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An experimental study of the man-machine interface Masulis, Paul Stanton 1978

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EXPERIMENTAL  STUDY OF THE MAN-MACHINE INTERFACE  by PAUL STANTON MASULIS B.S., C a r n e g i e - M e l l o n U n i v e r s i t y ,  1976  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUSINESS ADMINISTRATION  xn THE FACULTY OF GRADUATE STUDIES (Commerce and B u s i n e s s A d m i n i s t r a t i o n )  We a c c e p t t h i s t h e s i s a s c o n f o r m i n g to t h e r e q u i r e d standard:  THE UNIVERSITY OF BRITISH COLUMBIA May, 1978 (c) P a u l S t a n t o n  Masulis,  1978  In  presenting  requirements  this for  thesis an  Columbia, I agree  freely  available  permission  scholarly or  by  Faculty  may  without  my  be  25,  of  the  make  I further this  the Head  o f my  I t i s understood  of i t  agree  thesis  for  Department  that copying  gain  shall  Paul  Stanton  not  or be  written permission.  of Commerce and  May  shall  study.  copying  of  the U n i v e r s i t y  Library  and  g r a n t e d by  fulfillment at  thesis for financial  Business Administration  The U n i v e r s i t y o f B r i t i s h 2075 wesbrook P l a c e V a n c o u v e r , Canada V6T 1J6  Date:  the  reference  his representatives. of t h i s  degree  that  extensive  purposes  publication allowed  for  for  partial  advanced  British  that  in  1978  Columbia  Masulis  ABSTRACT In t h i s t h e s i s , first  objective  convenient, (designed second  was  with  appropriate addition,  about  The  with  were  experimental  the  fixed  optimum  time  intention  for  automatically  profit  used  participant  was  coqnitive  style  Frequent  In  for this  was  were  slower,  less  user  types.  of  In  v a r i o u s beha-  a  participants  periodic user  searched  performance,  of  special  solution  recorded.  The  users  given  determined  were  features, of  cateqorized  risk  attitude,  by  a  a  attitude,  protocol  were  (heuristic/analytic), as  simple  measurements  the  battery  and each by and of  questionnaires. the  results,  the dcminatinq finished  c o n f i d e n t than  proqram  were most  r e s e a r c h was  also,  analyzinq  level  users  interfaces  the e f f e c t s  on  p r e v i o u s computer e x p e r i e n c e p r e - t e s t s and  The  reaching  i n a three-dimensional space,  collected  variables;  program  of  various  requests f o r reports, u t i l i z a t i o n other  a  investigated. tool  limit. ,  of  various types of  i n t e r a c t i v e c o m p u t e r game i n which t h e for  example  computer  program  about  The  programmer - i n m i n d ) .  the  which  theories  variables  the  objectives.  working  t o i n v e s t i g a t e how  convenient  some  a  two  interactive  the computer,  and  pursued  present  with the user - not  conclusions  vioural  to  "idiot-proof",  o b j e c t i v e was  interact some  the author  interface  factor  less  on  a l l  found  players.  f o u n d t o be  that  experience  dimensions:  f r e q u e n t l y , and  experienced was  i t was  were  novices  siqnificantly  A hiqhly  structured  more a p p r o p r i a t e f o r t h e s e  new u s e r s . , use  of  effect  Experience  reports,  was a l s o t h e d o m i n a t i n g  and  analytic-types  in  a l t h o u g h n o v i c e s d i d show a marked  over time - as d i d a l l  performance  factor  users  behaviour.  As  and r i s k - t a k e r s  were more c o n f i d e n t  than  on  most  played  and  of  hypothesized,  significantly  heuristic-types  learning  dimensions  previously  the  f a s t e r and  risk-averters,  respectively. Concerning was f o u n d t h a t unfamiliar clear-cut  Also,  depended  much  less  defaults  (ones and  s p e c i a l program f e a t u r e s , i t  which didn't  influenced  in  were new o r d i d n o t have affect  Analytic-types  made  least  a l li n use o f  abbreviated  length,  i t was i n d e e d f o u n d  structured  than a n a l y t i c - t y p e s . .  likely  at  t h e e x t e n t t o w h i c h commands were their  least  them  abbreviate  upon  were  users  to  protocols,  much  problem  situations  Bisk-averters  commands.  of  response  circumstances.  defaults.  were  input  responses),  familiar  solution  utilization  Finally,  i n the area of  that  heuristic-types  i n t h e i r approach t o s o l v i n g t h e  iv  TABLE OP  CjONTEIIS  Chapter  Page  1.  Introduction  ..............  1  2.  L i t e r a t u r e Review  3.  The Computer P r o g r a m  4.  Data C o l l e c t i o n  5.  Hypotheses  25  6.  Analysis  29  7.  Conclusions  ...............  3 14  Methodology  ..... . . . . . . . . . . . . . . . . . . . . . .  of Results  19  ...........................................  50  Footnotes .................................................  57  Bibliography  60  ...... . . . . . . . . . . . . . . . . . . .... . . . . . . . . . . . . . . . . . .  Appendix  A - Program L i s t i n g  ..............................  Appendix  B - Game I n s t r u c t i o n s  A p p e n d i x C - Sample I n t e r a c t i o n s Function  62 84  ..........................  Appendix  D - Profit  Appendix  E - Sample Program O u t p u t  Appendix  F - Sample P r o t o c o l s  88  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99  A p p e n d i x G - Summary o f R e s u l t s  .,..,.........,....,,,.101 103  ..........................  107  V  L I S T OF TABLES Table  Page  1.  ANOVA - Game Enjoyment  31  2.  ANOVA - M i n u t e s / P e r i o d  32  3.  ANOVA - T e r m i n a t i o n  33  4.  ANOVA - C o n f i d e n c e L e v e l  5.  T-TESTS - P e r f o r m a n c e and S t r u c t u r e  on Time . . . . . . . . . . . . . . . . . . . . . . . . . . .  34 . . . . . . . . . . . . . . . . . . . 35  6., ANOVA - E r r o r H a t e  38  7.  ANOVA - O p e n i n g  Defaults  8.  ANOVA - A c c e p t a n c e  9.  ANOVA - E x t e n t  10.  ANOVA - A b b r e v i a t i o n  .............................  39  of Defaults  . . . . . . . . . . . . . . . . . . . . . . . . 40  of Abbreviation  41  by L e n g t h  .....42  11. T-TESTS - C o m p a r i s o n s o v e r Time . . . . . . . . . . . . . . . . . . . . . . .  42  12. ANOVA - Use o f H i s t o r y  Reports  45  13. ANOVA - Use o f O r d e r e d  History Reports  14. ANOVA - Use o f G r a p h s  ........................  . . . . . . . . . . . . . . . . 46 .. 47  15. ANOVA - P r o t o c o l S t r u c t u r e  48  16. ANOVA - P r o t o c o l  48  Dispersion  vi  ACKNOWLEDGEMENT I would advisors. their  like  Professors  role  research: doing  to  in  the  take  this  albert  Dexter  programming instilled  carefully  man-machine  regarding  implementation  administrative to  this  final  member. P r o f , and  research  desire  to  research;  for  also for  t h a n k my  his  this  assistant, games more  suggestions  for  especially for their  Taylor,  of  investigate  interface);  I  a d d i t i o n , I owe  Saint  Andrew*s  sincere  Residence  s u p p o r t , e n c o u r a g e m e n t , and and  completion as  my  Benbasat, f o r  i n t e r a c t i v e computer  this  document, Ronald  1977  thank  occasional  contributions  third  additional  committee assistance  enthusiasm. In  of  my  of  s u p p o r t ; and  in  to  Izak  and  f o r two  (work which f i r s t the  and  establishment  f o r summer employment  systems  opportunity  throughout  Columbia.  my  two  t h a n k s t o many of Hall  at  students  for their participation,  fellowship  years  the  the  during  this  U n i v e r s i t y of  research British  1  Chapter  One  INTRODUCTION Even w i t h t h e i n c r e a s i n g the  development  simulations interface  and  interactive  games),  has c o n t i n u e d  Many  of  encountered example,  of  the  tended  some  programming  design t o be  of  effort  programs the  has  to  For  be  quite that  frustrating  input  w i t h an u n i n t e l l i g i b l e s y s t e m e r r o r  installation  very  system  visited. i n chapter  A  of  attention  abound  have  considered  of  communication were  often  interactive most and  paid  their  standard quite  described,  to  this  b u t few  that  quite  computer are  insufficient  issue.  man-computer  Computer  hints  on  man-computer topics  covered  f o r the designer of  terminals.  dozens o f i n t e r f a c e  interface  subjects.  texts  g e n e r a l or s o p h i s t i c a t e d  chapter,  were  literature  f r u s t r a t i n q ; the  programs f o r n o r m a l CRT  useful  illeqal  I t was n o t  they  from t h e  or discouraqed t h e i r the  required  t o o l s , b u t few r e s e a r c h e r s a p p e a r t o  whether  was a l s o too  examples;  the l i t e r a t u r e indicated  biased  Perusal  for  message.  out,  two.  as r e s e a r c h  significantly  Others  program l i b r a r i e s o f e v e r y  seems t o have been  games  use.  o t h e r s r e s p o n d e d t o an  Some e x a m p l e s  illustrated  review  Still  far  to  e n t i r e commands be s p e l l e d  i n a f i x e d format.  the  man-machine  neglected.  input  in  {especially  actual  when one o r two l e t t e r s would be unambiquous.  prolific  into  i n t e r a c t i v e programs which t h i s a u t h o r  required  necessary to look  going  Even  in  d e s i g n s were  were g i v e n a s t o  when  the  listed  each  was  2  appropriate.  A l s o , few r e f e r e n c e s were s u g g e s t e d  further details  (reinforcing  the notion  that  f o r seeking  this  area  had  a few  interface  been f o r g o t t e n i n t h e l i t e r a t u r e ) . The  goal  of  this thesis  was t o examine  designs e x p e r i m e n t a l l y , with t h e i n t e n t i o n conditions indicating lesser  under  which  each  any f o r m s which may  g o a l was t o a l s o s t u d y  variables  was  of determining  most  appropriate  bias the user's the e f f e c t s  upon p e r f o r m a n c e , a t t i t u d e ,  and  reviewed.  analyzed,  prompts,  with  the  protocol.  the  results  i s  first  program c o d e i s p r e s e n t e d  attention  paid  to  f o r a c c e p t i n g i n p u t from user  the  input  t h e u s e r , and input  errors  t o as " i d i o t - p r o o f i n g " ) .  the  described; then  A  o f some b e h a v i o u r a l  and s o l u t i o n  f o r d e t e c t i n g and h a n d l i n g  referred  Next,  particular  methods  the techniques (often  Then, t h e a c t u a l  and  behaviour.  I n t h e f o l l o w i n g pages, t h e r e l e v a n t l i t e r a t u r e briefly  the  actual  data  collection  the f o l l o w i n g chapter  relating  d e f a u l t s and command  to  user  and  presents  and  performance,  a b b r e v i a t i o n s , behaviour  analysis  are  discusses  u s e o f program over  time,  and  the p a r t i c i p a n t s ' s o l u t i o n p r o t o c o l s . Finally, directions chapter.  for  some  practical  research  are  implications suggested  in  and the  future  concluding  3  Chapter LITERATURE J3§c&3round In  _nd  is  articles,  protocols,  reference  and  upon  intensive computer  review,  user  the  work,  however,  involving  problem  solution  interface  l o o k i n g a t the l i t e r a t u r e  this  engineering  experimentation  man-machine  an  this  are a l l  which has  indirectly  direct related  i s mentioned. man-machine  communication  serious attention, i t  history. provided  background  computer  t e x t s on  Before  Although received  presented:  v a r i a b l e s , l i t e r a t u r e concerning  discussed. bearing  some o f t h e l i t e r a t u r e r e l e v a n t t o  previous  behavioural  REVI Eg  Motivation  t h i s chapter,  research  Two  I n h i s book S y s t e m s a  very  good  development programs  relationships  has  of  o f computer  i n t h e e a r l y 1960s  in  the l a t e  Machine I n t e r r e l a t i o n s h i p s , "  had  Psychology,  summary  1960s. was  has a 1  its  very  recently  interesting  Kenyon  B.  history,  equipment and  only  i n the  DeGreene from  1950s, t o  man-machine  inter-  C h a p t e r 10, e n t i t l e d  described  very  well  in  own i n t r o d u c t i o n : T h i s c h a p t e r f i r s t r e v i e w s h i s t o r y and t r e n d s t o w a r d greater computer s y s t e m a t i z a t i o n . A r e a s of s p a t i a l and t e m p o r a l i n t e r f a c e between man and computer receive special attention. We then consider important specialized areas of research and application, which i n c l u d e means o f d i r e c t , u s u a l l y dynamic man-computer communication by input and display devices in terms of given language structures, time-sharing, and "symbiotic" problem solving. Human f a c t o r s and managerial c o n s i d e r a t i o n s i n computer systems f o l l o w . The c h a p t e r ends w i t h an e v a l u a t i o n o f t h e c o n t i n u e d s o c i e t a l impact of c o m p u t e r s . 2  the  ^Manits  4  It  also  included  a  useful  section  d e s i g n and o p e r a t i o n a l e r r o r i n this  reference  ideas  presented  provides  is  by P e t e r G. W. K e e n  probably  t h e s i s . Keen program decide  cycle.  style  of  allowed would 'request  for  should  is  a  doctoral  University; i n fact, i t  be  the  user  like  to  computer  In h i s  simulation  n e a r l y complete freedom t o do  next,  instead  of  who  this  concept  display  solving,  a  had  rather  mentioned,  however,  of less  in  non-analytic  this  the implications  c o n s i d e r s t h e concept  the  input-simulate-display output-repeat* strong  e a s e o f use by i n e x p e r i e n c e d c o m p u t e r  problem test  interactive  that  by t h o s e  experimentally It  research  an  Hypothesizing  possibly  thesis.  a t Harvard  3  f o r many o f t h e  suggested  he  implications  this  Overall,  major cause o f t h i s r e s e a r c h .  which what  background  i n this  to  systems.  the single  traditional  and  related  computer  good  and p r a c t i c e d  More d i r e c t l y thesis  a  on t h e main s o u r c e s o f  author of  structured  t h e proper  author  computer  important  -  environment.  they  would  be  appropriate  f o r programs  frequently,  by  experienced  users.  to  suggestions.  this  very  cognitive  decided  Keen's  that  users  also  interfaces  For instance,  which  are  run  { S i n c e t h i s r e s e a r c h was  begun, i t has been l e a r n e d t h a t B o t k i n *  found  unstructured  e f f e c t i v e n e s s by b o t h  analytic The  was u s e d  and h e u r i s t i c Inventory  extensively British  model  decision  equal  was  and  such  an  makers).  Management Game, a r e s e a r c h  by B e n b a s a t s  Columbia,  with  that  others  another  at  the  influential  tool  used  quite  University cause  of  of this  5  thesis. game  Experience  demonstrated  For  instance,  to  be  to  in  and  unintelligible REPLACEMENT  Game has have  full;  any  '8TS,»" A corrected  Taylor , 7  the  computer  order and  to  describe to  Benbasat  Science.» for  p a r a m e t e r s , and headings  "L,  by  ENTER  and  results and  the  authors  relating  a  For  maker  details,  Benbasat  6  J,  the  J u n e , 1969  authors s t a t e d research  employ t h e  was  abilities  computer?" program  issue  i n the  a problem environment  outputs I,  and  interactive  to be  of both  They t h e n  a  answer  the  structured  in  the  manager  proceeded  which r e g u i r e d  table  with  of  introduction  the  the  to  user  continue  "SRULE=3, H R U L E = 6 , HRS=80, QZ=-201*" t o  M,  some  decison  Schroeder ,  OF  Management  a non-user-oriented  in  their  realtime  which  the  8  job-shop s i m u l a t i o n  or  were  LINE FROM POINT  t y p e s u c h non-mnemonic commands as "F0RSIM=2*" t o  simulating  were  CHARACTER,  Inventory  system  and  values  had  Dexter .  The  should  on-line, a  information  appeared  effectively  the  the  user. -  answered  these shortcomings,  e a r l y example o f  "How  of  the  reguests  d e c i s i o n making p e r f o r m a n c e .  motivation  guestion  were  REST OF  interesting  B e n b a s a t and  program  Management one  an  p a p e r s by  and  version  some  resulting  Another  that  new  computer  *NG»  default  "ILLEGAL  RE-ENTER  many o f  c h a r a c t e r i s t i c s of  consult  OR  the  neglected  some i n p u t  errors  message  of  * YES* and  reasonable  typing  NUMBER,  provided  the  including  no  system  version  i t unnecessarily  minimize r o u t i n e t y p i n g ;  ambiguous;  ERROR, OR  that  original  a i l responses -  typed  provided  to  with the  change  ambiguous  NEXT, KACT, PROM, L E F T , CUSH, L I P R ,  6  COMP, SETUP, IQ."  To  this  convincing  to  "effectively  effort  b o t h manager and  computer.  U s e r En£ineej_in_  Methods  One  of  Conference entitled  the was  "The  outcomes an  author,  of  excellent  this employ"  the  1973  article  Design o f ' I d i o t - P r o o f  A c c o r d i n g t o Wasserman, a program  just  not  a  the a b i l i t i e s  of  National  by A n t h o n y Interactive  i s said  was  Computer  Wasserman,  10  Programs."  t o be i d i o t - p r o o f i f  it i s d e s i g n e d t o a n t i c i p a t e any p o s s i b l e a c t i o n by i t s u s e r s and t o r e s p o n d i n s u c h a manner as to minimize the chances of program o r s y s t e m f a i l u r e while s h i e l d i n g the user from the e f f e c t s of such a failure. 1 1  Bearing  in  wrong w i l l  mind  Murphy's  Law  - anything that  go wrong - Wasserman s u g g e s t e d f i v e  can p o s s i b l y  go  principles:  1. P r o v i d e a p r o g r a m a c t i o n f o r e v e r y p o s s i b l e t y p e of input. 2. M i n i m i z e t h e n e e d f o r t h e u s e r t o l e a r n a b o u t t h e Computer S y s t e m . 