z e of the l a r g e s t p o s s i b l e l o s s ($70.00). Whether t h i s d i f f e r e n c e causes the r e s u l t s t h a t we got or not cannot be a s c e r t a i n e d . E. The f o l l o w i n g s t r a t e g i e s are examined t (1) Choosing the a l t e r n a t i v e t h a t would earn the most money. (2) Choosing the a l t e r n a t i v e t h a t would l o s e the l e a s t money. (3) Choosing the a l t e r n a t i v e w i t h the l e a s t p r o b a b i l i t y of success. (4) Choosing the a l t e r n a t i v e w i t h the gre a t e s t v a r i a n c e . (5) Choosing the a l t e r n a t i v e w i t h the p r o b a b i l i t y one l i k e s . A (1) s t r a t e g y i m p l i e s choosing the a l t e r n a t i v e w i t h the l a r g e s t amount of p o s s i b l e g a i n . The l a r g e s t p o s s i b l e g a i n i s i n Set C (item 5 w i t h a p o s s i b l e g a i n of $70.00). As we s a i d before (see Table XXVlJ 20$ (or 7 s u b j e c t s ) chose t h i s a l t e r n a t i v e . Losing the l e a s t money may be i n t e r p r e t e d as choosing the sure t h i n g ( p o s s i b l e l o s s = 0.0) or l o s i n g the $1.10 i n the wager options of Set B. For the f i r s t i n t e r p r e t a t i o n , 9 chose 109 the sure t h i n g most of the time (2 of these deviated i n Set B i n t h a t they chose the 'both win* a l t e r n a t i v e — i . e . , win of $10.00 or a win of $1.40). As f o r the second i n t e r p r e t a t i o n , t h i s would mean choosing item 3 i n Set B as rank 1. Nine sub- j e c t s chose t h i s a l t e r n a t i v e as t h e i r o v e r a l l choice (which was not played o u t ) . Strategy (3) suggests t h a t the sub j e c t s would choose the 7$ p r o b a b i l i t y of success. Only 3 s u b j e c t s chose t h i s l e v e l most of the time ( i . e . , except f o r Set D and f o r the two sets whose l o s s e s were not constant throughout). As f o r Strategy (4), no one c o n s i s t e n t l y used t h i s s t r a t e g y i n the s e t s . Five s ubjects chose the options w i t h the l a r g e s t v a r i a n c e i n some s e t s . The o p t i o n , among the r e s t , w i t h the gre a t e s t v a r i a n c e i s item 1 of Set B. No one has ranked t h i s item as t h e i r f i r s t choice among the other options i n the same se t . P r o b a b i l i t y preference i s a l s o examined. We i n d i c a t e d be- f o r e t h a t 62$ could be the ' f a v o r i t e ' p r o b a b i l i t y of the sub- j e c t s . Ten subjects chose t h i s l e v e l most of the time but f i v e of these chose to minimize l o s s (sure t h i n g or l e a s t l o s s ) when the ' l o s e ' amount v a r i e d from one item to another. I f expected value i s the s o l e c r i t e r i o n employed f o r some s u b j e c t s , t h e i r responses to Set C would i n d i c a t e t h i s ( i . e . , ranks f o r the r e s p e c t i v e items would bet 5, 4, 3, 2, 1 ) . A Spearman rho c o e f f i c i e n t i s c a l c u l a t e d f o r each subject but be- cause of the number of items, we can only accept a rho of 1.0 as i n d i c a t i o n of EV maximizing. Only three s u b j e c t s have rho's of 1.0. 110 Variance Preference (or some f a v o r i t e v a r i a n c e l e v e l ) i s not observed i n the group. Variance M i n i m i z a t i o n i s a l s o examined—though a b i t crude. The average variances of the gambles i n each set i s d e r i v e d . The s e t s i n t u r n are ranked according t o the s i z e of the average v a r i a n c e (where 1.0 i s given to the lowest v a r i a n c e , 2.0 to the next and so on). This k i n d of ranking i s i n t u r n compared w i t h the ranks generated by the s u b j e c t s . The Spearman rho i s com- puted. The rho*s, i n order to be s i g n i f i c a n t , should be 1.0. None are found to be s i g n i f i c a n t . However, 21 of the 33 com- p l e t e d set rankings, have negative rho's (ranging from -0,89 to -0.01) w h i l e 12 have p o s i t i v e c o r r e l a t i o n (ranging from 0.90 to 0.10). . Thus, from the r e s u l t s i t seems tha t the s t r a t e g y employed most of the time (39$ of the s u b j e c t s ) i s choosing the a l t e r n a - t i v e w i t h the f a v o r i t e p r o b a b i l i t y . However, based on the 30$ who employed t h i s s t r a t e g y , t h i s cannot be claimed to be general f o r the group. Extremity Confidence i n Judgment A. The aggregate extremity score f o r each subject i s the average squared d e v i a t i o n of the item chances from f i f t y . The confidence score i s the average confidence value subjects assigned to the f i f t e e n items.(the code being 1 f o r Very Sure, 2 f o r Quite Sure, and so on). B . F i g u r e 6-15 gives us an ide a of how. the extremity scores are d i s t r i b u t e d , w h i l e Figure 6-16 summarizes the con- fidence score d i s t r i b u t i o n . I l l The extremity score, on the average, i s thus low as e v i - denced by the d i s t r i b u t i o n . This i m p l i e s t h a t the subjects do not take high r i s k s concerning knowledge. They are al s o moder- a t e l y confident i n t h e i r responses as revealed by the mean con- fidence score. No. of 13 Subjects 10 i o FIGURE.6-15 Histogram of Extremity Scores 36.2% .3*3% - 14.3% 8.6% 2 9 % 1 OS •IO .iasr •75 more risk, averse Means 0.082 Variance i 0.001 Range i 0.128 Mediant .078 225 -25 extremity score 112 FIGURE 6-16 Histogram, Confidence Scores No. of Subjects VO 25.736% ZS.7% 14.34-3% O . S I.O Mean i 3.05 Variance J . 0.39 5.86% 14.3% 8.6% 1 5 z.o 2.5 i _ J 1 3% »ess confident Range t 2.6 -Median i 3.11 3.5 4.o 4.er 5 confidence sc. C. Item 13 concerns the assignment of the chances t h a t an American mot o r i s t w i l l have a severe car accident on the U.S. highway t h i s Sunday. This i s i n t e r e s t i n g l y d i s t r i b u t e d as evidenced by Figure 6-17, which d e p i c t s the d i s t r i b u t i o n of chance assignments, and by Figure 6-18, the r e s u l t a n t extremity score d i s t r i b u t i o n of t h i s item. 113 FIGURE 6-17 Histogram, Chance Assignment D i s t r i b u t i o n Item 13 5 8 % 2 0 No. of Subjects is to •10 ZO 19% ?.9% I I 30 AO .50 Z.9% 2.9% 1 1 1 •<oO •TO 80 Meant .4168 Mediant .03 Variance t .16.54. Range t 1.00 •90 1O0 chance The strange d i s t r i b u t i o n of the responses to Item 13 may be a t t r i b u t e d to m i s i n t e r p r e t a t i o n . Instead of reading the item as 'An American taken at random,' the i n t e r p r e t a t i o n has e i t h e r been 'a p a r t i c u l a r American motorist* or 'one American m o t o r i s t . ' This item's ambiguity must be c o r r e c t e d by adding the phrase 'taken at random.' 114 No. of Subjects 30 FIGURE 6-18 4 0 Histogram, Extremity Scores Item 13 86% 20 IO 5 8 % 2.9% 5.8% O.025 O.Q5 Meant .235 Mediant. .227 •075 4 •IO .125 .15 m o r e H S K a v e r s e Range t .221 V a r i a n c e i .189 •175 . 2 . " S T .25- extremity score Table XVIII gives us the breakdown of the confidence score f o r t h i s item. The confidence score f o r t h i s item on the aver- age i s high. But, due to the s u b j e c t s ' p o s s i b l e m i s i n t e r p r e t a - t i o n , we cannot r e l a t e the confidence score to the extremity score. This item's average confidence score i s the highest among the items. 115 .TABLE XVIII Confidence Score, Item 13 Absolute R e l a t i v e Value Frequency Frequency 1 17 48.6 2 7 20.0 3 6 17.1 4 4 11.4 5 5 2.9 Meant 2.000 Modet 1.000 Variancet 1.-412 Item 6, concerning the chances t h a t a Canadian woman w i l l a b s t a i n t o t a l l y from a l c o h o l i c beverage i s another i n t e r e s t i n g item i n t h a t the average assigned chance i s .198. Figure 6-19 i l l u s t r a t e s how these chances are d i s t r i b u t e d . FIGURE 6-19 Histogram, Chance Assignments Item 6 Median t 9.7$ Ranget .68 Variancet .127 .40 .50 .60 70 .80 .QO t.OO c n a n c e 116 Thus, on average, subjects b e l i e v e d t h a t there i s a s l i m chance t h a t a Canadian woman w i l l a b s t a i n from a l c o h o l i c bever- age; The mean confidence f o r t h i s item i s 2.6 which i s a l i t t l e b e t t e r than 'Moderately Sure.* TABLE XIX Confidence Score Item 6 Absolute R e l a t i v e Value Frequency Frequency 1 3 8.6 2 13 37.1 3 11 31.4 4 6 17.1 5 2 5.7 D. Table XX gives us an i n d i c a t i o n of the s t r e n g t h of a s s o c i a t i o n between the aggregate extremity score and the item, and the i n t e r c o r r e l a t i o n s of the items w i t h one another. I n t e r - item extremity score c o r r e l a t i o n s are not encouraging. How- ever, except f o r items 4, 8, 9 and 14, the c o r r e l a t i o n of the item score w i t h the aggregate score i s s i g n i f i c a n t at the 0.05 l e v e l . Item 4 (s uniqueness i s apparent from the Table XX. Thus, usi n g the c r i t e r i o n of basing item v a l i d i t y on the r e s u l t i n g c o r r e l a t i o n w i t h the aggregate score i m p l i e s t h a t items 4, 8, 9 and 14 are p o s s i b l e candidates f o r r e j e c t i o n . Item 6 (con- cerning a Canadian woman a b s t a i n i n g from a l c b h b l ) i s another candidate f o r r e j e c t i o n even though i t s c o r r e l a t i o n w i t h the aggregate score i s s i g n i f i c a n t (see C). TABLE XX Correlation Matrix Extremity Scores Item 1 2 3 4 5 6 7 8 9 10 11 12 • 13 14 15 Ave. Score 1 .1114 (.285) .09? (.48) (.29) - 0 . 0 3 -0.04 -0.11 -0.04 0.09 .231 --0.05 .105 .002 (0.376) 2 0.051 (.324) .17 0.07 .24 -.09 (.29) .10 .25 -0.02 .11 .28 .26 (.645) 3 .02 ' .20 .24 .09 .08 -.14 -.11 .18 .26 - . 2 0 . 0 7 -0.09 (.33) 4 .09 -.14 .18 - . 2 1 .24 -.04 -•0.13 - . 1 7 - . 1 5 -•0.03 .26 .26 5 (.36) .12 -0.02 (-.28) .23 • 30 .24 .08 - . 0 0 2 - . 0 7 (.493) 6 - . 1 3 .19 -.18 (.34) (.33) • 13 .001 . 0 1 - . 2 7 (0.328) 7 - . 2 7 (•3D - . 1 2 -.19 - . 1 2 --0.002 .018 (.469) (.3004) 8 -0.16 .048 .017 .05 .21 - . 2 7 - . 1 6 -0.0114 9 -.24 -.19 (-.28) .004 ( .324) .063 .052 10 .13 .03 .13 -.04 -0.012 (.311) 11 (.323) ( . 3 5 D . 2 7 -.19 (.47) 12 . - - - . 0 8 -.04- .21 (.36) 13 .13 .007 (.36) 14 - . 0 1 0 .202 15 ( .32) Ave. Score Correlation coefficients (Pearson) are significant at the 0.05 l e v e l when enclosed i n parenthesis. TABLE XXI > Correlation Matrix Confidence Scores Ag.. Item 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Score 1 (.48) .25 .20 (.39) (.35) .13 .18 .16 ( .30) (.39)...26 .18 . 13. .21 (,54); 2 (.59) (.42). .25 (.35) (.45) .05 (.43) .22 ( . 3 8 ) , . - . 0 5 .14. .07. (.30). (.62), 3 (.42) (.35) .23 (.40). .26 ( .52); (.37)> .26 (.33);. .15 .04. .18 ( . 6 3 ) , 4 ( .63) (.49) (-39). .16 (.57) • ( . 3 8 ) : ( .52). .20. ( . 4 3 ) ; (.31.); ( .43), (.76). 5 (.56) .18 .22 .27. (.45) (.31) ( . 3 0 ) , .17 .26 .25 ( .67). 6 .26 .23 .18 .02 .22 .05 .28 .14 .16 (.55); 7 -.02 (.46) .22 .21 .03 -.09 (.43); (.45). ( .54) 8 .20 ( .32) .15 .16 .28 -.01 .22 ( .38) 9 (.41) (.33) .09 .18 .22 .2? (.64) 10 (.51) (.37). .11. .31. (.43) ( .63). 11 .09 (.39).. (.39), (.56), (.65) 12 .13. .0. .21 (.37). 13 .23 .12 (.42). 1^ • • (.42); (,.45), 15 Ag. Score Correlation coefficients enclosed in parenthesis are significant at .05 level. 119 Table XXI r e v e a l s to us the i n t e r c o r r e l a t i o n s of the con- fidence scores. A l l are s i g n i f i c a n t l y c o r r e l a t e d w i t h the aggregate confidence score. I n t e r - i t e m confidence score cor- r e l a t i o n s are s i g n i f i c a n t f o r some but a few of the r e s t are not s i g n i f i c a n t . But one must remember that confidence and extremity scores are used j o i n t l y so that r e j e c t i o n of one item i n the question- n a i r e means r e j e c t i o n of the confidence and extremity scores f o r t h a t item. E. Following Kogan and Wallach (1964), an a n a l y s i s which d i v i d e s extremity scores under high confidence (Very Sure-Quite Sure) and low confidence ( S l i g h t l y Sure-Not Sure at A l l ) i s undertaken. The extremity scores of the subjects under high confidence range from .25 to 0.0 w h i l e the extremity score under low range from 0.17 t o 0.0. Kogan and Wallach a s s e r t e d that 'one takes g r e a t e r r i s k s (or higher extremity score) when one i s more confident.* For each s u b j e c t , the d i f f e r e n c e of the scores between the two c o n d i t i o n s i s taken; These d i f f e r e n c e s are added up i n order to u t i l i z e the t s t a t i s t i c s . The r e s u l t i n g t i s O.769 w i t h 34 degrees of freedom and i m p l i e s t h a t the d i f f e r e n c e i s not s i g n i f i c a n t , although 30 of the subjects have higher ex- t r e m i t y scores (mean i s about .097) under high confidence than under low (mean = .0092). This may be due to the s i z e of the pooled standard d e v i a t i o n (.032). Thus, as f a r as our group i s concerned, we must r e j e c t Kogan and Wallach's hypothesis concerning confidence and r i s k t a k i n g . 120 The c o r r e l a t i o n of the average confidence score w i t h the squared extremity i s not s i g n i f i c a n t (r = -0.003)• The same i s t r u e w i t h the r between confidence score and the a l t e r n a t e extremity score (r = -0.006). This again i s an i n d i c a t i o n t h a t confidence score i s not at a l l r e l a t e d to r i s k t a k i n g . Event Occurrence and A c t i v i t y I n t e r e s t A. Two scores are generated from t h i s q u e s t i o n n a i r e . The i n t e r n a l c o n t r o l score i s j u s t the sum of the i n t e r n a l - c o n t r o l - o r i e n t e d a l t e r n a t i v e s chosen by the subject w h i l e the optimal s t i m u l a t i o n score (or sensation seeking score) i s the sum of the 'sensation seeking' o r i e n t e d a l t e r n a t i v e s chosen. B. Figure 6-20 and Figure 6-21 d e p i c t the d i s t r i b u t i o n s of these two scores. FIGURE 6-20 Histogram, I n t e r n a l C o n t r o l Scores No. „ of 20 Subjects 34.3% 20.0% g.9% S.7% Q.6% 8.6% more, eidWnally^confroilecf Meanj 6.314 Mediani 6.625 V a r i a n c e i 3.163 114% 5.7% 8 *.9% IE SCORE more internaly contr. > 121 FIGURE 6-21 No. of Subjects I I \o 6 5 Histogram Sensation Seeking Scores 34.3% 20.0% 171% n.4-% 8 6 % 5.7% 3 * 2.9% 1 less sensation s.<- Meani 4.628 Mediant 4.458 Variancet 2.29 "* more sensation seeking SS SCORE The i m p l i c a t i o n of the above i s t h a t the students are more i n t e r n a l l y c o n t r o l l e d than they are s t i m u l a t i o n - s e e k i n g . On the whole, i t may be argued t h a t the Master's students do perceive g r e a t e r l o c u s of c o n t r o l i n human a f f a i r s . But they do'-.not seem t o seek 'excitement* from s t i m u l a t i n g events or s o c i a l i n t e r c o u r s e . C. We break the items i n t o two ca t e g o r i e s t IE C o n t r o l and Sensation Seeking. Figure 6-22 gives us a p i c t u r e of how the subjects respond to each item. 122 FIGURE 6-22 Histogram, Responses f o r Each Item No. of I n t . C o n t r o l A l t . Chosen Zo 30 24 28 22 2 0 > 3 5 'less IE chosen. I5-! 