3. P r o v i d e a l a r g e number o f e x p l i c i t d i a g n o s t i c s , a l o n g with e x t e n s i v e o n - l i n e user a s s i s t a n c e . 4. P r o v i d e program s h o r t - c u t s f o r k n o w l e d g e a b l e u s e r s . 5. A l l o w t h e u s e r t o e x p r e s s t h e same message i n more t h a n one way. These p r i n c i p l e s  were a l l d e s c r i b e d  which then c o n c l u d e d  i n d e t a i l i n the  article,  with the f o l l o w i n g statement:  There i s a s e r i o u s need f o r i m p r o v e d f a c i l i t i e s f o r the design of idiot-proof interactive programs, with a growing number of non-programmers using computers, development of comfortable man-machine interfaces w i l l o u t w e i g h many t r a d i t i o n a l c o n s i d e r ations i n the o v e r a l l creation of interactive programs. 1 2  As s t a t e d provide  earlier, a  working  the purpose o f t h i s example  p e r h a p s make some c o n t r i b u t i o n  t h e s i s was,  o f an i d i o t - p r o o f  i n fact,  to  program and t o  to the above-mentioned  need.  7  another  excellent  engineering, Joint  or  Computer  suggested  article  error  about  engineering)  Conference.  In  f o u r user e n g i n e e r i n g  idiot-proofing  (or  user  came o u t o f t h e 1971 F a l l  i t , Wilfred  J.  Hansen  1 3  principles:  Know t h e u s e r Minimize memorization S e l e c t i o n not entry Names n o t numbers Predictable behavior A c c e s s t o system i n f o r m a t i o n Optimize operations R a p i d e x e c u t i o n o f common o p e r a t i o n s Display i n e r t i a M u s c l e memory R e o r g a n i z e command parameters Engineer f o r e r r o r s Good e r r o r messages E n g i n e e r o u t t h e common e r r o r s Reversible actions Redundancy Data Since of  some  structure  integrity * 1  of these p r i n c i p l e s  are quite terse,  a few o f t h e more vague ones f o l l o w :  suggests than  that  users  'Predictable  t h a t t h e program h a v e a " p e r s o n a l i t y " display  suqqests  that  necessary suqqests  input  carrying  need  to  out desiqn  'Display  system  and  engineered  also  proqram.  provided  an  inertia'  so  'Muscle that  as  memory'  repetitive  part of the brain ( i n  t h e same way a s many o f t h e o p e r a t i o n s i n d r i v i n q article  suggests  s h o u l d change a s l i t t l e  o p e r a t i o n s c a n be d e l e q a t e d t o t h e l o w e r  The  names r a t h e r  a n d be c o n s i s t e n t i n i t s  requests; a  numbers'  behavior'  requirements;  the terminal display  in a  and  not  be a l l o w e d t o e n t e r a c t u a l  a s s o c i a t e d number c o d e s ;  output  'Names  descriptions  and t y p i n g ) .  e x c e l l e n t example o f a u s e r -  8  Previous  Experimentation  another  reason  behavioural  K.  D.  Eason  Oser."  In i t , o f 200  major  causes  of  were a n a l y z e d .  The  manager's  not  of  users  learn  computer  a new  o f "The  were: an  new  and  caused  expectations  (as t h e y  complex  the  possible  to  design  managers,  this  future;  role  he  forms for  time  systems.,  programs w o u l d have t o be in  Computer  more  of the  system the  desire  to  found  that  and  more  "unless i t i s  interaction  acceptable  manager  be  may  to  realize  Eason  that  systems  by  and  a  four  match  convenient  concluded  then  finally,  problems  l a c k of both  various  presented,  d e s c r i b e d , and,  some  instance,  Manager as a  management was was  For  inadeguate  operate  flexible  concept;  f o u r causes  needs,  to  relate  with computer  potential),  how  to  user d i s s a t i s f a c t i o n  advancement, changes i n user computer's  was  to t h e i r r e a c t i o n s to  a study  the n a t u r e  for  research  users  T h i s was  computer  Behavioural Variables  this  performed  1 5  survey  the  for  aspects  program f e a t u r e s .  with  very  to short  lived." * 1  a similar  study  "Human  Factors  Storage  and  government Reference  described  Evaluation  Retrieval computer  and  is  Control  of  System." system  a 1 7  called  in  an  article  Computer B a s e d The the  (CIRC) s y s t e m , and  authors  entitled  Information evaluated  Central Information found  that:  In r e v i e w i n g t h e r e s u l t s from the e v a l u a t i o n , there a p p e a r e d t o be t h r e e main f a c t o r s which i n f l u e n c e an individual's satisfaction with the CIRC system: (1) t r a i n i n g and l e v e l o f p r o f i c i e n c y , (2) amount o f i n f o r m a t i o n i n t h e s y s t e m t o meet t a s k r e g u i r e m e n t s , and (3) t h e i n d i v i d u a l ' s tolerance for irrelevant material. 1 8  a  9  The  third  to  mention  is  point i s particularly  no l e s s ;  unstructured decide  to l e t the user  he  needs  from  Data  Mock s t u d i e d  Information  c o n s i d e r i n g t h e impact technical  Base,  user  System  no  t h e user t o  Theodore  performance  models, w i t h  of s e v e r a l  information  profit  -  f o r p r o v i d i n g more  J.  "A L o n g i t u d i n a l S t u d y o f Some I n f o r m a t i o n  Accounting  systems  next.  article  Alternatives."  makers*  what  program i n t e r f a c e s which a l w a y s a l l o w  an  described  choose  t h i s may be a j u s t i f i c a t i o n  what he n e e d s  In  I t i s worthwhile  t h a t one o f t h e a d v a n t a g e s o f i n t e r a c t i v e  the p o t e n t i a l  more,  interesting.  Structure  with  various  variables  variables  p e r f o r m a n c e and l e a r n i n g  1 9  the objective of  behavioural  structure  Mock  upon  and  decision  patterns.  In summary, the f i r s t s e t o f experiments did demonstrate the feasibility of experimentally i n v e s t i g a t i n g expected differences i n information structures and t h e i m p a c t of certain behavioural variables... E x p e r i m e n t a l data which i m p l i e s the significance of behavioural factors increases validity of suggesting tailorized information systems f o r decison makers exhibiting different behavioural c h a r a c t e r i s t i c s . 2 0  Another "Experienced Decision  study, Managers*  System  by  Wynne  and  Simulation."  (MHDIS),  ran experiments using  the  (which,  reached  Decision  a  result  two main  of  Information  an i n t e r a c t i v e  their  conclusions;  research,  at  Man-Machine  were c o n c e r n e d  u n f o r t u n a t e l y , was n o t e x p l i c i t l y  article).As  Dicksen  Man-Machine  They  of  program  looked  2 1  Performance i n Experimental  effectiveness and  Dickson,  with t h e Systems  simulation  described i n Wynne  and  10  First, the d i f f e r e n t i a l performance of s u b j e c t s i s r e l a t e d not only t o p e r s o n a l i t y v a r i a b l e s but also t o i n f o r m a t i o n a c q u i s i t i o n and usaqe p a t t e r n s . . . It appears from work thus far t h a t p e r s o n a l i t y and c o g n i t i v e s t y l e impact the effectiveness of HMDIS throuqh the s t r a t e g y o f s y s t e m u s a g e by t h e human. S e c o n d , t h e e f f e c t i v e n e s s o f an 8MDIS must t h e n be a f u n c t i o n o f t h e e a s e (or d i f f i c u l t y ) w i t h which the i n t e r a c t i v e c o m p u t e r program e n a b l e s a d e c i s o n maker to implement his preferred information handling strateqy. 2 2  In a paper e n t i t l e d Information the  System  "The  Desiqn,"  Impact o f  Coqnitive  B e n b a s a t and  2 3  Styles  Taylor  on  suqqested  f o l l o w i n g three g e n e r a l i z a t i o n s : 1. A n a l y t i c decison-maker types tend to prefer decision aids and reporting systems which are q u a n t i t a t i v e i n nature with r e s u l t s supported with mathematical formulas. 2. H e u r i s t i c d e c i s i o n - m a k e r s need t o have more d a t a search c a p a b i l i t i e s prior to reachinq decisions. Since t h e y r e l y on f e e d b a c k and t r i a l and e r r o r , an i n f o r m a t i o n system c a p a b i l i t y which can hiqhliqht trends and provide period by period comparisons would be s u i t a b l e f o r them. The i n f o r m a t i o n system should qive them capabilities to t r y a l t e r n a t i v e s o l u t i o n s and a n a l y z e t h e p o s s i b l e outcomes before they decide on t h e i r f i n a l a p p r o a c h t o s o l v i n q t h e problem. 3. D e c i s i o n - m a k e r s a r e a l s o d i f f e r e n t in terms of their data gathering s t y l e s . The p r e c e p t i v e s would want a s y s t e m w h i c h has c a p a b i l i t i e s of organizing and aggregating data i n t o categories according to qiven parameters and exception reporting aids, whereas t h e r e c e p t i v e s or maximal d a t a u s e r s p r e f e r an i n f o r m a t i o n s y s t e m which has access to every piece of h i s t o r i c a l d a t a . * 2  Turning by  Taylor  and  now  t o toward the  Dunnette  2 5  area  contained  an  of r i s k  attitude, a  interesting  result:  Although r i s k - t a k i n g p r o p e n s i t y influenced heavily both the amount of information processed and d e c i s i o n l a t e n c y , i t does not a p p e a r t h a t h i g h r i s k takers attain faster decisions by processing each item of information more r a p i d l y . . . Bather, i t would a p p e a r that they are quite deliberate in  paper  11  a t t e m p t i n g t o e x t r a c t as much v a l u e as p o s s i b l e the s m a l l e r s e t of i n f o r m a t i o n t h e y examine. *  from  2  These  results  administered provided  were  decision  an  from  an  simulation;  determinants  of  In  another  bounded  Solution  dered style  this  decision  compared  that  thesis),  and  on  heuristics rational  protocols  2 9  was  used  In  trial  looked  analysis.  the  of  consi-  cognitive  relevant. styles  Barrett on  five  i t was  and p l a c e d  emphasis  area  of  and p l a c e d  search  to  on less  strategy,  a n a l y t i c s used  approach  said  formal  analysis,  and f e e l i n g s , whereas  models o f t h e s i t u a t i o n .  Interface  of  at t h i s time,  the  concepts  chapter,  i t s original  purpose  interface  at  low  a  briefly  more by a n a l y z i n g  F i n a l l y , regarding  i s reiterated a t many  provides  2 7  to learning,  and e r r o r , w h i l e  a n a l y t i c s developed e x p l i c i t  It  Taylor  decision  more by a c t i n g  feedback.  Jan-Machine  thesis  psychological  description  h e u r i s t i c s u s e d common s e n s e , i n t u i t i o n ,  The  on  (also  directly  analytic  a n a l y t i c s learned  emphasis  of t h i s  studies,  F o r example, w i t h r e g a r d  h e u r i s t i c s learned  feedback;  paper,  Barrett's  approaches  heuristic  dimensions.  manually  Protocols  the area of s o l u t i o n in  and  t h e same h y p o t h e s e s i n a  rationality,  e x a m p l e s c f more r i s k a t t i t u d e  In  the research  opportunity t o consider  computer e n v i r o n m e n t .  problem  individually  fairly  that  although t h i s  mentioned  throughout  was t o s t u d y  level,  with  thesis  the  this  t h e man-machine objective  of  12  reaching  some c o n c l u s i o n s  technigues  are  bias  behaviour.  their  research  the  most h e l p f u l f o r  and,  literature.  as  This  of  users,  appeared  and  of various  s y s t e m s , but  implications  which i n t e r a c t i v e programming  stated e a r l i e r ,  Many a r t i c l e s  philosophies  prototype  about  t o be was  least an  untouched i n  books e x i s t e d  have  likely  o r i g i n a l area  quite  i n d i v i d u a l s and  few  their  and  which  techniques  for  user  of the  suggested  described  experimentally  to  working  tested  performance  the and  behaviour. The and some  standard  Design of  situations.  of  Martin's  chapter  Dialogues  although  t o be  practical  chapter: for  Man-Computer  assistance,  sophisticated  more  t e x t s , Han-Machine C o m m u n i c a t i o n by  of  the  they  direct  were  assistance  t e x t , f o u n d by two,  by  this  d i d have one  seven e x p l i c i t l y  Martin, often  i n normal, author  a l p h a n u m e r i c computer t e r m i n a l s  with  general  to  display  TV-like  or  day-to-day  particularly  considered  29  provided  3 0  too  Meadow  be  the  relevant methods  screens:  I n t a c k l i n g an a p p l i c a t i o n , t h e s y s t e m s a n a l y s t must make some b a s i c d e c i s i o n s a b o u t t h e s t r u c t u r e o f t h e screen conversation...Twenty-three techniques of c o n v e r s a t i o n a r e i l l u s t r a t e d below. They have been g i v e n t h e names: 1. Simple query 2. Mnemonic t e c h n i q u e s 3. English-language technigues 4. Programming-like statements 5. A c t i o n code systems 6. M u l t i p l e a c t i o n code s y s t e m s 7. B u i l d i n g up a r e c o r d 8. Scroll techniques 9. Simple i n s t r u c t i o n t o o p e r a t o r 10. M u l t i p l e i n s t r u c t i o n t o o p e r a t o r 11. Menu s e l e c t i o n 12. M u l t i s c r e e n menu 13. T e l e p h o n e d i r e c t o r y t e c h n i q u e 14. M u l t i p a r t menu  13  15. 16. 17. 18. 19. 20. 21. 22. 23. Martin very  M u l t i a n s w e r menu Use o f d i s p l a y e d f o r m a t s Variable-length multiple entry Multiple-format statements Form f i l l i n g Overwriting Panel m o d i f i c a t i o n techniques T e x t - e d i t t i n q techniques Hybrid d i a l o g u e 3 1  then good  indicated  proceeded detail  when  finds himself complex  to  but,  d e s c r i b e each o f these  unfortunately,  e a c h was a p p r o p r i a t e .  barraged  methods  of  with  designinq  philosophy  of  the  remainder  upon v a r i o u s u s e r  types  really  very  simple  to  very  a t e r m i n a l i n t e r f a c e , and c a n  of  for his situation. this  man-machine i n t e r f a c e  the e f f e c t s o f a s m a l l  seldom  So t h e s y s t e m s a n a l y s t  twenty-three  o n l y q u e s s w h i c h i s most a p p r o p r i a t e Throughout  too  methods i n  thesis,  a  personal  d e s i g n i s p r e s e n t e d , and  s e t o f man-machine i n t e r f a c e are investigated.  techniques  14  Chapter  Three  THE COMPOTES Program  Description  The  primary  interactive provided the  tool  computer  for this game.„  listing  game  a small  programming interface  was and  Part  British including  collect  timing  character The  routines,  four.  version),  two  which i n t u r n  subroutines.  one  actual  amount o f user  University  subprogram routines,  both  and  a  described i n  version  version  of  library$  was  highly  by l o o p i n g was  To  rather  facilitate  had t o be h i q h l y  main proqram* which  subroutines  game  t o l e a d t h e s i m u l a t i o n by  he l i k e d .  t h e prcqram  called  of  I t was a l s o  the simulation  and the o t h e r  was made up o f a b r i e f "control"  aspects  desired  the  versions,  expected t h e user  concept,  w i l l be  data.  control  through  commands i n any o r d e r  proqram of  file  Briefly,  and l e d t h e user  version  Centre  distinct  a s e t of questions;  enterinq  one  from  two  and  game  i n FORTRAN (a  The  the  subroutines  game  unstructured  achieve  reguired  routine.  structured  The  written  a l l the  comparison  i n chapter  through  to  Computing  had  simple  next.  was c o m p l e t e l y  necessary  Columbia  a  o f t h e program; a s i g n i f i c a n t  n e c e s s a r y t o u s e a few  dual  the  o f t h e code a p p e a r s i n A p p e n d i x A ) .  only  detail  of  was  the user engineering  computer program a r e d e s c r i b e d computer  research  Details  i n t h e next chapter;  The  is  PROGRAM  {to  this  modular. called  qet the appropriate  a number o f t h e  remaininq  ten  15  One  of  the  ten  subroutines,  program s t a r t u p t o r e a d matrix).  Another  simulation  o f another  the  terminal input. of  a l l output  i n the p r o f i t function  subroutine,  subroutines,  period  GETLIM,  messages  needed  them  one  recompiled  whenever t h e u s e r  (a  and  at the  30  performed  ( i . e . another GETLIT,  gathering  more  SIMUL,  One s u b r o u t i n e ,  in  READPF, Was c a l l e d  by  the actual  trial).  Three  GETNUM,  a  throughout  program;  place, only  collection  one r o u t i n e needed  interface  was  of  handled a l l  OUTMES, was j u s t the  70  refined.  by  t o be Three  r o u t i n e s , HISTRY, SORTH, and SGRAPH, d i s p l a y e d t h e t h r e e  available  reports. ,  Finally,  p e r f o r m e d a l l end-of-game In  the  subroutine  simply  prescribed version,  structured  t h e program w a i t e d  programming  versions  the  lay  of  for a  the s p e c i f i e d  effort  in  the  reguired  two  the  routine,  game,  appropriate  as a c o n t i n u o u s  decoded i t , and c a l l e d extra  remaining  ZEND,  cleanup. version  called  order,  the  (quite  subroutines  loop.  in  a  I n the u n s t r u c t u r e d  command  from  routine. in  the c o n t r o l  the  user,  Hence, t h e o n l y  order  t o p r o v i d e two  straightforward)  control  routines. User E n g i n e e r i n g The engineering a  personal  reader and  will  Methods  remainder aspects one  of  this  chapter  o f t h e program.  developed  through  Although years  n o t e t h a t t h e methods s a t i s f y  suggestions  describes  the  the approach  user i s  of experience, t h e  many o f t h e c r i t e r i a  o f i a s s e r m a n and Hansen p r e s e n t e d  in  chapter  16  two. In from  designing  the user,  need  for  the actual  input of responses  e a s e o f u s e was g i v e n t o p p r i o r i t y .  memorization  by  users  was  version,  a  list  descriptions  of  -  was  available  prompts  were  them input  of  a l l  illustrated  by t h e f o l l o w i n g example:  c a n be s e e n ,  response value  range  was  value  first  level  anytime.  