9 21 13 15 29 ll 17 19 ITEM N O Items 9, 13t and 17 concern c o n t r o l i n personal l i f e ( t r u s t i n g to f a t e not t u r n i n g out w e l l i n item 9; almost c e r - t a i n t h a t plans made by s e l f can be made t o work i n item 13; and 'what happens to me i s my own doing' i n item 17)• The l e a s t perceived c o n t r o l i s i n item 19 concerning fortune and people i n ge n e r a l . Thus, the subjects f e l t t h a t they had great- est c o n t r o l over thei r personal l i v e s and l e s s c o n t r o l over world a f f a i r s , government d e c i s i o n s and other people's l i v e s (items 11, 15, e t c . ) . 123 Figure 6-23 shows us how the sensation-seeking items are answered. FIGURE 6-23 Histogram, SSS Response f o r Each Item No. of 30 SSS a l t e r - n a t i v e s chose \o 12. 14- \& 18 ZO I T E M N O . Items 4, 12, 18 and 20 e l i c i t e d the l e a s t number of SSS responses. Items 4, 18 and 20 are concerned w i t h s o c i a l a c t i - v i t i e s (e.g., choosing f r i e n d s who are r e l i a b l e and p r e d i c t a b l e or not, enjoying or d i s l i k i n g r o u t i n e works, and p r e f e r r i n g people who are calm and even tempered or n o t ) . Item 12 may be considered as sensual s t i m u l a t i o n ( i . e . , whether one dives i n t o a c o l d pool or g r a d u a l l y s i n k s i n t o i t ) . The items where the subjects f e l t they should be more sensation-seeking con- cern t r a v e l l i n g . We could say th a t because of these r e s u l t s , 124 the subjects are most s t i m u l a t e d by t r a v e l l i n g (items 8, 14) and l e a s t by s o c i a l a c t i v i t i e s . D. Because of the way the IE-SSS scores are coded f o r computer a n a l y s i s , only aggregate scores f o r each person are a v a i l a b l e . However, an i n d i c a t i o n of item v a l i d i t y may be se- cured from Rotter's (1966) r e s u l t s and from the b i s e r i a l c o r r e - l a t i o n t a b l e Zuckerman, et a l . (1964) provided. Table XXII and Table XXIII have been reproduced from the s t u d i e s conducted by Rotter and Zuckerman. The item nos. r e - f e r r e d to i n the t a b l e s are the item numbers as they appeared i n our q u e s t i o n n a i r e . The b i s e r i a l c o r r e l a t i o n s of the IE items are much b e t t e r than those of the SS items. Item 91 although i t e l i c i t e d high I n t e r n a l Control r e s - ponses, as shown from R o t t e r ' s , i s one of the poorest among the IE items. Item 19» i n the same v e i n , doesn't have high b i s e r i a l c o r r e l a t i o n . As f o r the SS items, item 4 and item 14 are, based on the t a b l e , the poorest. I f one d e s i r e s to reduce the number of items i n t h i s ques- t i o n n a i r e , the candidates are the items mentioned i n t h i s sub- s e c t i o n . E. Are e x t e r n a l l y c o n t r o l l e d i n d i v i d u a l s l e s s 'sensation- seeking' ? This question i s r a i s e d w i t h the i n i t i a l b e l i e f that i n d i v i d u a l s who f i n d that most events are beyond t h e i r c o n t r o l do not seek s t i m u l a t i o n from unpredictable s o c i a l acquaintances, t r a v e l l i n g without guides, e t c . Instead, they p r e f e r the n o t i o n of a 'quiet' l i f e knowing that they are being e x t e r n a l l y TABLE XXII The IE Scale w i t h C o r r e l a t i o n s of Each Item w i t h T o t a l Score, Excluding that Item* Item No. B i s e r i a l Item C o r r e l a t i o n s 200M 400M+F 1 .265 .460 3 .345 .319 5 .238 .289 7 .391 .301 9 .152 .164 11 .313 .357 13 .313 .265 15 .295 .307 17 .331 .238 19 .108 .152 Reproduced from Rotter (1966) n = 400. TABLE XXIII SS Scale w i t h C o r r e l a t i o n s of Each Item w i t h T o t a l Score, Excluding that Item 2 Item No. B i s e r i a l Item C o r r e l a t i o n s 2 .270 4 .155 6 .318 8 .391 10 .307 12 .192 14 .152 16 .185 18 .229 20 . .271 Zuckerman, et a l . (1964) n = 180. 126 c o n t r o l l e d anyway. On the other hand, people who perceive g r e a t e r locus of c o n t r o l over t h e i r l i v e s are perhaps those who a l s o seek higher s t i m u l a t i o n l e v e l s . The c o r r e l a t i o n of IE Scores w i t h SS Scores f o r our group i s -0.032 (p > 0.05). Thus, the n o t i o n i s not confirmed. I t i s p o s s i b l e that the un d e r l y i n g dimensions of the SS items are not the ones th a t the subjects perceive to c o n t r i b u t e to stimu- l a t i o n - s e e k i n g . The items t h a t subjects have low SS responses to are those which concern choice of s o c i a l acquaintances. I f they f e l t t h a t they should have c o n t r o l over s o c i a l acquain- tances, they might not p r e f e r u n p r e d i c t a b l e f r i e n d s or emo- t i o n a l l y expressive but unstable p e r s o n a l i t i e s (see Figure 6-23). However, based on our r e s u l t s , the two con s t r u c t s are not r e l a t e d at a l l . D i s c u ssion Analyses of the d i s t r i b u t i o n s of su b j e c t s ' r i s k scores have been discussed together w i t h some rough item analyses. The analyses i n d i c a t e d t h a t some items should be r e v i s e d or removed. The r e s u l t s a l s o suggest that trimming i s necessary. Some items which are l e s s business r e l e v a n t should not be i n - cluded (e.g. item 3 of Choice Dilemma, item 2 of In-Basket, e t c . ) . Items which do not seem to d i s c r i m i n a t e the r i s k t a k e r s from the r i s k a v e r t e r s are e i t h e r subject to r e v i s i o n or to t o t a l e l i m i n a t i o n (items 4 and 5 of Scale of Wager, item 5 of In-Basket, e t c . ) . 127 Also, f o r each measure, some of the past hypotheses are examined. The s e v e r i t y of consequences is s u e i s not confirmed ( i . e . , people who perceive the r i s k y a l t e r n a t i v e as more s e r i - ous i n terms of consequences do not n e c e s s a r i l y tend to be l e s s r i s k - t a k e r s ) . This i s s u e i s examined f o r the In-Basket and the Choice Dilemma measures. In a d d i t i o n , Kogan and Wallach's con- c l u s i o n s on the e x t r e m i t y - c o n f i d e n c e - i n judgment que s t i o n n a i r e are examined; the r e s u l t s of t h i s study r e v e a l that the extremity scores under high confidence are not s i g n i f i c a n t l y d i f f e r e n t from those under low confidence. S t r a t e g i e s i n r i s k t a k i n g are a l s o examined i n In-Basket and Stock P r i c e Wagers and found to be h i g h l y i n d i v i d u a l i s t i c . In Chapter 7, an o v e r a l l a n a l y s i s of these measures i s undertaken by p r e s e n t i n g the c o r r e l a t i o n matrix of the r i s k measures and the f a c t o r analyses r e s u l t s . 128 CHAPTER 7 OVERALL ANALYSIS OF RISK MEASURES Overview In order to look at how the r i s k measures r e l a t e to one another, a c o r r e l a t i o n matrix i s constructed and the i m p l i c a - t i o n s are discussed. This chapter a l s o presents us w i t h the f a c t o r analyses of the measures and discusses the r e s u l t s i n the l i g h t of our expectations. An attempt at model-building i s shown i n the l a t t e r sec- t i o n i n t h a t r i s k - t a k i n g , as measured by some of these i n s t r u - ments, i s examined i n r e l a t i o n to demographic v a r i a b l e s . C o r r e l a t i o n Matrix of Risk Measures Table XXIV summarizes the s i g n i f i c a n t c o r r e l a t i o n s among the r i s k measures. Spearman rho's are used because we are p r i m a r i l y i n t e r e s t e d i n the placement of i n d i v i d u a l s as r i s k t akers by these measures r a t h e r than the va r i o u s magnitudes. The p e r s o n a l i t y type measures l i k e IE and SSS do not seem to be r e l a t e d to the r i s k measures. IE i s n e g a t i v e l y c o r r e l a t e d w i t h the Memo Score, suggesting t h a t the s t r a t e g y one takes i s r e l a t e d to one's perceived locus of c o n t r o l . This i m p l i e s t h a t a person who perceives more c o n t r o l i n h i s s i t u a t i o n s w i l l recommend a r i s k i e r s t r a t e g y . This i s contrary to the n o t i o n t h a t more i n t e r n a l l y c o n t r o l l e d i n d i v i d u a l s are moderate 129 r i s k t a k e r s . As f a r as SSS i s concerned, i t seems tha t people "become more extreme i n t h e i r judgments when they are more 'sensation-seeking.' But the d i r e c t i o n of causation cannot be a s c e r t a i n e d . Extremity i n judgment i s c o r r e l a t e d i n the r i g h t d i r e c t i o n only w i t h the r a t e of r e t u r n u t i l i t y scores s i n c e higher r i s k - t a k i n g i s r e f l e c t e d by higher extremity scores while higher r i s k t a k i n g i s r e f l e c t e d by lower scores i n the r i s k measures l i k e In-Basket and u t i l i t y scores. This suggests that i n d i v i - d u a l s, encountering a l t e r n a t i v e s where r a t e of r e t u r n i s used as an a t t r i b u t e measurement, w i l l be g r e a t e r r i s k takers when they are more extreme i n judging event occurrences. The confidence score, r e f l e c t i n g the confidence l e v e l of i n d i v i d u a l s , i s deleted from the matrix as i t i s not s i g n i f i - c a n t l y c o r r e l a t e d w i t h any of the r i s k measures. The s i g n i f i c a n t c o r r e l a t i o n of the Stock P r i c e Wager score and the Scale of Wager score suggests that r e a l and imaginary wager r e s u l t s are r e l a t e d — i . e . , i n d i v i d u a l s who recommend t a k i n g g r e a t e r r i s k i n h y p o t h e t i c a l gambling s i t u a t i o n s w i l l a l s o gamble w i t h higher r i s k s when confronted w i t h r e a l wagers. Though s i g n i f i c a n t , the c o r r e l a t i o n c o e f f i c i e n t i s only .29 (suggesting t h a t the r e l a t i o n s h i p i s f a i r l y weak). The Choice Dilemma Score, which may be regarded as "ad- v i s o r y r i s k t a k i n g , " c o r r e l a t e s s i g n i f i c a n t l y w i t h Scale of Wager and odds i n In-Basket. The l a t t e r c o r r e l a t i o n may be p a r t l y explained by the contention that s i m i l a r i t y i n "format" ( i . e . both ask the subjects to a s s i g n minimum odds) w i l l TABLE XXIV Spearman Rho's of Risk Measures (One t a i l e d t e s t , p< 0.05) V a r i a b l e s IE SSS Stock Eqext Choice Compenst. Scale Rate P r o f i t Odd Memo Semdiff. IE 1.00 — — — — — — — — ~ -.42 sss 1.00 — .36 — — — — 0.31 Stock 1.00 — — — 0.29 ~ 0.30 Eqext 1.00 O.36 — — -0.41 — Choice 1.00 — .35 — — . 31 — Compenst. 1.00 .48 — — .38 — Scale 1.00 .32 .55 .61 — Rate 1.00 .30 P r o f i t 1.00 0.37 — Odd 1.00 — 0.28 Memo 1.00 Semdiff. 1.00 Legend 1 IE - I n t e r n a l E x t e r n a l Control Scores SSS - Sensation Seeking Score Choice - Choice Dilemma Scores Eqext - Squared Extremity Scores Stock - Stock P r i c e Wager Scores Compenst. - Compensation U t i l i t y Scale - Scale of Wager Rate - Rate of Return P r o f i t - Net P r o f i t U t i l i t y Odd - Minimum Odd, In-Basket Memo - Memo Scores, In-Basket Semdiff. - Semantic D i f f e r e n t i a l Scores 131 r e s u l t i n s i m i l a r placement of i n d i v i d u a l s . As to the c o r r e - l a t i o n w i t h Scale of Wager, there seems to he no other explana- t i o n except the general n o t i o n t h a t they are measuring the same co n s t r u c t . (This general n o t i o n i s i n f a c t a p p l i e d to the ana- l y s i s of the e n t i r e matrix.) Scale of Wager seems to have the l a r g e s t number of c o r r e - l a t i o n s w i t h other measures. On the other end, the Semantic D i f f e r e n t i a l score has the l e a s t number of s i g n i f i c a n t c o r r e l a - t i o n s . Because i t r e f l e c t s s u b j e c t s ' e v a l u a t i o n of r i s k t a k e r s t h i s may not be considered as a d i r e c t r t propensity measure and the c o r r e l a t i o n s may be explained w i t h t h i s d i s t i n c t i o n . I f Compensation U t i l i t y i s considered as "personal" mone- t a r y r i s k t a k i n g , i t should c o r r e l a t e h i g h l y a l s o w i t h Stock P r i c e Wager. But the matrix shows i t c o r r e l a t e s only w i t h Scale of Wager and odds i n In-Basket. The r e s u l t s revealed by the matrix suggest that the under- l y i n g r i s k t a k i n g propensity i s not as unidimensional as we i n i t i a l l y thought. They a l s o suggest that our i n i t i a l l y de- f i n e d "business r i s k " dimension i s q u i t e broad. Thus, the c o r r e l a t i o n s may i n d i c a t e t h a t these measures are not measuring the same t h i n g . A s t a t i s t i c a l method c a l l e d Factor A n a l y s i s i s used by researchers to i s o l a t e e i t h e r c l u s t e r s of r e l a t i o n s h i p s , or u n d e r l y i n g dimensions. The more important phase of t h i s type of a n a l y s i s i s to define the f a c t o r s based on the r e s u l t s and on the i n i t i a l assumption of what these f a c t o r s are. This 132 method of a n a l y s i s i s employed when the simple c o r r e l a t i o n matrix does not e x h i b i t the f a c t o r s or c l u s t e r s of r e l a t i o n - ships c l e a r l y . Factor A n a l y s i s On the assumption t h a t the u n d e r l y i n g dimensions may be i n t e r r e l a t e d , the Pearson c o r r e l a t i o n matrix of the r i s k mea- sures i s used as input to oblique f a c t o r a n a l y s i s . The number of f a c t o r s i s set at f o u r because of the i n i t i a l b e l i e f t h a t the p o s s i b l e f a c t o r s inherent i n the data are» (1) advisory r i s k t a k i n g — i . e . , Choice Dilemma; (2) business r o l e r i s k t a k i n g — i . e . , Rate of Return and Net P r o f i t U t i l i t y items, In-Basket, e t c . ; (3) personal r i s k t a k i n g — e . g . , compensation, extremity score (which can be i n t e r p r e t e d as " r i s k t a k i n g i n the knowledge dimension"); (4) gambling p e r s o n a l — e . g . Stock P r i c e Wager and Scale of Wager. The oblique f a c t o r a n a l y s i s shows that the f a c t o r s are not s i g n i f i c a n t l y c o r r e l a t e d (ranging from .067 to -0.015). Also, i t i n d i c a t e s that there are f i v e f a c t o r s (using eigen value >1.0 as c u t - o f f p o i n t ) . Table XXV gives us the r o t a t e d f a c t o r l o a d i n g matrix and the f a c t o r s t r u c t u r e . Factor 1 i s loaded on by Scale of Wager, Net P r o f i t U t i l i t y , odds i n In-Basket and the weighted grade- odds score (from I n - B a s k e t ) — u s i n g a c u t - o f f c r i t e r i o n of l o a d i n g g r e a t e r than .50. Only the two extremity scores l o a d h e a v i l y on Factor 2 w h i l e the Semantic D i f f e r e n t i a l , Stock P r i c e Wager and Compensation U t i l i t y scores l o a d h e a v i l y on TABLE XXV 0B3LIQUE FACTOR MATRICES USING PEARSON'S AS INPUT 1 133 ROTATED FACTOR-LOADINGS MATRIX ~ * INDICATES A VALUE GREATER THAN OR EQUAL TO 0.60000 FACTOR 1 VARIABLE 1 SPWAGERS 2 SQEXTREM 3 "E XT SCORE 4 CONFIDEN 5 CHOICEDL_ 6 COMPENST 7 SCWAGERS 8 RATERETM 9 PROF I TNT 10 WIRES COR 11 ODINBASK * - 0.2787 0.0034 0.0201 0.4 533 0_.Q9 5 5_ 0.1474 0.5 740 0.15 92 0.7 574 0.0 109 0.8 2 49 * - 12 GRADEODD 13 SEMDIFSC -0.9590 -0.0 539 0.1936 0.9031 0.8894" 0.1482 0_j_1091 0.2634 C.1194 0.3982 0.3359 0.C532 0.262 3 0. 