of  the  indicated  nothing  i n parentheses,  i n brackets,  else  In  same  then then  the default  which t h e c o m p u t e r would assume t h e u s e r  entered  (in t h i s case,  for  routine typing.  memorization,  were a v a i l a b l e The This  the  respond  handled  wanted  a l l user  errors  This  Input.  reminded  responses,  to  e l i m i n a t e t h e need  processing  software  t o by t h e s i m p l e  Please  the  user  could  message o r i n t e r r u p t .  activity  itself.  find  i t  In t h i s  statement  He-enter.  was f o l l o w e d by a r e p e a t o f t h e o r i g i n a l  course  order  were i n t e r c e p t e d b y t h e program  before the system  were r e s p o n d e d  Incorrect  i f he  which he had  of a l l previous  a l l input  w i t h some i l l e g i b l e  game, e r r o r s  default  v a l u e was t h e  the p r i c e  to f u r t h e r  histories  also  ("idiot-proofing") and  format,  t o t h e user a t anytime.  program  way,  Finally,  complete  both  the allowed  c h o s e n i n t h e p r e v i o u s p e r i o d ) , and was i n c l u d e d i n reduce  the  (1-30) [ 1 0 ] :  t h e g u e s t i o n was a s k e d ,  was i n d i c a t e d  In  a l l commands - and b r i e f  versions,  Enter desired price  F i r s t , the  minimized.  unstructured  As  and commands  of  and t h e c u r r e n t d e f a u l t  the  prompt,  guestion,  value.  the  which o f allowed  17  The  program r e a d  characters character that  (up  to  a l l input 60  of  by c h a r a c t e r * up  substring  was  as a  them). to t h e  considered  were more c h a r a c t e r s f o l l o w i n g would be u s e d  as t h e r e s p o n s e  experienced  users  to  frustration.  I f the  original  response,  then  commands and letters)  only  - thereby  original  blank the  next  the  substring  (or  to  I f there  comma),  they  save  wanted  an  alphabetic  used  (since a l l  with  different  c h a r a c t e r was  game b e g i n  a  and  and  with  time  then  the  and  I f the program  number; a d m i t t e d l y , t h i s  i n e x p e n s i v e and  the  user  well  was  worthwhile  In  o f a computer c r a s h or o t h e r  program  had  c o m p u t e r and  p r o t e c t e d not  from  the event  the  n e e d e d t o be  h i m s e l f , but  a special  file.  run  major  As  the  I f anything caused  parameter  a t e x a c t l y where he  allowed  left  only  from  the environment i n g e n e r a l .  a save/restart facility.  wrote out a s i m p l e  program  comma,  user.  Finally,  halt,  or  scanned,  prompt(s) - a l l o w i n g  ahead, prompt  was  response.  blank  to the  alphanumeric  permitting unlimited abbreviation.  awkward i n F0BT8AN, but s t i l l the  t o be  of  string  prompt wanted a n u m e r i c r e s p o n s e ,  converted  for  first  type  in this  The  the  the f i r s t  responses  string  off  the -  the  program r a n , i t the  user as  problem,  program  to  to r e s t a r t  the  i f  nothing  had  f e a t u r e s d i d not  come  happened. It without  is  quite  a cost.  processing  apparent  that these  However, t h e r e i s no  r o u t i n e s c o u l d not  reason  why  have b e e n d e s i g n e d  the as a  input package  18  t o be  linked  with  all  other  interactive capabilities programming  costs  written  more a p p r o p r i a t e  to  in a  increase  efficiency amount likely  of be  program, could  be  i n the  an  their  only while  approach  future.  language  issue.  the  the  part of savings  guite substantial.  needing  This  is  Indeed, i n  the  total cost  in  user's  save  routines could  (probably  a program s p e n d s p r o c e s s i n g  a small  programs  which would l i k e l y  Also,  efficiency.  is a critical time  application  not most user of  t i m e and  be  assembler), to  say  that  cases,  the  input running  would any  frustration  19  Chapter  Four  DATA COLLECTION Pre-testing The  and C l a s s i f i c a t i o n  actual  obtaining  data c o l l e c t i o n  participants,  data  There virtually  five  cash  quite  fifty  a l l of  whom  (some  were  As  diverse:  research  automatically  some  in  students,  desired,  were  the  and  programmes,  been  others  near  from  computer)  the  a l l of  some  one o f were  others  sere  computers,  while  were  engineering,  them  participants  undergraduates,  one;  experiment,  o f winning  some had e x t e n s i v e e x p e r i e n c e w i t h  o t h e r s had n e v e r  (by  played.  by t h e p o s s i b i l i t y was  involved  them, a r r a n g i n g f o r them  participants  lured  prizes).  graduates;  and  on them a s t h e y  were  volunteers  for this  pre-testing  t o p l a y t h e computer game, collecting  METHODOLOGY  from  and s t i l l  commerce  others  from  arts. , The  experience  experiment part  (necessary  questionnaire  computers.  As  asked  their  people  a  was  a  for testing  of the p r e - t e s t i n g  short  used  difference  on-line  result  experienced computer thesis  computer or  their  history  of t h i s  faculty,  of  However,  that the experience  number  they  (novice) bear  effect  contact  q u e s t i o n n a i r e , which  terminals,  inexperienced  systems.  to  this  t h e main h y p o t h e s e s ) .  of  c o m p u t e r s v i a punched c a r d s , a n d number  used  one  As  f o r t h e game, p a r t i c i p a n t s c o m p l e t e d  about  year,  crucial  in  times  were  simply had  t h e y had  c l a s s i f i e d as  users mind  with  they  o f times  a  of  on-line  throuqhout  may be somewhat  this  confounded:  20  experienced  computer  users  mathematical t r a i n i n g Next, t h e and  paper  score  on  (see  this  (15 on  i t  is  a  18).  to the  advanced  of  of  the  terms).  For  d i v i d e d a t i t s mean  say  analytics rather  The  cognitive styles  this i s a rather to  pencil  whether  these  g r o u p was  appropriate  timed  participants.  analytic  definitions  Since  high  more  a  3 2  indication  research, the  more  and  high  division  that this  than  pure  research  heuristics  a n a l y t i c s . ,. Finally,  risk  the  p a r t i c i p a n t s completed  questionnaire.  provided  split  All  Their  3 3  a measure o f t h e i r a t i t s mean  r i s k - t a k e r s or  of  for  this  compares low  was  administered  provided  two  of  had  novices.  d i s p l a y e d h e u r i s t i c or  a s c a l e of  value,  and  was  test  chapter  purposes  also  Group Embedded F i g u r e s T e s t ,  test,  participants  than  often  ten  j u s t over  30  pre-testing computer  risk  on  the  attitude;  on a s c a l e o f  and  above p r e - t e s t i n g was  the  group  classified  over  a three  day  p e r i o d , and  minutes to complete. s e s s i o n , he  game  during  administered  As  each  each  s e l e c t e d a convenient the  f o l l o w i n g week.  as  instructions  e x p l a i n the  nature  directions  for  of the  using  features.  left  a  brief  These i n s t r u c t i o n s d i d  c o m p u t e r game; r a t h e r , t h e y  the  There  session  A l s o as they  of  B).  computer was  groups  time to play  p r e - t e s t i n g s e s s i o n , p a r t i c i p a n t s were g i v e n (see Appendix  to  subject  the  program  questionnaire  again,  60)  wallach  risk-averters.  of the  about  (30  score  t h e Kogan and  terminals  a separate  set of  and  took the the left set not  provided special  instructions  21  for  e a c h o f t h e two v e r s i o n s  had  been randomly  Adfleistering The is  sample  The three  o f p l a y i n g and a d m i n i s t e r i n g  i n this section.  appear  limit  of  automatically. exceeding  course 30  game  d i s c u s s i o n , the  Appendix  t h e computer game  o f one week.  minutes,  About o n e - h a l f  the time  in  the  C  may  be  groups  of  o f any vague p o i n t s .  p a r t i c i p a n t s played the  Throughout t h i s  which  forclarification  over  time  t h e Game  interactions  consulted  the subjects  assigned.,  a c t u a l process  described  o f t h e game t o which  after  in  The game had a maximum which  i t  of the subjects  terminated  finished  before  limit.  When p l a y i n g t h e game, e a c h p a r t i c i p a n t was i n s t r u c t e d a t the  beginning  and  that  preduct he  that  he  was  he was t h e manager o f a o n e - p r o d u c t expected  t o manufacture  was  t o m a x i m i z e h i s company's p r o f i t .  combinations resulting If  and  a subject  simulating  found  "rewarded"  and  beeped  until  next  <price,  period  t h e maximum p r o f i t him by i n f o r m i n g  congratulated  quantity>  to  get the  w i t h i n 30  minutes,  screen  him w i t h filled  the player, while  time.  This  a l l manner o f  up w i t h  only  served  to  bell  Actually, the  announced an a p o l o g y t o t h o s e net  dollar  the terminal  s t e p p e d by t h e game a d m i n i s t r a t o r .  same b e l l s and w h i s t l e s of  different  the  and w h i s t l e s : t h e t e r m i n a l  signs  out  setting  Hence, p l a y i n g t h e  profit.  game  bells  s e e k t h e optimum q u a n t i t y o f  and t h e p r i c e t o s e l l i t f o r ; t h a t i s ,  game i n v o l v e d r e p e a t e d l y  the  to  company  attract  who  ran  t h e game  22  administrator*s please  three  decisions  second by  was  graph  step  unstructured  guantity,  by  be  participants  needed to  The  with  profit  of  predefined  or look  none  startup.  optimum Thus,  led  through  order.  I n the  However, n o v i c e  the  was  f o r each  reports). had any  In addition,  had no p r o b l e m s subjects  f r o m t h e game a d m i n i s t r a t o r  function  as  (to s e t p r i c e o r  game v e r s i o n .  the unstructured  version,  t o proceed  at  computer e x p e r i e n c e  version.  profit  f o r each  of the s u b j e c t s  in  often order  version.  which t h e u s e r s were a t t e m p t i n g t o D.  The b a s i c p r o f i t  same f o r e v e r y o n e ; however, t h e < p r i c e , the  and  had more f r e e d o m  that  maximize a p p e a r s i n Appendix the  a  the structured  assistance  3-dimensional  In the structured  any o f s i x commands  mentioned  get s t a r t e d  in  the user  with previous  verbal  was a  t a k e n by t h e hand,  step,  the unstructured  The  thus f a r .  another p e r i o d ,  i n using  25 p e r i o d s .  game i n t e r a c t i o n s i n Appendix C, one  entering  simulate  should  difficulty  by  version,  wished  with  and  history of  ( i . e . one d i g i t )  o f t h e two game v e r s i o n s .  game,  It  amaze  was a s i m p l e  the t h i r d  p a i r simulated  u s e r was e s s e n t i a l l y  he  both  e x c e p t t h a t i t was o r d e r e d  Profit/10  T h e r e a r e two sample  the  to  f o r the previous  Finally,  displayed  guantity>  f o r each  The f i r s t  and p r o f i t s  profit.  which  <price,  reports.  also a history report,  decreasing  the  appeared  t h e game p r o c e e d e d , t h e p a r t i c i p a n t s had a c c e s s t o any  a l l of  their  but  the participants.  As or  attention,  generated participant,  f u n c t i o n was  guantity>  randomly the  position  at  optimum  program profit  23  occured  a t a randomly  quantity shape,  set price  between 15 and 55. but  only  moved,  difficult  between  70  different  and  f o r each  possibility Data  s i n c e each person  steps should  f o r some  were s c a l e d by a n o t h e r  subjects,  These  steps  participant  a  and  could  search  also, the profit constant  essentially therefore  game values  to  values  made t h e game  eliminated  any  of c o l l u s i o n .  the  participants  automatically  collected  of  features.  program  recorded chosen  data  played  about t h e i r  For  each  a b o u t : t h e amount o f t i m e price,  quantity,  the  and  game,  period, taken  resulting  input  typeahead  of  option;  abbreviation;  utilization  listing  aspects.  A  participant  a p p e a r s i n A p p e n d i x E.  A d d i t i o n a l data attitude  as  he  of  of  a  was c o l l e c t e d  played.  After  code 2 i n t h e sample d a t a  flew of a c t i v i t y i n questionnaire program  to  the  get  usability,  game  number  report;  and  file  the of  errors  each  other  f o r one  participant's  p e r i o d s 5, 10, 15, ...  (note  i n A p p e n d i x E) , t h e n o r m a l  was  the user's  interrupted confidence  and e n j o y m e n t  i n t e r a c t i o n s i n Appendix C ) .  i t ;  number o f  output  about  file  was  amount o f u s e made o f  each  sample  use  information  profit;  made;  program and  t o complete  number o f d e f a u l t s t a k e n ;  extent  the  performance  commands e x e c u t e d ;  the  at  Collection As  line  and  n o t have made t h e  randomly generated  99.  25,  S i n c e t h e f u n c t i o n d i d n o t change  and  anywhere he w i s h e d , t h e s e more  between 5 and  level  by  level, (see  a  brief  rating of  the  sample  24  The  data  solution  collected  p r o t o c o l f o r each  e a c h s u b j e c t moved t h r o u g h of  the  <price, F)  optimum  profit.  guantity>  and  then  also  participant,  a  machine-readable  indicating  the two-dimensional  I t was  found  p a i r s i n order  connecting  contained  the  that  space by  of simulation dots,  one  could detect  or  search  which w i l l  be  In the the  fifty  discussed  or other  participants  are  and  whether error,  w e l l - d e f i n e d a l g o r i t h m , a l l of  more c o m p l e t e l y  remainder o f t h i s  the  (as i n A p p e n d i x  a random s e a r c h , a s t r u c t u r e d t r i a l  binary  how  in search  plotting  u s e r s employed a  exactly  thesis,  presented  i n chapter s i x .  the output and  results  discussed.  for  25  Chapter THE  Jive  HYPOTHESES  Introduction Before briefly  the  results  are  i n t r o d u c e s t h e hypotheses  Although  the  possibilities were  final  data  from  f o r analysis,  t h e major m o t i v a t i o n s  the  to  theoretical  verify  hypotheses  and  simply  to  this  chapter  being  provides  tested. numerous  t h e 26 h y p o t h e s e s o f t h i s  chapter  f o r t h i s r e s e a r c h and w i l l  receive  t h e remainder o f t h i s some  of  the  b a s i s ; however, o t h e r  the findings of others,  will  connection  were  game  i s exploratory research,  have no s t r o n g attempt  which  this  most o f t h e a t t e n t i o n t h r o u g h o u t Since t h i s  analyzed,  be s t a t e d , w i t h  previous  research  thesis.  hypotheses  h y p o t h e s e s do  In t h i s detailed  chapter, analysis  to f o l l o w i n the next  chapter. In  nearly  independent (structured  risk  or  anc  Bisk,  each  hypotheses, at  unstructured),  cognitive style attitude  simplicity,  the  variables,  experienced), and  a l l of  these  two  there  levels:  experience (low a n a l y t i c  (risk-averter  variables w i l l  or  are game  level  four  version  (novice  or h i g h  analytic) ,  risk-taker).  be c a l l e d Mode,  or  Exp,  For Style,  respectively.  F e r f o r m a n c e and Game V e r s i o n The user  performance  hypothesis to  first  category and  o f hypotheses  the  two  i s rather special,  differentiate  game  i s related versions.  and i s a s s i g n e d  i t from t h e r e s t .  to general The  t h e number  first zero  26  S l £ 2 _ k § _ i S 2. ~  Everyone w i l l  H y p o t h e s i s J. -  Mode,  affect  the average  t i n e spent  Hypothesis 2 affect  Exp,  enjoy  playing  Style,  playing  and  each  Mode,  Exp,  Style,  whether t h e s u b j e c t s  finish  within  Exp,  Style,  t h e game.  Risk  will a l l  period. and  Risk  t h e 30  will a l l  minute  time  limit. Hypothesis 3 affect  Mode,  the average  confidence l e v e l  SXEothesis 4 -  Unstructured  faster,  finish  structured  more  version  more o f t e n ,  error  Special The special  players  will  confident  be  than  8 -  will  will  be  than  novices.  be  faster,  faster,  finish  t h a n low a n a l y t i c s .  Risk-takers  and be more c o n f i d e n t  rate  more  players  High a n a l y t i c s  and be more c o n f i d e n t  Hypothesis  be  and be more c o n f i d e n t  Hypothesis 7 often,  and  will a l l  of the participants.  game v e r s i o n  Experienced  Hypothesis 6 more o f t e n ,  Risk  players.  Hypothesis 5 finish  often,  and  will  be f a s t e r , f i n i s h  more  than r i s k - a v e r t e r s .  The Mode/Exp i n t e r a c t i o n w i l l  affect  the  of the p a r t i c i p a n t s .  Program  features  next c a t e g o r y o f hypotheses i s r e l a t e d program  features,  such  as  t o t h e use o f  default  values  and  abbreviations. Hypothesis 9 (at  The d e f a u l t  v a l u e s f o r p r i c e and  t h e b e g i n n i n g o f t h e game) w i l l H y p o t h e s i s _0 -  Setting  influence  the  most  default  guantity  users.  response  for  27  questions •yes  (about t h e u s e r ' s d e s i r e t o s e e v a r i o u s r e p o r t s )  rather  1  actual  than  'no' s i l l  not i n f l u e n c e the p a r t i c i p a n t ' s  response.  Hypothesis H  -  Exp, S t y l e , and  whether u s e r s a c c e p t d e f a u l t Hypothesis affect  to  J2 -  Hypothesis factor  13 -  affecting  values  (when  Exp,  Style,  Mode,  t h e e x t e n t t o which  Risk  will  a l l affect  appropriate). and  Risk w i l l a l l  u s e r s a b b r e v i a t e commands.  