1185 0 .2064 0.6731 •0. 1193 -0.1550 0. 3436 •0. 1062 -0.7507 -0.1057 -0.0225 0. 1030 -0.C485 -0.0482 0.157 5 0.8101 -0.2616 -0.1144 -0.1134 -0.3622 * -0.7711 -0.1057 * -0.5269 -0.4753 0 .1893 0.4421 -C.2302 -0.C465 0.1956 SUM OF SQUARED FACTOR-LOADINGS DIVIDED RY SUM O F COMMUNAL I TIES 0.3233 0.2495 0.2146 0.1882 f ATI *IX OF CQRR ELAT ION'S OF FACTORS WITH VARIABLES. VARIABLES ARE REORDERED ACCORDING TO HIGHEST CORRELATION WITH A FACTOR. * INDICATES A MAGNITUDE GREATER THAN OR EQUAL T O 0.50O. :• FACTOR 1 2 3 4 VARIABLE 4. CONFI DEN 6.4233' -0. 15 54 ' 0.3 592 -0.3351 7 SC WAGERS- * -0.6 459 -0. 1787 -0.1102 * -0.6119 9 PROF I TNT * -0.7 20 7 -Go 3363 0.0218 0.039C 11 ODIN3ASK * -0.862 9 0.243 0 -0 .0296 . -C.31GL • 12 GRADEODD • * -0.96 2 8 0.1524 0. 144 5 -0.1713 * * * * * * ** ****** 3 EXT SCORE ""-0.0220 * -0.920 5 -0.2587 - 6.20 59 2 SQEXTREM O.C 023 * -0. 9304 -0.2239 -0.2C71 y - -u s ' ^ a, * * * * * * ** 13 SE MDIF SC -0.0 064 0.32 3 5 * 0.823 3 0.1679 1 SPWAGERS -0.2889 -0.1391 * 0. 6 540 -0.3570 6 CGMPENST - C . l 7 9 3 -0.3642_ * -0.7320 -0.1 I 46 J - J, v > , , 1 , ^fj 'f V " » " • *f 'f 'C- -f * * * * * * * * 10 WI RES COR 0.0679 0.0953 -0.C653 0.452C 8 RATERETN -0.2 322 0.346 3 0.046 8 -0.4517 " 5" CHOICEDL -0.0096 -0. 2091 -0.0754 * -C.7646 ****** Wer to table XXVIfor meanings of the abbreviated variable names. 134 Factor 3« The Choice Dilemma items are p r i m a r i l y of Factor 4. The f a c t o r s t r u c t u r e i s shown by the second matrix of Table XXV w h i l e the f i r s t matrix ( u s u a l l y not discussed i n s t a t i s - t i c a l a n a l y s i s ) i s the f a c t o r p a t t e r n . Factor 2 may be con- s i d e r e d as the business knowledge dimension because of the loadings by Extremity scores and Factor 4 may be c a l l e d ad- v i s o r y dimension due to the Choice Dilemma; as to Factor 3» the dimension cannot be named reasonably. I f we d i s r e g a r d Semantic D i f f e r e n t i a l ' s l o a d i n g , we can c a l l t h i s the 'person- a l ' r i s k t a k i n g dimension due to Stock P r i c e Wager and Com- pensation U t i l i t y scores. O v e r a l l , the f a c t o r s e x t r a c t e d are n e i t h e r expected nor i d e n t i f i a b l e . Because the f a c t o r s are reasonably u n r e l a t e d , an ortho- gonal f a c t o r a n a l y s i s w i t h varimax r o t a t i o n i s done using the Pearson c o r r e l a t i o n matrix of r i s k scores as i n p u t . The r e s u l t s of r o t a t e d f a c t o r matrix revealed i n Table XXVI shows more or l e s s the same ki n d of r e l a t i o n s h i p s . The Extremity Scores may be explained mostly by Factor 1 ( c a l l e d the knowledge dimen- s i o n ) ; the odds i n In-Basket and the weighted Grade Odds are loaded h e a v i l y on Factor 2; Compensation U t i l i t y scores, on Factor 3? Scale of Wager, on Factor 4; and Choice Dilemma, on Factor 5« This time f i v e f a c t o r s are ex t r a c t e d as the com- puter program ove r r i d e s one's i n i t i a l s e t t i n g of the number of f a c t o r s by us i n g the eigen value r u l e . I d e n t i f y i n g the f a c t o r s becomes harder. Factor 1 i s s t i l l the knowledge dimension; 135 TABLE XXVlbftTllOGONAL FACTORMATRIX AND TRANSFORMATION MATRIX Using Pearson's. V A R I M A X R O T A T E D F A C T O R M A T R I X ( Without spedifying the number of variable factors) F A C T O R 1 F A C T O R 2 F A C T O R 3 F A C T O R 4 F A C T O R 5 Stock Price Wagers 0 . 0 7 9 11 0 . 0 9 5 0 6 - 0 . 2 7 6 8 7 0 . 3 9 3 5 7 0 . 0 2 9 3 3 Extremity Scores'*" # 0 . 9 6 0 5 2 - 0 . 0 3 7 2 7 0 . 0 9 4 1 3 0 . 0 2 8 9 2 0 . 1 2 3 2 9 Plain Extremity # 0 . 9 33 4 4 - 0 . 0 3 7 1 1 0 . 1 3 9 8 6 0 . 0 7 2 6 6 0 . 0 6 6 4 1 Confidence " 0 . 0 0 9 4 7 ' - 0 . 4 1 0 8 0 ' - 0 . 0 3 5 4 9 •"' 0 . 1 2 1 3 0 0 . 0 7 2 1 6 Choice Dilemma 0 . 1 7 5 3 9 - 0 . 0 4 7 0 4 0 . 0 8 3 2 9 0 . 2 2 0 0 2 # 1 . 2 4 1 7 9 Compensation Util. 0 . 2 2 3 5 2 O . C 8 4 3 3 * 1 . 2 4 1 1 5 - 0 . 0 0 4 1 9 0 . 0 2 9 9 7 Scale of Wagers 0 . 1 3 4 0 5 0 . 1 2 6 9 3 0 . 2 0 5 5 8 * 0 . 9 4 4 6 7 0 . 0 3 2 0 5 Rate,of Return - 0 . 1 7 7 0 5 0 . 0 3 6 9 5 - 0 . 0 5 3 3 3 0 . 3 3 1 3 0 0 . 0 5 2 1 9 Profit Net Util. 0 . 2 2 6 3 7 0 . 3 9 5 8 4 0 . 1 5 4 4 4 0 . 3 7 6 9 7 - 0 . 1 8 3 3 0 In-Basket Memo - 0 . 0 6 9 6 6 0 . 0 0 3 1 4 " " ~ 0 . C 0 3 1 6 - 0 . 1 9 1 2 5 - 0 . 1 1 3 6 1 In-Basket Odd - 0 . 1 9 4 1 7 * 0 . 6 6 5 0 1 0 . 0 4 3 7 1 0 . 4 9 4 5 4 0 . 1 1 9 4 4 Grade-odd In-Bask. - 0 - 0 3 0 9 4 . • * 1 . 0 9 6 4 1 — 0 .--0-4-6 2-6 * 0 . 4 5 5 3 1 0 . 0 6 9 6 3 Semantic Differen. 0 . 2 1 8 9 1 0 . 2 6 9 4 9 0 . 2 9 2 1 9 0 . 0 3 0 5 1 0 . 1 0 3 1 8 Squared-Extremity Score - - T R A N S F O R M A T I O N M A T R I X F A C T O R 1 F A C T O R 2 F A C T O R 3 F A C T O R 4 F A C T O R 5 F A C T O R 1 - 0 . 2 9 4 3 0 o . - O . 6 0 5 0 0 - 0 . 3 1 3 7 7 - 0 . 6 1 8 3 0 - 0 . 2 5 8 0 9 F A C T O R 2 0 . 7 3 3 2 5 - 0 . 4 3 9 2 2 0 . 4 4 3 5 0 - 0 . 2 3 0 7 6 0 . 2 3 5 6 2 F A C T O R 3 - 0 . C O 6 6 7 0 . 2 4 2 5 0 0 . 5 5 7 5 3 - 0 . 1 9 5 9 3 - 0 . 7 6 9 3 3 F A C T O R 4 - 0 . 6 1 8 2 5 - 0 . 0 4 6 5 4 0 . 6 0 5 4 3 - 0 . 1 6 4 1 5 0 . 4 7 1 2 9 F A C T O R 5 0 . 1 7 1 7 2 0 . 6 1 6 5 1 - 0 . 1 6 5 5 6 - 0 . 7 0 6 4 8 0 . 2 5 2 7 7 136 Factor 2 i s the b u s i n e s s - r o l e r i s k t a k i n g ; Factor 3 i s the personal u t i l i t y dimension; Factor 4 may be c a l l e d hypothe- t i c a l monetary r i s k t a k i n g and Factor 5, 'advisory' r i s k t a k i n g . The business u t i l i t y items are not loaded h e a v i l y on any of the f a c t o r s ; the same can be s a i d of the Semantic D i f f e r e n t i a l score. The Stock P r i c e Wager scores have the heaviest l o a d i n g on Factor 4 but the l o a d i n g i s not great. The r e s u l t s of the loadings may be explained by the low c o r r e l a t i o n s of the r i s k measures. Because the loadings are g e n e r a l l y weak (or small i n v a l u e ) , f a c t o r analyses r e s u l t s should not be r e l i e d on s o l e l y . Using the Spearman c o r r e l a t i o n matrix r a t h e r than the Pearson, an oblique f a c t o r a n a l y s i s i s undertaken. The f a c t o r c o r r e l a t i o n m a trix of Table XXVIII r e v e a l s t h a t Factors 1 and 5 are s i g n i f i c a n t l y c o r r e l a t e d (at .05 l e v e l , r > .29). The c o r r e l a t i o n of Factors 4 and 5 i s a l s o s i g n i f i c a n t at .05 l e v e l . Five f a c t o r s are e x t r a c t e d t h i s time. Using a c u t - o f f p o i n t at l o a d i n g g r e a t e r than or equal t o . 5 0 , the Scale of Wager i s discovered to load h e a v i l y on three f a c t o r s (1, 4 and 5). T h i s , together w i t h the loadings of the weighted grade odd, may e x p l a i n the r e s u l t a n t f a c t o r c o r r e l a t i o n mentioned above. By comparing Table XXV w i t h Table XXVII, we f i n d t h a t the Choice Dilemma score i n the l a t t e r t a b l e does not l o a d h e a v i l y on any of the f a c t o r s . Also Factor 3 seems to be loaded hea- v i l y by the Memo score i n Table XXVII. The d i s s i m i l a r i t y of the two t a b l e s may be t r a c e d to the d i f f e r e n t c o r r e l a t i o n ma- t r i c e s used. However t h i s d i f f e r e n c e i s not overwhelming when we consider t h a t only net p r o f i t and Choice Dilemma scores are 137 not as h e a v i l y loaded as i n Table XXV. Though the f a c t o r s e x t r a c t e d i n Table XXVII are c o r r e l a t e d , an orthogonal f a c t o r a n a l y s i s (varimax r o t a t e d ) i s a l s o under- taken u s i n g the Spearman c o r r e l a t i o n matrix as i n p u t . A com- pa r i s o n of Table XXVI and XXVIII which shows the r e s u l t a n t f a c - t o r l o adings i s done. Factor 1 of Table XXVIII i s s i m i l a r t o Factor 2 of Table XXVI w h i l e Factor 2 (of XXVIII) i s s i m i l a r to Factor 1 of XXVI. Factor 3 of both i s s i m i l a r . This can a l s o be s a i d of Factor 4. Factor 5 i s e n t i r e l y d i f f e r e n t i n XXVIII because the confidence score and the memo score l o a d on t h i s w h i l e i n XXVI, only the Choice Dilemma does. These f a c t o r a n a l y t i c a l methods are u t i l i z e d i n order to a i d us i n i d e n t i f y i n g the f a c t o r s . However, the r e s u l t s of these methods do not seem t o be of much help to us. The r e l i - a b i l i t y of the f a c t o r s e x t r a c t e d by these methods are moreover open to doubt because of i t s i n s t a b i l i t y . The s t a b i l i t y check i s done by f i r s t d i v i d i n g the data ramdomly i n t o two s e t s . An oblique f a c t o r a n a l y s i s i s done f o r each s e t . Four c a n o n i c a l c o r r e l a t i o n s between the two sets of f a c t o r scores (because f o u r f a c t o r s are requested) are derived. These are 0.98, O.83, 0.74, 0.42 r e s p e c t i v e l y (16, 9, 4, 1 degrees of freedom f o r the r e s p e c t i v e c o r r e l a t i o n s , and p = -0 .0 , -0 .0 , 0.00053, 0.013 based on ch i - s q u a r e ) . Factor c o e f f i c i e n t s derived under the fou r c a n o n i c a l c o r r e l a t i o n s assumption r e v e a l that these run i n d i f f e r e n t d i r e c t i o n s (i.e., f a c t o r c o e f f i c i e n t s of one set are p o s i t i v e w h i l e the f a c t o r c o e f f i c i e n t s i n the second set are n e g a t i v e ) . This means tha t f a c t o r s e x t r a c t e d i n the f i r s t 138 TABLE XXVJI- O B L I Q U E F A C T O R M A T R I C E S U S I N G S H E A R M A N ' S A S I N P U T AFTER R OTATION WITH K i l S C R NORMAL I ZAT ION FACTOR ° A T T E R N STOCK S SOFXT F AC TOR 1 0. 01576 0. 03071 ' " F A C T O R T ~ 0,07936 0.9 22 92 FACTOR" 3 ' -0.01053 -0.01350 "-~F~A"CTOR'4 0.040 50 -0. 18561 FACTOR 5 0.36100 0.10500 EXT sr. AVECO CHO ICE COMPUT SCALES RATERT 0.0 3323 0. 225Q6 -0. 145 8 2 -0.34? 24 -0. 1941 9 0. 19 2° 2 0.93109 -0.06 307 0.33361 "-'0.1415 7 0.22321 -0. 1. 764 3 -0 . 1209 9 0.52 3 84 0.22173 0.325 2? 0.22660 -0.448 8 5 0.03955 0.009 88 0. 082 01 C". 50507 0.47100 0.739 33 -0.04495 -0.C07C3 0 . 1 6 5? 8 -0.13135 0. A 673 9 0.2 3489 PROF IT WI R E S C OOINBS 'GRAODO""" SEMOI C -0.0428 1 0. 13 597 -0. 6 6 3 4 7 - 1 . 06701 -0. 432 3 9 - 0 . 06720 - 0. C 1 84 2 -0.1139 6 -0.20411 0.16386 0.0 643 2 -0.50240 -0.0419 3 -0.29318 0.05030 -0.0 36 08 0.039 78 0.21867 -0.17 8 5 3 • 0.01780 0.82483 -0.06115 0. 2 2 388 " 0. 5 2 616 , -0.10656 FACTOR STRUCTURE FACTOR 1 •EACT OR 2 FACTOR 3 •FACTOR 4 FACTOR 5 "STOCK S -07112 16 _ „ _ . _ _ _ 0.12716 0'.'3 7 86'4 SOEXT -0. 11766 +0.9 5713 0.08563 -0.30742 0.16109 EXTSC -0.10846 * 0 . 9 4 5 2 6 0.02063 -0.145 46 0.08698 AVECO 0. 153 95 -0.02362 0.48787 0.01933 -0.11138 CHOICE -0. 2976 4 6. 3 5895 0.28447 0.13415 0.25785 C0 MPUT -0.4 3510 -0.1 308 3 0.410 9 r, * 0 . 593 05 0.07742 SCALES * - 0 . 506 1 2 "0." 2-3 02 6"" '07303 92 " " * 0.6 3;> 7 5 * 0.67554 RATFRT 0. 0 J2 56 -0.35942 -0.44737 * 0. 750 33 0.3 9411 PROF T T -0. 2 7 7 3 5 0.05930 0.0075 3 0.22566 .#0. 81477 V I R E S C 0. 2 32 3 3 -a.127"6 #-0.51762 -0 . C 5C ">'> -0.0619 8 0DIN3S *"-0. 7547 1 - 0 o 0 1511 0.04641 0.4 3949 0.47236 GRAGOO * - 1 . 10630 0.0 3 270 - 0 . 21404 0.20321 * 0.7 8 366 SEMOIP -07440? 2 ' 07"2'2"95T 0. 14614 0.0 58 5? 0.04462 FACTOR CORRELATIONS FACTOR 1 F A C T O R 2 " FACTOR"" 3 FACTOR 4 FACTOR' FACTOR 1 1. 0000 0 - 0 . 17271 -0.14728 -0.212 66 -0.29 68 5 FACTOR 2 -0. 1 72 71 1 .00000 0. 14352 -0. ] 5S 0.12701 FACTOR 3 -0. 14723 0,143 5 2 1.00000 0.09397 -0.0606 8 FACTOR 4 -0. 212 66 -0.13559 0.0 9397 1.COO 00 0.28629 FACTOR 5 -0. 2963 5 ' .<__ 0.12701 -0.0606 8 _ 0.28629 1.00000 - refer to tg.ble XXVIfor the meaning of abbreviated variable names 139 TABLE XXVIII ORTHOGONAL FACTOR MATRIX USING SPEARMAN'S AS INPUT F A C T O R 1 F A C T O R 2 F A C T O R F A C T O R F A C T O R S T O C < S S Q F X T J X T S : _ A V F C O ' C H O I C E C O M P U T S C A L E S R A T E R T _PP0F_1J_ W f R E S C " C D I M O S G R A O D D 0 . OH- 7 7 7 0 . 0 I t 9 4 _ 0 ^ 0 2 6 6 4 -o.i . ' U j 0 . 2 3 0 9 6 0 . 4 5 4 5 3 0 . 0 9 1 2 0 * 0 . 9 4 1 0 4 * 0 . 9 5 2 ^ 9 ""-OT04 7 4 3 0 . 3 2 5 6 6 - 0 . 1 6 5 7 1 0 . 0 6 6 9 2 - 0 . 2 2 2 9 9 - 0 ^ 0 2 2 9 9 07"013 8" 3 " 0 . 0 5 2 1 8 0 . 4 3 6 5 8 0 . 4 0 3 5 3 - 0 . 0 4 9 8 2 _ 0 . 1 5 2 5 9 _ ""-"iT ."lT6 4 2 * 0 . 7 2 4 0 0 At 1 . 0 3 6 9 0 0 . 2 1 9 4 2 - 0 . 3 C 7 6 1 - O . f 0 7 _ 3 9 • - 0 . cTioT - 0 . 0 8 2 5 0 - 0 . 0 8 0 1 4 0 . 4 4 7 4 1 * 0 . 7 6 0 9 0 0 . C 4 O 5 3 0". 0 7 0 4 2 / 0 . 2 1 2 2 3 - 0 . 1 2 3 5 5 0 . 3 6 5 8 2 C . 1 3 0 3 6 0 . 0 3 0 4 1 -0T05"801" 0 . 2 1 8 7 8 C O 0 3 1 0 C . 5 9 0 4 ? 0 . 3 3 5 6 8 * C . 8 0 4 6 6 " ~ - 0 . 0 6 4 4 6 " 0 . 3 6 1 0 3 * 0 . 6 4 7 5 9 - 0 . 0 1 8 3 3 0 . 0 1 C I O - 0 . 0 4 7 0 5 M c . 5 1 T 5 9 0 . 2 4 9 8 4 0 . 4 0 7 9 0 l . 2 9 3 3 4 - 0 . 3 6 8 0 8 0 . 0 1 3 4 4 * - 0 . 4 9 5 5 1 - 0 . 0 0 0 5 2 - 0 . 3 1 1 9 2 SEMOf F 0 . 4 3 1 1 0 0 . 1 9 3 0 2 - 0 . 0 2 2 4 4 - 0 . 0 2 1 1 5 0 . 0 8 7 8 2 T R A N S F O R M A T I O N M A T R I X F A C T O R F A C T O R F A C T O R 3 F A C T O R F A C T O R F A C T O R F A C T O R F A C T O R . F A C T O R F A C T O R 1 2 - 0 . 7 2 7 4 6 0 . O 0 6 9 6 3 4 5 0 . 1 5 1 2 3 -0. 5 5 1 5 0 - 0 . 3 7 9 1 1 - 0 . 0 6 9 9 3 0 . 9 3 5 0 3 - 0 . 0 9 5 5 3 0 . 2 3 3 7 0 - 0 . 2 3 3 0 0 - 0 . 2 3 2 7 2 - 0 . 3 2 2 9 3 0 . 1 5 0 2 3 0 . 7 2 0 5 0 - 0 . 5 4 7 5 6 - 0 . 6 4 3 . 5 2 0 . 0 0 4 1 4 - 0 . 2 3 5 8 1 0 . 3 3 6 2 1 C . 6 ^ - 7 9 1 - C . 0 1 3 7 7 0 . 1 4 6 0 5 0 . 9 4 3 3 0 0 . 0 8 1 8 9 0 . 2 8 6 2 7 * REFER TO TABLE XXVIfor meaning of the abbreviated variable names. 