The l e n g t h o f commands w i l l  be t h e  main  t h e e x t e n t t o w h i c h t h e y a r e a b b r e v i a t e d by  users. Comparisons The  over  third  comparisons  Time category  over  of  time,  and  hypotheses indicates  i s  with  expected  regard  differences  between b e h a v i o u r d u r i n g t h e b e g i n n i n g o f t h e game a n d the remainder  decrease  with  spent  p l a y i n g each  period  time. User  confidence w i l l  fllfifithesis  16  User  ratings of  -  program w i l l  improve  17 -  The  game p l a y e r s w i l l H y p o t h e s i s 18  with  time  15 -  Hypothesis tured  Average  Hypothesis  computer  during  o f t h e game.  H y j L o t h e s i s 14 will  to  -  with  i n c r e a s e with  the  usability  of  time. the  time.  e x t e n t o f a b b r e v i a t i o n by u n s t r u c -  i n c r e a s e with  Usage o f H i s t o r y  time. reports  will  decrease  time. Hypothesis  decrease  with  19 -  Usage  of  Ordered  History  reports  sill  time.  fiy.J22th.esis 20  -  Usage o f Graphs w i l l  i n c r e a s e with  time.  28  Regort  Usage and  These l a s t reports  or  Solution five  solution  H y p o t h e s i s 21 use  cf  History  of Ordered  cf  protocol -  either  the  usage  of  dimensions. and  Style s i l l  a l l affect  the  22  -  Mode, Exp,  and  Style w i l l a l l affect  the  23  -  and  Style w i l l  the  24  -  reports. Mode, Exp,  a l l affect  Graphs.  Hypothesis  Exp,  whether u s e r s d i s p l a y e d problem  (with  the  Hypothesis amount (with  concern  Mode, Exp,  History  Hypothesis use  hypotheses  reports.  Hypothesis use  Protocols  of the  The chapter  Exp,  two  will  approach t o  a l l affect  solving  the  Style).  S t y l e , and  displayed  e m p h a s i s a g a i n on  Risk  Risk w i l l  i n the  search  a l l affect f o r the  the  optimum  Style) .  hypotheses are  explained  i n more  detail  in  of a l l these hypotheses  are  chapter,  the  six.  The  results  presented results  25 -  and  a structured  e m p h a s i s on  dispersion  last  Style,  and  of  analyzed  the  tests  in the  appears i n Appendix  G.  next  A summary o f  29  C h a p t e r -Six ANALYSIS  OF  RESULTS  DaJS P r e p a r a t i o n Before had  to  output into  be  converted  files  copied  each,  derive directly  were  extractions still  to  a  from  new  averages  mentioned  game v e r s i o n  (user  and r i s k  taker).  for  Again,  referred  Social  simply  o t h e r s were summations playing  the  game),  others  were  10 p e r i o d s ) , and ( f o r example, t h e  nearly  attitude  a l l  four two-level  of  variables:  experience  style  (1=low  (1=risk-averter, these  and B i s k ,  variables  the  level  analytic, 2=riskwill  be  respectively.  Analysis  a l l of  Sciences  with d e t e r m i n i n g affected  v a r i a b l e s were  t o 100  cognitive  simplicity,  Three b a s i c types o f analysis,  compressed lines.  2=unstructured),  t o a s Mode, Exp, S t y l e ,  Statistical  Thus t h e  50 v e r y l o n g  time  five,  following  2=experienced),  2=high a n a l y t i c ) ,  i t  p e r 100 p e r i o d s ) .  chapter  the  form.  confidence),  normalized  (1=structured,  (1=novice,  some  analyzed,  were  per p e r i o d f o r the f i r s t  in  involve  with  the o r i g i n a l f i l e ,  were r e s u l t s  hypotheses  one f i l e file,  number c f g r a p h s r e q u e s t e d As  more c o n v e n i e n t  ( f o r example, t o t a l  (minutes  others  yielding  this  o r i g i n a l data  others  c o u l d be s t a t i s t i c a l l y  f o r e a c h o f t h e 50 p a r t i c i p a n t s  one l i n e To  of  t h e game d a t a  a  were  Performed  them u s i n g t h e S t a t i s t i c a l  (SPSS). * 3  which  given  analysis  Since  factors  game  outcome  (dependent  this  Package f o r t h e  most h y p o t h e s e s (independent  in  were  concerned  variables) variable),  most an  30  analysis  of  variance  hypotheses, either and  using  a three-way  four-way  general  the  was  employed  AUOVA r o u t i n e  i n SPSS.  assumed t o be  the dependent v a r i a b l e , variables,  interaction  e f f e c t s , and  and  main e f f e c t s hypotheses  values  were u s e d  perform  with the  remaining  paired  test,  were  In  the  reproduced  o f two  tables  interactions  w i t h how  two  groups  In these  two  used  to  t-tests SPSS  was  display  (expressed as  the  T-  used  the  two  different).  The  to Comparisons over  Time)  over  a l l  subjects;  these hypotheses.  t o perform  the t e s t ;  Again, however,  specified*  follow,  standard  of  cases,  The  groups,  be  variables  o b s e r v a t i o n s were  their  to  to t e s t  was  analyses  in  except  compared, so o n e - t a i l e d  ( a l l related  were employed  paired  same,  The  effects.  variable.  assumed  cN  terra.  using a pooled v a r i a n c e (since  the comparison  time  variance  concerned  t o be  t h e SPSS T-TEST r o u t i n e this  the  hypothesized r e l a t i o n s h i p s .  hypotheses  t-tests  was  cases c l a s s i f i e d into  population variances  involved  were  were  to t e s t the  TEST r o u t i n e ,  The  effects,  the e r r o r  six interaction  d i f f e r e d on an i n d i v i d u a l  mean  used.  t h e o v e r a l l mean, xN  e was  with four  subjects  three-way  was  bN were t h e main  classification  to  I n most c a s e s ,  z e r o ) was  a was  model f o r t h e f o u r - w a y  Other  these  *• b2x2 + b3x3 * d x 1 x 2 • c 2 x 1 x 3 + c 3 x 2 x 3 • e  were t h e i n d e p e n d e n t the  test  or four-way c l a s s i f i c a t i o n (with  interactions  a • b1x1  where y was  two  to  model f o r t h e t h r e e - w a y c l a s s i f i c a t i o n  y =  were  (ANOVA)  the  formats. main  SPSS The  effects  results  are  analysis  of  and  "variable/variable").  the  2-way  31  Hypotheses about The playing the  Performance  r e s u l t s concerning t h e game - were  entire  h y p o t h e s i s 0 - Everyone w i l l  especially  encouraging.  game, t h e mean e n j o y m e n t  enjoy  Throughout  l e v e l f o r a l l p l a y e r s was  7.0 on a s c a l e o f 1 t o 9, where  labored  game  q u e s t i o n n a i r e i n appendix C ) .  (see t h e  sample a t t i t u d e  T h i s was i m p o r t a n t results: the  out  subjects  game o v e r  probably  because  i t added  d i d not j u s t  with; they  go t h r o u g h  significance  As c a n be s e e n  variables level  was  to  the  the  game  t h e motions t o g e t  t h e game  and  quite  An a n a l y s i s o f v a r i a n c e was c a r r i e d  t o s e e whether any p a r t i c u l a r  independent  9=enjoying  credence  a c t u a l l y enjoyed  "played t o win,"  more t h a n o t h e r s . ,  and  user types enjoyed i n table  significant;  t h e game  1, none o f t h e f o u r  indeed,  the  overall  was o n l y 0,71, ^  <  SOURCE VAR.  S.SQ.  DF. ,  Mode Exp Style Bisk  0.64 0.04 0.35 0.47  !  Mode/Exp Mode/Style Mode/Bisk Exp/Style Exp/Risk Style/Risk  0.40 0.45 0.06 2,08 9.08 0.24  1 . 1 1 1 1  Explained Residual Total  13.82 76. 18 90.00  1 1 1  1  10 39 49  M. SQ.  F  SIGNXF.  0.64 0.04 0.35 0.47  0.33 0.02 0. 18 0.24  0.57 0.89 0.67 0.63  0.40 0.45 0.06 2.08 9.08 0.24  0.20 0.23 0.03 1.06 4.64 0. 12  0.65 0.64 0. 87 0.31 0.04** 0.73  1 .38 1.95 1.84  0.71  0.71  1  J  Table The  1.  ANOVA - Game Enjoyment  analysis o f hypothesis  1 - Mode, Exp, S t y l e , a n d R i s k  32  will is  a l l affect  presented  style  i n table  impacted  experience minutes  t h e average 2.  speed.  p l a y i n g each  i n v e s t i g a t e d i n more d e t a i l  SOURCE VAR.  Mode/Exp Bode/Style Mode/Bisk Exp/Style Exp/Risk Style/Risk  168.27 572.40 137. 12 225.70 2152.16 348.61  1 1 1 1 1  10124.80 30601.30 40726. 10  10 39 49  Table 2  1.  112.68 2321.79 255.99 3154.83  -  Mode,  Exp,  finish  results  indicated  Cognitive style  2.  ANOVA -  level  Style,  the  number  level was  M.SQ. ,  F  SIGNIF. 0.71 0.09** 0.57 0.0 5**  168.27 572.40 137.12 225.70 2152 .16 348.61  0.21 0.73 0.18 0.29 2 .74 0.44  0.65 0.40 0.68 0.60 0.11* 0.51  1012.48 784.65 831.14  1.29  0.27  Minutes/Period  a l l affect  were  also  completely (see  hypothesis whether t h e  limit.  was h i g h l y s i g n i f i c a n t ,  This suggests  be  0.14 2.96 0.33 4. 02  attitude  of the players  will  112.68 2321.79 255.99 3154.83  and R i s k w i l l  almost  of  5 and 7 ) .  Again,  t h a t game v e r s i o n had no e f f e c t  and r i s k  termination  details).  1  a t t i t u d e and  ( t h e s e two f a c t o r s  w i t h i n t h e 30 m i n u t e t i m e  while experience  experience  1  risk  period cognitive  3 d i s p l a y s the a n a l y s i s of variance f o r  subjects  game  1 1  nor  upon  i n hypotheses  DF.  S.SQ.  Table  effect  period  Mode Exp Style Risk  Explained Residual Total  p l a y i n g each  However,  had a s i g n i f i c a n t  spent  spent  N e i t h e r game v e r s i o n  playing  both  time  the  whatsoever.  insignificant, indicating  determined  hypothesis  that researchers should  5 be  that  by t h e  for  more  extremely  33  wary o f t h i s f a c t o r line  computer  when c a r r y i n g  out  using  on-  terminals.  I  ______  SGOBCE VAB.  _  S.SQ.  : -J  DF.  SIGNIF.  1. SQ.  Mode Exp Style Bisk  0.00 3.28 0.29 0.21  0.00 3.28 0.29 0.21  0.00 16.75 1.46 1.08  Mode/Exp Mode/Style Mode/Bisk Exp/Style Exp/Bisk Style/Bisk  0.05 0.08 0.06 0. 33 0.14 0.01  0.05 0.08 0.06 0.33 0.14 0.01  0.24 0.39 0.32 1.73 0.73 0.05  0.62 0.54 0. 57 0.20 0.40 0.83  0.48 0.20 0.26  2.46  0.02  Explained Besidual Total  4.83 7.65 12.48  10 39 49  T a b l e 3.  ANOVA - T e r m i n a t i o n on  H y p o t h e s i s 3 - Mode, Exp, S t y l e , the  average c o n f i d e n c e l e v e l  next. was  As t h e a n a l y s i s once a g a i n  level  appeared this  highly  influence  1.00 0.00** 0.23 0.31  Time  and B i s k  will  demonstrates,  game  insignificant; risk attitude Experience  upon  again  confidence,  a s an i m p o r t a n t  a l l affect  o f t h e p a r t i c i p a n t s - was  ( t a b l e 4)  of significance.,  strong  factor  seemed  version  had a weak to  and c o g n i t i v e  (hypothesis 6 w i l l  tested  have  style  a  also  investigate  further). Having  tested  the  performance, the next a  experiments  four  more d e t a i l e d l e v e l .  7 appears i n t a b l e relative  importance  5.  three  general  hypotheses  hypotheses i n v e s t i g a t e  The a n a l y s i s  about  t h i s area a t  f o r hypotheses 4 through  W h i l e t h e p r e v i o u s ANOVAs i n d i c a t e d t h e  o f t h e f a c t o r s when  considered  together.  34  SOURCE VAB.  S. SQ.  Mode Exp Style Bisk  1 1  23.79 101.21 556.72 172.51 9.51 448.38 6678.06 13437.94 20116.00 Table  the  t-tests  4.  Term,  spent  speed  playing  1 1 1 1 1 1  23.79 101.21 556.72 172.51 9.51 448.38  0.07 0.29 •1.62 0.50 0.03 1.30  0.79 0.59 0.21 0.48 0.87 0.26  10 39 49  667.81 344.56 410.53  1. 94  0.07  Confidence  variable, In  time  variable, each p e r i o d .  performing  guestionnaire  example  Hypothesis faster,  better  finish  structured  version  in  5,  table  completely  rejected.  5,  directions the  or  Min/Per.,  variable  not  (Term. = 1).  The  i s t h e number o f m i n u t e s  Finally,  Confid.  (user  confidence)  ( o u t o f 100) whom u s e r s  than  of  them  (see  the  thought attitude  i n appendix C ) .  often,  players  where  the  differences  v a r i a b l e i n d i c a t i n g whether  (Term.=0)  4 - Unstructured more  and  table  i n d i c a t e s t h e number o f p e o p l e were  Level  t e s t t h e hypothesized  i s a two-level  p e o p l e f i n i s h e d on playing  0.95 0.01** 0.08** 0,11*  will  differences. (termination)  0.01 6.99 3.32 2.64  ANOVA-  to follow  SIGNIF.  F  1.60 2409.76 1145.42 910.34  1  between g r o u p s on a s i n g l e those  M. SQ.  1 .  1.60 2409.76 1145.42 910.34  Mode/Exp Mode/Style Mode/Bisk Exp/Style Exp/Risk Style/Bisk Explained Besidual Total  DF.  game v e r s i o n  and  be  - was t e s t e d  i t was  seen  Consistent  more  w i l l be  confident  by t h e f i r s t  that  with  players  than  3 t-tests  t h i s h y p o t h e s i s was  the  findings  of  the  35  1  J  VARIABLE  GROUPING  #  MEAN  ST DEV.  T  PROB  J Term.  Struct. Unstruct.  24 26  0.50 0.46  0.51 0.51  0.27  0.34  I Min/Per.  Struct. Unstruct.  24 26  0.77 0.78  0.33 0.25  -0.22  0.41  j Ccnfid.  Struct. Unstruct.  24 26  40.88 39.73  24.35 16.02  0.20  0.42  Novice Exper.  30 20  0.70 0.15  0.47 0.37  4.44  0.00**  Novice Exper.  30 20  0. 84 0.69  0.33 0.19  1.84  0.04**  | Ccnfid.  Novice Exper.  30 20  46.57 30.85  17.48 20.89  2.88  0.00**  J Term.  High-anal. Lou-anal.  21 29  0. 38 0.62  0.49 0.50  -1.69  0.05**  I Min/per.  High-anal. Low-anal.  0.74 0. 83  0.24 0.35  -1.06  0. 15*  | Confid.  High-anal. Low-anal.  21 29 21 29  34. 83 47.81  20.67 17.46  -2.34  0.01**  I Term,  Risk-taker R-averter  19 31  0.37 0.55  0.50 0. 51  -1.23  0. 11*  I  Risk-taker R-averter  19 31  0.67 0.84  0.18 0.32  -2.20  0.0 2**  Risk-taker R-averter  19 31  33.42 44. 48  16.65 21.36  - 1.93  0.03**  i  r  -  I Term. j  Bin/Per.  Min/Per.  I Confid.  t  — _  Table ANOVAs,  5.  game  T-TESTS - P e r f o r m a n c e and S t r u c t u r e  version  had  no  significant  impact  upon t h e  v a r i a b l e s s p e e d , t e r m i n a t i o n , and c o n f i d e n c e .  T h i s would  to  game  contradict  superiority; just  the claim of however,  too simple  the  unstructured  i t i s quite likely  t o provide  a significant  version's  that this  difference  seem  game was  i n freedom  36  between t h e two v e r s i o n s . administrator, playing,  problems  and  indicated  Actually,  verbal  a  with  starting  comments  greater  observation  from  difference  game t h a n e x p e r i e n c e d The  fourth  than  through  was  of  utilize  finish  analytics  -  hypothesis  termination  significant generally Taylor  be  5;  unstructured  table  5  this  indicating  that  again  be s e r i o u s l y a c c o u n t e d f o r  most  that  and by  "experienced  desirable  6 - High  subjects to  research." * 3  analytics  will  be more c o n f i d e n t  t-tests  confidence between  with  more  As e x p e c t e d ,  7  the  both  9.  The  variable,  displayed  groups.  be  t h a n low  through  weakly s i g n i f i c a n t on t h e s p e e d  differences  tested  be f a s t e r , f i n i s h  concluded  the  often,  and  consistent  table  highly  T h e s e r e s u l t s were  conclusions  of  Benbasat  and  {see c h a p t e r t w o ) .  The finish  who  3S  provided  was o n l y  in  a l l  These r e s u l t s a r e s i m i l a r t o the  hypothesis  more  was  participants  the  in  making e x p e r i m e n t s a n d  analysis for  faster,  was  supported,  to  i n decision  The  but  seemed  will  which s h o u l d  MacCrimmon,  individuals  with  than novices.  a l l computer e x p e r i m e n t s .  findings  game  participants  implied  rows  players  strongly  experience i s a factor in  sixth  and be more c o n f i d e n t  hypothesis  the  players.  hypothesis 5 - Experienced often,  novice  the  n o v i c e s a p p e a r e d t o have more t r o u b l e  by  test  of  more o f t e n ,  provided  confidence  by  hypothesis  7 - Risk-takers  and be more c o n f i d e n t the l a s t  three  than  will  risk-averters  tests i n table  showed v e r y s i g n i f i c a n t d i f f e r e n c e s  be f a s t e r ,  5.  Speed and  between  groups.  37  while termination contradict  the  with r e s p e c t however,  further  of  Taylor  period  This  would  last  (see chapter  investigation  hypothesis of t h i s  since  section  n o v i c e s would have d i f f i c u l t y  version,  seem  to  and D u n n e t t e , e s p e c i a l l y  with  two). their  decision-making i n a ncn-computerized  The that  findings  t o time per  needs  involved  was l e s s s i g n i f i c a n t .  This, research  environment.  tested  the  belief  the unstructured error  rate.  H y p o t h e s i s 8 - The Mode/Exp i n t e r a c t i o n w i l l a f f e c t t h e  error  rate 6.  and would d i s p l a y i t t h r o u g h an i n c r e a s e d  game  o f t h e p a r t i c i p a n t s - was a n a l y z e d C l e a r l y , there  the  hypothesis  compensated  were no h i g h l y  was  rejected  any d i f i c u l t i e s  c a r e t o e a c h move t h e y by  the  effects were any  playing  significant  ( i t may  speed  be t h a t  by d e v o t i n g i n c r e a s e d  findings).  i n t h e game.  variables,  well  made, a p o s s i b i l i t y  was p o s s i b l y c a u s e d  made  by t h eftNOVft i n f a b l e  than  5  errors  averaged 2 e r r o r s  lack  of s i g n i f i c a n t  by t h e f a c t t h a t v e r y  few  Out o f 50 p a r t i c i p a n t s , o n l y  e n t e r e d each SlEotheses Like price  and  influence  and f o u r  errors 11 made averaged  analytics  inputs  were  period).  h y p o t h e s i s 0, h y p o t h e s i s guantity most  at  high  (where up t o 6  a b o u t t h e u s e o f S p e c i a l Program  found i n t h i s accepted  p e r 100 p e r i o d s  and  which was s u p p o r t e d  The  p e r 100 p e r i o d s ,  novices  thought  e r r o r s anywhere i n t h e game; s e v e n low a n a l y t i c s  less  and  (at the  users  -  experiment least  9 - The d e f a u l t  beginning  was t e s t e d that  28  Features  of  the  values f o r game)  by s i m p l e c o u n t . of  the  50  one o f t h e o p e n i n g d e f a u l t  will I t was  participants values  (values  38  i  1  SCOECE VAR.  S.SQ. ,  Hode Exp Style B isk Mode/Exp Mode/Style Bode/Risk Exp/Style Exp/Risk Style/Risk Explained Residual Total ., .  ,.,,,  ,  DF.  M. SQ.  15.34 20.77 66.26 5.76  1 1 1 1  15.34 20.77 66.26 5.76  0.63 0.85 2.70 0.24  0.43 0.36 0. 11* 0.63  4.96 22.15 2.37 41.06 0.02 6.47  1 1 1 1 1 1  4.96 22.15 2.37 41.06 0.02 6.47  0.20 0.90 0.10 1 .68 0.00 0.26  0.66 0.35 0.76 0.20 0.98 0.61  221.78 872.64 1096.42  10 39 49  22.18 22.37 22.38  0.90  0.35  T a b l e 6. which o r i g i n a l l y  were a r b i t r a r i l y  indicate  that  uncertain  about e x a c t l y  accept  investigate to  in  default  accept  sources of  values  situations  than  seemed  to  (where t h e u s e r was he  likely  to  make h i s own d e c i s i o n s .  