140 set are not i d e n t i c a l to the f a c t o r s i n the second s e t . Thus, the f a c t o r s are s a i d to he unstable. I t i s a d v i s a b l e not to read too much from the r e s u l t s of the f a c t o r a n a l y s i s as these may not be s t a b l e . I t i s recom- mended t h a t f u t u r e research u t i l i z e s the analyses undertaken here i n order to r e s o l v e the multidimensional i s s u e and name the f a c t o r s f i n a l l y . This i s done when the sample s i z e ( d e f i - n i t e l y g r e a t e r than the ones we have secured) i s s u f f i c i e n t l y l a r g e . Risk Taking as a Function of Other V a r i a b l e s I f one were to c o n s t r u c t a model of r i s k t a k i n g behavior, one would l i k e to look at how other v a r i a b l e s — e . g . , demographic— r e l a t e to r i s k t a k i n g . This i s u s e f u l i n p r e d i c t i n g r i s k t a k i n g propensity once we know what the exact r e l a t i o n s h i p s are. A l - though seemingly elementary, the a n a l y s i s to f o l l o w can be con- s i d e r e d as a f i r s t step i n model b u i l d i n g . Before d i s c u s s i n g the model, we would l i k e to present here the r e s u l t s of the demographic in f o r m a t i o n secured from the s u b j e c t s . The Personal Record questionnaire intends to secure i n f o r - mation concerning the s u b j e c t s ' demography—e.g., age, amount of a s s e t s , number of years at work, dependents, academic back- ground, amount of l i a b i l i t y , e t c . A review of some of these responses w i l l a l s o shed l i g h t on the nature of the subjects used. Only three of the subjects are female, rendering the i n - v e s t i g a t i o n of s e x - r i s k t a k i n g r e l a t i o n s h i p h i g h l y u n l i k e l y . 141 C u l t u r a l d i f f e r e n c e s i n r i s k t a k i n g propensity cannot be examined because 7 3 $ of the subjects are Canadian. Twenty-eight of the subjects are M.B.A.'s while f i v e are M.Sc. w i t h one M.B.A.-Ph.D. combined and two missing. An i n t e r - e s t i n g p o s s i b i l i t y , given a l a r g e sample s i z e , i s to look at r i s k t a k i n g propensity d i f f e r e n c e s and the degrees sought by s u b j e c t s , or t h e i r o p t i o n areas. This q u e s t i o n n a i r e a l s o asks questions on hobbies and spor t s from which we t r y to deduce a person's r i s k t a k i n g a t t i - tudes ( i . e . , are the sports the su b j e c t s engaged i n r i s k y or notj do they gamble i n r e a l l i f e , e t c . ) . S k i i n g , considered as a r i s k y s p o r t , i s engaged i n by 42$ of the s u b j e c t s . But a l l of the subjects have such m u l t i p l i c i t y of hobbies (ranging from v i o l i n to k n i t t i n g ) t h a t the r i s k t a k i n g a t t i t u d e s based on hobbies could not be deduced. As to gambling, 40% do not en- gage i n any form of gambling—not even i n investments. Because of t h i s l a c k of v a r i a b i l i t y o r , to be s p e c i f i c , the f a i l u r e to a s c e r t a i n the su b j e c t s ' r t propensity from t h e i r hobbies and l e i s u r e , these v a r i a b l e s are del e t e d . Only a few important v a r i a b l e s are r e t a i n e d f o r p r a c t i c a l purposes. The degrees of freedom are not l i k e l y to be b i g be- cause of our sample s i z e and because of the p a r t i a l c o r r e l a t i o n s that w i l l " be undertaken. The f o l l o w i n g v a r i a b l e s are usedi average age of the dependents, working years, s a l a r y , face value of insurance, amount of assets and amount of l i a b i l i t i e s . Age i s d e l e t e d because the p a r t i a l c o r r e l a t i o n s of t h i s v a r i a b l e w i t h r i s k measures are not s i g n i f i c a n t . 142 There i s a l s o the question of what r i s k measures should be r e t a i n e d . For some q u e s t i o n n a i r e s , two or more scores are ex t r a c t e d and they are cl o s e s u b s t i t u t e s of one another. For example, the p l a i n extremity score i s delete d because i t can be s u b s t i t u t e d by the squared extremity score. A l s o , i f a measure showed poor r e l a t i o n s h i p w i t h the r e s t of the scores, i t i s delet e d f o r t h i s a n a l y s i s . The candidates are Semantic D i f f e r e n t i a l (discussed i n the C o r r e l a t i o n Matrix s e c t i o n and i n the Factor A n a l y s i s s e c t i o n ) and Net P r o f i t U t i l i t y . Table XXIX r e v e a l s to us a l l the s i g n i f i c a n t p a r t i a l cor- r e l a t i o n s of the r i s k measures w i t h the s e l e c t e d demographic v a r i a b l e s . The r e s u l t s of the matrix imply t h a t most of the r i s k measures are not d i r e c t l y r e l a t e d to these v a r i a b l e s . Compensation and s c a l e of wager do not have any r e l a t i o n s h i p at a l l w i t h these demographic v a r i a b l e s . These r e s u l t s may be i n t e r p r e t e d to i n d i c a t e t h a t more work should be undertaken f o r the r i s k measures i n terms of r e v i s i o n s and trimming. And i f the Personal Record responses were u n r e l i a b l e , t h i s suggests th a t the design c a r r i e d out f a i l e d to e l i c i t t r u e responses on personal r e c o r d s — e . g . , most of the subjects f e l t t h a t t h e i r anonymity was being threatened by g i v i n g responses on t h e i r personal l i v e s . Stock P r i c e Wager score (Stock) i s n e g a t i v e l y r e l a t e d to number of years at work (Wyear). This suggests t h a t there i s the tendency f o r people w i t h more years at work to take more r i s k when o f f e r e d stock p r i c e wagers. I t can be i m p l i e d t h a t the more 'experienced* a subject i s , the gr e a t e r r i s k - t a k e r he i s . 143 Salary and number of years at work are h i g h l y r e l a t e d to extremity i n judgment. But the r e l a t i o n s h i p s are negative. The subjects w i t h higher previous s a l a r y and number of years at work become l e s s extreme i n t h e i r judgment. I t i s p o s s i b l e to guess that the more experienced one i s the l e s s one dares to take r i s k i n the knowledge dimension. The Choice Dilemma score, which r e f l e c t s advisory r i s k - t a k i n g , i s n e g a t i v e l y r e l a t e d to number of years at work, amount of previous s a l a r y and amount of l i a b i l i t i e s , but i t i s p o s i t i v e l y r e l a t e d to face value of insurance. This i m p l i e s t h a t higher s a l a r i e d , 'more years at work' i n d i v i d u a l s recom- mend other people to take g r e a t e r r i s k s . But i f t h e i r i n s u r - ance face value i s hi g h , they advise other people to take l e s s r i s k s . One must however e x e r c i s e c a u t i o n i n i n t e r p r e t i n g these r e s u l t s . Choice Dilemma, by f a r , has the most r e l a t i o n s h i p s w i t h these demographic v a r i a b l e s . The r e l a t i o n s h i p of the memo score and the age (average) of the dependents i s strange i n t h a t i t i m p l i e s t h a t a person w i t h heavy r e s p o n s i b i l i t y (support of the dependents) recommends t a k i n g g r e a t e r r i s k i n business ventures. This r e l a t i o n s h i p i s thus h i g h l y d o u b t f u l . The p o s i t i v e r e l a t i o n s h i p of the number of years of work and s a l a r y w i t h the memo score suggests t h a t the more experienced subjects are more conservative. The In-Basket Odd score i s p o s i t i v e l y r e l a t e d t o amount of l i a b i l i t i e s — i . e . , i n d i v i d u a l s who have l a r g e amounts of l i a b i l i t y tend to be more r i s k averse. 144 I n t e r n a l - E x t e r n a l c o n t r o l , based on the t a b l e , can be viewed as a f u n c t i o n of s a l a r y and average age of dependent. Following t h i s l i n e of ca u s a t i o n , we can say that as an i n d i - v i d u a l gets more and more s a l a r y , r e f l e c t i n g more promotion or reward f o r a b i l i t i e s , he becomes more i n t e r n a l l y c o n t r o l l e d . The r e l a t i o n s h i p of IE c o n t r o l and age of dependent i s dou b t f u l because i t could imply t h a t the age of the dependent determines a person's IE c o n t r o l . This means the i n d i v i d u a l becomes more i n t e r n a l l y c o n t r o l l e d when the average age of h i s dependents i n c r e a s e s . Sensation-seeking i s r e l a t e d s i g n i f i c a n t l y only to the amount of previous s a l a r y . This i m p l i e s that s u b j e c t s w i t h higher previous s a l a r i e s tend to seek more s t i m u l a t i o n from t r a v e l l i n g , s o c i a l a c t i v i t i e s , e t c . Asset, expressed i n terms of gross v a l u e , does not have any r e l a t i o n s h i p w i t h any of the v a r i a b l e s . Taken at i t s face v a l u e , t h i s would mean the r e j e c t i o n of the v a r i o u s hypotheses concerning s i z e of asset and r i s k t a k i n g . The poor r e s u l t s of the t a b l e can be t r a c e d t o e i t h e r of three sources t (1) e i t h e r the personal records d i d not e l i c i t t r u e responses i n t h a t subjects d i s g u i s e d t h e i r answers to pro- t e c t anonymity, (2) the m a j o r i t y of r i s k measures are f a u l t y so th a t the hypothesized r e l a t i o n s h i p s between measures and demo- graphic v a r i a b l e s d i d not occur; or (3) both the measures and the personal record q u e s t i o n n a i r e are f a u l t y . Source (1) seems to be predominant i n that the v e r b a l feedbacks from the subjects a f t e r they responded i n d i c a t e d t h a t they had to put down u n r e a l TABLE XXIX P a r t i a l C o r r e l a t i o n s of Risk Measures wi t h Selected V a r i a b l e s Age Dependent Working Years Salary Insurance Face Value Assets L i a b i l i t i e s Stock — -0.44 — — — Extremity Sc. — -0.98 -.98 -- Choice Dilemma .689 -0.69 -.55 0.40 -0.43 Compensation — — — — — Scale Wager — — — — — Rate Return — — •.;T— • — — Memo Score -0.597 0.497 0.51 — — In Basket Odd — — — — 0.43 I n t . - E x t . Control .40 — — — SSS . . . — .39 — 1 Only those s i g n i f i c a n t ( p<0 . 0 5 ) presented, DF = 16. Legend t Stock - Stock P r i c e Wager Extremity - Squared Extremity Score Choice - Choice Dilemma Odd SSS - Sensation Seeking 146 amounts sometimes because the que s t i o n n a i r e was too pe r s o n a l . As to source (2), some of the measures must be r e v i s e d . This has been suggested i n the previous p a r t s . Discussion The c o r r e l a t i o n matrix of the v a r i o u s r i s k measures i m p l i e s t h a t the u n d e r l y i n g construct i s not unidimensional. Although one should not r e l y too h e a v i l y on the f a c t o r analyses c a r r i e d out, extremity-confidence i n judgment i s d e f i n i t e l y of a d i f f e r - ent dimension. This e n t i r e measure, when viewed i n the l i g h t of our p r e v i o u s l y c i t e d c r i t e r i a , may be removed. The Seman- t i c D i f f e r e n t i a l score i s another r i s k score that should be e l i m i n a t e d because of i t s weak a s s o c i a t i o n w i t h the other scores and because i t i s not a d i r e c t r t propensity measure. The U t i l i t y measures can be dichotomized i n t o two kinds i a personal and a business u t i l i t y measure. Net P r o f i t U t i l i t y appears to be weakly loaded on a l l the f a c t o r s . The r e s u l t s of the f a c t o r analyses r e v e a l t h a t the f a c t o r s are n e i t h e r expected nor i d e n t i f i a b l e . The Memo score, as revealed by the o v e r a l l a n a l y s i s , i s i m p l i e d to be questionable i n v a l i d i t y . This may be c o r r e c t e d by a b e t t e r judging procedure than the one employed here. An attempt at model-building r e v e a l s t h a t the demographic v a r i a b l e s l i k e age of dependents, insurance, l i a b i l i t i e s , e t c . , have very l i t t l e r e l a t i o n s h i p w i t h our r i s k measures. Asset, considered by many to be h i g h l y r e l a t e d to r i s k t a k i n g , has no s i g n i f i c a n t r e l a t i o n s h i p w i t h any of the r i s k measures. Com- pensation and Scale of Water u t i l i t y scores cannot be considered 14? as f u n c t i o n s of the demographic v a r i a b l e s we look a t . The e m p i r i c a l study undertaken should be considered as a p r e - p i l o t i n t h a t the o b j e c t i v e i s not t o undertake a major e m p i r i c a l research venture but to get a f e e l of how the ques- t i o n n a i r e s are being responded t o . I t i s suggested th a t one could use t h i s group as a p i v o t f o r studying other g r o u p s — e.g., comparison of t h i s group w i t h other p r o f e s s i o n a l groups l i k e a c t u a l businessmen, economists, e t c . 148 CHAPTER 8 CONCLUSIONS Men do not l i v e by- expected value alone. A l f r e d Kwong, 1973 The purpose of t h i s study has been to develop a s e r i e s of r i s k t a k i n g measures which are r e l e v a n t to business. T h i r t y - f i v e graduate students were administered a package of r i s k t a k i n g measures i n business, personal record and person- a l i t y q u e s t i o n n a i r e s . Several research questions were examined. The r e s u l t s of the i n t e r c o r r e l a t i o n s among the v a r i o u s r i s k measures suggest t h a t the u n d e r l y i n g c h a r a c t e r i s t i c i s not unidimensional. Several f a c t o r a n a l y t i c a l methods were t r i e d but the r e s u l t a n t f a c t o r s were n e i t h e r expected nor i d e n t i f i a b l e . The r i s k measures were developed by adopting r e v i s e d ver- sions of past measures and c o n s t r u c t i n g measures r e l e v a n t f o r our purposes. Chapters 2 and 3 d e a l w i t h the background, economical and p s y c h o l o g i c a l , of r i s k measures and the research conducted i n the past concerning these measures. Chapter 4 describes the package of measures and discusses the importance of studying r i s k t a k i n g p r o p e n s i t y , e s p e c i a l l y i n r e l a t i o n to d e c i s i o n theory. 149 Chapter 5 o u t l i n e s the method employed i n the e m p i r i c a l study, emphasizing the way the package has been administered; and the i n s t r u c t i o n s to the s u b j e c t s have been presented i n t o t o . Chapter 6 examines the measures and the responses i n the l i g h t of past hypotheses concerning r i s k - t a k i n g . Item analy- s i s , although f a i r l y g e n e r a l , has been done. Chapter 7 presents an o v e r a l l a n a l y s i s of the measures by examining the r e s u l t i n g c o r r e l a t i o n matrix of the r i s k mea- sures, the f a c t o r a n a l y t i c a l r e s u l t s of f o u r d i f f e r e n t methods and the r e l a t i o n s h i p of r i s k t a k i n g w i t h demographic v a r i a b l e s . Risk t a k i n g p r o p e n s i t y , due t o the s t a t e of the a r t , i s an •unknown p r i m i t i v e ' according to S l o v i c . However, attempts at the f i n a l e m p i r i c a l d e f i n i t i o n of the construct have not been numerous. The m u l t i d i m e n s i o n a l i t y i s s u e , r a i s e d f o r q u i t e some time, i s s t i l l extremely d i f f i c u l t to r e s o l v e . The r i g h t d i r e c t i o n i s taken only when more con s t r u c t v a l i d a t i o n of past measures and of newer measures i s undertaken. The i n t e r e s t i n the area i s beginning to move i n the r i g h t d i r e c t i o n . The study of r i s k t a k i n g p r o p e n s i t y i s not confined to one d i s c i p l i n e . Each d i s c i p l i n a r y approach to the study, how- ever, has i t s advantages and disadvantages. U t i l i t y theory has progressed t o such a stage that r i s k a v e r s i o n i s examined f o r normative reasons. C u r r e n t l y , economists are more concerned w i t h the forms of u t i l i t y curves, the equations and the i n d i c e s , than w i t h the problem of v a l i d a t i n g the measures. However, there i s a contention t h a t by examining the forms of the 150 u t i l i t y curve and d e r i v i n g u t i l i t y f u n c t i o n s the economists are v a l i d a t i n g t h e i r measures. The p s y c h o l o g i s t s , on the other hand, have g e n e r a l l y been more preoccupied w i t h u s i n g past measures and examining the r e l a t i o n s h i p of r i s k t a k i n g and p e r s o n a l i t y v a r i a b l e s than i n more c r e a t i v e endeavours l i k e newer c o n s t r u c t i o n and 'updating v a l i d a t i o n . ' For the layman l i k e myself, the c e n t r a l question i s how to make use of the f a c t s concerning r i s k t a k i n g p r o p e n s i t y . And t h i s i s important i n the f i e l d of decision-making. The present study undertaken has i t s l i m i t a t i o n s . One i s the sample s i z e and two, the nature of the sample. A l s o , the suggestions contained i n Chapters 6 and 7 would mean more design work (by design, I mean the design of the measures themselves). The t h e s i s , however, has been able to i n d i c a t e areas of weakness i n the measures themselves. The d e f i n i t i o n of b u s i - ness r e l a t e d r i s k t a k i n g has a l s o been examined and found to be a broader construct than we o r i g i n a l l y thought. Our major accomplishment i s i n suggesting what a f i n a l package of b u s i - ness r e l a t e d r i s k measures should c o n t a i n . Recommendations f o r Future Research Data from d i f f e r e n t segments of the p r o f e s s i o n (e.g., graduate students i n other areas) might y i e l d d i f f e r e n t r e s u l t s — e.g., d i f f e r e n t f a c t o r s might emerge, d i f f e r e n t c o r r e l a t i o n s might r e s u l t , e t c . A l s o , the purpose of the study i s to con- s t r u c t ' b u s i n e s s - r e l a t e d r i s k measures' and what other group can a i d us i n v a l i d a t i n g these measures than the businessman. Based on a s t a t i s t i c a l a n a l y s i s of data from other samples, one could a s c e r t a i n once and f o r a l l which measures should be 151 r e t a i n e d , r e v i s e d or completely removed. The psychology of economic development has been an enigma ever s i n c e someone thought up the t o p i c . We hear comments about r i s k t a k i n g and the l i k e , but they are not confirmed. Thus, a f u r t h e r extension would be the development of a com- prehensive business r i s k t a k i n g measure on an i n t e r n a t i o n a l b a s i s . A f u r t h e r dynamism would be a study of r i s k t a k i n g propensity i n the i n t e r n a t i o n a l s e t t i n g u s i n g time as a v a r i - a b l e , i . e . , t r a c i n g the nature of changes i n r i s k t a k i n g pro- p e n s i t y . The s o - c a l l e d theory of independence i m p l i e s that s o c i e t y would b e n e f i t economically i f i t s components took g r e a t e r r i s k s i n business. Various government i n c e n t i v e s have been imple- mented to encourage business r i s k t a k i n g s . However, the empir- i c a l f i n d i n g s concerning the r i s k t a k i n g propensity of the business community are -not i n e x i s t e n c e . Assumptions of the general r i s k a v e r s i o n of the p u b l i c are u s e f u l but knowing the exact degree of r i s k a v e r s i o n would be a b e t t e r guide to govern- ment economic i n c e n t i v e planning. A l s o , what determines one's business r i s k t a k i n g may be answered a f t e r a package of business r t measures has been f i - n a l l y v a l i d a t e d and developed. Perhaps the r e s u l t of an i n t e n - s i v e study suggests a newer form of o r i e n t a t i o n — s p e c i f i c a l l y , newer methods i n teaching business students. For the business o r g a n i z a t i o n , possession of a s a t i s f a c - t o r y r i s k t a k i n g measure would help i n s e t t i n g up a corporate r i s k p r o f i l e and i n human resource a l l o c a t i o n . This i s one of 152 the major i m p l i c a t i o n s of the f i n a l development of a sound business r i s k t a k i n g measure. Bargaining and r i s k t a k i n g i s another i n t e r e s t i n g t o p i c to research i n t o i n tha t r i s k sharing or the d i v i s i o n of s p o i l s may become more systematic and d e t e r m i n i s t i c as a r e s u l t of the study. A l s o , the v a r i o u s c o a l i t i o n models may be examined i n a r i s k - t a k i n g - p r o p e n s i t y c o n t e x t — i . e . , whether r i s k t a k i n g propensity i n f l u e n c e s the type of c o a l i t i o n t h a t r e s u l t s or not. A Model of r i s k t a k i n g , as a f u r t h e r development, should be attempted i n which one could look at r i s k t a k i n g propensity and the v a r i o u s v a r i a b l e s t h a t are r e l a t e d to i t . There are, to be sure, many p o s s i b i l i t i e s once one gets beyond the development stage. 153 BIBLIOGRAPHY ANDERSON, R.M. "Handling Risk i n Defense Contracting." Harvard Business Review. July-August 1969. 90-98. ALDERPER, C P . & BIERMAN, H., J r . "Choices with Risk: Beyond the Mean and Variance." Journal of Business, Vol. 43 (1970), 341-353. ARROW, K.J. "Alternative Approaches to the Theory of Choice i n Risk-taking Situations." Econometrika, v o l . 19 ( 1 9 5 D . 417,426. ,T ", ".C_ Aspects of the Theory of Risk Bearing, Academic Book, H e l s i n k i , Finland 1965- ATKINSON, J.W. "Motivational Determinants of Risk Taking Behaviors." Psychological Review, 64 (1957), 358-372 . , . . .« BASTIAN, J.R., EARL, R.W., & LITWIN, G.H. "The Achievement Motive, Goal Setting & P r o b a b i l i t y Preferences." J. of Abnormal So c i a l Psychology, 60 ( I 9 6 0 ) , 27-36. BASSLER, J.F. "The Consistency of Risk Attitudes i n Decision Making Under Uncertainty.^- Unpublished Dissertation 1972. Carnegie Mellon Univ., Graduate School of I n d u s t r i a l Administration. BATESON, N. "F a m i l i a r i z a t i o n , Group Discussion & Risk Taking." J. of Experimental S o c i a l Psychology 2 (1966) 119-129. BERNOULLI, D. "Specimen Theoriae Novae de Mensura S o r t i s " Commentarii Academiae Scientiarum Imperiales Petropolitanae Translated into English by L, Sommer as "Exposition of a New Theory i n the Measurement of Risk". Econometrica 12 (1954): 23-36. BORCH, K. "Introduction," Risk and Uncertainty (K. Borch & J. Mossin ed.), IEA, MacMillan, N.Y. 1968, p . x i i i . BREHAUT, CH. "Uncertainty and the Capital Investment Decision." Unpublished Master's Thesis. UBC, 1968. Graduate School of Business. BRIM, O.G., J r . & Hoff, D.B. "Individual and S i t u a t i o n a l Differences i n Desire f o r Certainty." J. Abnormal Soc. Psych. 54 (1957), 225-229. BRO'EHL, W. J r . "A Less Developed Enterpreneur" Columbia J . of World Business, 5-2 (1970), March-April, 26-27. 154 BRUNER, J.S. & TAJPEL, H. "Cognitive Risk and Environmental Change." J. Abn. Soc. Psych, 62 (1965),-231-241. BUCHAN, P.B. "An Inquiry Into the Risk Taking Attitudes of Managers" Unpublished Dissertation, 1969, Univ. of Michigan, CAMERON, B. & MYERS, J.L. "Some Personality Correlates of Risk Taking" J. Gen. Psych., 74 (1966), 51-60. CAMPBELL, D.T. & FISKE. D.W. "Convergent and Discriminant Va l i d a t i o n by the Multi-trait-Multimethod Matrix." Psvch. B u l l e t i n 56 (1959), 81-105. COHEN, J. Chance, S k i l l & Luck Baltimore, Penguin, i 9 6 0 . • ., And HANSEL M. Risk and Gambling. N.Y., Philosophical ' Library,• 1 9 5 6 . COOKS, S.W. & SELLTIZ, C. "A Multiple-Indicator Approach to Attitude Measurement." Psych. B u l l e t i n 62 (1970), No.l, 36-55. COOMBS, CH. & HUANG, L. "Test of a P o r t f o l i o Theory of Risk Preference." J. Exp. Psych. 85-I (1970), 23-29. , & PRUITT, D.G., "Components of Risk i n Decision Making." J. Exp. Psych. 60 ( i 9 6 0 ) , 265-277. CRONBACH, L.J., "Response Sets & Test V a l i d i t y . " Educ. Psychol. Meas. 60 (1946), 265-277. DANIELSON, L.E. "Gambling Proneness" Its Measurement and Expression in Examination Situations." Unpublished Doctoral Dissertation (1957) Univ. of Michigan, DE GR00T, M.H. Optimal S t a t i s t i c a l Decisions. N.Y. McGraw- H i l l 1970. EDWARDS, W. "Probability Preference in Gambling". American J . of Psych., 66 (1963). 349-364. "Probability Preference Among Bets.With -Differing , "Expected ..Value" / A:.:. J. Psych. 67 (1954), 56-67 "(a) "~ "Variance Preference i n Gambling", Am. J. Psych. 67 (1954), 441-452 (b) 1 5 5 ELLSBERG'-, D. "Risk Ambiguity & The Savage Axioms. "Q.il. of Economics 1961. 6 4 3 - 6 6 9 . FELLNER, W. "Distortion of Subjective P r o b a b i l i t y As a Reaction to Uncertainty," Q.J.E. Nov. 1961, 670-689. FILLENBAUM, S. "Some S t y l i s t i c Aspects of Categorizing Behavior." J. Personality, 27; (1959) 187-195. FISHER, I. "Is ' U t i l i t y ' The Most Suitable Term for the Concept I t i s Used to Denote?" Am. Eco. Review 8 (June, 1918), 335-337. FREDERIKSEN, N. "Factors i n In-Basket Performance". Psycholo- g i c a l Monographs, 76 (22, Whole No. 541) 1962. FRIEDMAN, M. & SAVAGE L.J. "The U t i l i t y Analysis of Choices Involving Risk" J.P.E. 56 (1948), 279-304. GARDNER, R.W. "Cognitive Styles i n Categorizing Behavior," J. of Pers., 22 (19*53) t 214-233. GILLEY, D.R. "Investment Decision under Risk and the Modig- l i a n n i and M i l l e r Hypothesis," Unpublished Master's Thesis, 1967, UBC. GORDON, L.V. " V a l i d i t i e s of the Forced Choice & Questionnaire Methods of Personality Measurement." J. Applied Psych. 35 (1951), 407-412. GRAYSON, J.C. Decisions Under Uncertainty. Boston. Harvard Business School, D i v i s i o n of Research, i 9 6 0 . GULLIKSEN, H., Theory of Mental Tests N.Y. Wiley 1950 HAMMOND, J . S . I l l , "Better Decisions with Preference Theory." H.B.R., Nov-Dec. 1967, 123-141. HARDY, CO. Risk and Risk Bearing. UC Press, Chicago, 1923. HEMPHILL, J.K., GRIFFITHS, D.E., & FREDERIKSEN, N. Administrative Performance and Personality. A Study of the P r i n c i p a l i n a Simulated Elementary School. N.Y. Teacher's College, Bureau of Publication 1962. HERTZ, D.B. "Risk Analysis i n Capital Expenditure Decisions." HBR, Jan-Feb. 1964, 95. 156 HOWARD, R.A. "Decision Analysis: Applied Decision Theory" i n D.B. Hertz and J. Melese ed, Proceedings of the 4 t h International Conference on Operations Research 196"S JELLISON, G.M. & RISKIND, J. "Social Comparison of A b i l i t i e s and Interpretation of RT Behavior." J. Pers. & Soc. Psych. 1 5 - 4 ( 1 9 7 0 ) , 3 7 5 - 3 9 0 . KEYNES, J.M. A Treatise on Pr o b a b i l i t y . London: MacMillan 1921 p.21. KOGAN, N. & WALLACH, M.A. Risk Taking: A Study i n Cognition & Personality. N.Y.: Holt, Rinehart & Winston 1964. "Risk Taking as a Function of the Situation, The Person and the Group" i n New Directions in Psychology I I I , N.Y.: Holt, Rinehart & Winston, 1967. 113-224. KNIGHT, F.H. Risk, Uncertainty & P r o f i t Boston: Houghton- M i f f l i n , 1921. LEFCOURT, H.M. & STEFFY, R.A. "Level of Aspiration, Risk Taking Behaviors and Projective Test Performance: A Search for Coherence" J. of Consulting & C l i n i c a l Psychology (1970) 3 4 - 2 , 193-198". LIETAER, B.A. "Managing Risks i n Foreign Exchange." HBR March-April (1970) 127-138. LINDSAY, R. & SAMETZ, A.W. Fin a n c i a l Management Hanewood: R. Irwin 1963. LIVERANT, S. & SCODEL, A. "Determinants of Decision Making Under Conditions of Risk." Psych. Rep. 7 (I960) 5 9 - 6 7 . LORANGE, P. & NORMAN, V.D., "Risk Preference Patterns Among Scandinavian Tankship Owners" In s t i t u t e of Shipping Research, Bergen. 1971* 1-48. LUCE, R.D. & RAIFFA,: H. Games & Decisions N.Y.: Wiley 1957 Chapter 2. LUTZ F.. & LUTZ, V. The Theory of Investment of the Firm Princeton: Princeton U. Press 1951 • MACCRIMMON, K.R. & T0DA$, M. "The Experimental Determination of Indifference Curves" Rev, of E-C-o. Studies 3 6 - 4 (1969) 433-^51 Vrj) 157 MacCRIMMON, KeR„ "elements of Decision Making" (PART I) NOV., Working Paper 7 5 , UBC, Faculty of Comm. & B.A., 1 9 7 0 . , & TODA, M. "The E f f i c i e n t Determination of True Preference Equivalences" June, W.P. 9 5 , U.B.C. Faculty of Comm, & B.A., 1 9 7 1 , "Managerial Decision Making" Feb., W.P. 117, U.B.C., Faculty of Comm. & B.A,, 1 9 7 2 . , & KWONG, A.C. "Measures of Risk Taking Propensity." June, Interim Report, ITC Risk Study Project, W.P.I. , UBC'; 1 9 7 2 . MADARAS, G.R. & BEM D.J. "Risk and Conservatism i n Group Decision Making." J. Exp. Soc. Psych. 4 ( 1 9 6 8 ) , 3 5 0 - 3 6 5 MAEHR, M.L. & VIDEBECK, R. "Predisposition to r i s k and pe r s i s - tence under varying reinforcement-success schedules" J. of Pers. & Soc. Psych. 9 (1968) 9 6 - 1 0 0 MAGEE, J.F. "Decision Trees for Decision Making". HBR, July - Aug. (1964) p.126 "How to Use Decision Trees i n Capital Investment" HBR, Sept.-Oct, (1964) p.79. MARKOWITZ, H. "Po r t f o l i o Selection" J. Finance 7 (March, 1952) 77-91 (a) "The U t i l i t y of Wealth" JTE 60 (1952) 1 5 1 - 5 8 . P o r t f o l i o Selection. N.Y.: Wiley & Sons, 1 9 5 9 . MARQUIS, D.G. "Individual R e p o n s i b i l i t y and Group Decisions Involving Risk" In d u s t r i a l Management Review 3 ( 1 9 6 2 ) , 8 - 2 3 . MARTUZA, V.R. "An Investigation of the effects of Strategy A v a i l a b i l i t y , Bankroll & Sex on R-T Behavior Measured in a Psychometric Context" J. Personality 3 8 - 1 (1970) 146-159. MASSE, P. Optimal Investment Decisions Englewood C l i f f s : Prentice H a l l , 1 9 6 2 . MENGER, K. "Das Unsicherheitzmoment in der Wertlehr" Z e i t s c h r i f t fur Nationalokonomie 51 (1934) pp. 4 5 9 - 4 8 5 ; mentioned i n K.J. Arrow's Aspects of the Theory of Risk Bearing. 158 MORRIS, J.L. "Propensity for RT as A Determinant of Vocational Choice: An Extension of the Theory of Achievement Motivation." J. Pers. & Soc. Psych. 3-3 (1966), 328-335. MOSTELLER, F.C. & NOGEE, P. "An Experimental Measurement of U t i l i t y " JPE ( 1 9 5 D . 