To  As i n d i c a t e d i n t a b l e 7, t h e r e  was  likely was  were no s i g n i f i c a n t  variance. 10  -  Setting  (about t h e u s e r ' s  actual  r e s p o n s e - was t h e n e x t  were p e r f o r m e d  than  'no* w i l l  f o r three  Ordered  default  players  response reports)  for to  not influence the p a r t i c i p a n t ' s t o be t e s t e d .  v a r i a b l e s : use  History  a s s u m p t i o n was t h a t  the  d e s i r e t o see v a r i o u s  rather  of  selected)., This  d e f a u l t s , an a n a l y s i s o f v a r i a n c e  'yes'  use  rate  what t o do n e x t ) , rather  SIGJ3IF.  whether any p a r t i c u l a r u s e r t y p e s were more  Hypothesis questions  unfamiliar  these opening  performed.  A NOV A - E r r o r  F  reports, with  and  *yes»  of  To do s o , AMOVAs History  use  reports,  of Graphs.  d e f a u l t s would  look  The at  39  i  '  :  | SOUBCE VAB.  S.SQ. ,  DF.  M. SQ.  0. 63 0. 34 0. 65 0. 07  1 1 1 1  0.63 0.34 0.65 0.07  0 .70 0 ,38 0 .72 0 . 08  0.41 0.54 0.4C 0.78  •1. 59 0. 30 0. 11 0. 51 0. 54 0. 52  1 1 1 1 1 1  1.59 0.30 0.11 0.51 0.54 0.52  1 .78 0 , 33 0 .12 0 .57 0 .61 0 .58  0.19 0.57 0.73 0.46 0.4 4 0.45  5. 18 34. 50 39. 68  10 39 49  0.52 0.90 0,81  0 . 59  0.75  Mode 1 Sxp Style Bisk Mode/Exp Mode/Style Mode/Bisk Exp/Style Exp/Bisk Style/Bisk Explained Besidual Total  1  _ Table  more  r e p o r t s than  value  (l^'yes*,  7.  ANOVA  - Opening  p l a y e r s with  F  Defaults  "no* d e f a u l t s ;  2=*no') was o n e o f t h e  hence. D e f a u l t -  independent  in  t h e t h r e e ANOVAs,  not  p r o v i d e d , but i n a l l t h r e e c a s e s  Default-value  to  be  of variance  level  a  very i n s i g n i f i c a n t  0.47 t c  familiar to  Tc conserve  SIGBIF.  level  do n e x t ) , d e f a u l t  source  0.97).  circumstances  space,  The  variables  t h e SPSS r e s u l t s a r e was  found  {ranging  implication  was  that  from in  (where t h e u s e r was g u i t e s u r e o f what  v a l u e s had no i n f l u e n c e upon  the  user's  decisions. The will in be  analysis  a l l affect  table very  attitude analytics  8.  f o r hypothesis  whether u s e r s a c c e p t d e f a u l t  I t c a n be s e e n significant,  had  any  made  11 - Exp, S t y l e , and B i s k  that cognitive style  while  affect.  the least  values -  neither  turned  experience  Surprisingly,  on  use c f t h e d e f a u l t  appears out to  nor  average,  risk high  values; i n fact*  40  out  o f every  100 p e r i o d s t h e y  could  have a c c e p t e d , w h i l e  This  i s  certainly  a  very  avoided  low a n a l y t i c s a v o i d e d  difficult  use f u r t h e r  58 d e f a u l t s  result  to  which only  explain,  they  about  and  3.  could  investigation.  i  1  SOURCE VSR.  S.SQ. ,  Exp Style Risk  0.06 4 .38 1.57  0.81 0.0 5** 0.23  143.20 4515.86 8428.04  1 1 1  143.20 4515.86 8428.04  0.03 1.04 1 .94  0.86 0.32 0.18  38531.88 73718.50 1 12250.38  6 17 23  6421.98 4336.38 4880.45  1 .48  0.24  by  Acceptance o f Defaults  v a r i a n c e was a l s o  of  Exp,  AHOVA -  Style,  which users a b b r e v i a t e  The  and R i s k w i l l commands.  and r i s k a t t i t u d e  s i g n i f i c a n c e o f t h e game the p h y s i c a l  used t o t e s t  difference  both t o  abbreviated  to s i g n i f i c a n t l y l e s s extent  every  fear of  100 c h a r a c t e r s  of t r y i n g  a feature  (table  significant.  could  be  interesting:  last  for risk-takers) .  hypothesis  This  program  (on  v e r s u s 35  may i n d i c a t e  do n o t u n d e r s t a n d , o r a  regarding  The r i s k  risk-averters  possible,  t h e computer t o i n t e r p r e t t h e i r a b b r e v i a t i o n s The  explained  than r i s k - t a k e r s  100 c h a r a c t e r s  they  9) showed  very  between t h e two v e r s i o n s . more  55 o f e v e r y  be  factor  factor  average, typing  was  The r e s u l t s  version  hypothesis  a l l a f f e c t the extent to  attitude  of  SIGNIF.  261.02 19007.54 6805.41  Analysis  game v e r s i o n  F  1 1 1  T a b l e 8.  Mode,  H.SQ.  261.02 19007.54 6805.41  Exp/Style Exp/Risk Style/Risk Explained Residual Total  DF.  a  mistrust  correctly. features  was  41  —  t  SODBCE VAB.  DF.  S. SQ. ,  Mode Exp Style Bisk  6726.46 642.78 665.26 3898.38  Mode/Exp Mode/Style Mode/Bisk Exp/Style Exp/8isk Style/Bisk  1062.67 336.99 512.94 26.20 876.26 33.01  Explained Besidual Total  1  M.SQ.  1. 1 1 1  1 1 1 1 1  16453.66 35033.00 51486.66  10 39 49  F  SIGNIF.  6726.46 642.78 665.26 3898.38  7.49 0.72 0.74 4.34  0.01** 0.40 0.40 0.0 4**  1062.67 336.99 512 .94 26.20 876.26 33.01  •1.18 0.38 0.57 0.03 0.S8 0.04  0.28 0.54 0.45 0.86 0.33 0.85  1645.37 898.28 1050.75  1.83  0.09 1  I—  Table hypothesis affecting In  the  9.  ANOVA - E x t e n t  13 - The l e n g t h o f commands w i l l the extent  analysis,  The  or long  t o which t h e y the  variable indicating mnemonics)  main  be t h e main  are abbreviated  effect  Length  (5 t o 8 l e t t e r )  experience  relatively  significant  was  clearly  the  short, users  users  will  devise  and  will  tend  affects. periods  factor.  to  played.  the hypothesis.  Conclusion:  them  in  are  i f commands  full;  i f  long,  abbreviations. over  Time  s e v e n h y p o t h e s e s were a l l r e l a t e d Each  (3 t o 5 l e t t e r  o f v a r i a n c e , l e n g t h o f commands  t o type  Hypotheses about Comparisons These  users.  experience/cognitive style  sources  dominating  by  commands was b e i n g  a n a l y s i s a p p e a r s i n t a b l e 10 and v e r i f i e s  factor  was a t w o - l e v e l  whether t h e game w i t h s h o r t  Although  are  of Abbreviation  compared  behaviour  user over  behaviour  over  a l l remaining  t o user l e a r n i n g the  first  10  p e r i o d s , and was  42  |  I  SOUBCE VAB.  S. SQ.  DF. ! .  1381.94 72. 14 16.93 8144.06  P I Style I Eisk ) length E x  1 1 1  1 . 1 1 1 1  ) Exp/Style 1359.23 | Ixp/Bisk 606.73 I Exp/Length 94. 17 I Style/Bisk 1091.69 I Style/Length 102.56 261.68 J Bisk/Length | Explained J Besidual I Total  tested  1  17828.54 5927.01 23755.55  Table  10.  10 15 25  ANOVA  by a p a i r e d t - t e s t  VABIABLE  GBOUPING  Kin/Per. Ccnfid. Usability Abbrev. Histories Crd-Hist. Graphs  M. SQ.  F  SIGMIF.  1381.94 72.14 16.93 8144.06  3.55 0.18 0.04 20.94  0.08** 0.67 0.84 0.0 0**  1359.23 606.73 94.17 1091.69 102.56 261 .68  3.49 1.56 0.24 2.81 0.26 0.67  0.0 8** 0.23 0.63 0. 12* 0.62 0.43  1782.85 395.13 950.22  4.45  0.01  - A b b r e v i a t i o n by L e n g t h (shown i n t a b l e 1 1 ) .  #  SEAN  10 P e r i o d s Bemainder  45 45  0.70 0.53  0.21 0. 16  6.07  10 P e r i o d s Bemainder  45 45  47. 16 47.29  24. 98 27.43  -0.03  0.49  10 P e r i o d s Bemainder  45 45  5.24 5.71  2.35 2.86  - 1.38  0.09**  10 P e r i o d s Bemainder  45 45  49.34 46.42  33.55 33.04  2.36  0.01**  10 P e r i o d s Bemainder  45 45  14.20 7.38  14. 40 10.28  3.26  0.00**  10 P e r i o d s Bemainder  45 45  9.58 8.78  11.06 11.76  0.38  0. 35  10 P e r i o d s Bemainder  45 45  19.16 25.80  22.63 24.64  -2.1 1  Table  11.  STDEV. ,  T  T-TESTS - C o m p a r i s o n s o v e r Time  PBOB 0.00**  0.02**  43  Hypothesis will  14 - A v e r a g e t i m e  decrease  increased obvious,  with  from  the  increase  essentially  encouraging,  time no  -  no m a t t e r  users s t i l l  felt  of  may  in  15 - User  user  how c l o s e t h e y  that everyone e l s e  comparative  performance  usability indicated 5.71  was h y p o t h e s i s  (on a s c a l e  from  to  16 - User  time.  some  the  indication possible.  ratings  improve  with  of  9),  indicating  the  time.  r a t i n g s changed from some  As 5.24  higher  had a c h a n c e t o t r y many  17  -  The  extent  u n s t r u c t u r e d game v e r s i o n p l a y e r s ) w i l l was a l s o  verified,  people  read  in  the  a b b r e v i a t e and d i d so from a b b r e v i a t e from The decrease  test with  the s t a r t  -  typed.  i n c r e a s e with  was  It  instructions  the start  of hypothesis time  abbreviation  During  100 c h a r a c t e r s were t y p e d ;  o f t h e game, 46 were  either  of  though l e s s d r a m a t i c a l l y .  p e r i o d s , 4 9 o f each  remainder  not  over  was  i t s features. Hypothesis  ten  will  must be a t t h e same s t a g e .  average  1  (an  came t o t h e optimum,  program w i l l  11, t h e i r  speed  there  confidence  a p p r e c i a t i o n o f t h e program o n c e t h e y of  rejected;  ( r e i n f o r c e m e n t ) whenever  o f t h e computer i n table  user  confidence  be d e s i r a b l e t o p r o v i d e t h e u s e r w i t h  Also supported  to  supported;  period  result).  definitely  change  Apparently,  It  was  each  t o 0.53 m i n u t e s / p e r i o d  o t h e r hand, h y p o t h e s i s  with  playing  - was c l e a r l y  0.70 m i n u t e s / p e r i o d  yet s t i l l  On  time  spent  would that  (by  time  -  the f i r s t during the seem  they  that could  o f t h e game, o r t h e y  did  a n d o n l y a few l e a r n e d t o do s o .  18 - Usage o f H i s t o r y r e p o r t s highly significant.  The  will  average  44  number to  c f H i s t o r i e s requested  7, p r e s u m a b l y  as p e o p l e l e a r n e d  Hypothesis decrease  p e r 100 p e r i o d s  19  -  Osage  throughout  the  Their  14  o f t h e Graphs.  c f Ordered H i s t o r y  w i t h t i m e - was r e j e c t e d .  constant  t h e value  dropped from  use  reports  will  remained  game; i n f a c t , t h e y  quite  were n e v e r  very  popular. Finally, with  hypothesis  though,  nearly  quickly  learned  should  also  per  the value  increase  next three  looked  The Mode,  at  more further  per  hypothesis  Users  the  of  existence), (preferring  while the  100  variable periods.  i n this will  It  revealed  u s e r s who showed  Protocols  i s The  the  number  are  of  two  hypotheses  protocols.  area  is  hypothesis  21  a l l a f f e c t t h e use o f H i s t o r y  version  experienced more  report.  appears i n  table  and e x p e r i e n c e a s s i g n i f i c a n t  structured  (presumably because t h e y  users  a l l r e l a t e t o usaqe of r e p o r t s ;  The a n a l y s i s o f v a r i a n c e game v e r s i o n  19  periods,  data a n a l y s i s  were t h e o n l y  dependent  shews o n l y  10  pictorial  Osage a. n<| S o l u t i o n  E x p , S t y l e , and B i s k  reports.  after  only  I t would a p p e a r t h a t  these both r e l a t e t o s o l u t i o n first  increase  i n t h e i r use o f Graphs.  hypotheses  a l l of these, the  following  a  (low a n a l y t i c s )  !22J:0.theses a b o u t Be p o r t  reports  of  will  Initially,  periods;  26 were r e q u e s t e d .  heuristics  The  100  be m e n t i o n e d t h a t  no s i g n i f i c a n t  in  Graphs  t i m e - was s u p p o r t e d b y t h e r e s u l t s .  g r a p h s were r e q u e s t e d  that  20 - Osage o f  used  constantly players  informative  12,  factors.  H i s t o r i e s most reminded used  graphical  and  of  often their  them l e a s t  often  report),  The  45  report game  frequency players  experienced  | SOUSCI | 1 f I  by u s e r  and  6  for  Mode Exp Style Risk.  S.SQ.  I Explained I Residual I Total  DF.  0.04** 0.51 0.94 0.78 0.92 0.90  | | | | I |  3583.96 6287.26 9871.22  10 39 49  358.40 161.21 201.45  2.22  0.04  |  will  The  -  Mode,  only  st r u c t u r e d  Style,  significant  than  this report  interaction).  version  unstructured  result.  |  users,  Risk w i l l a l l analyzed  is  game  Again,  faced  users.,  with  would  repeated Histories  No o t h e r  was n o t v e r y p o p u l a r i n g e n e r a l )  the  version it  s e l e c t Ordered  game  in  single  ( r e c a l l from t h e a n a l y s i s o f h y p o t h e s i s  t e s t of Hypothesis  a l l affect  and is  factor  report's existence,  had much i m p a c t  intriguing  Exp,  History reports  an e x p e r i e n c e  of the  0.00** | 0,03** J 0.92 | 0.64 J  ANOVA - Use o f H i s t o r y R e p o r t s  13.  The  }  4.68 0.44 0.01 0.08 0.01 0.02  table  19 t h a t  SIGNIF.  754.70 71.52 1.03 13.13 1.44 2.60  t h e use c f O r d e r e d  factor  F  1 1 1 1 1 1  affect  with  M. SQ.  754.70 71.52 1.03 13.13 1.44 2.60  22  often  for  10. 17 5.01 0.01 0.22  Hypothesis  more  reports  1639.96 808.12 1.82 35.74  12.  reminders  16  1 1 1 1  Table  that  unstructured;  1639.96 808.12 1.82 35.74  | Mode/Exp | Mode/Style | Mode/Risk | Exp/Style I Exp/Risk I Style/Risk  seem  was: 18 r e p o r t s f o r s t r u c t u r e d  p l a y e r s and 7 f o r n o v i c e s .  VAR.  (together  type  use  There  23 of  Mode, Exp, Graphs  were o n l y  Style, had  a  *  and  Risk  particularly  weakly s i g n i f i c a n t  sources  46  SOUfiCE VAR.  S.SQ.  Mode Style Risk  634.87 121.95 29.10 63.46  Mode/Exp Mode/Style Mode/Risk Exp/Style Exp/Risk Style/Risk  343.67 3.64 32.88 37.64 7.47 125.66  Explained Residual Total Table of  DF. 1 1 1 1  1  1 1 1 1 1  1618.67 3013.31 4631.98 13.  10 39 49  players  v s . 20) and h i g h (31  8.22 1.58 0.38 0.82  0.01** 0.22 0.54 0.37  343.67 3.64 32.88 37.64 7.47 125.66  4.45 0.05 0.43 0.49 0.10 1.63  0.04** 0.83 0.52 0.49 0.76 0.21  161.87 77.26 94.53  2. 10  0.05  and c o g n i t i v e s t y l e  reguested  SIGNIF.  634.87 121.95 29.10 63.46  ANOVA - Use o f O r d e r e d H i s t o r y  variance: experience  Experienced  F  M.SQ.  more  a n a l y t i c s reguested  Reports  (see t a b l e  Graphs than more t h a n  14).  novices  low  (32  analtyics  v s . 21) .  SOURCE VAR. Mode Exp Style Risk Mode/Exp Mode/Style Mode/Risk Exp/Style Exp/Risk Style/Risk Explained Residual Total  S.SQ.. 556.49 1393.66 1170.53 268.33 0.02 258.70 45.41 59.37 674.95 852.69 5328.19 20734.72 26062.91 Table  14.  DF. •j 1 1 1  1  1 1 1 1 1  10 39 49 ANOVA -  M. SQ. 556.49 1393.66 1170.53 268.33 0.02 258.70 45.41 59.37 674.95 852.69 5328.19 531.66 531.90  F  SIGNIF.  1.05 2.62 2.20 0.51  0.31 0.11* 0.15* 0.48  0.00 0.49 0.08 0.11 1.27 1 .60  0.99 0.49 0.77 0.74 0.27 0.21  1.00  0.46  Use o f Graphs  I  47  The  last  solution pairs  two  hypotheses  protocols.  By  plotting  user's  protocol  examples).  By  then  Some  employing  original  a  binary  search,  a spiralling used  tested  p o i n t i n the  every  p a r t i c i p a n t s showed  affect  through test  no  the problem  users  protocol  diagram f o r each  most  and  other  (but with  user  was  results  factor.  high  to  (i.e. hill  they  Other  routinely  no  apparent  Finally,  a l l ; they  - Exp,  the  a  just  Style,  and  seme  wandered  Bisk w i l l a l l  structured  emphasis traced  in  approach  on  Style)  manually,  table  Comprising  analytics  structured,  (see c h a p t e r  error;  a  activity,  model.  An  were  supporting  -  to the  and  the  ANOVA was  then  15.  Although  significant, cognitive style  significant  systematic  24  the  weakly  players,  One  attempting  explicit  and  for  c o u l d get  search  as s y s t e m a t i c o r n o t .  yielding  structured  cations  was  F  of  space.  (with  classified  at  displayed  problem  was  or other  method  the  experience  one  the optimum when n e a r e d ) .  solving  performed,  dots,"  problem space  hypothesis  whether  approach  picture  Appendix  gradient  a structured t r i a l  t o zoom i n on  To  the  participant  a  path,  participants  randomly  (see  guantity>  participants displayed highly systematic  climbing),  desire  obtained  to users*  <price,  were s i m u l a t e d , a  "connecting  good i d e a o f what t h e do.  was  thesis relate  a l l of the  i n the o r d e r i n which t h e y  each  the  of this  20  was  clearly  of  the  more  27  frequently  Barrett s f  classifi-  two).  measure  was  made upon the  user  p r o t o c o l s : based  48  SOURCE VAR.  S. SQ.  DF.  Exp Style Risk  1.62 3.31 0.01  1 1 1  1 .62 3.31 0.01  2.34 4.78 0.01  0. 13* 0.03** 0.94  Exp/Style Exp/Risk Style/Risk  2.61 0.44 0.16  1 1 1  2.61 0.44 0.16  3.76 0.64 0.24  0.06** 0.43 0.63  9.31 29.81 39. 12  6 43 49  1.55 0.69 0.80  2.24  0.06**  Explained Residual Total Table  SOURCE VAR.  15.  ANOVA - P r o t o c o l  F  SIGNIF.  Structure  S. SQ.  DF.  Exp Style Risk  0.79 0.08 0.03  1 1 1  0.79 0.08 0.03  3.36 0.32 0. 14  0.07** 0.57 0.72  Exp/Style Exp/Risk Style/Risk  0.27 0.75 0.02  1 1 1  0.27 0.75 0.02  1. 13 3.18 0.08  0. 29 0.08** 0.77  6 43 49  0.36 0.24 0.25  1.51  0.20  Explained Residual Total  2. 15 10.17 12. 32 Table  upon t h e e x t e n t problem  space,  prctocols hypothesis amount  16. to  which  or just  participants concentrated  were m a n u a l l y c l a s s i f i e d 25  -  (together  16, with  the a  SIGNIF.  Exp,  Style,  searched  as d i s p e r s e d  and  Risk  or not.  will  significant  risk  attitude  entire  search  factor  Then  a l l affect the f o r t h e optimum  on S t y l e ) - was t e s t e d .  only  the  upon one s m a l l a r e a , t h e  cf dispersion displayed i n their  table  F  M.SQ.  ANOVA - P r o t o c o l D i s p e r s i o n  {with t h e e m p h a s i s a g a i n in  M.SQ,  was  interaction);  As i n d i c a t e d experience apparently,  49  experienced and  p l a y e r s were more f a m i l i a r  d i d not f i n d  space.  Neither  much o f t h i s As results  with  this  type  any need t o " f e e l a r o u n d " t h e e n t i r e  of the p s y c h o l o g i c a l v a r i a b l e s  could  of  task  problem explain  behaviour,  mentioned  i n the previous chapter,  appears i n appendix  G.  a summary o f t h e s e  50  Chapter  Seven  CONCLUSIONS In t h i s  t h e s i s , a new r e s e a r c h t o o l  interactive  computer  program)  has  (in the  been  form  a  convenient,  facilitate  "idiot-proof"  investigation  communication  of  computer  some  an  of  The  exauple  program,  aspects  which c o u l d be o f i n t e r e s t  an  introduced.  