371-404. NIE, N.H., BENT, D.H. & HULL, CH. S t a t i s t i c a l Packages For The S o c i a l Sciences (SPSS) NY: MacGraw H i l l , 1970 NUNNALLY, J . C Psychometric Theory NYs MacGraw H i l l , 1967, Chap. 3 : 75-102; Chap. 7: 207-235. OSGOOD, C E . &7SUCI, G.J. "Factor Analysis of Meaning"in J.G. Snider & C.E. Osgood (ed.) Semantic D i f f e r e n t i a l Technique Chicago: Aldine Publishing, 1969, 42-55. PETTIGREW, T.F., "The Measurement and Correlates of Category Width as a Cognitive Variable" J. of Personality 26 (1958), 532-544. PHELAN, J. "An Exploration of Some Personality Correlates to Business Risk Taking Behavior." J. of Psych. '53 (1962) 281-287. PRATT, J.W. "Risk Aversion in the Small and i n the Large." Econometrica 32 (1964) 122-136. PRUITT, D.G. "Pattern and Level of Risk i n Gambling Decisions" Psych. Review, 69 (1962), 187-201. RIGGS, J. Economic Decision Models, N.Y: McGraw H i l l , 1968. RIM, Y. "Social Attitudes & RT" Human Relations 17-3 (1964), 259-265. ROTTER, J.B. "Generalized Expectancies f o r Internal vs. External Control of Reinforcement." Psych. Monographs 80-1 (1966) Whole No. 609. , SEEMAN, M. & LIVERANT, S. "Internal vs. External Control of Reinforcements: A Major Variable i n Behavior Theory" i n N.F. Washburne (ed.) Decisions, Values & Groups, Vol. 2, London: Pergamon Press, 473T516 SAVAGE, L.J. The Foundations of S t a t i s t i c s , N.Y.: Wiley & Son, Inc. 1954. " E l i c i t a t i o n of Personal P r o b a b i l i t i e s and Expec- tations," J. of Amer. Stat. Assn. December 66-336 (1971) 783-787. 159 SCHLAIFFER, R. P r o b a b i l i t y and S t a t i s t i c s For Business Decisions NY: McGraw H i l l (1959). 117. Computer Programs for Elementary Decision Analysis. Div, Research, Grad, Sch. of Bus. Adm., Harvard, (1971) Chapters 2 , 3 . 27-53. SCHUMPETER, J.A. The Theory of Economic Development Cambridge: Harvard U Press, 1934. SCODEL, A., RATOOSH, J. & MINAS, J. "Some Personality Correlates of Decision Making Under Conditions of Risk". Behavioral Sciences, 4 (1959), 19-28. SHACKLE, G.S.L. Uncertainty i n Economics London: Cambridge U Press, 1955. Decision, Order and Time Cambridge U Press 1961 SHURE, G.H. & MEEKER, R.J. "A Personality/Attitude Schedule f o r Use in Experimental Bargaining Studies." J. of Psych. 65 (1967), 233-252. SIEGEL, S. & ZAJONC, R.B. "Group RT in Professional Decisions." Sociometry 30-4 (1967), 339-349. SLAKTER, M.J. "Generality of RT on Objective Examination" Educ. & Psycho. Measurement 29 .(1969)1 115-128. SLOVIC, P. "Convergent Validation of RT Measures." J. Abn. & Soc. Psych. 65-I (1962), 68-71 "Assessment of RT Behavior" Psych. B u l l e t i n 61-3, 220-233. "Seeking Information to reduce Risk of Decision." American J. Psych. 78, 188-197. "Information Processing, Situation S p e c i f i c i t y , and the Generality of RT Behavior, "Oregon Research In s t i t u t e , Eugene, Oregon, Res. Bui. Vol. 11, no. 3 , (197D , A p r i l . SPETZLER, C "The Development of a Corporate Risk P o l i c y for C a p i t a l Investment Decisions," IEEE Transactions on Systems Science & Cybernetics. SSS-4,3 (Sept, 1968) 279-300. 160 STIGLER, G.J. "The Development of U t i l i t y Theory" JPE LVIII, (Aug. So October 1 9 5 0 ) , 3 0 7 - 3 2 7 , 3 7 3 - 3 9 6 . STOBAUGH, J. J r . "How to Analyze Foreign Investment Climates" HBR (Sept. - October 1 9 6 9 ) , 1 0 0 - 1 0 8 . STREUFFERT, S., CLARDY, M.A, , PR I VER, M.J., KARLINE, 1V1. , SCHROEDER, H.M. & SUEDFELD, P. "A T a c t i c a l Game for the Analysis of Complex Decision Making i n Individuals and Groups." Psych. Report 17 (1965) 7 2 3 - 7 2 9 . SUYDAM,'M.M. & MYERS, J.L. "Some Parameters of RT Behavior" Psych. Report, 10 ( 1 9 6 2 ) , 5 5 9 - 5 6 2 , SWALM, R.O. " U t i l i t y Theory - Insight into Risk Taking" HBR (Nov - Dec. 1 9 6 6 ) , 123 - 1 3 6 . SWINEFORD, F. "The Measurement of a Personality T r a i t , " J. Educ. Psych. 29 (1938) 2 9 5 - 3 0 0 . "Analysis of Personality T r a i t , " J. Educ. Psych. 32 ( 1 9 4 1 ) , 4 3 8 - 4 4 4 . TEGER, A.I., ,PRUITT, D.G., JEAN, R.S., & HAALAND, G.A. "A Reexamination of the Fa m i l i a r i z a t i o n Hypothesis in Group Risk Taking." J. Exp. Soc. Psych. 6 ( 1 9 7 0 ),346 - 3 5 0 . & PRUITT, D.G. "Componenets of Group Risk Taking" J. Exp. Soc. Psych. 3 ( 1 9 6 7 ) , 1 8 9 - 2 0 5 . TOBIN, J. " L i q u i d i t y Preference as Behavior Towards Risk" Rev. Eco. Studies, 26 ( 1 9 5 8 ) , 6 5 - 8 6 . TORRANCE, E.P. & ZILLER, R.C. "Risk and L i f e Experience': Development of a Scale for Measuring Risk Taking Tendencies" USAF PTRC, res. Rep (1957) No. 5 7 - 2 3 . VON NEUMANN, J. &. MORGENSTERN, 0 . The Theory of Games and Eco. Behavior Princeton Univ. Press, 3 r d E d i t i o n 1 9 5 3 , Chap.l, Sec. 3 . VOTAW, O.F. "The Ef f e c t s of Do-not-guess directions on the V a l i d i t y of True-False as Multiple Choice Tests" J. Educ. Psych. 27 ( 1 9 3 6 ) , 6 9 8 - 7 0 3 . WALLACH, M;A;. & KOGAN, N. "Sex Differences and Judgment Processes" J. Personality 27 ( 1 9 5 9 ) , 555-56^-. , KOGAN, N. & BEM. D.J. "Diffusion of Res p o n s i b i l i t y and Level of RT i n Groups" J. Abn. Soc. Psych. 68 ( 1 9 6 4 ) , 2 6 3 - 2 7 4 161 , & MABLI, J. "Informationvs. Conformity i n the E f f e c t s of Group Discussion on RT" J.Pers. & Soc. Psych. 1 4 - 2 (1970), 1 4 9 - 1 5 6 . , & WING, C.W., J r . "Is Risk A Value?" J. Pers. & Soc. Psych. 9 (1968) 101-106. WEINSTEIN, M.S. "Achievement Motivation and Risk Preference" J. Pers. & Soc. Psych. 13-2 (1969) 153-172 WEINSTEIN, E. & MARTIN, J. "Generality of Willingness to Take Risks" Psych. Rep. 24 (1969), 499-501. WHITE, R.W. "Risk Aversion in Open-End Investment Companies" Unpublished Masters Thesis, UBC, 1968. WILLIAMS, L.K. "The Measurement of Risk Taking Propensity i n an I n d u s t r i a l Setting" Unpublished Doctoral Dissertation Univ.of Michigan i 9 6 0 . WINDER, C.L. & WURTZ, K.R. "A Study of Personality Correlates of Judgment Behavior." Report, Standord Univ., Dept. of Psychiatry, Office of Naval Research, Contract No. 22'5-01, 1954. WOODS, D.H. "Improving Estimates that Involve Uncertainty" HRR, July-August 1966, 91-98. ZAJONC, R.B., W0L0SIN, R.J. & W0L0SIN.M.A. "Group RT Under Various Group Decision Schemes" J. Exp. Soc. Psych. 8 (1972), 16-30. ZILLER, R.C. "A Measure of the Gambling Response Set i n Objective Tests" Psychometrika, 22 (1957), 289-292 (a) "Vocational Choice and U t i l i t y for Risk" J. Counselling Psych. 4 (1957), 6 1 - 6 4 (b) ZUCKERMAN, M., KOLIN, E.A., PRICE, L. & Z00B, I. "Development of a Sensation-Seeking Scale" J. Consulting Psychology 28-6 (1964). 162 APPENDIX A LIST OF RAW DATA APPENDIX A - l CHOICE DILEMMA IE CONTROL - SSS 1 row per subject, s t a r t i n g with subject's I.D., IE Control Score-, SSS Score, 10 Choice Dilemma Ranks and 10 minimum odds f o r 10 items. APPENDIX A-2 EXTREMITY CONFIDENCE IN JUDGMENT 1 row per subject, s t a r t i n g with subject's I.D., 15 extremity scores, 15 confidence scores for 15 items. APPENDIX A-3 IN BASKET RESPONSES 2 rows per subject, F i l e Numbered. 1st row: 7 Memo Strategy Scores, Memo Scorew/5 & 6 included Memo Score 5 & 6 treated as 2,5 and Memo Score 5 & 6 excluded; 2nd row: 7 minimum odds, minimum odd average, 7 Grade assignments, average Grade assigned, Weighted Minimum odd score with Grade as weight, 4 Semantic D i f f e r e n t i a l Scores, a consolidated SD Score. APPENDIX A-3 IN BASKET (CONTINUED) APPENDIX A-4 UTILITY RESPONSES 2 rows per subject 1st row: Subject's I.D., 4 compensation response, No. of NO Answers to Scale of Wager, 5 Scale of Wager responses. 2nd row: 5 Rate of Return responses, 6 Net P r o f i t responses. APPENDIX A-4 UTILITY RESPONSES (CONTINUED) APPENDIX A-5 PERSONAL RECORDS 2 rows per subject 1 s t row: SUBJ'S. I.D. SEX: 1 for Male, 2 f o r Female, 99 missing 163 AGE: 95 missing STATUS (MARITAL): 1-married, 2-single, 3-separated, 4-divorced, 99,0-missing, NUMBER OF DEPENDENTS: 99 for missing. AGE OF DEPENDENTS: Average, 999 f o r missing. CITIZENSHIP: 1 f o r Canada: 2 f o r H.K., 3 f o r Singapore, 4 - B r a z i l , 5 - U.S., 6 - India, 7 - Others, 0,99 - missing. PRESENT YEAR: 1-MBA I; 2-MBA II; 3-MsCI; 4-Msc II , 5~Phd; 6-0thers, 7-MsC no year; 8-MBA no year; 95-missing, OPTION: - 1-Acctg; 2-Mktg; 3-Transportation, 4-Urb. Land Economics; 5-Finance, 6-Int. Business; 7-Management Sc.; 8-0. Behavior,9-0thers, 99 missing. AVERAGE GRADE LAST YEAR - number represent the ordered item checked. Please see questionnaire. PREVIOUS DEGREE - two d i g i t number used. F i r s t d i g i t represent degree, 2nd d i g i t represent option, 1st d i g i t : 1-B Comm; 2-Eng'g., 3-Education, 4-Law, 5-B.Science, 6-Computer Sc.; 7-0thers; 8-BA; 9-Masters; 2nd d i g i t : Eng'.g-l: C i v i l ; 2-Mech; 3 - E l e c t r i c a l ; 4-Chem., 5-Agricultural, 6-0thers; Others- 0 (for other degrees). 9^-missing. NUMBER OF DEGREES COUNTRY OBTAINED - same code as c i t i z e n s h i p . Working Years - n o , of years at work. Salary: l a t e s t salary i n thousands. Po s i t i o n ( l a t e s t ) : 1-higher l e v e l management; 2-middle manage- ment; 3-employee; 95-^issing, 2nd row: NUMBER OF SOURCES - count the number of sources of educational financing. See Questionnaire. 99-missing. TOTAL AMOUNT OF EDUCATIONAL FINANCING SOURCE WITH GREATEST FINANCING COMING FROM: Number referred to number i n the item, AMOUNT OF LARGEST FINANCING - i n thousands. FACE VALUE OF INSURANCE - i n thousands TYPEINSURANCE - type of insurance 1-with savings feature 2-without saving feature. 164 AMOUNT OF ASSET - Total i n ten thousands AMOUNT OF LIABILITIES AVERAGE INTEREST RATE APPENDIX A - 6 STOCK PRICE WAGER RESPONSES 1 row per subject, with subjects I.D., 5 ranks per set, f i v e sets in. a l l and 5 o v e r a l l set rankings. L I S T I N G O F C H O I C E D I L E M M A AND CniNTROL-SSS W I T H IO O F S U B J r I N T E R N A L C Q N T R O L , S E N S A T I ON S E E K I N G , 1 G C H O I C E D I L E M M A R A N K S AND 1 0 M I N I M U M O D D S 4. 6671. c * 7. 4. 11. 11. 11. 11. 4. 7 . 6 . 1. 3. 11. 11. 11. 11. 8. 2. 4. 5. 11. 11. 7. 9. 10. 7. 7. 9. 7. 7. 9 . 7. 7. 9. 457. 50?. 563. "240 f. 37 20. 90349. 3. 7. 7 . " "9." 10. 6. 101112. 121314. 121943. 1241 6 7." 131313. 1912 35. 214714. 224903. 23560?. "241805. 261039. 330043. 356126.. 4040 44. 449771. '44 39 71 . 474747. 5197 25. 614715. 654321. 654537. '755316. 306662. 960321. 977713. 998377. 999000. 4 . 2 . 3 ._ 6". 4. 6 . 4 . 3. 4 . 2 . 4 . 1 . 1. 6. 1. 1 . 2. 3. 4. 10. 8.__ 2. "2.~ "5". 4. 10. 3. 9. 7. 5 . 7._ "6." 5 . 8. 6 . 9. 5. "7. 6. 5 . 6. 1. " 8 . ' 7. 10 . 9 . 1 0 . 7. 8. 9._ 1 0 . 9'. "id"."" 3. 9. 5. 7. 5. 7. 5._ 5. 7. 3. 7 . 3. 7." 5. 5. 5. 5. 5 . 7. 9. 7. "9"."" 7. 7 . 7. 9. 9. 10. 5 . 5. ""3." 7 . 7. 10. 10. 9 . . 7. 10. 3. 7 . 7 . "4." 8. 7 . 2. 5. 11 . ""3. 3. 4 . 6 . 11 . 4 . 4. 1. 1. 1 1. 1. 1 . 3. 11. 3. 2. 5. 7. 11. 10. 10. 7. 2. 11. ' " 5 . 9. 9. 10. 8. 4 . 11. _11_. 7. 6." 8. 5. 1 0 . 3. 1. 2. 5. 4. 8. 3. 9. 10. 1 1 . 1 1 . "9 . "2 . 7. 6. 7. 8. 3. 5 . 9. "7." 9 . 3. 7 . 5. "9." 5 . 3. 9 . 6. 7. 7 . 4 . 6 . 5 . 8. 1. 1. 1 . 2." 1. 2. 5. 7. 3. 10. 5. 7. 9. 2. 4 . 8 . T O . 2. 9. ' 4. 5 . 6. 1 . 4 . 5. 10. 6 . 10 . 7. 2. 10. 8. '"' 7 . '" 9 . 5. 10.' 8. . 7. 7. 5. 3. 7. 3. 5. 7 7 5. 3. 7. 1 . 7. 5. 7 . 5. 7." 7 . 10. 5. 7 . 9. " 5 . " 9. 7. 7. 5. 7. 7. 5. 7. 5. 5 . 7. "7." 5 . 9. 5 . 7. 5. 10. 10. 5. 9 . 7 . "5."' 9 . 10. 7 . 9. 9." 7 . 3 . 9. " 5 . 5. 1 0 . 9. ' 7 . 9 . 1 0 . 7. 6. 5. •3 ̂ 6. 6 . 4 . 4. 4 . 6 . 4. 7 . 1 . 9. 1. 1'.' li 11. 2. 4. 5. 10. 10. 9. 4. 10. 7. 3. 2. ' 5 6. 1 . 8. 1 0 . 7. 6. 3. "fl ." 5. 7. 4. "4. 7 . 5. 9. 8. 5. "1 0 . " 8. 6. 3. 9. 5. ' 5 . 7. 3. 7. ? ̂ 7. ' 7 . 1 . 10. 9. 7. p . " 9 . 5 . 9. 10. 9. 11. 3. 7. 5 . 9. " 7 . ' 1 0 . 9. 6. 5 . 7 . 7. 6. 8. 4. •5. 2 . 5 . 7, 5 . 8. 9. 4. " 7 . " 4 . 4. 8 . 6 . 5. 3. 1 . i . " ' 1 . 1 . 3 . 9. 5 . 1 0 . 3 . 7 . ' 2 . T o . " 2 . 1 0 . 5 . 8. 2 . 1. 2. 5 . " 3. 9. 5. 8. 5. 8. ' 7. 6 . 2. 6. 4. 6. 3. 10. 11 . 7. 10. '3.'" 8. 7. 7. 10. 6. 7. 9. ' 9 . 9. 6. 7. 7. 3. 5 . ' 5 . 7. 5. 9 . 1 0 . ' 9 . 1 0 . 9. 7. 9 . 9. 5. 9 . 9. 4. 6 . 8 , 4. 9 . 7 . 5. 1 . 3. 2 . 5. 5. 7. 6. 1. 5. 10. 2. 4. 3. 7 . 4 . 6. 4. 1. 5 . 9 . 7 . 3. 2 . APPENDIX' A-1CHOICE""DILEM?/ 1 row r>er subject, s t a r t i n g Score," SSS Score, 10 Choice odds for 10 items. 10. 6. 1. 3- 8. 9. 7. 5 . 10. 8. 9. 9. A. IE'"CONTROL" 7 . 5 . 7. SSS" 5. 7 . 7. 5. 7 . 3. 5." 5. 3._ "'3. 3 . 9 . 7. 9. 7. ' 5 . " 10. 10. 7. 7. 9. T . 9 . 5.' 9. 9 . 9 . " 9. 10. 5. 9. 9 . 1 0 . 9 . 10. 9 . 10 3. 7. 7. "' 3. K T "7. 7. 9 . 5. 10. 10. 9 . 9 . 9. 7 . 10. ~~r~. 9. 5 . 3. 3. 7 . 5. 7 # 3 . " 7. 5. 10. " S T 1. 7 . 9. 5. 9 . 3. 7 . 9 . 5. 1 . _7. "11. 5 . 3. 5. 7. 3 . 7 . v/ith subject's I.D., Dilemma Ranks and 10 IE Control minimum I . 5 . 9 . H O N 4 . 3 0 . 3 j . 30 . 3 0 . 0 . 3 0 . 3 0 . 3 0 . 3 0 . 0 . 3 0 . 30 . 30 . 30 . 3 0 . 5 . 2 . 2. 2 . 4 . " " 2 . 2 . 3 . T " . ._ ^ "5".' " 3 . " 2 : ." ~"3'. "3 7" 6 6 7 1 . 4 0 . 1 0 . 43 . 1 0 . 5 . 3 0 . 0 . 3 0 . 0 . 20 . 0 . 10 . 4 9 . 2 0 . 0 . 3 . 3 . 5 . 3 . 3 . 2 . 4 . 2. 4. 4 . 4 . 4 . ' ' '1. ' ; 3. 4 . 4 5 7 . 10 . 4 0 . 0 . 10 . 1 0 . 2 5 . 30 . 0 . 25 . 2 0 . 4 0 . 0 . 4 9 . 2 5 . 0 . 3 . 3 . 3 . 4 . 4 . ' 3 . 2 . 4 . 5 . 4 . 4 . 3 . 2. •7. # 4 . 5 0 2 . " 2 0 . ' '2 0 . " 3 0 . 1 0 . 2 0 . ' 2 0 . 3 0." ""20"." "10." 40." '2 5 . " "' 0 . " 5 0 . ' 0 . 2 0 . " "" 4 . " "' "5," ""4. 3 . " 3 . " ' 2 . 4 . ' 3 . ' 3 . " ' 4 : ' • .2. " ' 2 . ' 5 6 3 . 10 . 2 0 . 10. 4 0 . 10 . 4 0 . 2 0 . 2 0 . 3 0 . 4 5 . 2 0 . 0 . 4 9 . 2 0 . 1.0. 2 . 3 . 5. 5 . 4 . 3 . 3. .3. 5. 1. 3 . 5 . 4 . 2. 3 . 240 1 . ZC-. 40 . 10 . 1 0 . 3 0 . 4 0. 10. 4 0 . 10 . 10 . 3 0 . 2 0 . 45 . 1 0. 3 0 . 3 . 3 . 3 . 3 . 2 . 3 . 3 . • 2 . 3 . 2 . 3 . 2 . 2 . 3 , 3.'- . 3 7 2 0 . 3 5 . 1 0 . 10. 2 0 . 40 . 4 9 . 1 0 . 0 . 20 . 3 0 . 3 0 . 10. 4 0 . 20 . 2 0 . l . 2 . 2 . .3. 2 . 1. 3 . 4 . 3". 4 . 3". 3 • 2 . i . ^ . 9 0 3 4 9 . 10. 4 5 . 15. 15 . 4 0 . 25 . 20 . 2 5 . 2 0 . 4 0 . 4 5 . 0 . 4 9 . 4 5 . 1 0 . 2 . 1. 1 . 2 . 1. 1. 2. 2. 3. 1. 1. 5 • 1. i • 3 . 1 0 1 1 1 2 . C . 5 0 . 0 . 5 0 . 0 . 0 . 5 0 . 0 . 50 . 0 . 0 . 0 . 50 . 0 . 5 0 . 5 . 2 . 3 . 2 . 4 . 2 . 1. 2 . 1. .3 . 2 . 5 . 1. { m 1. 1213 1 4 . 1 0 . 0 . 0 . " " ' o ' . 0 . "4 0 . C . " 2 0 . 0 . 2 0 . 40." 0 . 4 9 . •" 0 . ' b . " " 2 . " 2 . ' 3 . 3 . 5 . 2 . ' 3 . 3 . 3 . 3 . 2 . 1. 1 2 1 9 4 3 . 0 . 2 0 . 30 . 0 . 3 0 . 2 0 . 4 0 . 3 0 . 0 . 1 0 . 2 0 . 4 9 . 4 5 . 0 . 3 0 . 4 . 3 . 2 . 4 . 3 . 2 . 2. 1. 5 . 3 . • 3 . 2 . 2. 3 • 3 . . 1 2 4 1 6 7 . 3 0 . 4 0 . 0 . 0 . 2 0 . 4 5 . 10. 4 0 . 3 0 . 25 . 10 . 4 9 . 0 . 2 0 . 3 . 4 . 2 . 5 . 4 . 2 . 4 . 1. 5 . 3 . 4 . 2 . 1. 5 . 3 • 1313 1 3 . 4 " . 43 . 30 . 3 0 . 40 . 4 5 . 4 0 . 30". ~ 2 0 T 10 . 3 ^ • 10. 4 5 . 4 0 . 2 0 . 3 . 2 . • 3 . 0 . 2 . "2. 3 . 4 . 3 . 3 • 3 . 3 . I , 2 . 191235 . 0 « 10 . .30. 0 . 10. 4 0 . 4 0 . 10 . 10 . 2 0 . 4 0 . 10 . 4 9 . 3 0 . .30 . 2 . 2 . -) c * 4 . 5 . 4 . 1. 1. 2. 2 . 2 . 3 . 2 . i . 2 . 2 1 4 7 1 4 . 4 0 . 20 . 0 . 2 0 . 20 . 2 0 . 20 . 20 . 20 . 3 0 . 4 0 . 4 0 . 4 9 . 3 0 . 3 0 . 3 . i 4 . 4 . 5 . 4 . 3 . 5 . 5 . 4 . 2 . 3 . 1. 3 . 