m o t i v a t i o n f o r t h i s h a s been d e s c r i b e d : t o p r e s e n t of  of  and  to  man-machine  t o other information  systems r e s e a r c h e r s . , Seme o f t h e r e l a t e d the  Next,  research  was p r e s e n t e d .  described  details  Again, the  discussed;  to  be  and p a r t i c i p a n t ,  convenience  quite  only  one  then  particularly need  to  carefully  found  t h a t some p e o p l e  need  to  otherwise  for  both  o v e r one h a l f - h c u r .  were  half-hour,  First,  then  presented.  making  i t easy  to  with. two  items  are  d e s p i t e heavy e m p h a s i s on t h e  t h e i n s t r u c t i o n s i n a d v a n c e , i t was  just  reiterate  r e s e a r c h was  convenient  of the experiments,  read  personally tutor  this  the p o s s i b i l i t y of subjects getting  running  noteworthy.  for  c o u l d n o t be o v e r - e m p h a s i z e d :  t o hurry t o get i t over  In the a c t u a l  forthis  taking just  aspect  and m i n i m i z i n g  or needing  terminal  The p r e - t e s t i n g  shown  lasted  administer bored  process o f data c o l l e c t i o n  o f the computer experiment  the  qame  the a c t u a l  and  administrator  or  h a s been  u s e r e n g i n e e r i n g o f t h e computer program was d e s c r i b e d i n  detail.  The  literature  d i d n o t do i t . every  the  s c r e e n ) ; no m a t t e r  This  suggests  new u s e r o f a computer  instructions  (perhaps  a  system cn  the  how w e l l t h e d o c u m e n t a t i o n may be  51  written,  seme p e o p l e  properly  understand  (poor  results  just  will  not read  i t - and t h e  now  and  lack  i t or take  results  of  can  faith  be  t h e time t o disastrous  i n computers i n t h e  future). The  second  involved version  problem  getting of  the  novice game;  processor  appeared  to  Personal  attention  was  sometimes  observed  users started the be  until  they  from  chapter  with  of  a  general  too sophisticated  needed  to  explain  the  I t seemed q u i t e c l e a r  three  what was h a p p e n i n g . that  game  the u n s t r u c t u r e d command f o r them. task  that  w i t h t h e s t r u c t u r e d qame v e r s i o n -  understood  w r i t e a proqram  concept just  demonstrate i t .  would be h a p p i e r  while administering the  and  novices  at  least  To t h i s e n d , r e c a l l  t h e e x t r a programming n e c e s s a r y t o  which c o u l d be r u n i n e i t h e r  mode  was  quite  minimal. Finally, presented.  the  process  attitude,  collected  by  (both  with  even  computer  solution  proqram.  SPSS, u s i n g a n a l y s i s and  a r e now r e v i e w e d ,  time  were a l l  data  variance  paired).  this  protocol This  of  performance,  was  and  then  t-tests  The r e s u l t s o f these  in a different  order  and  added d i s c u s s i o n . In  was  with  the  and  normal-one-tailed  analyses  and c o n v e r s i o n was  I t was m e n t i o n e d t h a t d a t a a b o u t u s e r  behaviour,  analyzed  o f data c a p t u r e  relating  found  whether  psychological  that  cognitive  people  finished  confidence  l e v e l throughout  style the  variables had  game  t h e game.  a on  t o performance, i t  strong time,  High  effect  upon  and upon  their  analytics  finished  52  more  often  indicating tasks?)  and  were  more  confident  that  this  game  (and  may  impacted  favor  report  analytics)  were t h e  later  structured displayed  found  i n the  than  high  the  Another to  (implying a  affect  (guestionning Also,  much l e s s e x t e n t  caused  a mistrust  dispel this  user's  Experienced  most  previous players  were s i g n i f i c a n t l y indicates  the  the  use  high  less  analytics default  investigation).  for  less  i t  was  structured  the  optimum  Barrett) .  and  a t t i t u d e , was  found  confidence;  risk-  were more c o n f i d e n t  findings were  than other  of  found users.  than  Taylor to  and  abbreviate If  this  computer, e f f o r t s s h o u l d  is  be  made  dimensions  was  fear.  However, t h e the  by  move and  of the  (low  f o r the  protocols,  search  risk-averters  commands t o  also  graphical  accepting  further  p l a y i n g speed  risk-avexters  to  avoid  psychological variable, risk  l e s s time per  by  The  solution  their  spent  Dunnette).  to  requiring  in  style  heuristics  preference  feedback).  tendency  model s u g g e s t e d  significantly  takers  that  a n a l y t i c s were s i g n i f i c a n t l y  analytics  (supporting  many m a t h e m a t i c a l  i t s dependence upon  a n a l y s i s of user  low  analytics,  Cognitive  found  increased  result  low  which n e i t h e r d e c r e a s e d i t s  l e s s summarized  (a  that  was  group  game  a significant  responses Finally,  nor  i n the  and  i t  only  perhaps  analytics.  usage:  of h i s t o r y r e p o r t s reports  high  than  dominant  experience  f a c t o r on with  all  o n - l i n e computer  systems.  were much f a s t e r , f i n i s h e d more o f t e n , more c o n f i d e n t  importance  of  than n o v i c e s .  explicitly  This  recognizing  and  clearly these  53  f a c t o r s i n any for  that  computer r e s e a r c h  matter).  Experienced  game v e r s i o n , w h i l e , as n o t e d lost  with  the  participants  made t h e  indicating  relevant  least  users  use  ability  material.  Again,  any  novices  were  Finally,  version,  (statistically) speed,  termination,  reasonably The  simple  ideal,  their  to  solution  detect  and  him  should  be  and  noted  significantly  user  factor,  confidence.  l e t him  disregard less  that  experienced  change with  reports  which was  were f o u n d  typographical errors  any  aspects  memorization,  indication  abbreviation,  etc.)  Ordered  of  types  errors.  However, some  i t  behaviour:  players of  was  the  requested  error  rate.  with  respect  In f a c t ,  there  were  game;  the  in  this  computer proqram  allowed  both  History reports.  participants of the  useful.  comfortable  period)  considered b r i e f l y  range  that, for  user with  time) .  reminds  found neither  equally  i s more  each  among u s e r  or  made by  enqineerinq  are  t h a t game v e r s i o n d i d a f f e c t  the  was  affecting  to provide the  (which  research.  I t would seem  versions  showed  protocols,  hand,  choose whichever  more H i s t o r y and  differences  few  weak  t a s k s , both  of  Another area  very  other  structured version  availability  making  nor  (a c h o i c e which may  users of the  No  a very  the  t h e r e f o r e , would be  alternatives, for  t o be  initially  o f H i s t o r y r e p o r t s , and  i t i s p o i n t e d out  on  either  experienced  s u b j e c t s seem t o have an a d v a n t a g e i n c o m p u t e r i z e d Game  research,  were h a p p y w i t h  game.  dispersion in  an  probably  earlier,  unstructured  t h e l e a s t amount o f both  {ana  responses,  seem t o have m i n i m i z e d  the  to  {sinindzed unlimited  possibilities  54  for  error. The  also  impact  studied.  quantity  was  found  were  accepted  i n the f i r s t  a  report  effect  upon  Hence,  in  select  to  *yes»  whether less  suggested  (as  by  not  him  (to minimize unnecessary typing) ,  users.  Players  of  commands a b b r e v i a t e d game  with  implications  5  to  of this:  presumably p l a y  long;  t o " f o r c e " users reasonably  intelligibility). appropriate is  best  game  letter  with  commands.  t o " f o r c e " users faster),  f o r themselves. provided  in  of  3  (but  are only  do that  It  these  On t h e e t h e r  as  program  an  appear aid to  usage was t h e  abbreviation  by  t o 5 l e t t e r mnemonic than  players  of  the  T h e r e a r e two p o s s i b l e to abbreviate  intentionally  I t i s proposed  when t h e r e  appear t o  commands  make t h e commands  t o remember t h e commands i n f u l l ,  short  to  report.  people  and a r e recommended  f a r l e s s frequently  8  the  desire  i s clear, defaults  upon t h e e x t e n t  the  (and  them  be  examined c o n c e r n i n g  o f command l e n g t h  of  that  may b i a s t h e r e s u l t s ) .  t o i n f l u e n c e the user,  effect  requested  than t h i n k  values  they  area  one-half  situations,  not  last  p r i c e and  about the user's  hand, i n s i t u a t i o n s where t h e c h o i c e  The  opening  over  actually  rather  that default  circumstances  the  was  r a t h e r t h a n 'no' had no s i g n i f i c a n t  they  value  circumstances  p e r i o d o f t h e game, whereas s e t t i n g  well-defined  the default  various that  d e f a u l t response t o guestions  see  is  It  defaults  participants the  o f d e f a u l t s under  not the  compromise former  i s  make their more  a few commands and t h e l a t t e r  when t h e number o f commands i s g u i t e  larqe.  55  The  last  performance t o the  area c o n s i d e r e d i n t h i s research and  behaviour  remainder  revealed  that  of  i n the f i r s t  the  game.  p l a y i n g speed,  The  extent  reports  desirable ratings  from of  slightly,  a systems  the  they  result  was  would  seem  do  know how  are  had that  that  time  that  time  point  the  everyone only  feedback  of  program  to get c o m f o r t a b l e  how  else  well  of were  view). also  use  use  which  Oser  increased  program  with i t .  A  more  surprising  change w i t h  time;  i t  people are d o i n g , i f they  i s doing, they  average.  results  and  ( a l l of  users a p p r e c i a t e d the  no m a t t e r  of  over time,  designer's of  p e r i o d s o f t h e game  analysis  user c o n f i d e n c e d i d not  performing  performance  over  usability  indicating  after  not  decreased  user  o f a b b r e v i a t i o n , and  of Graphs a l l i n c r e a s e d s i g n i f i c a n t l y History  10  compared  assume t h a t  Perhaps  c o u l d remedy t h i s  some  they  comparative  (when i t i s  available,  of c o u r s e ) . I n summary, a v e r y s i m p l e , y e t e f f e c t i v e research  tool  experiment cf  been  described,  and  u s i n g i t have b e e n p r e s e n t e d .  the  enjoyable!)  results cf  Some o f t h e  p r e v i o u s r e s e a r c h e r s have been c o n f i r m e d ; some new  have  been p r o v i d e d a b o u t  many o f t h e s e more use  has  (and  results  research cf  reports  versions impact  with  man-machine i n t e r f a c e .  have t o u c h e d  could  only the  be done i n t h i s  could and  the  be  without  upon p e r f o r m a n c e ,  investigated graphical  behaviour,  findings results Clearly,  s u r f a c e , and  area.  much  F o r example;  further  r e p o r t s and attitude,  by  the  having  studying and  an  the  solution  56  protocol;  the  comparisons  period-by-period (first  10  could  be  aspects  of  including  over time could  time s e r i e s data,  periods studied  versus  r a t h e r than  remainder);  more c a r e f u l l y and  s p e c i a l program utilization  of  features  typeahead  upon p l a y i n g s p e e d , e r r o r r a t e ,  be  the  applied t o two  solution  be  averages  or  other  investigated,  c a p a b i l i t i e s and  etc.  the  protocols  scientifically; could  to  i t s impact  57  FOOTNOTES  B e G r e e n e , Kenyon B. 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T a y l o r , R o n a l d N. " P s y c h o l o g i c a l D e t e r m i n a n t s o f Bounded R a t i o n a l i t y : I m p l i c a t i o n s f o r Decision-Making S t r a t e g i e s , " D e c i s i o n S c i e n c e s , V. 6, No. 3 ( J u l y , 1975) , pp. 409-429." T a y l o r , R o n a l d N., and M a r v i n D. D u n n e t t e . " R e l a t i v e C o n t r i b u t i o n of Decision-Maker A t t r i b u t e s t o D e c i s i o n P r o c e s s e s , " O r g a n i z a t i o n a l .Behavior and Human P e r f o r m a n c e . V. / l 2 . No. 2 ( O c t o b e r , 1974), p p . 286-2S8., wasserman, Anthony I . "The D e s i g n o f ' I d i o t - P r o o f * I n t e r a c t i v e P r o g r a m s , " P r o c e e d i n g s , 1973 N a t i o n a l Computer C o n f e r e n c e , V. 4 2 , pp. M34-M38. W i t k i n , H . A . , P. K. O l t m a n , E . R u s k i n , and S. A. Karp. The Embedded f i g u r e s T e s t , P a l o A l t o , C a l i f o r n i a : C o n s u l t i n g P s y c h o l o g i s t P r e s s , I n c . , 1971. Wynne, E a y a r d E. and Gary W. D i c k s o n . " E x p e r i e n c e d Managers* P e r f o r m a n c e i n E x p e r i m e n t a l Man-Machine D e c i s i o n System S i m u l a t i o n , " Academy o f Management J o u r n a l . V. 18, No. 1 (March, 1975), pp. 25-40.  62 Appendix A PROGRAM A listing  of  the  a p p e a r s on t h e n e x t in  FORTRAN  and  source  21 p a g e s .  i s  about  subprograms  ( f o r timing,  comparison)  which  are  LISTING code  suffice  In  the  computer  The program i s w r i t t e n 1000 file  specific  C o l u m b i a , and hence c a n p r o b a b l y others.  for  lines  long.  control,  entirely  I t u s e s some and  character  t o the U n i v e r s i t y of B r i t i s h only  serve  a s an example  t h e p a g e s t o f o l l o w , t h e program comments  as g e n e r a l documentation.  game  for  should  63 C C C C C C C C C C C C C C C  CBT GAME FOB THESIS DATA COLLECTION P. MASULIS -DECEASES,1977 TO BUN THIS GAME: B *FTN SCARDS=PSM.FTN SFUNCH=PSM B PSM*CPU:LIB P A B = C C C , Y Y ¥ , L L L , < U S E R » S NAME> WHERE CCC=CYC * FOB STRUCTURED INPUT =CMD FOB UNSTBUCTUBID INPUT Y¥Y=YES * FOB *YES* DEFAULT/LONG COMMANDS =NO FOB «NO» DEFAULT/SHOBT COMMANDS LLL=L08 * FOB (10,25) I N I T I A L (PBICE,CTY) =HI FOB (20, 45) INITIAL (PRICE,QTY) * INDICATES DEFAULT VALUE IMPLICIT INTEGEB (A-Z) LOGICAL EQUC INTEGEB*2 MODE{30) , C M D / » C 0 • / , N O / * N O * / , H I / * H I • / , B E C O V B / * B E V 10GICAL*1 YNDEF,Y/*Y'/,E/*E*/,S/*S'/,N/*N*/,0/*0*/,BLANK/* */ LOGICAL*1 SDUM{10) INTEGEB*2 NAME(6) EQUIVALENCE (NAME (1) , MODE (9) ) INTEGEB*2 DATA,SAVE LOGICAL ATTN BEAL RZ COMMON PERIOD,PRICE,QTY,PBOFIT, DATA (30, 70) ,SAVE{ 100,4) ,ATTN COMMON MINPBF,HAXPBF,MAXPTR,YNDEF(4),REP(3),BUMNUM,NUBHLP COMMON NDMLIT,NUMGET,NUMCMD,NUMDEF,NUMERB,MAXCHR,NUMCHR,RZ COMMON NUMNCA,NUMNEN  C C C  PRELOAD COMMON VARIABLES RUMLIT-0 NUMGET=0 NUMCMD=0 NUMDEF=0 NUMEBB=0 MAXCHB=0 NUMCHB=0 NDMNUM=0 NUMHLP=0 NUMNDA-=0 »UMNDN=0 BEP(1)=0 BEP (2)=0 REP{3)=0 MAXPTR=1 PEBIOD=0 MAXPBF=0 MINPRF=999 SAVE(MAXPTB,4)=0  C C C  SETUP I/O CALL ATNTEP (ATTN) LEN=7 , CALL CNTRL { * BAT E 10',LEN,6)  64 LEN=4 CALL CNTBL('BOLL', LEN,6) CALL FTNCMD(* DEFAULT 7=PSM# 1 ,16) CALL FTNCMD( DEFAOLT 8=IZAK:FUNCTION 1  1  C C C  CHECK FOB BECOVEBY  • ,24)  BON  CALL PAB {MODE(3),NI,24,S6,S6) 6 IF{MODE(3) . NE.BECOVB) GOTO 19 BEAI(7,7) MX,MY,8Z 7 FOBMAT(24X,I3,5X,I3,5X,F5.3) CALL BEADPF (NAME,MX,MY,BZ) BEAD{7,8) MODE (3) , {YNDEF (I) ,1=1 ,3) 8 FOEMAT(10X,A2,26X,3A1) 11 BEAD(7,12,END=60) ICODE,PBICE,QTY,MTIM 12 FOaMAT<I2,3X,2l3,29X,I5) IF(ICODE.EQ.1) CALL SIMUL(.TfiUE.,MTIH) GOTO 11 C C C  CBEATE F I L E S I F NOT  BECOVEBY  BUN  19 CALL DESTBY {*PSM#1 ») CALL CBEATE (* PSM# 1 «,1,0,256) CALL OUTMES {1) C C C  SELECT APPBOPSI ATE MODES 30 I F {MODE <5) . EQ. NO) GOTO 35 YNDEF {1)=Y YNDEF (2) =E YNDEF (3) =S GOTO 40 35 YNDEF (1) =N YNDEF (2)=0 YNDEF (3) =BLANK 40 I F (MODE (7) * EQ. HI) GOTO 50 PBICE=10 QTY=25 GOTO 51 50 PBICE=20 QTY=45  C C C  BEAD IN PBOFIT FUNCTION, THEN C A L L PBOPEB INPUT MONITCB 51 MX=0 CALL BEADPF(NAME,MX,MY,BZ) 60 IF(MODE(3) .EQ.CMD) CALL GCMAND CALL GCYCLE STOP END  65 SUBROUTINE GCMAND C C C  INPUT  MGRITOB - UNSTBUCTUBED  INPUT  IMPLICIT INTEGEB(A-Z) LOGICAL EQUC LOGICAL*1 DOM ( 2 ) , CM B (10) , N/ • N»/# L NGCM D/ . TR U E. / INTEGEB*2 CMD2,G/» G ' / , J / ' J ' / . S / ' S»/#NULI/» •/ EQUIVALENCE (DUM (2) ,CMD{1) ) EQUIVALENCE (DUM (1) ,CMD2) 1GGICAL*1 YNDEF INTEGEB*2 DATA, SAVE LOGICAL ATTN BEAL RZ COMMON PEBIOD,PRICE,QTY,PBOFIT,DATA{30,70),SAVE{100,4),ATTN COMMON MINPBF, MAXPBF,M AXPTR, YNDEF (4) ,BEP (3) , NUMNUfl,NUMHLP COMMON NOMLIT,NUMGET,NUMCMD,NUMDEF,NUMEBR,MAXCHB,NUMCHB,BZ COMMON NUMNBA,NUMNDN C C C  INITIALIZATION CMD2=NULL CALL TIME(O) I F (EQUC { YNDEF ( 1 ) , N ) ) LNGCMD=.FALSE. IF{PEBIOD.GT.O) GOTO 10 CALL GETLIT(.TRUE.,CMD,LEN,10) »RITE{7,5) PRICE, QTY, ( Y N D E F f l ) ,1= 1, 3) 5 FORMAT (* 0MODE=2 (CMD) PRICE=»,I2,» QTY= ,I2,» CALL OUTMES{2) GOTO 80 f  C C C  READ AND  PROCESS COMMAND  10 CALL GETLIT(.FALSE.,CMD,LEN,19) I F (IEN.EQ.0) GOTO 80 IF(CMD2.LT.S) GOTO 12 BTN=CMD2-S+13 GOTO 18 12 I F (CMD2.LT.3) GOTO 15 RTN=CMD2-J«-4 GOTO 18 15 RTN=CMD2-G*1 18 I F ( R T N . L T . 