3. " 2 2490 3 . ' " 2 0 . 15 ." 4 0 . ' " 1 0 . 15 . " " 4 0 . ' 25 . " " 0 . " " 3 0 . " 0 . " 20 . 2 5 . " " 1 5 . 2 0 . 1 0 . " 4." ~'Y. "2." 5'.'' 4 . 5 . 4 . " " 2 . 2 . 2 . 5 . ' 2 ' 4 . 5 . ' " 5 . " 2 3 5 6 0 2 . 30 . 0 . 40 . 0 . 3 0 . 4 0 . 2 5 . 3 0 . 0 . 1 0 . 4 0 . 4 0 . 4 9 . 0 . 2 0 . 2 . 4 . 5 . 3 . 3. 2 . 3. 2. 5. 3 . 1. 1. 2 . 4 . 2 4 1 R G 5 . 0 . 4 6 . 30 . 25 . 10. 4 5 . 10 . 15. 30. 30 . 4 0 . 20 . 50 . 4 0 . 2 0 . 3 . 2 . 2 . 2 . 3 . 3 . 3 . 3 . 3 . n £. * 3 . 1 . 2 . 3 • 2 6 1 C 3 9 . 4 1 . 3 0 . 2 5 . 0 . 10 . 2 5 . 20 . 15 . 4 0 . 0 . 3 0 . 2 0 . 49 . 4 T T . 2 5 . 2 . 3 . 2. 3. 4 . 2". 2". 3 . " 2. 2 . 3 . i • 1. l . 3 . 3 3 0 T 4 3 . 5 0. 5 0 . 40 . 2 5 . 50 . 4 5 . 4 0 . 0 . 0 . 5 0 . 4 0 . 5 0 . 4 0 . 0 . 4 0 . 5 . 5 . 4 . 4 . 5. 3 . 3. 3. 5. V • 4 . 5 . 4. 4 . 4 . 3 5 6 1 2 6 . 4 0 . 47 . 4 0 . 10 . 20 . 3 0 . 3 0 . 10 . 30 . 10 . 4 5 . 20 . 50 . 3 0 . 2 5 . V. -> • 5 . 5 . 5 . 5 . 4 . 4 . 5 . 5 . 4 . 4 . 5 . 3. 4 . " 4 C 4 0 4 4 . ' C . 45 . ' 0 . ' 0'. ' 0 . " 2 0 . 20 . ' 20. ' 4 0 . " 4 5 . 2 0 . 0 . 5 0 . 3 0 . 3 0 . "' 3 . " ' 1 . ' 37' 5." 5 • 2 . 4. 3. 4 . 5 . 4 . 5 . 1 . 4. 5 • 4497 7 1 . 20 . 10 . 10. 0 . 10 . 4 0 , 2 0 . 2 5 . 3 0 . 4 0 . 0 . 4 0 . 10 . 0 . 2 0 . 2 . 2 . 3 . 4 • 3. 4 . 2. 4 . 5. 3. 4 . 2 . 3 . • 3 . 2 . 4 4 3 ^ 7 1 . 1 0 . 3.0 . 10 . 0 . 2 0 . 4 0 . 0 . ? o . C . 4 0 . 4R. 4 5 . 5 0 . 3 0 . 0 . 4 . 5 . 4 . 3 . 3 . . 4 . 3 . 3 . 3 . 3 . 3 . 1. 3 . 4 . 4 7 4 7 4 7 . 4 0 . 4.5 . 0 . 10 . 10 . 3 0 . 2 0 . 0 . 10 . 2 0 . 4 5 . 4 0 . 4 9 . 4 0 . 4 0 . 4 . 4 . 5 . 5. 5 . 4 . 5 . 3. 5. ""3 . 3 . 4 . 1. 2 . 3 . 5 1 9 7 2 5 . 30 . 4 0 . 43 . 10 . 10 . 4 5 . 3 5 . 4 0 . 3 0 . 2 0 . 3 0 . 0 . 4 0 . 2 5 . 1 0 . 2 . 2 . 3. 5 . 5 . 3 . .̂ 2. 5. 5 . 4 . 5 . 3. 5. 5 . 6 1 4 7 1 5 . 3 5 . 30 . 30 . 2 0 . 4 0 . 4 5 . 20 . 0 . 0. 4 0 . 4 8 . 40 . 5 0 . 3 5 . 1 0 . 3 . 4 . 4 . 3. 3 . 3 . 3 . 3 . 4 . 3 . 3 . 4 . 1. 2 . . 3. "654321 . 40 . " ' 4 5 . " 2 0 . 1 0 . 3 0 . ' 5 0 . 4 5 . " " 1 0 . " "10 . " " 4 9 . 1 0 . 0 . 4 5 . "3 0 . " 4 0 . jL # 1 . ' 2." o " 2 . 1." 1." 2 . 2. ' 2 . ' '2 . ' 2 . " " 4 . " -a ^ 1.' 6545 3 7 . 15. 4 0 . 0 . 2 0 . 10. 4 5 . 3 0. 15 . 10 . 2 0 . 1 5 . 0 . 3 5 . 0 . 2 5 . 3 . 2 . 5 . 0 . 4 . 2 . 2. 4. 3 . 4 . 4 . 5. 5 . .̂ 7 5 5 3 1 6 . 3 5 . 1 0 . 0 . 3 0 . 3 0 . 3 5 . 25 . 3 5 . 20. 35 . 10 . 10 . 5 0 . 0 . 2 0 . 2 . -1 . 3 . 2 . 3 . 3 . 4 . 3 . 3 . 3 . 4 . 1. 3. 8 0 6 6 6 2 . 2 0 . 40 . 4 0 . 2 0 . 10 . 4 0 . 0 . 4 0 . 0 . 4 0 . 4 5 . 50 . 50 . 0 . 4 0 . 2 . 3 . 4 . 3 . ~i ^ 2 . 5. 1 . 5 . 2 . 2 . 1 . x . 5 . 2 . 9 6 03 2 1 . 30 . 4 0 . 40. 4 0 . 2 0 . 2 0 . 10 . 0 . 0 . 2 0 . 2 0 . 10 . 0 . 2 0 . 2 0 . 3 . 1 . 2 . 3 . 5 . 5 . 3. 3. 3 . 2 . 2 . 3 . 2 . 4 . 2 . 9777 1 3 . 4 0 . 40 . 20- 10 . 3 0 . 4 0 . 20 . 10 . 4 0 . 10 . 20 . 3 0 . 5 0 . i O . 1 0 . 2 . 2 . 2 . 3 . 3 . 2 . 2 . 2 . 2 . ' 3 . 4 . 2 . 1. 2. 3. "' 99887 7." 2 0 . " ' 0 . ' 0 . " 1 0 . 10 . " ' 0 . ' 15. " 1 0 . 0 . " 0 . " 0 . "10 . 4 0 . ' 20." 3 0 . 3 . 4 . " 5 . " ' 5 . ' " 5 . 3. " 3 . 2 . 5. ' 5--"' 4.'"" 4 . ' " 3 ." "' 2 . 2 . 9 9 9 0 0 0 . 4 3 . 4 5 . 25 . 2 5 . 4 0 . 4 0 . 10 . 3 0 . 2 0 . 1 0 . 4 3 . 10 . 4 9 . 0 . 0 .- 4 . 4 . 5 . 5 . 5 . 4 . 3. 3 . 5. 4 . 5. 5 . 3 . 3 . 4 . APPENDIX A-2 EXTREMITY CONFIDENCE IN JUDGMENT 1 row per sub j e c t , s t a r t i n g w i t h subject's I.D., 15 e x t r e m i t y scores, 15 confidence scores f o r 15 items. Os Os 1 5 1 6 1 7 " 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 3 1 3 2 3 3 3 4 3 5 3 6 3 7 3 8 3 9 4 0 4 1 4 2 4 3 4 4 a . t L I S T N E W B A S 1 2 5 3 _ 5 ""' " " 6 ~ " ~ 5 . 7 8 l G j 9 1 0 4 . 1 1 1 2 4 . 1 3 1 4 5 . 2. 6 6 7 1 . 5 . 6. 4 b / . 6 . V . 5 0 2 . _2_.__i>. 5 6 f . 2 . 1 0 . 2 4 0 1 . 2 ' . " 1 . 3 7 2 0 . 5 . 3 . 1 . 1 . 4 . _ 9 . _ 9 . _ 5 . 5 . 4". 2. n 1 0 . 8 . 6 . 3 . 5 . 1 . 2 . 1 . 5 . 6 . 4 . 4 . 1 . A . 1 0 . 10 . 5 . 3. 1 . 9 . 1." 1 0 . 4 . 5 . 5 . 5 . 1 . 1 . 4 . 5'*' V.'"4. 2 . 9 9 . 3 . 0 . 9 . 6 . 3 . 9 0 3 4 9 . 7 . 4 . 6. 1 0 1 1 1 2 . " 5 . ! . ' • ' < . 1 2 1 3 1 4 . 5 . 4 . ' 7 . 1 2 1 9 4 3 . 5 . 8 . 7 . 1 2 4 1 6 7 . 4 . 3 . 5 . 1 3 1 3 1 3 . 5 . 5 . 7 . 4 . 1 . 1 . 3 . 1 0 . 6 . 7 . 1 . 4 . 3 . " " ' 7 . '(»"." 8 .""6. 1 . 9 . 1 . 1 0 . 1 0 . 7 . 5 . 1 . 4 , 6 . 2 8 6 i" . 4; 6 . 5 7 1 5 . 4 . 4 . 4 2 9 2 . 4 . 6 . 8 5 7 3 . 2 , 5 . 7 1 4 5 . 9 . ' 3 . 4 2 9 9 . 1 , _ 4 . _ 4 2 9 _ 1 . " 4 . 6 . 1 4 3 2 . 5 . ' 4 . 7 1 4 4 . 4 . 6 . 3 5 7 1 . 9 0 . i. 7 0 . 5 . 1 0 0 . 1 . U e. 9 . 9 9 9 . 5 . " " 7 b . 9 . 1 . 9 9 9 . 1 . sc. 4 . _ 5 0 . 9 7 ' 5 0 . 9 . 5 0 . 3. 8 0 . " 3." 9 9 9 . 4 • " 4 0 . 5 . _ 9 _ 0 . 4 . " 5 0 . 1 . " 9 9 9 . 9 . 1 0 0 . 2 . 2 9 I C O . 2 . 1 7 " 9 0 . 3 . 6 7 6 5 . 2 . 7 1 B 5 . _ Tfo 'c 9 9 9 . 3 . 5 C 7 5 . ' 2 . 7 5 _ I1!' 2 .7 <f 9 0 . 2 . 4 3 9 9 9 . ' 2 . 2 0 9 0 . 2 . 2 9 2 - _ 7 0 . 4 0 . " 2 . 1 7 " " ? . 6 0 . 1 0 0 , 2 . 3 3 2 . " 9 0 . 5 G , 2 . 7 1 2 . ° 0 . 9 5 . _ T . 0 0 " " " 2~. 9 9 9 . 9 ^ 9 . 2 . C O 2 . " 5 0 . ~ 9 0 . 2 . 0 0 2 . 2 0 . 8 5 . 2 . 2 9 ? ' . 5 C . 1 0 0 . 2 . 0 0 2 . 9 ' 9 9 ". " 9 9 9 . 2 . 2 0 2 . 5 0 . 7 0 . 2 9 6 0 . 8 0 . 7 0 . C O O 6 . 4 C 8 - 2 5 . 0 . 1 0 . - 4 4 . 0 0 1 7 4 2 7 1 6 5 . 7 5 . 7 2 . 8 5 7 6 . 5 9 8 0 . 1 4 . 1 9 . 1 8 . - 1 3 . 0 0 7 0 . " 6 0 . 6 9 . 2 8 6 4 . 2 4 7 - t . - 7 . - 7 . " 3 6 . - 4 2 . 0 0 9 5 . 9 0 . 9 0 . 7 1 4 6 . 9 8 4 3 5 . 6 . 4 . 2 0 . 1 3 . 0 0 O C 9 9 9 . 9 9 9 . 9 9 9 . 2 5 . ' ' 6 0 . " 5 5 . " 6 2 , 1 3 4 0 . 7 5 . _ 6 J _ . 2 9 7 5 . 6 5 . 7 3 , 07 ' 9 9 9 . ' " 9 9 9 " . 9 9 9 . 2 0 5 0 . 4 0 . 6 8 . 0 0 0 9 9 9 . 0 0 0 1 6 . 0 5 7 " ' "3 . ' 5 1 1 7 . 1 4 3 4 . 9 7 7 6 . 1 1 . 2 2 . " " 7 . " 1 6 . 9 . - 2 . 1 7 . 3 i . 9 . • 1 0 . 0 0 - 1 5 . 0 0 - 1 4 . 0 0 5 7 1 6 . 5 8 3 3 7 . 0 0 0 9 9 9 " . 0 0 0 " - 1 3 " . 5 7 1 6 . 6 2 5 - 5 . - 4 4 . 2 . 3 0 . - 1 0 . 1 6 . " " - 3 7 " 4 0 . 6 7 . 0 0 6":b"c - 8 5 . O C 1 . 4 . 1 . 5 . 9 . 8 . 3 . 1 . 9 . 1 . 1 . 1 0 . 4 . 8 . 1 . 9 . 1 . 0 . 1 0 . 6 . 3 . 2 . 4 . 6 . 4 2 9 1 . 4 , 5 . 0 0 0 2 . 4 . 5 . 1 4 3 4 . 9 9 9 . 1 . 8 0 . 5 . 9 0 . • 1 9 1 2 3 5 . 7 . 5 . 9 . 2 1 4 7 1 4 . " 8 . 5 . 5 . 2 2 4 9 0 3 . 5 . 5 . 5 . 1 . 2 . 4 . 1 0 . 9 . 9 . 8 . 6 . 1 . 1 . 5 . 1 0 . 5 , 1 . 1 . 2 . 4 . 5 . 8 . 5 . 1 . 3 . 5 , 8 . 1 4 3 2 . 4 , 5 . 5 7 1 3 . 4 . 4 . 8 5 7 5 . 8 5 . 1. Too'. 1 . 8 0 . 1 . 9 9 9 . 4 . 9 5 . 1 . J L C C _ . " 1 . 3 0 . l . _ " 5 0 . 2. 7 0 . 2 . 4 3 9 9 9 . 2 . 0 0 8 5 . 2 . 3 3 ___80_. 3 . O O " I C O . 2 . 2 9 9 0 . 2 . 4 3 9 0 . 2 . 4 3 2 , 9 9 9 . 9 9 9 , 2 . 0 0 2 . 7 0 . 1 0 0 . 1 . 8 0 I . 7 0 . 4 0 . 2 . 2 0 9 C . 1 . 6 7 " 8 0 . 2 . 4 3 7 5 . 4 3 9 9 9 . 9 9 9 . 9 9 9 0 0 6 5 . 5 0 . 7 7 9 2 - 5 0 . 6 0 . 7 0 2 9 . 0 0 0 9 9 9 . 0 0 0 - 3 . . 8 5 7 5 . 0 6 4 2 3 . . 0 0 0 4 . 8 7 8 2 . 3 . 6 . 1 1 . - 3 . 4. - 1 0 . 2 1 . 2 4 . 2 3 . - 2 1 . 0 1 - 1 5 . 0 ( - 3 5 . 0 0 9 0 . 7 9 8 0 . 6 0 . 2 3 5 6 0 2 . 4 . 3 . 6. 2 4 1 8 0 5 . 7 . 3 . 4 . 2 6 1 0 3 9 . 5 . 1 . 0 . 1 . 9 . 2 . 1 0 . 1 0 . 6 . 1 0 . 4 . 9 . 1 . 3 . 9 . 5 . 2 . 2 . 1 . 4 . 3 . 1 0 . 9 9 . 2 . 4 , o c o 4 , 1 4 3 4< 5 0 0 7 5 . 7 7 . 8 5 7 8 . 4 9 5 2 4 . 3 . 6 . 2 0 . 7 . C O ' 80'."" 7 2 . 8 5 7 5 7 2 5 5 " " 3 4 . -I. - 8 V . 2 6 * * I.'00* 6 5 . 7 2 . 1 4 3 4 . 8 7 1 1 1 . 1 7 . 4 . 9 . - 1 1 . 0 0 1 . 9 0 . 1 . ' 7 0 , 5 ' . 9 9 9 . 4 . 1 0 . 1 . 8 0 . 5 . 9 9 9 . 3 3 0 0 4 3 . 5 . 0 . 1 . 3 5 6 1 2 6 . 4 . 2 . 5 . 4 0 4 0 4 4 . 3 . 9 9 . 6 . 1 . 9. 1 . 2 . 1 C . 1 . 2 . 4 . 1 . 1 . 9. 9. 6 . " 3 . 2 . 9. 6 . S . 1 0 . 6 . 2 . 2 . 4 . 3 . 0 0 0 3 . 4 . 5 . 4 2 9 5 . 4 . 5 . 8 3 3 2 . 8 5 . 1 . ' 5 . 9 . 9 5 . 1 . 6 5 . 1 . 0 " . 1 . 2 0 . 2 . 3 3 6 0 . 2 . 5 0 3 5 ' . ' 3 . 2 9 _ 9 9 9 _ . _ l.*R3 7 0 . 2 . 1 4 2 0 . ' 3 . 6 0 8 0 . 2 . 3 3 1 0 0 . 2 . 5 0 " 4 0 . 2 . 6 C 9 9 9 2 . 0 . 2 . " 7 5 . . 2 . 9 9 9 , 1 . 8 3 T; 3 3 2 0 . 9 5 . 5 3 , 5 0 6 0 ' . " " 5 5 . 5 9 , 5 7 9 9 9 . 9 9 9 . 9 9 9 . 8 3 ' 5 7 1 7 . 5 2 0 - 3 . 2 8 6 6 . 4 4 6 " " 2 7 ; 0 0 0 9 9 9 . 0 0 0 1 4 . 1 1 . - 1 5 . 9 . 6 . 1 7 . 0 . 3 0 . " 1 5 " . " ' 0 . - 5 9 . 0 0 " " " 9 " . 0 0 - 3 . 0 0 7 5 . 2 . 1 4 " 1 0 . 2 . 3 3 9 0 . 6 9 , 2 . " 1 5 . 2 . 3 0 . 1 4 4 0 4 0 . 1 0 0 . 7 2 . 0 0 0 3 . 1 2 5 5 . 2 3 . - 1 8 . 3 . - 3 9 . 0 0 2 0 . 3 0 . 1 4 . 2 8 6 " " 5 . 5 5 0 1 5 . " - 9 . ""i 2 . " " ' 2 1 . " ' " " 1 5 . 0 0 8 5 . 8 0 . 7 5 . 7 1 4 5 . 5 7 5 1 4 . . p . - ? . 6 . 6 . 0 0 APPENDIX A-3 IN BASKET RESPONSES 2 rows r>er subject, F i l e Numbered. . . m 1st row: 7 memo strategy scores, memo score w/ 5&6 included ¥emo Score 5 & 6 treated as 2.5 and Memo Score 5&6 Excluded; 2nd row: 7 minimum odds, minimum odd average,, 7 Grade assignments, average Grade assigned, weighted Minimum odd -score v/ith Grade as wei^X 4 Semantic^Differential Scores, a consolidated SD Score. I c o -0 -I 1 (M ~* o ° o ! w IA w O r v i O c i n c i ( • r\• ~* (\j c- ,r\j o i n <7 ' i n ^ C (\ O P J X O O : o < ro m - o I IT. O O o ro • • CC : • <? CM 'CM O u"v co cc o* r-i O • CT- • O : » O n j r>; a - .(M .—< <r <r M O ^ C] H c m IT. ^ M • O CT- o c c . LO rr- r\j o —' o ^ a o w - ^ i n cr o oc a> o c i v O ^ ^ iv. - ( ^ h N * O C ' iv f O o r- i*-; m c o ; o o tri i r . ! o i o m f-- ro ^ >o tr> ro i n v*- o i M ^ r- ,-. *V[ -T —t IT. n ^ m <i (VJ IP. isf IA vt m \t- r- 'r\j r~~ m m c - inirn o ^- cc ^ ir. c• f - vj- rvj u~> m v0 o m f - *-> 0 | f \ j •£> <M -0" •—< ro <r <} r~ ~ o —• m vj- vf o o r> m o co fNJ <v sr T- c o O <r> a- H IP H IT ^ !f\ if ^ L1", --i IT. 03 LO M N ^ N r~. O r- C O p.; —* jro <-« -o if\t ,_. .-J r- c , o . . . . _ • !ro • r— • u. • o * c ro ro f\: —• a O -j- c c ! ^ c m »t — C M T c c ? IP <f ^ r » ^ m |LO o u", O j o r- cr '.o • IT1 * O • -O • vC • r— • CC •1c* « C7- • Q; • C" • o o n j m o w I—I E H • o EH X W M W D W S < t-H ^ <t a ; cr o w m . f </\ . o -3- <j- <f ^ i n ir. i n IA ir. t n ir. r - ' x o ' O p - ' t v m . j ' m ^ c p ^ c c ' c r o u . U T I L I T Y R E S P O N S E S , C O M E f ' N S A T I O N TM THOUSANDS O F D O L L A R S , S C A l F f l F W A G E R Iti A M O U N T S S V F ' C I F I F D , R A T E O F R E T U R N I N Pf . R C G N T A G E , NE T P R O F I T I N P R O B A B I L I T Y M I S S I N G I S A 9 9 . O R A 0 . 0 4 . a . 1 0 . 2 0 3 0 . 4 . 0 . 1 0 O . C O 0 . 0 0 0 . 0 0 0 . 0 0 4 0 . 0 . 3 0 0 0 . 5 0 0 0 . 1 5 0 0 . 3 0 0 6 0 0 . 2 0 0 . 0 . 2 5 0 0.aoo 0 . 5 0 0 0 . 5 0 0 6 6 7 1 . a. 1 3 . 2 4 3 5 . 2 . 0 . 2 5 1 . 0 0 5 . 0 0 0 . 0 0 0 . 0 0 4 7 . 0 . 3 5 0 0 . 6 0 0 0 . 1 5 0 0 . 2 5 0 6 f 0 . 1 0 0 . 0 . 3 0 0 0 . 7 0 C 0 . 4 C 0 0 . 6 0 0 4 5 7 . 1 5 . 2 5 . 3 0 4 0 . 2 . 1 . 0 0 1 . 0 0 5 0 . 0 0 0 . 0 0 • 0 . 0 0 3 0 • 0 . 2 0 0 ' b" . 3 0 C 0 . 1 5 0 0 . " 2 5 0 1 0 0 . ' " 1 ^ 0 . 0 . 5 0 0 0 . 3 0 0 0 . 5 0 0 0 . 5 0 0 ' 5 0 2 . 1 2 . 2 5 . 4 0 . 1 0 0 . 4 . 0 . 5 0 0 . 0 0 0 . 0 0 0 . 0 0 • 0 . 0 0 1 2 . 0 . 2 0 0 0 . 3 0 0 0 . 2 0 0 0 . 2 5 0 2.oo_._ 5 0 . 0 . 7 0 0 0 . 7 0 0 0 . 9 0 0 0 . 8 5 0 5 6 3 . 8 . 1 5 . 2 0 3 0 . 3 . 1 . 3 0 1 0 . C. 0 0 . 0 0 0 . CO 0 . 0 0 4 0 . 0 . 4 0 0 o. 5 0 0 0 . 3 0 0 0 . 1 0 0 6 0 0 . 3 0 0 . 0 . 3 3 0 0 . 6 0 C 0 . 6 0 0 0 . 7 0 0 _ _ . 2 4 0 1 _ . . 1 2 . 1 4 . 1 5 1 6 . 1 . 0 . 5 0 5 . 0 0 2 5 . 0 0 I O C . C O 0 . 0 0 6 0 0 " . " " 0 . 1 5 0 " o. 4 0 0 0 . 0 5 0 0 . 2 5 0 "" 4 0 ". " 2 0 . 0 " . " 4 0 0 " 0 . 10 0 0 . 6 0 0 0 . " 4 0 0 " .. ... „ 3 7 2 0 . 1 2 . 1 4 . 1 5 1 8 . 0 . 0 . 3 0 3 . 0 0 3 0 . 0 0 3 0 0 . 0 0 3 0 0 0 . 0 0 2 0 0 . 0 . 2 5 0 0 . 1 3 0 0 . 3 8 0 0 . 2 5 0 5 . 1 . 0 . 4 6 0 0 . 5 0 0 0 . 5 0 0 0 . ^ 6 0 9 0 3 4 9 . 1 0 . 1 5 . 2 2 3 0 . 3 . 0 . 3 0 2 . 5 0 0 . 0 0 0 . 0 0 0 . 0 0 6 0 0 . 0 . 1 0 0 fl 4 1 5 0 0 . 0 7 0 0 . 1 2 0 4 C . 2 0 . 0 . 7 5 0 0 . 9 0 0 0 . 7 5 0 0 . 7 5 0 J L O l l 12_ . 6 . 3. 1 0 . 0 . 1 . 5 0 1 5 . 0 0 1 5 0 . 0 0 1 5 0 0 . C O 1 5 0 0 0 . 0 0 ' " 4 Q . " ' " 0 . 5 0 0 " " "o'T " 5 0 0 0 . 5 0 0 0 . 5 0 0 " 6 0 0 . ' 3 0 0 . 0 " . 7 5 0 I . 0 0 0 0 . 7 5 0 0 . 8 5 0 1 2 1 3 1 4 . 1 5 . 2 2 . 3 0 3 5 . 3 . 0 . 2 5 2 . 5 0 0 . 0 0 O . C O 0 . 0 0 4 0 . 0 . 3 0 0 0 . 2 0 0 0 . 5 0 0 0 . 3 0 0 6C 0 . 3 0 0 . 0 . 7 5 0 0 . 6 0 0 0 . 7 5 0 0 . 7 5 0 1 2 1 9 4 3 . 1 2 . 1 6 . 2 0 3 0 . 5 . O . O C 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 6 0 0 . 0 . 1 0 0 0 . 2 0 0 9 . 9 9 0 0 . 1 5 0 4 0 . 2 0 . 0 . 9 0 0 0 . 8 0 0 0 . 8 0 0 0 . 7 0 0 1 2 4 1 6 7 . 1 0 . 1 3 . 1 8 3 0 . 4 . 0 . 2 5 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 " " 4 0 . 0 . 2 5 0 " 0 . ' '4 00 'O.T0 0 0 . 2 5 0 " '6"ooY 5 0 . " 0 . 8 0 0 0 . 9 0 0 0 . 7 0 0 0 . 9 0 0 - " • • - - - - • 1 3 1 3 1 3 . 1 0 . 1 1 . 1 3 1 5 . 1 . 1 . C O 1 . 0 0 1 0 . 0 0 1 0 0 0 . 0 0 0 . 0 0 6 0 0 . 0 . 5 0 0 0 . 7 5 0 0 . 2 5 0 0 . 5 0 0 4 0 . 2 0 . 0 . 3 3 0 0 . 5 0 0 0 . 5 0 0 0 . 3 3 0 1 9 1 2 3 5 . 1 2 . 2 0 . 5 6 . 1 4 5 . 5 . 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 O . O C B O O . 0 . 1 0 0 0 . 1 0 0 . 0 . 1 0 0 0 . I C O 4 0 . 5 . 0 . 7 5 0 0 . 7 5 0 0 . 7 5 C 0 . 7 5 0 . 2 1 4 7 1 4 . 1 5 . 3 0 . 5 0 7 5 . 3 . 0 . 5 0 5 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 " " " 4 0 . " " 0 . 3 0 0 " 0 ." "5"00 ' 0".' 1 5 0 0" . 1 0 0 " ' 6 0 0 ' . " " " 3 0 0 . 0 . 7 0 0 0 . 4 0 0 " 0 . 5 0 0 0 . 6 0 0 " 2 2 4 9 0 3 . 1 0 . 1 2 . 1 4 1 7 . 0 . 0 . 5 0 5 . C O 5 0 . 0 0 5 0 0 . 0 0 5 0 0 0 . 0 0 6 0 0 . 0 . 5 0 0 0 . 7 5 0 0 . 2 5 0 0 . 5 0 0 4 0 . 2 0 . 0 . 3 3 0 0 . 5 0 0 0 . 5 0 C 0 . 6 7 0 2 3 5 6 0 2 . 2 0 . 2 4 . 0 0 . 3 . 0 . 1 0 0 . 2 0 0 . 0 0 0 . 0 0 0 . 0 0 6 0 0 . 0 . 1 5 0 0 . 2 5 0 0 . 1 2 I 0 . 1 6 0 4 0 . . 2 0 . 0 . 7 0 0 0 . 3 0 0 1 . 0 0 0 0 . 4 0 0 _ 2 4 1 B 0 _ 5 . 9 . 1 2 . 1 5 2 1 . 2 . 0 . 3 5 4 . 0 0 3 0 . 0 0 o.c-o 0 . 0 0 ' 2 0 0 ' . " " 0 . 2 5 0 " 0"." ' 4 0 0 ' " 0 . 1 2 0 ' 0 . 2 5 0 " ' " 50 " . . " " 2 0 . 0. 7 0 0 0 . 7 5 0 0 . 4 0 0 C . 6 0 0 " ' ' " — 2 6 1 G 3 9 . 1 2 . 1 5 . 2 0 2 5 . 0 . 1 . 0 0 1 0 . C O 1 0 0 . 0 0 1 0 0 0 . 0 0 1 0 0 0 0 . 0 0 . 4 0 " . 0 . 2 5 0 0 . 7 5 0 0 . 2 5 0 - 0 . 5 0 0 6 0 0 . _ 3 0 0 . 0 . 7 5 0 0 . 5 0 0 C . 5 C 0 0 . 7 5 0 APPENDIX A-4 UTILITY RESPONSES l ^ l % ^ f t b . , k Compensation Response, No. of NO answers to g o c P l e of wa."'or, 5 s c a l e of wager responses. 2ncTrow: 5 r a t e of r e t u r n responses, 6 net p r o f i t responses 330043. 3 0 . 3 5 . 46" 6 i . 3. 0.50 5.GO G.OC COO 0.00 600. 0.500 0.500 0.130 0.250 40. 2 0 . 0.750 0.670 0.670 0.670 3561 26._ 10 . 30. 60. 2 0 0 . 4._ 0.49 0.00 0.00 O.CO 0.00 600.' d .500 0 .750 6."'250 0. 50 0 " 4 0 . " 8. " 0. 500 0. 500' "0. 5C0" 0. 500" " ~ 404044. 10. 11. 13. 14. C . 1.50 15.00 110 .00 1005.00 10010 .00 600. 0.250 0. 380 0. 130 0. 500 40. 2 0 . _0.2 5C_ _060 0__0_. 750 0 .250 449771. 1 0 . 13. 0 . 0. 1. 0 .50 5. CO 5'CTOO" "~"!TO~OT6T5 5"0""0"7C0~ 600. 0.000 0.000 O.COO 0.000 40. 2 0 . COCO COCO 0.000 0.000 4439_71. 12. 18. 30. 45. 3. 0.49 3.00 0.00 0 .00 0 .00 "" "40 ." 0 .200 "0 "."400 0." 150'07250 600. 2 0 0 . 0.500 0.500' 0. 500 0 . 5 0 0 " 474747. 12 . 14. 19. 23. 1. 0.00 O.CO 0.00 O.CO 0.00 40. 0.450 0. 70C 0. 200 0. 400 600. 300. 0. 500 ^ . 5 50 0.4 50 0.400 519725. . 1 0 . 13. 15 . 16. """5. 0 70C 0.00 C'OO" GTOO" 0"700~ 40. 0.250 0.50C 0.250 0.200 600. 300. 0.930 0.950 C.90C 0.500 614715. 16. 50. 70. 80. 3. 