1 .OR. BTN.GT.13) GOTO 80 GOTO(70,50,80,80,80,80,80,80,60,20,30,80,40), BTN C C C  SET PRICE 20 CALL GETNUM{.FALSE.,PRICE,1,30,11 MAXCHB=M AXCHR+5 NUMCHB=NUMCHB+LEN NUMCMD=NUMCMD+1 GOTO 10  C C C  ,12)  SET QUANTITY 30 CALL GETNUM(.FALSE.,QTY,1,70,13,14) MAXCHB=MAXCHB+3  DEF-«,3A1)  I F (LNGCMD) MAXCHR=MAXCHR+5 NUMCH8= NUMCHR+LEN NUMCMD=NDMCMD«-1 GOTO 10 SIMULATE ANCTHEB PIB10 D CALL SI.1IUI. (. FALSE. ,0) MAXCH8=MAXCHl+3 I F (LNGCMD) MAXCBR=MAXCHR + 5 NUMCHR=NUMCHR+LEN NUMCMD=NUMCMD+1 GOTO 10 DISPLAY  HISTORY REPORT  CALL HISTRY MAXCHR=MAXCHR+4 I F (LNGCMD) MAXCHR=MAXCHR + 3 NUMCHR=NOMCHR+LEN NUMCMD=NUMCMD+1 GOTO 10 DISPLAY SORTED HISTOBY CALL SOBTH MAXCHR=MAXCHR+3 I F (LNGCMD) MAXCHR=M AXCHR+5 NUMCHR=NUMCHR*LEN NUMCMD=NUMCMD+1 GOTO 10 DISPLAY GRAPH CALL SGRAPH MAXCHR= MAXCHR + 5 NUMCHR=NUMCHR+LEN NUMCHD=NUMCMD*1 GOTO 10 USER COMMAND EBROR IHES=31 I F (LNGCMD) IMES=18 CALL OUTMES(IMES) I F (LEN. GT.O) NUMERR=NUMERR+ 1 CALL CLRSTR GOTO 10 END  67 SUBROUTINE C C C  GCYCLE  INPUT MONITOR - STRUCTURED  INPUT  IMPLICIT INTEGER (A-Z) LOGICAL EQUC LOGICAL*1 B O O L ( 1 0 ) / 1 0 * ' •/,Y/'Y*/,N/'M*/ LOGICAL*1 YNDEF INTEGER*2 DATA,SAVE LOGICAL ATTN REAL RZ COMMON PERIOD,PRICE,QTY,PROFIT, DATA (30, 7 0 ) , SAVE (100,4) ,ATTN COMMON MINPRF,MAXPRF,MAXPTR,YNDEF(4),REP(3),NUMNUH,NUMHLP COHBCN NUMLIT,NUMGET,NUMCMD,NUMDEF,NUMERR,MAXCHfi,NUMCHR,RZ COMKCN NUMNDA,NUMNEN C C C  INITIALIZATION CALL TIME{0) I F (PERIOD. GT. 0) GOTO 10 CALL GETLIT (.TRUE. , EOOL,LEN, 10) HRITE(7,5) PRICE,QTY, (YNDEF (I) ,1= 1,3) 5 FORMAT {' 0MODE=1 (CYC) PRICE=',I2,* QTY=',I2,* CALL OUTMES{3)  C C C  GET PRICE & QTY, AND  DEF=»,3A1)  SIMULATE  10 CALL GETNUM(.TRUE.,PRICE,1,30,11,12) CALL GETNUM (.TRUE. , QTY, 1,70, 13, 14) NUMCMD=NUMCMD*2 CALL SIMDL{.FALSE. ,0) C C C  DISPLAY HISTORY  REPORT - I F DE-SIRED  2 0 CALL G E T L I T (.TRUE. ,EOOL,LEN, 15) IF(EQUC(BOOL{1) ,N) .OR. (LEN.EQ.O . AND. EQUC (YNDEF (1) ,N) ) ) GOTO 30 I F (EQUC (BOOLJ1) , Y) .OR. (LEN. EQ. 0 .AND. EQUC (YNDEF (1) ,Y)) ) GOTO 25 CALL OOTMES (8) NUMERR=NUMERR+1 GOTO 20 2 5 CALL HISTRY IF(LEN.GT.0) HAXCHR=MAXCHR+1 30 I F (LEN.G-T. 0) MAXCHR=MAXCHR*2 IF(EQUC (BOOL (1) ,YNDEF (1) ).) NUMNDA=NUMNDA+1 NUMCHR=NUMCHR+LEN I F (LEN.EQ.O) NUMDEF=NUMDEF+ 1 C C C  DISPLAY SORTED HISTORY - I F DESIRED  CALL GETLIT (.TRUE. , BOOL,LEN, 16) IF(EQUC(BOOL(1) ,N) .OR. (LEN. EQ.O . AND. EQUC (YNDEF (1) , N) ) ) GOTO 4 IF(EQUC(BOOL(1) ,Y) .08, (LEN.EQ.O . AND. , EQUC (YNDEF (1) , Y) ) ) GOTO 3 CALL OUTMES(8) NUMERR=NUMERR+1 GOTO 30 35 CALL SORTH IF(LEN.GT.O) MAXCHR=MAXCHR+1  68  40 I F (LEN. GT. 0) HAXCHE^MAXCHR+2 I F (EQUC (BOOL (1) , YNDEF (1) j ) 8UMNDA=NUMNDA+1 NUHCHR=NUMCHR+LEN I F (LEN.EQ.O) NUMDEF=NUM DEF+ 1 C C C  DISELAY GRAPH - I F DESIRED CALL GETLIT (.TRUE. , BOOL,LEN, 17) IF(EQUC(BOOL(1) ,N) .OR, (LEN.EQ.O * AND. EQUC (YNDEF (1) ,N))) GOTO 50 I F (EQUC { EOOL ( 1) ,Y).OR, (LEN.EQ.O .AND, EQUC (YN DEF (1) , Y) ) ) GOTO CALL OUTMES{8) NUMERR=NUMERR+1 GOTO 40 45 CALL SGRAPH I F (LEN,GT,0) MAXCHR=HAXCHR+1 50 I F (LEN . GT. 0) HAXCHR = I3AXCHR«-2 I F { E Q U C ( B O O L ( 1 ) , Y N D E F ( 1 ) ) ) NUHNDA=NUHNDA+1 NUMCHR=NUMCHR+LEN I F (LEN.EQ.0) NUMDEF=NUMDEF+1 N 0MCflD=N UMCMD+3 GOTO 10 END  SUBROUTINE GET  GETLIN(STBING,LENGTH)  AN INPDT L I N E FROM THE CRT  IMPLICIT INTEGER (A-Z) LOGICAL EQUC 10GICAL*1 S T B I N G ( 6 0 ) , ELANK/* •/ LOGICAL*1 YNDEF INTEGEB*2 DATA,SAVE LOGICAL ATTN BEAL BZ COMMON PERIOD,PRICE,QTY,PROFIT,DATA(30,70),SAVE(100,4),ATTN COMMON MINPBF, MAXPRF, MAXPTR, YNDEF (4), BEP (3) , N UMNUM , NUMHLP COMMON NUMLIT,NOMGET,NUMCMD,NUMDEF,NUMEBB,MAXCHR,NUMCHR,RZ COMMON NUMNDA,NUMNDN READ A 60 CHARACTER STRING  FROM USER  NUMGET=NUMGET+1 LENGTH=0 HRITE(6,10) FOBMAT (*&: •) DO 15 1=1,60 STBING(I) = BLANK CONTINUE READ(5,20) (STRING (I) ,1=1,60) FORMAT(60A1) STBIP OFF TRAILING BLANKS DO 30 1=1,60 I F (EQUC (STRING (61-1) , BLAKK) ) GOTO 30 LENGTH=6 1-1 GOTO 40 CONTINUE BETUBN END  SUBROUTINE GETLIT (NEWSTR, L I T , L I T L EN ,PRO MPT) GET NEXT LITERAL IN INPUT STBING (UP TO 10 CHARS) LITEBAL I S DELIMITED BY SPACES OR A COMMA I M P L I C I T INTEGER (A-2) LOGICAL EQUC,NEWSTR,ATTN LOGICAL*1 STRING (60) ,CHAB,LIT{10) , BLANK/ «/#COMMA/»,'/ INTEGER S PT B/1/,LENGTH/0/ LOGICAL*1 YNDEF INTEGEB*2 DATA, SAVE BEAL RZ COMMON PERIOD,PRICE,QTY,PROFIT, DATA(30, 70) ,SAVE{100,4) ,ATTN COMMON MINPRF,MAXPRF,MAXPTR,YNDEF(4),REP{3),NUMNUM,NUBHLP COMBCN NUMLIT,NUMGET,NUMCMD,NUMDEF,NUHEBB,MAXCHR,NUMCHB,RZ COMMON NUMND A,NUMN DN 1  INITIALIZATION NUMLIT= NUMLIT+1 LITLEN= 0 DO 5 1=1,10 L I T (I) =BLANK CONTINUE IF(.NOT.NEHSTR .AND. SPTR.LE.LENGTH) GOTO 10 CA1L OUT MES (PBO MPT) CALL GETLIN(STRING,LENGTH) IF(LENGTH.EQ. 0) GOTO 50 SPTR=1 STRIP OFF LEADING BLANKS IF{.NOT.EQUC(STBING(SPTR),BLANK)) GOTO 20 SPTB=SPTB+1 GOTO 10 BUILD ACTUAL L I T E B A L , CHAB  BY CHAB  CHAR=STBING (SPTR) I F (EQUC (CHAB,BLANK) . OR. EQUC(CHAB, COMMA) ) GOTO 30 LITLEN=LITLEN*1 I F (LITLEN. LE. 10) L I T (LITLEN) =CHAR SPTR=SPTR+1 IF(SPTR.GT.LENGTH) GOTO 50 GOTO 20 STRIP OFF TRAILING BLANKS AND COMMAS IF(.NOT.EQUC(STBING(SPTB),BLANK)) GOTO 40 SPTB=SPTB+1 GOTO 30 I F (EQUC (STBING (SPTB),COMMA) ) SPTR=SPTR*1 RETURN ENTRY CIRSTR SPTR=100 RETURN END  SUBROUTINE  GETNUM(NEWNUM,NOMBER,LOW,HIGH,HELP,PROMPT)  GET NEXT INTEGER NUMBER I N INPUT STRING IMPLICIT INTEGER (A-Z) LOGICAL*1 DUM (2) ,LITNUM (11) LOGICAL NEWNUM,BOOL I N T £ G E R * 2 NMCHR2,ZERO/* 0*/#NULL/« »/ EQUIVALENCE(DUM (1) ,NMCH82) LOGICAL*1 YNDEF INTEGER*2 DATA,SAVE LOGICAL ATTN REAL RZ COMMON PERIOD,PRICE,QTY,PROFIT,DATA(30,70),SAVE(100,4),ATT COMMON 8INPBF,MAXPRF,MAXPTR,YNDEF(4),REP(3),NUMNUM,NUMHLP COMMON NUMLIT,NUMGET,NUMCMD,NUMDEF,NUMERR,MAXCHR,NUMCHR,RZ COMMON NUMNCA,NUMNDN INITIALIZATION NUHNUM=NUMNUM+1 NMCHR2=NULL BEFALT=NUMBER BOCL=NEWNUM CALL G E T L I T (BOOL,LITNUM,LITI-EN,PROMPT) I F ( L I T L E N . EQ. 0) GOTO 40 CONVERT STRING LITERAL TO INTEGER NUMBER=0 DO 20 I=1,LITLEN DUM(2)=LITNUM(I) DIGIT=NMCHR 2-ZERO I F ( D I G I T . L T . Q .OR. DIGIT.GT.9) GOTO 30 NUMBER=NUMBEfi*10+DIGIT CONTINUE IF(NUMBER.LT.LOW .OR. NUMBER.GT.HIGH) GOTO 30 IF(NUMBER.EQ.DEFALT) NUMNDN=NOMNDN+1 GOTO 50 REQUEST USER  TO RE-INPUT THE NUMBER  CALL OUTMES (HELP) NUMHLP=NUMHLP+1 BOOL=.TRDE. GOTO 10 OSER TYPED JUST "RETURN", I F (DEFALT.LT.0) GOTO 30 NUMBER=DEFALT NUHEEF=NUMDEF+1 RETURN END  GIVE HIM THE DEFAULT - I F ANY  SUEBOUTINE  HISTRY  OUTPUT MOST BECENT  GAME RESULTS  I K E L I C I T INTEGEB (A-Z) LOGICAL*1 YNDEF INTEGER*2 DATA,SAVE LOGICAL ATTN REAL RZ COMMON PEBIOD,PRICE,QTY,PBOFIT,DATA(30,70) ,SAVE (100,4),ATTN COMMON MINPBF, M AXPBF, M AXPTB , YNDEF (4) ,BEP (3) ,NUMNUM, NUMHLP COMMON NUMLIT,NUMGET,NUMCMD,NUMDEF,NUMEBB,MAXCHR,NUMCHR,RZ COMMON NUMNDA,NUMNDN BEP (1)=BEP (1) +1 I F (PERIOD.GT.0) GOTO 5 CALL OUTMES{7) GOTO 30 K=25 I F (PERIOD.LT.K) K=PERIOD CALL OUTMES{28) DO 20 1=1,K J=PERIOD-K+I 8RITE(6,10) J , S A V E ( J , 1 ) ,SAVE(J,2) ,SAVE(J,3) FORMAT (IX,418) CONTINUE RETURN END  73 SOBROOTINE OUTMES (MSG) C C C  PRINT A MESSAGE ON THE CRT SCREEN IMPLICIT INTEGER (A-Z) LOGICAL*1 YNDEF INTEGER*2 DATA,SAVE LOGICAL ATTN REAL RZ COMMON PERIQD,PRICE,QTY,PROFIT, DATA (30, 70) ,SAVE(100,4) ,ATTN COMMON MINPRF,MAXPRF,MAXPTR,YNDEF(4),REP<3),NUMNOM,NDMHLP COMMON NOMLIT,NUMGET,NUHCMD,NGMDEF,NOMEBR,MAXCHB,NOMCHB,RZ COMeCN NDMNEA,NOMNEN  C GOTO(1,2,3,4,5,6,7,5,9,99,5,12,5,14,15, 16, 17,18,19,5,21, * 5,23,5,25,26,27,2 8,29,30,31,32,3 3,5,34,5,36,5,38,5,40, * 5,42,5,44,5,46,48,49), MSG 1 WRITE(6,1Q1) 101 FORMAT (10 {/) , * 'You a r e t h e G e n e r a l Manager f o r a s m a l l company ', * ' c a l l e d XYZ (name •/ * ' d i s g u i s e d ) , which m a n u f a c t u r e s and s e l l s one p r o d u c t , ', * 'Widgets ( a g a i n •/ * ' d i s g u i s e d ) . I n y o u r c o n t i n u i n g e f f o r t s t o meet », * 'company o b j e c t i v e s »/ * ' - i . e . t o m a x i m i z e p r o f i t (what e l s e ! ! ! ) - *, * ' y o u r e c e n t l y h i r e d a n '/ * 'M.B.A. s t u d e n t , John Doe, t o u n d e r t a k e some *, * •quantitative analysis.*// * 'John was i n s t r u c t e d t o d e v e l o p a model a n d •, * 'computer program t o h e l p •/ * ' f i n d t h e o p t i m a l R e t a i l P r i c e and P r o d u c t i o n *, * 'Quantity f o r Widgets.'/ * ' A f t e r weeks o f d i l i g e n t work he h a s p r o d u c e d a ', * 'very " s o p h i s t i c a t e d " ' / * 'WATFIV program t o do t h e j o b . ' / ) WRITE (6,201) 201 FORMAT(*It i s Monday m o r n i n g , and J o h n i s w a i t i n g *, * ' f o r you when y o u a r r i v e ' / * ' a t t h e o f f i c e . He p r o u d l y p r e s e n t s h i s work t o you. *, * 'Unfortunately,*/ * ' b e i n g f r o m a famous E a s t e r n B u s i n e s s S c h o o l , ', * 'he n e v e r t h o u g h t t o ' / * ' u s e t h e c o m p u t e r t c a c t u a l l y d e t e r m i n e *, * ' t h e optimum a u t o m a t i c a l l y ; ' / * ' i n s t e a d , he d e s i g n e d a program w i t h which ', * 'you c o u l d s e e k t h e o p t i - * / * 'mum y o u r s e l f (by s p e n d i n g p r e c i o u s time a t *, * *a c o m p u t e r t e r m i n a l , * / * ' s i m u l a t i n g t h e r e s u l t s o f d i f f e r e n t *, * 'Price/Quantity combinations).*/) WRITE (6,301) 301 FORMAT(•You r e f r a i n f r o m s t r a n g l i n g J o h n , *, * 'and c a l m l y t h a n k him f o r h i s ' / * ' e f f o r t s ( w h i l e making a m e n t a l memo ', * ' t o h i r e o n l y 0.B.C. g r a d u a t e s ' / * ' i n t h e f u t u r e ) . You t h e n p r o c e e d t o ',  * * * * * * * * * *  'the Computing C e n t r e t o t r y / ' o u t t h e new p r o g r a m . ' / / ' fis you a r r i v e a t t h e t e m i n a l room, *, 'you r e c a l l y o u r m a r k e t i n g manager''s'/ * r e p o r t i n d i c a t i n g t h a t y o u r f i r m ' » s demand', * function i s rather unusual.'/ » You make a m e n t a l n o t e n e t t o l e t your *, ' i n t u i t i o n l e a d you a s t r a y , * / ' and t h e n s t a r t r u n n i n g t h e p r o g r a m . . . ' / / / ' S P r e s s BETUHN t o c o n t i n u e . * } RETURN 2 WRITE(6,102) 102 FOBMAT (25 (/) ,» 1*** THE PBOGEAM •****// * * The . s i m u l a t i o n i s d i r e c t e d by you, t h e u s e r . * / * ' When t h e word "COMMAND :" a p p e a r s , e i t h e r e n t e r a command'/ * ' o r j u s t p r e s s RETURN t o g e t a l i s t o f a v a i l a b l e commands.'/ * » Remember: A l l commands may be t y p e d i n f u l l OR a b b r e v i a t e d »/ * • a s you w i s h . • / / * « Some h e l p f u l h i n t s : ' / * ' 1. The p o s s i b l e p r i c e r a n g e i s 1-30.*/ * * 2. The p o s s i b l e q u a n t i t y r a n g e i s 1-70.'/ * » 3. T h e r e i s one and o n l y one maximum p o i n t . ' / * * 4. The qame w i l l a u t o m a t i c a l l y s t o p a f t e r 25 m i n u t e s . ' / * ' 5. The qame w i l l a l s c s t o p when you f i n d t h e optimum.'/ * * 6. The optimum v a l u e s a r e d i f f e r e n t f o r e v e r y o n e ! ' / * ' 7. a f t e r a few p e r i o d s , be s u r e t o t r y a l l r e p o r t s ' / * » i n o r d e r t o l e a r n what t h e y a r e . . . * / / / ) RETURN 3 WBITE{6,103) 103 FOBMAT (25 {/) , ' 1 *** THE PROGRAM * * * ' / / The proqram w i l l g u i d e you t h r o u g h t h e s i m u l a t i o n , *, * s t e p by s t e p . */ S i m p l y answer a l l q u e s t i o n s a s d i r e c t e d . ' / / * Some h e l p f u l h i n t s : ' / 1. The p o s s i b l e p r i c e r a n q e i s 1-30.'/ 2. The p o s s i b l e q u a n t i t y r a n q e i s 1-70.'/ 3. T h e r e i s one and o n l y one maximum p o i n t . ' / 4. The qame w i l l a u t o m a t i c a l l y s t o p a f t e r 25 m i n u t e s . ' / * 5. The qame w i l l a l s o s t o p when you f i n d t h e optimum. */ * 6. The optimum v a l u e s a r e d i f f e r e n t f o r e v e r y o n e ! * / 7. A f t e r a few p e r i o d s , be s u r e t o t r y a l l r e p o r t s * / * i n o r d e r t o l e a r n what t h e y a r e . . . ' / / / ) RETURN 4 WRITE (6,104) 10 4 FORMAT ( 15 (1X,78 (»$•)/) , 1X , 1 5 (• $ •) ,48 X ,1 5 {» $ «)/1 X , 15 (* $ *) , 2X , * *CONGRATULATIONS! YOU HAVE FOUND THE MAXIMUM!•,2X, * 15 ('$')/1X,15{»$') , 4 8 X , 1 5 ( ' $ » ) / 1 X , 15 (* $*) ,2X, * 'PLEASE TELL THE SUPERVISOR THAT YOU ARE DONE',2X, * 15 {'$'}/lX,15{'$') ,48X,15{»$') / 1 5 ( 1 X , 7 8 ( ' $ » ) / ) ) RETURN 5 WRITE (6, 105) 105 F O R M A T { » 1 * * * I L L E G A L INPUT *** T r y again...,?/) BETORN 6 WRITE{6,106) 106 FOBMAT (/'6ENTEB LOWEST PRICE TO BE DISPLAYED (1-26)') BETUBN 7 WRITE{6,107) 1  75 107  FOBMAT(* ONo r e p o r t s u n t i l y o u have bequn p l a y i n q ! ! ' / ) BETUBN 9 WRITE(6,109) PERIOD,PRICE,QTY,PROFIT 109 FORMAT(//' P e r i o d ',13,* h a s been s i m u l a t e d . . . ' / / * With PBICE= ,13, » and Q U A N T I T Y = » , 13,• y o u r p r o f i t was $* * ,12///) RETURN 12 WRITE{6,112) PRICE 112 FOBMAT(/'SEnter d e s i r e d p r i c e l e v e l (1-30) [',I3,'1«) RETURN 14 WRITE (6,114) QTY 114 FOR MAT (/' S E n t e r d e s i r e d q u a n t i t y p r o d u c e d (1-7C) [',13,']*) RETURN 15 WRITE (6,115) (YNDEF (I) ,1=1,3) 115 FORMAT(/'&8ant t o s e e H i s t o r y R e p o r t (YES o r NO) J" * #3A1, » 3?•) RETURN 16 « R I T E ( 6 , 1 1 6 ) (YNDEF (I),1=1,3) 116 FORMAT (/'SWant t o s e e O r d e r e d R e p o r t (YES o r NO) [',3A1,»]?») RETURN 17 WRITE(6,117) (YNDEF (I) ,1=1,3) 117 FORMAT{/'&Want t o s e e Summary G r a p h (YES o r NO) [ ' , 3 A 1 , * j ? * ) RETURN 18 WRITE(6,118) 118 FORMAT(//* * * * * * O n l y a v a i l a b l e commands a r e : * / / * 'PRICE Set r e t a i l price f o r t h i s period*/ * 'QUANTITY Set production quantity f o r t h i s period'/ * • SIMULATE Simulate t h i s p e r i o d " s r e s u l t s * / * 'HISTORY Provide H i s t o r y Report'/ * 'ORDERING Provide Ordered H i s t o r y Beport'/ * * GRAPH P r o v i d e Summary Graph'//) RETURN 19 WRITE(6,119) 119 FORMAT(/'&COMMAND') RETURN 21 WRITE (6, 121) 121 FORMAT (» I f 100 o t h e r p e o p l e were p l a y i n q t h i s qame r i q h t now,' * /'& how many would be c l o s e r t o t h e optimum t h a n you (0-100)?') RETURN 23 WRITE(6,123) 123 FORMAT {/' How would you r a t e t h e " u s a b i l i t y " o f t h i s program;» * /••£ f r o m 1 t o 9, where 1 = f r u s t r a t i n q , 9 = c o n v e n i e n t ( 1 - 9 ) ? * ) RETURN 25 WRITE (6, 125) 125 FORMAT{/• How would you d e s c r i b e y o u r p r e s e n t a t t i t u d e * * /*S t o w a r d t h i s qame; 1=bored, 9 = e n j o y i n g i t (1-9)?*} RETURN 26 WRITE(6,126) 126 FORMAT (/1X,65 ( ' : ' ) / / * • P l e a s e CAREFULLY answer t h e f o l l o w i n q t h r e e q u e s t i o n s ; ' / ) RETURN 27 WRITE(6,127) 127 FORMAT {/1X,65 (':•)///) RETURN 28 HRITE(6,128) 128 FORMAT(32(/),' H i s t o r y R e p o r t f o r most r e c e n t 25 p e r i o d s . ' / / * « PERIOD PRICE QTY PROFIT'/) BETUBN 1  9  76 29 WHITE (6,12 9) 129 FORMAT (32 (/) ,' H i s t o r y R e p o r t - o r d e r e d by P r o f i t . ' / / * » PERIOD PRICE QTY PROFIT*/) RETURN 30 «RIIE(6,130) 130 FORMAT(///23X,'Graph o f PEOFIT/10 VS. PRICE,QTY*) RETURN 31 WRITE (6,131) 131 FORMAT(//* ***** O n l y a v a i l a b l e commands a r e : * / / * 'PRICE Set r e t a i l p r i c e f o r t h i s p e r i o d * / * «QTY Set p r o d u c t i o n q u a n t i t y f o r t h i s p e r i o d * / * *SIM Simulate t h i s period''s r e s u l t s * / * 'HIST Provide History Report*/ * '08D Provide Ordered History Report*/ * »GRAPH P r o v i d e Summary Graph*//) RETURN 32 BRITE{6,132) 13 2 FORMAT (15 (1X,78 {•$•)/) ,1X,15(*$») ,48X,15 (» $•)/1X ,15 (* $») ,2X, * »Y0U HAVE EXITTED WITH AN ATTENTION INTER UPT. » ,2X, * 15 (*$*)/lX,15(*$») ,48X, 15{*$*)/1X, 15 {* $») ,2X, * •PLEASE T E L L THE SUPERVISOR THAT YOU ARE DONE*,2X, * 15 («$')/lX,15 {•$*) ,48X, 15{*$») / 1 5 ( 1 X , 7 8 ( « $ * ) /) ) RETURN 3 3 WRITE (6 ,133) 133 F08MAT(15{1X,78{*$*)/) ,1X,15('$') ,48X,15 (• $ » ) / 1 X , 15 (*$*) ,2X, * * SORRY, YOU HAVE EXCEEDED THE MAXIMUM TIME. «,2X, * 15 (»$')/lX,15{*$*) ,48X, 15 (»$*)/1X, 15 (« $') ,2X, * * PLEASE TELL THE SUPERVISOR THAT YOU ARE D O N E » , 2 X , * 15 (»$')/1X,15 {*$») , 4 8 X , 1 5 ( * $ » ) / 1 5 ( 1 X , 7 8 { « $ ' ) / ) ) RETURN 3 4 WRITE (6, 134) 134 FORMAT(/* I f 100 o t h e r p e o p l e had p l a y e d t h i s game, how many* * /*8 would h a v e f o u n d t h e optimum i n f e w e r p e r i o d s (0-100) ?») RETURN 36 WRITE (6 , 136) 136 FORMAT(/* I f 100 o t h e r p e o p l e had p l a y e d t h i s game, how many' * /*& would have f o u n d t h e optimum i n l e s s t i m e ( 0 - 1 0 0 ) ? * ) RETURN 38 WRITE (6,138) 138 FORMAT{//' *** F o r t h e n e x t 3 q u e s t i o n s , " 9 " i s b e s t ***•/ * /*SHow u s e f u l was t h e H i s t o r y R e p o r t , f r o m 1 t o 9 ( 1 - 9 ) ? ' ) BETUBN 40 WRITE{6,140) 140 FORMAT(/*SHow u s e f u l was t h e O r d e r e d H i s t o r y R e p o r t ( 1 - 9 ) ? ' ) BETURN 42 WRITE{6, 142) 142 FOB MAT {/'£How u s e f u l was t h e Graph R e p o r t ( 1 - 9 ) ? * ) RETURN 44 8RITE(6,144) 144 FOBMAT(/* I n y o u r s e a r c h f o r t h e optimum, a b o u t how many* * /» p e r i o d s d i d i t t a k e you t o zoom i n o n t h e g e n e r a l * * /•& v i c i n i t y o f t h e optimum PBICE,QTY p a i r ( 1 - 5 0 ) ? * ) BETUBN 46 WBITE{6,146) 146 FORMAT(/* Would you d e s c r i b e y o u r s e a r c h f o r t h e optimum a s * * /• reasonably d i r e c t S s t r u c t u r e d (enter "1 ) or r a t h e r * * /*£ random&haphazard ( e n t e r "2") (1-2)?*) M  77  BETUBN 48 WBITE(6,148) 148 FOBMAT{//////////////////* *** THANK YOU FOB PARTICIPATING ***»/ * ///* P l e a s e r e f r a i n f r c m d i s c u s s i n g t h e game w i t h o t h e r s u n t i l * * //» a f t e r March 3 1 s t . * / / / ) RETURN 49 8BITE(6,149) 149 FOBMAT{//*1 POST-GAME QUESTIONNAIBE*/» ========= = = = = = = = = = = = = = » / / ) 99 BETUBN END  SUBROUTINE  READPF(NAME,MX,MY,RX)  READS IN PROFIT FUNCTION (AFTER RANDOMLY SETTING LOCATION  OF OPTIMAL  POINT)  IMPLICIT INTEGER (A-Z) INTEGER*2 NAME (6) LOGICAL*1 YNDEF REAL RX INTEGER*2 DATA, SAVE LOGICAL ATTN REAL RZ COMMON PERIOD,PRICE,QTY,PROFIT,DATA(30,70) ,SAVE (100,4),ATTN COMMON MINPBF,MAXPRF,MAXPTR, YNDEF (4) ,REP (3) , NUMNUM, NUMHLP COMMON NUMLIT,NUMGET,NUMCMD,NUMDEF,NUflERR,MAXCHR,NUMCHR,RZ COMMON NUMNDA,NUMNDN IF(MX.NE.O) GOTO 60 CALL TIME(2,0,MX) MX=-MX MX=IRAND (MX) MX=IRAND (0) MX=IEAND(10) IF(MX.GT.5) MX=MX*7 MY=IEAND (20) IF(MY.GT.10) MY=MY+7 MZ=IEAND{375) 8X= (MZ + 870. G) /1000.0 HRITE{7,55) (NAME (I) ,1=1,6) ,MX,MY,RX FORMAT (» 0NAME=» ,6A2,» MX=«,I3,» MY=»,I3,» RZ=*,E5.3) DO 61 1=1,MY READ(8,65) CONTINUE DO 66 J=1,70 READ(8,65) (DAT A ( I , 1) ,1=1,MX) , (DATA ( I . J ) ,1=1,30) FORMAT (4713) CONTINUE RETURN END  79 SUBROUTINE C C C  SGRAPH  OUTPUTS & GRAPH OF PROFIT/10  VS.  PRICE,QTY  IMPLICIT INTEGER (A-Z) INTEGER PRVPER/1/ INTEGER*2 S C R ( 3 0 , 7 0 ) / 2 1 0 0 * 1 / LOGICAL*1 SHADE ( 1 2 ) / * * , • 0' , • 1 * , » 2* , * 3* ,»4* ,• 5* , * 6* , * 7» , * 8* * «9*,».