0.25 1.00 C O O 0.00 0.00 2 0 . 0 .300'0.250 0.700 0.400 2 0 0 . 50. C 8 0 0 0.700 0.3f0 0.800 654321. 15. 17. 2 0 . 30. 5. 0.00 0.00 0.00 0.00 O.CO _40._.0_.18_0_j). ?0p 0. 150 0. 120 6C0. 30C. 0.85C 0. 750 C 700 0.700 . 654537. 10." 14. . 17. 22. 3. 0.70 4 .GO " 0.00 O.CO '• bTccT 40. 0.100 O.lOO 0. 050 0.080 600. 300. C.400 C 700 0.6CC 0.400 755316. 9. 13. 17 . 23. 2. 0. 35 3 . 50 2 C 0 0 O.CO 0 .00 ' 40. 0.350 0.550 0.180 O.3O-0 ftOO. ICO. 0.550 0.75C O . « 0 0.600 806662. 6. 7. 8. 9. 0. 0.40 3 .00 2C0C 100.00 0.00 48. 0.500 0.750 0.250 _0 . 5 r 0 6 60. J. 1 C 0.920 0. 50 0 _ C 5 ' ? . C_.670 960321 . 9. 13. 25 . 5 07 " ' 2 . ' 0 ' . 50 2.0O" ' K .00 O.CO CTocT 6C3. 0.400 0.60C 0.250 0.450 47. 5. 0 .300 0.200 0.300 0.300 J577713. 16. 25. 28. 32. 4. . O.SC 0.00 O.CC o .CO 0.00 401 0.200 0'"503 6'."200 0. 300 600. 5 0 . 0.800 1 .000 1. C-r 0.700""", ' P96S77. 10. 12. 14. 0. 0. 0.50 5.CO 5C.C0 500.CO 5000.00 40. 0 . 1 0 0 C40'J 0.05Q 0. 200 600. 3 0 0. _ C . 750 _0 .J>CO .Oj.600 .ocgcoo. " a . i"2. 16. is". "5* ~o7o"o " ' ."o.'oc " c'"'--o T76o 67<W 6 0 C 0 .500 0.750 C.250 0.500 40. 20. 0 .800 0.700 0 . i50 0.900 APPENDIX A-4 UTILITY RESPONSES (CONTINUED) H O 171 APPENDIX A-5 PERSONAL RECORDS 2 rows per subject. 1st row SUBJ's I.D. SEX: 1 f o r Male, 2 for Female, 99 missing. AGE: 99 - missing STATUS (MARITAL): 1-married, 2-single, 3-separated 4-divorced, 99>0-missing NUMBER OF DEPENDENTS: 99 f o r missing AGE OF DEPENDENTS: AVERAGE. 999 for missing. CITIZENSHIP: 1 f o r Canada; 2 for H.K., 3 f o r Singapore, 4 - B r a z i l , 4- U.S.; 6-India, 7-0thers, 0,99-missing. PRESENT YEAR: 1-MBA I; 2-MBA II; 3-MsC I; 4-MsC II , 5-PhD., 6- Others, 7-MsC No. year; 8-MBA no year. 99 missing OPTION: 1-Acctg: 2-Mktg,; 3-Transportation, 4-Urb. Land Econ- omics; 5-Finance, 6-Int, Business, 7-Management Sc; 8-0.Behavior, 9-0thers, 99 missing. AVERAGE GRADE LAST YEAR - number represent the ordered item checked. Please see questionnaire. PREVIOUS DEGREE - two d i g i t number used. F i r s t d i g i t represent degree, 2nd d i g i t represent option. 1st g i g i t : 1-B.Comm; 2-Eng'g., 3-Education, 4-Law, 5-B.Science, 6-Computer Sc.; 7-0thers; 8-B.A.; 9-Masters; 2nd D i g i t : Eng'g -1: C i v i l ; 2-Mech; 3 - E l e c t r i c a l ; 4-Chem, 5-Agricultural, 6-others; others-0 (for other degrees), 99 missing. NUMBER OF DEGREES: COUNTRY OBTAINED - samecode as c i t i z e n s h i p . Working years - no of years at work. Salary - l a t e s t salary in thousands Positi o n ( l a t e s t ) : l-h-ighe-rrlevel management; 2-middle management; 3-employee, 99-missing. 2nd row NUMBER OF SOURCES - count the number of sources of educational financing. See questionnaire. 99-missing. TOTAL AMOUNT OF EDUCATIONAL FINANCING - i n thousands SOURCE WITH GREATEST FINANCING COMING FROM: number referred to number in the item. 172 AMOUNT OF LARGEST FINANCING - in thousands FACE VALUE OF INSURANCE - in thousands TYPEINSURANCE - type of insurance 1-with savings feature 2-without saving feature AMOUNT OF ASSET - t o t a l i n ten thousands AMOUNT OF LIABILITIES AVERAGE INTEREST RATE LISTING OF STOCK P R I C E WAGER»RESPONSES IN RANKS FROM SET A TO E AND OVERALL" SET RANKING,' MISSING IS A 0 OR A 9 . FIVE RANKS PER SET. 3 . 5 . 4. 2 . 1 . 5 . 4 . 3 . 1 . 2 . 2 . 5 . 4. 3 . 1 . i, • 2 . 3 . 5 . 4. 5 # 4. 3. 1. 2 . 0 . 0 . 0 . 0 . 0 . ^ 6 6 7 1 . 1. 2 . .3. 4. 5 . 5 . 4. 3 . 2 . 1. 2 . 1. 3 . 4 . 5. 5 . 4. 3 . *> i . * 1 . 5 . 4. 3 . 2 . 1. 3 . 5 . 1. 4. 2 . f 4 5 7 . 4. 3 . 2 . 1. 5 . 3 . 2 . 4. 5 . 1. 3 . 4. 2 . 5 . 1. 2 . 1. 4. 5 . 4. 3 . 5 . 2 . 1 . 3 . 4. 1. 2 . 5 . j 5 0 2 . 3 . 1. 2. 4 . 5 . 4 . 5 . 1. 2 . 3 . 1 . 2'. 3 . 4. 5 . 5 . 4. 2 . 1 . 4. 5 . 3 . 2 . 1 . 5 . 1 . 2 . 3 . 4 . : • 56 3 . 5 . 4. 3. 2 . 1. 5 . 4 . 3 . 1. 2 . 5 . 4. 3 . 2 . 1 . 5 . 4. 3 . 2 . 1 . 5 . 4. •3 _' • 1. 2 . 2 . 3 . 1. 4 . r. j" '""240 i . 3 . 2'. T . " "4." 5." 5"." '4. " 3 . " 1. " 3 . ' 2 . " 1."" "4." 5 . "5 . "4 . i 2 .'" 3 . " 5 . 4. 37 : i . 2 . 3 . .̂ 1. 4 . 2 . j 37 2 0 . 5 . 4. 3 . 2 . 1 . 5 . 4. 3 . 2 . 1. 5 . 4. 3 . 2 . 1. I. 2 . 3 . 4. 5. 5 . 4. 3 . 2 . 1 . 2 . 5 . 1. 4 . !' 903 4 9 . 2 . 3 . 1. 4. 5 . 5 . 4. 3. 1. 2 . 2 . 5 . 4. 3 . 1. 5 . 4. 3 . 2 . 1 . 5 . 4. 3 . 1. 2 . 4. 2 . 1. 5 . 3 . i 1011.12. 1. 2 . 3. 4. 5 . 2 . 3 . 1. 4. 5 . 5 . 3. 4. 1 . 2 • 1. 2 . 3 . 4. 5 . 4. 3 . 2 . 1 . 5 . 3". '57' 4 '7 1 . 2 . i 1 2 1 3 1 4 . 2 . 3 . 1. 4. 5 • 3 _ i J . . 4. 5 . 2 . 2 . 1. 3 . 4. 5 . 5 . 4. 1. 3 . 2 . 5 . 4 . 3 . 1 . 2 . 1 . 4. 5 . 3 . 2 . ! 1 2 1 9 4 3 . 1. 2 . 3. 4. 5 . 5 . 4. 3 . 2 . 1. 1. 2 . 3 . 4. 5 . 5 . 4. -a 4 2 . 1 . 5 . 4. 3 . 2 . 1 . ? • 3 . 1. 4. 5 . [ " . " 1 2 4 1 6 7 . 3 . 2 . ' " 1 . " 4 • 5 . '4." "1. " 3 . 2 . " "4 7" 3. I 7 2 . " 5 . '4'." 3 • 2 . 1." 5 . 4 . 3 • 1 . 2 . 2 . 3 . 1. 4. 5 # | 1 3 1 3 1 3 . 1. 2 . 3 ^ 4 • 5 . 5 . 3 . 4. 2 . 1. l . 5 . 4. 3 . 2 . 5 . 4. 3 . 2 . 1. 0 . 0 . 0 . 0 . 1 . 2 . 5 . 1 . 3 . 4. ! 1 9 1 2 3 5 . 3 . 4 . 2 . 1. 5 . 5 .• 4 . 3. ~> c . 1. 3 . d • 1 . 4 . 5 . 3 . 4. C J * 1 . 2 . 4. 5 . i 2 . 1 . 4. 5 . 1. 3 . 2 . j 2 1 4 7 1 4 . 5 . 2 . 1. 3 . 4 . 5 . 4 • 1. 2 . 3 . 5 . 4. 1 . 2 . ~3 . 4 . 2 . "TT" 3 . 9 . '4. 3 . ~9T ~ i JL . "2 r 4 " 3 . " 2 7 ~r: " 1 ~ 2 2 4 9 C 3 . i x . 4 • 2 . 3 . 5 . 5 . 4. 3 . 1 . 2 . 5 . 4. 3 . 2 . 1. 5 . 4 . 3 . 2 . , 1 . 5 . 4. 3 . 2 . 1 . 3 . 1. 2 . 5. 4. ' 2 3 5 6 0 2 . 1. 5 . 4. 2 . -a ^ 5 . 4. 2 . 3 . 1 . 1 . 5 . 4. 3 . 2 . 2 . 3 . 4. 5 . 1 . 5 . 4. 3 # 2 . 1 . 3 . 4. 1 . 2 . 5 . j 2 4 1 3 0 5 . "3 ^ "2 . " " 1." 4. 5 . 5 ." "2 . i . " '4.' 3." ~3 . " " 1 . " " 2.'" 4." '5. 5 . ' '4. 3." 2 . 1 . 5." 4. 3 . 1. 2 . 3 . 3 . 2 . 5 . 4. j 2 6 1 0 3 9 . 4. 3 . 1. 2 . 5 . 5 . 3 . 2 . 4. 1. 2 . 3 . 1 . 4. 5 . 4. 2 . 1 . 5 . 4. 3 . 1. 2 . 1. 5 . 3 . 4. 2 . i 3 3 0 C 4 3 . 3 . 2 . 1. 4 . 5 . 2 . 1 . 5 . 3 . 3 . 2 . 1 . 4. 5 . 5 . 4. 2 . 1 . 3 . 4 . 3 . 2 . 1. 5 . 5 . 4. 2 . 3 . 1. { 3 5 6 1 2 6 . 5 . 2 . 4 • 3 . 5 . 4. 3 . 2 . 1. 1. 5. .̂ 3 . ~"2""7 57 4. 3 . 2 . 1 . 5 . 4. 3 . 2 . 1". " 2 . I T "3T 5 7" ~4T : 4 0 4 0 4 4 . 4. 5 . 3 ^ 1. 2 . 5 . 4 . 1 . 3 . 2 . 4. 5 . 3 . 1 . 2 . 4 . 1 . 3 . 5 . 2 . 5 . 4. 3 . 2 . 1 . 2 . 5 . 1 . 4. 3 . ! 4 4 9 7 7 1 . 3 . 4. 1. 2 . 5 . 5 . 1 . 3 . 4 . 2 . 1 . T -> • 2 . 4. 5. 5 . 4 . 2 . 3 . 1. 5 . 4. 3. 2 . 1 . 3 . 4. 1. 5 . 2 . j 4 39717 . ' 5 . " 2 . " "•1". ".3'. " 4. s. "V." ' 1." "2 . "3 7 "5." 1. 2 . 3 . '4. 4." 3 . 2 . 1 . 5 . 4. 3 . 2 . 1 . 5 . 1 . 5. 2. .3. 4. I 4 7 4 7 4 7 . 1. 5 . 4. 2 . 3 . 5 . 4. 3 . 2 . 1. 5 . 4. 3 . 2 . i X . 5 . 4. 3 . 2 . 1. 5. 4. 1. 2 . 3 . 3 . 5 . 1. 4. 2 . ! 5 1 9 7 2 5 . 1. 2 . 3. 4. 5 . 5 . 4. 3 . 2 . X • 1. 2 . 3 . 4. 5 . 5 . 4. 3 . 2 . 1 . 5 . 4. 3 . 2 . 1 . 2 . 4. 1. 3 . 5 . ! 6 1 4 7 1 5 . 2 . 3 . 1. 4. 5 . 5 7" 4. 3. 1. 2 . 3 . 5 . 4. 1. 2 . 5 . 4. 3 . 2 . 1 . 5 . 4. 3 . I T - 2 . ~2"T" T T 4 . 5 _ 3 ~ 6 5 4 3 2 1 . 1. 3 . 2 . 4 . 5 . 5 . 2 . 3 . 4. 1. 1 . 2 . 3 . 4. 5 . 5 . 4. 2 . 3 . 1 . 4. 5 . 3. 2 . 1. 4. 5 . 2 . 3 . 1. 6 5 4 5 3 7 . 2 . 5 . 2. 3. 4 . A- « 3 . 1 . 2 . 1 . 5 . 4. 3 . 2 . 4. 1 . 3 w 5 . 2 . 5 . 4. 3 . . 2 . 1 . 4. 1. 3 . 2 . 5 . i 7 5 5 3 1 6 . 5 . " 4 . 3." 1. 2 . 4 ." 3 . T"7" "2." r; ^ 5 . 4." 3. 1. 2 . " 2 . " 1. 3 . 4. 5 . 4 . 3 . 2 . IT "5." 2 . 3 . 1. 4. 5 . | " ,06662. 3 . 2 . 1. 5 . 4. 4 . 2 . 1. 5 . 3 . 4. 3. 2 . 1 . 5. 5 . 4. 3 . 2 . 1. 2 . 3 . 4. 1. 5 . 4. 2. 1. 5 . 3 . I 9 6 0 3 2 1 . 4. 5. 2. 1. 3 . 1 . 2 . 3 . 4. 3 . 5 . 1 . 2 . 4. 5 . 2 . I . 4. 3 . 5. 3 . 2 . 1 . 4. 4. 2 . 1. 3 . 5 . i 9 7 7 7 1 3 . 1 . 2 . 3 # 4. 5 . 2 . 5 . 4. 3 . 1. 2 . 4. 3 . 1 . ' 5. 5 . 3 A 4. 1. 2 . 0 . 0 . 0 . 1. 0 . 0 . 0 . C\ "0. "'07 ! 9 9 8 8 7 7 . 1. 2. 3 . 4. 5. 5 . 4 . 3 . ;> m 1. 1. 5. 4. 3. 2 . 5. 4 . 3 . 2 . 1 . 5. 4. 3. 2 . 1 . 2. 5. 1. 3 . 4. ; 9 9 9 0 0 0 . 2 . 1. 3. 4. 5 . 5 . 4. 3 . 2 . 1 . 2 . 1. 3 . 4 . 5. 5. 4 . 3 . 2 . 1 . 5. 4. 3. 2 . 1 . 4. 1. 2. 3 . 5. APPENDIX A-6 STOCK PRICE WAGER RESPONSES 1 row per subject 5 ranks per set, f i v e sets in a l l and 5 o v e r a l l set ranking. L I S T I N G . O f - P E R S O N A L R E C O R D S 4 . 2 . 2 5 . 3 . 1 . 6 6 7 1 . J.. 2 3 . 3. ' 3 . 4 5 7 . 1 . 5 5 . 3 . 2 . D O ? . ) 2 5 . 9 9 . 2 . 5 6 3 . 1 . 2 ^ . 2 . 0 . 0 . 7 . 2 . . 2 . 3 . 2 . 0 . 2 . 0 . 0 . I. 4 . 1 . 4 . 1 1 . 1 . 2 . 0 . 1 . C . 5 . 3 . 1 5 . 1 . 1 . 2 4 0 1 . 37 2 0 . 9 0 3 4 9 . 9 9 . 1 . 9 9 . 1 . 9 ^ . 2 7 . 1 . 31 ." 1 . 2 3 . 3 . 1 . 2 . 0 . 1 . 2 . 4 0 . 1 . 2 . 9 0 9 9 . 2 . 1 . 3 5 . 1 . 2 . 4 . 1 . 2 . 4 . 2 . 2 . 0 . 0 . _ C U _ 2 . _ " 9 9 9 9 " . 9 9 . 9 ' . 9 9 9 9 " . 1. 2 . 2 6 . 1. 4 . 8 . 1 0 . 1 . 1 . 1 ' 3 . 20". 6 . 5 . 4 . 2 . 1 . 1 . 2 . 0 . 0 . 1. 2 . 0 . 6 . C . 9 . 4 . 1 2 . 1 . 1 . 2 . 1 3 . 1 . 9 . " "3 . 7 0 . " 1 . 1 . 0 . 3 . 7 . 9 . 9 9 . r 9 . 9 9 . 9 9 ^ <39. " 9 9 9 9 9 . 9 9 9 9 . 4 . 5 . 8 0 . 1 . 1 . 1 . 9 . 5 . 8 . "" 3 . 9 1 . 3 . 5 . 1 . 2 . C . 9 . 5 . 5 0 . 1 . 1 . 1 . O . C O 1 . ._ 0 . 0 0 3 5 . 0 . 0 8 9 9 . 0 . 9 9 9 9 . 1. 8 . 1 3 . 9 9 9 . 9 ° 9 . 1 0 1 1 1 2 . 12 ! . ' . ) 4 . " 1 2 1 9 4 3 . 1 2 4 1 6 7 . 131 3 1 3 . 1 9 1 2 3 5 . 2 1 4 7 1 4 . ~2249""0y. 2 3 5 6 0 2 . 3 . 2 . 3 . 1 . 2 . C , 1 . 2 5 . 2 . 0 . 0 . 1 . 8 . 0 . 1 . 2 . 1 . 9 . C . 1 . 3 4 . 1 . ' 3 7 2 7 . 5 " . 2 . 2 . 2 . 9 9 9 9 . < :9 . 1 . 5 . 1 . 2 9 . 2 . _ _ 0 . C 9 9 . 3_._ " 2 . 9 9 9 9". 9 9 . 9"." " 9 9 9 9 . 2 3 . 2 . 0 . 0 . 1 . 1 . 1 . 3 . 1 . 2 . 0 . 9 9 . " " 9 9 . " 9 9 " . " " ' " 9 9 " 9 '.' 9 9 . " 9 9 " . 9 9 . 9 . 9 9 9 . 9 9 . 9 . 9 9 9 9 . 9 9 . 9 9 . 0 9 . 9 9 9 . 9 9 . 9_9_. " 9 9 . 9 9 9 9 . " 9 9" . 9 . 9 9 9 9"; 3 1 . 1 . 0 . 0 . 1 . 2 . 2 . 9 9 9 9 . 9 9 . 1. ' 1 0 . 2 4 . 2 0 . " 0 . 2 . 2 7 3 . 9 9 9 9 . 9 9 . 2 . 0 . 3 C _ _ 1_. 3j ; U . _ J . . 2_^_ 1 . 9 " 9 ? 9 . 3 . T 7 0 . 1 . 2 . 5 . 3 . 5 4 . 1 . 1 . 0 . 0 . 0 . 5 . ' 3 . 5 0 . 1 . 1 . 2 . 6 . C . 6 . 9 9 . 9 4 . 2 . 1 . 0 . 9 9 2 . 0 . 05 ' 9 9 . " 0 . 0 0 __1<^_ 0 . 0 3 C . C O O 9 . '" 0 . 0 0 5 . 8 . 9 9 9 . " 1 0 . C 1 5 . 4 . 3 . 1 . 3 . " 9 9 . " 9 9 . 9 9 . 9 9 . 1 . _ 3 . 1 . 9 9 . 1 . 9 9 . 9 9 9 9 9 . 0 . 9 . 4 . 6 0 . 1 . 1 . 0 . 1 . 0 . 9 9 7" 9 9 . 9 9 . 9 9 . 9 9 . " 9 9 . 9 9 9 9 9 . 9 9 9 9 . 9 9 . 9 9 . 9 9 . 9 9 . 9 9 . 0 . 0 0 1 . 0 . 0 0 9 9 . 0 . 9 9 9 9 . 7 . 9 9 9 . 9 9 9 . 2 4 1 8 0 5 . 2 6 1 0 3 9 . 3 3 0 0 4 3 . 1 . 1 . 2 . "17 3 . 1 . 2 3 . 2 . 0 . 0 . - 1 . 3 . 2_. _ 4 . 1 . 2 4 7 1 7" T . " 2 4 7 1 . 3 . 3 . 1 . 1 . 2 6 . 1. 0 . 0 . 1. 6 0 . 2 . 2 . "2". 1 0 . 4 . 9 9 . 9 9 9 9 9 . 9 9 9 9 . 3 . 4 . 4 0 . 2 . 1 . 2 . 2 . 1 . 1 . 4 . 1 1 . 1 . T . 0 . 1 . 9 9 9 9 . 6 . 4 . 7 0 . 1 . 1 . 3". 1 2 3 . 2 2 . 9 . 4 . 12 . . 1 , 1 . 1 . " 6 . 4 . " 5 7 " " 4 7 " 80" . " 1 . 1 . 2 . 7 . 1 . 4 . 5 . 7 0 . 1 . 1 . " 0 . 9 9 5 . 0 . 0 5 " 9 9 . 0 . 9 9 5 . _ " 0 7 0 9 " 1 . 0 . 0 8 3. . . " ' 0 . 0 0 1 0 . 9 9 9 . " 2 C 7 . "12." 6 . ~~ 3 . 3 . 9 9 9 9 . 9 9 . 1 . 1 0 . 3 5 6 1 2 6 . 1 . 2 4 . 2 . 0 . 0 . 1 1 . 2 . 4 0 4 0 4 4 . " 17 2 7 . 2 . " 67 C»"."" 1 7 " 8 . 3 . 2 . 2 . 4 . 2 . 0 . 4 4 9 7 7 1 . 1 . 2 5 . 1 . 0 . 0 . 1 . 2 . 1 . " 9 . 1 . 6 . 5 . 0 0 . 1 . 1 . 0 . 0 . _ C 5 . 4 . 5 0 . 1 . " 1 . 0 . 1 . 2 . 3-. 4 . 1 2 . 1 . 1 . 3 . 2 . 9 9 9 9 . 9 9 . 1 . 1 5 . 4 4 3 9 7 1 . 1 . 2 6 . 1 . 0 . 2 4 . 7 . 2 . 2 . ^ 3 . 9 9 9 9 . 9 9 . 1 . _ 1 5 . 4 7 4 7 4 7 . ' r . ^ 3 7 . 2 . 6 7 " 0 ."""l7 " 8 . 3 . 1 . 9 9 9 9 . 3 . 2 . 0 . 5 1 9 7 2 5 2 . 0 _ 3 . _ 2 _ . 7 . _ J L . 8 . 99 " . 3 . ' 9 9 9 9 . ' 9 9 7 " " ? . " 0 . 6 1 4 7 1 5 . 1 . 3 0 . 1. 4 . 1 0 . 1 . 7 . 2 . 4 . _ 6 . 4 . 1 . 9 8 . 6'>4?.?1 . 1 . 2 8 . T . 0 0 . " 7 . " ' 8 . 2 . 4 . 8 . 4 . 1 . 3 0 . 6 5 4 5 3 7 . 1. 2 4 . 2 . 0 . 0 . 2 . 2 . 1 . 8 . C 5 . 1 . 9 1 . 2 . 7 , 2 . 1 1 . 0 . 9 4 . " 4 0 . 1 . 2". 0 . 22 0 . 2 . 2 . 6 . 7 0 . 1 . 1 . 0 . 9 9 9 9 9 . 1 . 5 . 3 . 1 5 . 1 . 1 . 0 . 5 7 . 2 2 . 6 . 3 . 1 5 . 1 . 3 . 1 . 4 . 0 . 5 0 . 1 . 1 7 5 5 3 1 6 . 8 0 6 6 6 2 . 9 6 0 3 2 1 . 0 . 2 . 3 . 1 . 2 . 0 . 1 . 2 7 . 1 . 0 . 0 . 1 . 1 . 3 . 2 , 9 9 9 9 . 9 9 . 2 . 0 . 1 . 2 5 . 2 . 0 . 0 . 1 . 2 . 1 . 1 . 1 . 1 . 2 . 0 . 1 . 0 . 2 . 0 . 0 . 2 . 2 . 0 . 1 . 3 . 1 . 0 0 . 1 . 1 0 . 6 . 9 . 4 . 8 0 . 1 . 0 . 5 . 1 . 3 . 1 1 . 1 . 3 . 3 . 2 . 2 . 2 . 0 . 9 7 7 7 1 3 . 2 . 2 5 . 1. 1 . 1 . 1 . 1 . 3 . 1 . 1 . 0 . l._ 0 . " 9 9 8 8 7 7 . 1 . 2 7 . 2 7 " 6 7 " " 6 7 " " l 7 7 ."' 9 9 . 1 . 9 9 0 9 . c -9 . 9 . 9 9 9 9 . 9 9 9 0 0 0 . 1 . 2 3 . 2 . 0 . 0 . 1 . 1 . 0 . 3 . 1 . 2 . 0 . 1 . 0 , 9 . 5 . 4 0 . 1 . 1 0 . 2 5 . 7 5 0 1 , 7 . 4 . " 5 0 . 1 . 1 9 9 . 9 9 9 9 9 . 9 9 9 9 , 9_. 5._ 5 0 . _ _ 1 _ . _ 1_ o . " " " 1 . " ~ 0 . 0 . 0 4 1 . 0 . CO " 2 . 0 . 0 0 J . _ 0 . 0 0 3 . 0 . 0 0 8 . 0 . 0 6 _ 9 9 . 0 . 9 9 " 7 . 0 . 0 7 4 . " 0 . 0 0 = o. 0 . 0 0 6 . 0 . 0 9 2 . 0 . 0 8 7., 0 . 00" 3 . 0 . 5 0 " 9 9 . 0 . 9 9 0 . _ cTcb 6 . ' 6 . 6 . 8 . 9 9 9 . 1 4 . 3 C . J O . 7 . 3 . _ / f * 8 . ' 9 9 9 . 7 . PERSONAL RISK PROFILE FOR I.D. 614715. > > X "d O CO td W O i-3 03 !—I o NOTE: THIS LISTING PROVIDES YOU WITH THE SCOPES ON THE VARIOUS MEASURES AND YOUR PERCENTILE ON IT THE HIGHER PERCENTILE WOULD MEAN HIGHER RISK TAKING . PERCENTILE IS BASEO ON GROUP 01 STR I BUT I ON . AL SO ALL ID TO SIX DIGITS. W E R E T R U N C A T E O IN RASKCT RESPONSE: RATING DF YOUR 7 MEMO RESPONSES PY JUDGE,WHERE 1 MEANS QUICK DECISION TD TAKE RISKY ALTERNATIVES KEAMS TAKING RISKY ALTERNATIVE BUT QUALI F l ED 3 MEANS QUICK BUT QUALIFIED CONSERVATIVE ALTERNATIVE ,4 MEANS TAKING CONSERVATIVE ALTERNATIVE,!? MEANS MORE INFO? MAT I' IN NI EDEO TO MAKE DECISION,AND YOUR MINIMUM CHANCE OUT OF 1C ON YOUR RATING OF LETTER WRITERS: YOUR SCORE 6 MEANS DELAY AS SCORE 3.500 THE 7 MEMOS: SCORE "5.1430 ST RATEGY. PERCENTIL E CHOICE DILEMMA SCORE UTILITY IT CMS COMPENSATION LEVEL AVERAGE CHANCE OUT YOUR SCORE •34.000 OF 1C YOU 6.800 PERCENTILE PERCENTIL E 5. 100. 100 . WOULD RECOMMEND PERCENTILE BEFORE 5. TAKING UNCERTAIN ACTION. COMPUTED ON BASIS OF RISK PREMIUM FROM EXPECTED VALUE f N PERCENTAGE: YOUR SCORE C.630 YOUR PERCENTILE 5. RATE CF RETURN - COMPUTED IN THE SAME WAY AS COMPENSATION. Y O U R S C O R E 0.081 N E T P R O F I T - C O M P U T E ! ) O N B A S I S O F R I S K P R E M I U M . Y O U R S C O R E 2.000 ; A L F O P W A G E R S - C O M P U T E O W I T H T H E B U Y I N G P R I C E O F O F N O R E S P O N S E S A S W E I G H T S : Y O U » S C O R F 16.663 PERCENTILE PERCENTIL E WAGER AND THE PERCENTIL E 100. 65. NUMBER 5. S T O C K P R I C E W A G E R - COMPUTED WITH VARIANCE AND RANKS AS WEIGHTS. YOUR SCORE 2.433909 PERCENTILE EXTREMITY-CONFIOENCF SCORE - EXTREMITY SCOPE COMPUTED AS AVERAGE .50,WHIL1 CONFIDENCE IS WITH THE FOLLOWING CODE: 1 FOR VERY 3 F T 9 MODERATELY SURF,4 FOR SLIGHTLY SURF,5 FOR NOT SURE YOUR EXTREMITY SCORE 0.111860 PERCENTILE SCORE 9 5 . SQUARED DEVIATION F R O M SURE,2 F O R QUITE SURE, 9 5 . YOUR CONFIDENCE PERSONALITY MEASURES INTER I^AL CONTROL - MEASURE OF HOW YOU ON THE OUTCOMES OF YOUR CHOICES. YOUR SCORE NEW EXP E R_I FNCES MSAS'J RE - ME A SURES_ JjjE NEW"SOCIAL ACQUAINTANCES AND YOUR SCORE 3.0670 PERCENTILE 55. PERCFIVE YOUR DECISION AS HAVING ANY INFLUENCE 6.00 DEGREE EXPERIENCES. 4 . PERCENTILE TO WHICH YOU SEEK. 85. V A P . I E T Y , PERCENTILE 100. •̂ 3

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