*/,YNDEF,FIRST/.TRUE./ LOGICAL*1 P L A B E L ( 3 0 ) / 1 1 * « X',* * , * E* , * C , * I * , * R * , * P * , * *,12* INTEGER*2 DATA, SAVE LOGICAL ATTN REAL RZ COMMON PERIOD,PRICE,QTY,PROFIT,DATA(30,70),SAVE(100,4),ATTN COMMON MINPBF,MAXPBF,MAXPTR,YNDEF (4) ,REP (3 ) , NUMNUM, NUMHLP COMMON NUMLIT,NUMGET,NUMCMD,NUMDEF,NUMERR,MAXCHR,NUMCHR,RZ COMMON NOMNDA,NUMNDN  ,  C C C  INITIALIZATION  1  2 3  4 5 C C C  BEP{3) =REP (3) *1 I F (PERIOD. GT. 0) GOTO 1 CALL ODTMES{7) GOTO 50 CALL OUTMES(30) I F (.NOT. FIRST) GOTO 6 DO 3 1=1,30 DO 2 J=5,70,5 SCR ( I , J ) = 12 CONTINUE CONTINUE DO 5 1=5,30,5 DO 4 J=1,70 S C R ( I , J ) = 12 CONTINUE CONTINUE FIRST=.FALSE. SET UP SCREEN MATRIX  6 DO 10 I=PRVPER,PERIOD SCR (SAVE(I,1) ,SAVE(I,2) ) =SAVE (I,3) /10*2 10 CONTINUE C C C  NOB DRAW THE GRAPH DO 40 J=1,30 I=31-J WRITE(6,30) I,PLABEL (I) , (SHADE (SCB(I,L) ) ,1=1 ,70) 30 F0RMAT(1X,I3,1X,71A1) 40 CONTINUE WRITE(6,45) 45 F O R M A T ( 5 X , 3 1 ( * X » ) , * QUANTITY *,30 { » X * ) / / 6 X , « 1 2 3 4 5 6 7 8 9 * , * 10 (»1«) ,10 (*2») ,10 (*3«) , 10 (*4*) , 10 {* 5* ) ,10 <*6«) , » 7 * / * 15X,6 (»0123456789»),«0«) 50 BETURN END  80 SUBBOUTINE SIMUL (RECOVR,MTIM) C C C  SIMULATE  ANOTHER PERIOD OF PLAY  I M P L I C I T INTEGER(A-Z) LOGICAL RECOVR INTEGER T I M N E W » T I M G L D / 0 / , T O T T I M / 0 / LOGICAL*1 YNDEF INTEGER*2 DATA,SAVE LOGICAL ATTN REAL RZ COMMON PERIOD,PRICE,QTY,PROFIT,DATA(30,70),SAVE{100,4),ATTN COMMON MINPRF,MAXPRF,MAXPTR,YNDEF (4),REP(3),NUMNOM,NUMHLP COMMON NUMLIT,NUMGET,NUMCMD,NUMDEF,NUMEBB,HAXCHfi,NUMCHB,RZ COMMON NUMNDA,NUMNDN C C C  CLEAR TYPEAHEAD AND RUN SIMPLE  SIMULATION  CALL CLRSTR PEEI0D=PERI0D+1 fBOFIT=RZ*DATA(PRICE,QTY) I F (MINPRF.GT.PROFIT) MIN P B F= PRO FIT IF(MAXPRF.LT.PROFIT) M A X P RF = PR 0 F I T SAVE (PERIOD, 1)=PRICE SAVE (PERIOD,2) =QTY SAVE (PERIOD,3) = EROFIT IF(RECOVR) TOTTIM=TOTTIM+MTIM I F (RECOVR) GOTO 15 CALL OUTMES(9) C C C  GET CONNECT TIME OF USER CALL TIME(2,0,TIMNEW) TIMNEB=TIMNEW/100 TIM-TIMNEW-TIMOLD TOTTI M=TOTTIM*TIM TIMOLD=TIMNEW WRITE (7,10) PERIOD,PRICE,QTY,PROFIT,NUMLIT,NUMGET,NUMCMD,NUMDEF, * NOMERR,MAXCHR,NUMCHB,NUHNUM,NUMHLP,NUMNDA,NUMNDN, * (REP(I) ,1=1,3) ,TIM 10 FORMAT (» 1 « , 4 1 3 , 1 2 1 2 , 2 1 1 , 1 5 )  C C C  GET USER ATTITUDES  (ONLY I N EACH 10TH PERIOD)  I F (MOD {(PERIOD-5), 1 0 ) . NE.O) GOTO 15 I1=-1 I2=-1 I3=-1 CALL OUTMES(26) CALL GETNUM {.TRUE. ,11,0,100,20,21) CALL GETNUM (.TRUE.,12,1,9,22,23) CALL GETNUM (.TRUE. ,13, 1,9,24,25) WBITE(7,12) 11,12,13 12 FOBMAT (» 2' ,313) CALL OUTMES (27) CALL TIME(2,0,TIMOLD) TIH0LD=TIMOLD/100  81 C C C  PUT NEW RECORD INTO SORTED CHAIN 15 IF(PERIOD.EQ. 1) GOTO 50 IF(PBOFIT.LT.SAVE(MAXPTR, 3) ) GOTO 20 SAVE(PERIOD,4)=HAXPTB MAXPTR=PERIOD GOTO 50 2 0 GLDITR=MAXPTR PTR=SAVE(OLDPTB,4) DO 30 1=1,499 IF(PTR.EQ.O) GOTO 40 I F ( P R O F I T . GE.SAVE(PTR, 3) ) GOTO 40 OLDPTR=PTR PTR=SAVE(QLDPT8,4) 30 CONTINUE 40 SAVE(PEEI0D,4) = PTR SAVE(OLDPTB,4) =PERIOD  C C C  CHECK FOE END-OF-GAME 50 I F (DATA (PRICE,QTY) .NE.8Q .AND. .NOT. ATTN * GOTO 60 XF (DATA (PRICE,QTY) .EQ. 80) GOTO 52 IF(ATTN) GOTO 54 I F (TOTTIM. GE. 15000) GOTO 56 52 CALL OUTMES (4) IWAY=1 GOTO 58 54 CALL OUTMES(32) IWAY=2 GOTO 58 56 CALL OUTMES(33) IWAY=3 5 8 CALL ATNTRP (ATTN) CALL BELLWT (1) CALL ZEND(IWAY)  C C C  RESET ALL COUNTERS 60 NUMLIT=0 NUMGET=0 NUMCMD=0 NU8DEF=0 NUMERR= 0 MAXCHR=0 NUMCHR=0 SUMRUM=0 NUMHLP=0 NUMNDA=0 NUMNDN=0 REP (1) = 0 REP(2)=0 REP (3) = 0 70 BETURN END  .AND. TOTTIM.LT.15000)  SUBROUTINE SGBTH OUTPUT SORTED  RESULTS  IMPLICIT INTEGEB(A-Z) LOGICAL*1 YNDEF INTEGEB*2 DATA,SAVE LOGICAL ATTN BEAD BZ COMMON PERIOD,PBICE,QTY,PROFIT,DATA(30,70),SAVE{100,4), ATTN COMMON MINPBF,MAXPBF,MAXPTB,YNDEF (4) , BEP (3 ) , NUMNUM ,NUMHLP COMMON NUMLIT,NUMGET NUMCMD,NUMDEF,NUMEBB,MAXCHB,NUMCHB,BZ COMMON NUMNDA,NUMNDN #  SEP (2)=REP{2) +1 I F (PERIOD.GT.0) GOTO 5 CALL OUIHES(7) GOTO 30 K=2 5 I F (PERIOD. LT.K) K=PEBIOD PTB=MAXPTR CALL 0UTMES{29) DO 20 1=1,K WRITE(6,10) PTR,SAVE(PTR, 1) , S AV E { PTR,2) ,SAVE (PTE,3) FORMAT (1X,418) PTR=SAVE(PTB,4) CONTINUE RETURN END  SUBROUTINE ZEND (IWA Y) END-OF-GAME CLEANOP IMPLICIT INTEGER (A-Z) INTEGER Q ( 9 ) / 9 * - 1 / LOGICAL*1 YNDEF INTEGER*2 DATA,SAVE LOGICAL ATTN REAL RZ COMMON PERIOD,PRICE,QTY,PROFIT,DATA(30,70),SAVE(10Q,4),ATTN COMMON MINPRE,MAXPRE,MAXPTR,YNDEF(4) ,REP(3),NUMNUM,NOMHLP COMMON NUMLIT,NUMGET,NUMCMD,NOMDEF,NOMERR,MAXCHR,NOHCHR,BZ COMMON NUMNDA,NUMNDN CALL OUTMES (49) CALL GETNUM {.TRUE. ,Q (1) ,0,100,34, 35) CALL GETNUM{.TRUE.,Q(2),0,100,36,37) CALL GETNUM (.TRUE. ,Q(3) , 1,9,22,23) CALL GETNUM{.TRUE.,Q{4),1,9,24,25) CALL GETNUM (.TRUE. ,Q (5) , 1,9, 38,39) CALL GETNUM(.TRUE.,Q(6),1,9,40,41) CALL GETNUM (.TRUE. ,Q (7) , 1,9,42,43) CALL GETNUM (.TRUE. ,Q (8) ,1 ,50,44,45) CAIL GETNUM (.TRUE. ,Q (9) , 1 ,2, 46, 47) CALL OUTMES (48) » R I T E ( 7 , 1 0 ) IWAY, (Q(I) ,1=1,9) 10 FORMAT( 3 » , 4 1 3 , 1 2 1 2 , 2 1 1 , 1 5 ) CALL RTHAIT{1500) CALL CMD('COPY PSM#1 TO IZAK: REPS (LAST* 1) • ,32) CALL C M D ( « S I G » ,4) STOP END 1  84  Appendix B GAME INSTEUCTIONS Listings few the on  o f t h e pre-game i n s t r u c t i o n s  pages; i n s t r u c t i o n s next the  game v e r s i o n  page, and i n s t r u c t i o n s f o r t h e u n s t r u c t u r e d  two  participant terminal  f o r the structured  a p p e a r on t h e  pages i s  following  only  Appendix C ) .  when  As  given d i r e c t i o n s f o r  a n d s p e c i a l program  game i s d e s c r i b e d  that.  the  features; game  i s  can  be  using  a r e on  game a r e  seen,  the  t h e computer  t h e exact nature actually  next  played  of the (see  INSTRUCTIONS You w i l l soon be p l a y i n g a s i m p l e computer game {a " s i m u l a t i o n " ) . The n a t u r e o f t h e game w i l l be d e s c r i b e d i n d e t a i l when you b e g i n p l a y i n g . I n t h e meantime, p l e a s e r e a d l a n d u n d e r s t a n d ! ) t h e f o l l o w i n g i n s t r u c t i o n s - t h e y a r e s h o r t , s o p l e a s e r e a d them a t l e a s t a few t i m e s :  1) To e n t e r i n p u t i n t o t h e c o m p u t e r , s i m p l y t y p e on t h e computer t e r m i n a l k e y b o a r d a s i f i t were a n o r m a l t y p e w r i t e r . A f t e r you have e n t e r r e d a l i n e , p r e s s t h e RETURN k e y t o t e r m i n a t e t h e i n p u t , 2) I f y o u make a t y p i n g m i s t a k e i n t h e c u r r e n t l i n e , j u s t p r e s s t h e DEL LINE k e y (near t h e t o p r i g h t ) and t h e n r e t y p e t h e l i n e . 3) A l l g u e s t i o n s a s k e d by t h e game a r e o f t h e same f o r m a t ; t h e f o l l o w i n g example i l l u s t r a t e s i t : Rant t o s e e t h e H i s t o r y R e p o r t  (YES o r NO) [ Y E S ] ?  :  As c a n t e s e e n , f i r s t t h e a c t u a l g u e s t i o n i s d i s p l a y e d , f o l l o w e d by t h e r a n g e o f p o s s i b l e answers i n p a r e n t h e s e s , f o l l o w e d - i n b r a c k e t s - by t h e answer which t h e c o m p u t e r w i l l assume you want i f you s i m p l y p r e s s t h e RETURN k e y . T o answer NO t o t h e above g u e s t i o n , y o u c o u l d t y p e NO o r N - and t h e n p r e s s RETURN. To answer YES, y o u c o u l d t y p e YES, Y, o r n o t h i n g a t a l l - and t h e n p r e s s RETURN, 4) F i n a l l y , t h e r e i s one r e p o r t which must be e x p l a i n e d . I t i s a 3 - d i m e n s i o n a l g r a p h , and i s b e s t e x p l a i n e d w i t h an example: PRICE  QTY  PROFIT  3 5 1 4 5  4 2 2 1 4  20 23 17 33 08  I 2 0 I 3 PRICE 3 I 2 2 i 1 I 1 I 5  ===>  12345 QTY  As c a n be s e e n , PRICE i s t h e v e r t i c a l a x i s , QTY i s t h e h o r i z o n t a l a x i s , and t h e PROFIT i s r e p r e s e n t e d by a s i n g l e d i g i t (PROFIT/10 no r o u n d i n g ! ) a t t h e i n t e r s e c t i o n o f t h e a s s o c i a t e d PRICE,QTY p a i r  86 INSTRUCTIONS You w i l l soon be p l a y i n g a s i m p l e computer game (a " s i m u l a t i o n " ) . The n a t u r e o f t h e game w i l l be d e s c r i b e d i n d e t a i l when you b e g i n p l a y i n g . I n t h e meantime, p l e a s e r e a d (and u n d e r s t a n d ! ) t h e f o l l o w i n g i n s t r u c t i o n s - t h e y a r e s h o r t , s o p l e a s e r e a d them a t l e a s t a few t i m e s : 1) To e n t e r i n p u t i n t o t h e computer, s i m p l y t y p e on t h e computer t e r m i n a l k e y b o a r d a s i f i t were a n o r m a l t y p e w r i t e r . A f t e r you have e n t e r r e d a l i n e , p r e s s t h e RETURN key t o t e r m i n a t e t h e i n p u t . 2) I f you make a t y p i n g m i s t a k e i n t h e c u r r e n t l i n e , j u s t p r e s s t h e DEI L I N E k e y ( n e a r t h e t o p r i g h t ) and t h e n r e t y p e t h e l i n e .  3) You w i l l h a v e t o t a k e t h e i n i t i a t i v e i n t h i s game; t h a t i s , you w i l l have t o i n s t r u c t t h e c o m p u t e r what t o do n e x t . To do t h i s , y o u must e n t e r commands v i a t h e k e y b o a r d ( t h e commands w i l l be d e s c r i b e d when you p l a y ) . When you e n t e r commands, you c a n t y p e t h e e n t i r e command, o r any a b b r e v i a t i o n o f i t . T h u s , t o e n t e r t h e command SIMULA! you c o u l d t y p e SIMULATE, SIMUL, SIM, S, e t c . and t h e n p r e s s RETURN. U) Some commands w i l l c a u s e a g u e s t i o n t o be a s k e d by t h e computer. A l l g u e s t i o n s a s k e d w i l l be o f t h e same f o r m a t ; t h e f o l l o w i n g example illustrates i t : Enter  p r i c e t o be c h a r g e d  next  period  (1-30) £ 10] :  As can be s e e n , f i r s t t h e a c t u a l q u e s t i o n i s d i s p l a y e d , f o l l o w e d by t h e r a n q e o f p o s s i b l e a n s w e r s i n p a r e n t h e s e s , f o l l o w e d - i n b r a c k e t s - by t h e answer which t h e c o m p u t e r w i l l assume y o u want i f you s i m p l y p r e s s t h e BETURN k e y . T o answer 2 0 t o t h e a b o v e q u e s t i o n , you c o u l d t y p e 20 - and t h e n p r e s s BETUBN. To answer 10, you c o u l d t y p e 10, o r n o t h i n g a t a l l - and t h e n p r e s s BETUBN. 5) You may a l s o combine commands on one l i n e ( s e p a r a t e d by s p a c e s ! ) i f you w i s h . F o r e x a m p l e , i f you knew t h a t t h e f o l l o w i n q s e q u e n c e o f e v e n t s would o c c u r ( n o t e t h a t a l l l i n e s e n d w i t h a RETOBN): Command : PBICE E n t e r p r i c e t o be c h a r g e d Command : SIMUL you  c o u l d have j u s t  typed  ;  Command : PBICE 20 Command : SIMUL or  even: Command  : PBICE 20 SIMUL  next  period  (1-30) [ 1 0 ] : 20  87 6) F i n a l l y , t h e r e i s one r e p o r t which must be e x p l a i n e d . I t i s a 3 - d i m e n s i o n a l g r a p h , and i s b e s t e x p l a i n e d w i t h an e x a m p l e : PRICE 3 5 1 4 5  QTY — 4 2 2 1 4  PROFIT — 20 23 17 33 08  ===>  5 4 PRICE 3 2 1  | 2 0 I 3 | 2 | J 1 j 12345 QTY  As c a n be s e e n , PRICE i s t h e v e r t i c a l a x i s , QTY i s t h e h o r i z o n t a l a x i s , and t h e PROFIT i s r e p r e s e n t e d by a s i n g l e d i g i t (PROFIT/10 no r o u n d i n g ! ) a t t h e i n t e r s e c t i o n o f t h e a s s o c i a t e d PRICE,QTY p a i r .  88  Appendix C SAMPLE INTERACTION The  next  computer game first  6  appears  pages  (a s t r u c t u r e d  pages, on  instructions,  while  the  terminal  H  the  graphs  and  an pages  several  questionnaire, that  provide  e x a m p l e s o f two s e s s i o n s  version  following of  a l l three  are  much  i n t e r a c t i o n a p p e a r s on t h e  unstructured  periods  more  where t h e d o t s a r e much  of the  version those),  simulation,  interaction The an  opening attitude  reports are presented, readable fainter).  on  the  (Note computer  89 You a r e t h e G e n e r a l Manager f o r a s m a l l company c a l l e d XYZ (name d i s g u i s e d ) , which m a n u f a c t u r e s and s e l l s one p r o d u c t , W i d g e t s ( a g a i n d i s g u i s e d ) . I n y o u r c o n t i n u i n g e f f o r t s t o meet company o b j e c t i v e s - i . e . t c maximize p r o f i t (what e l s e ! 1 ! ) - you r e c e n t l y h i r e d an M.E.A. s t u d e n t , John Doe, t o u n d e r t a k e some g u a n t i t a t i v e a n a l y s i s . J o h n was i n s t r u c t e d t o d e v e l o p a model and c o m p u t e r program t o h e l p f i n d t h e o p t i m a l R e t a i l P r i c e and P r o d u c t i o n Q u a n t i t y f o r W i d g e t s . A f t e r weeks of d i l i g e n t work he has p r o d u c e d a v e r y " s o p h i s t i c a t e d " WATFIV program to do t h e j o b . I t i s Monday m o r n i n g , and J o h n i s w a i t i n g f o r you when you a r r i v e a t t h e o f f i c e . He p r o u d l y p r e s e n t s h i s work t o you. Unfortunately, b e i n g f r o m a famous E a s t e r n B u s i n e s s S c h o o l , he n e v e r t h o u g h t t o u s e t h e c o m p u t e r t o a c t u a l l y d e t e r m i n e t h e optimum a u t o m a t i c a l l y ; i n s t e a d , he d e s i g n e d a program w i t h w h i c h you c o u l d s e e k t h e o p t i mum y o u r s e l f (by s p e n d i n g p r e c i o u s time a t a c o m p u t e r t e r m i n a l , s i m u l a t i n g the r e s u l t s o f d i f f e r e n t P r i c e / Q u a n t i t y combinations). You r e f r a i n from s t r a n g l i n g J o h n , and c a l m l y t h a n k him f o r h i s e f f o r t s ( w h i l e making a m e n t a l memo t c h i r e o n l y 8.-B.C. g r a d u a t e s i n the f u t u r e ) . You t h e n p r o c e e d t o t h e Computing C e n t r e to t r y o u t t h e new program. As you a r r i v e a t t h e t e r m i n a l room, you r e c a l l y o u r m a r k e t i n g manager r e p o r t i n d i c a t i n g t h a t your f i r m ' s demand f u n c t i o n i s r a t h e r u n u s u a l . You make a m e n t a l n o t e n o t t o l e t y o u r i n t u i t i o n l e a d you a s t r a y , and t h e n s t a r t r u n n i n g the program...  ***  THE  PSOGRAM  ***  The program w i l l g u i d e you t h r o u g h t h e s i m u l a t i o n , s t e p S i m p l y answer a l l q u e s t i o n s a s d i r e c t e d .  by  Some h e l p f u l h i n t s : 1. The p o s s i b l e p r i c e r a n g e i s 1-30. 2. The p o s s i b l e g u a n t i t y r a n g e i s 1-70. 3. T h e r e i s one and o n l y one maximum p o i n t . 4. The game w i l l a u t o m a t i c a l l y s t o p a f t e r 25 m i n u t e s . 5. The game w i l l a l s o s t o p when you f i n d t h e optimum. 6. The optimum v a l u e s a r e d i f f e r e n t f o r e v e r y o n e ! 7. A f t e r a few p e r i o d s , be s u r e t o t r y a l l r e p o r t s i n o r d e r t o l e a r n what t h e y a r e . . .  step.,  Enter desired  price level  Enter desired  quantity  Period  1 has been  With PBICE= 15  Bant  (1-30) f  produced  10]  : 15  (1-70) [ 2 5 ]  simulated..,  and QU ANTITY= 25  your  profit  t o see H i s t o r y  Report  (YES o r NO)  Bant t o s e e O r d e r e d  Report  (YES o r NO) [NO ] ?  Rant  Graph  t o s e e Summary  Enter  desired  Enter desired Period  price level quantity  2 h a s been  w i t h PRICE= 15  :  [NO ]?  (YES o r NO) [NO (1-30) [ 1 5 ]  produced  was  ]?  : NO : N :  :  (1-70) [ 2 5 ]  : 35  simulated.,,  and Q0ANTITY= 35  your p r o f i t  was  Want t o s e e H i s t o r y  Report  (YES o r NO) [ NO  ]?  :  Want t o s e e O r d e r e d  Beport  (YES o r NO) [NO  ]?  ;  Want t o s e e Summary  Graph  Enter desired  price level  Enter desired  quantity  Period  3 has been  With PRICE= 15  (YES o r NO) [NO (1-30) [ 1 5 ]  produced  ]?  :  (1-70) [ 3 5 ]  : 45  simulated...  and QUANTITY=  45  your  p r o f i t was  Report  (YES o r NO) [NO  ]?  z  Want t o s e e O r d e r e d  Beport  (YES o r NO) [NO  ]?  :  Want t o s e e Summary  Graph  (YES o r NO) [NO ]?  Enter  level  (1-30) [ 1 5 ]  Enter desired  price  $64  :  Want t o s e e H i s t o r y  desired  $27  quantity  produced  :  ; 10  (1-70) [ 45 ]  : 35  $77  91 Period  4 has been s i m u l a t e d . . .  With PRICE=  10  and  QUANTITY^ 35  your  profit  was  Want t o see H i s t o r y  Beport  (YES o r NO)  f NO  ]?  :  Want t o s e e  Beport  (YES  [NO  j?  :  Ordered  o r NO)  Want t o s e e Summary Graph  (YES  Enter desired  price  (1-30) [ 1 0 ]  Enter desired  quantity  Period With  5 has  level  produced  [NO ;  ]?  :  20  (1-70) [ 3 5 ]  :  been s i m u l a t e d . . .  PBICE= 20  and  QUANTITY=  P l e a s e CAREFULLY answer t h e If  o r NO)  $43  35  y o u r p r o f i t was  following  $43  three q u e s t i o n s :  100 o t h e r p e o p l e were p l a y i n g t h i s game r i g h t now, how many would be c l o s e r t o t h e optimum t h a n you ( 0 - 1 0 0 ) ?  How would you r a t e t h e " u s a b i l i t y " o f t h i s program; from 1 t o 9, where 1 = f r u s t r a t i n g , 9 = c o n v e n i e n t ( 1 - 9 ) ? How would you d e s c r i b e your p r e s e n t a t t i t u d e t o w a r d t h i s qame; 1=bored, 9 = e n j o y i n q i t ( 1 - 9 ) ?  Want t o see H i s t o r y  History  Report  Report  (YES  f o r most r e c e n t  o r NO)  25  PERIOD  PRICE  QTY  PROFIT  1 2 3 4 5  15 15 15 10 20  25 35 45 35 35  27 64 77 43 43  [NO  periods.  ]?  :  : 9  YES  : 7  :  25  92 Want t o s e e O r d e r e d  History  Report  ]?  : Y  R e p o r t - o r d e r e d by P r o f i t .  PERIOD  PRICE  QTY  PROFIT  3 2 5 4 1  15 15 20 10 15  45 35 35 35 25  77 64 43 43 27  Want t o s e e Summary Graph  Graph 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1  (YIS o r NO) [NO  X X. X  (YES o r NO) [NO ]?  o f PROFIT/10  vs.  : Y  PRICE,QTY  •• • •  P R I. C E  • • • ft.  X X. X X X X X. • ••• X X X X XX XXXXXXXXXXXXXXXXXXXXXXXXXXXXX QOANTITY XXXXXXXXXXXXXXXXXXXXXXXXX 123456789111111111122222222223333 33333344444444445555 555555666666 01234567890123 4567890123 4567 89012345678 901234567890123 45  Enter desired  price  level  Enter desired  quantity  (1-30) [ 2 0 ]  produced  (1-70) [ 3 5 ]  : 45  93 Period With  6 has been  PRICE= 20  simulated....  and Q0ANTITY=  45  your  profit  was  Want t o s e e H i s t o r y  Beport  (YES o r NO) [NO  J?  :  Want t o s e e O r d e r e d  Report  (YES o r NO) {NO  ]?  :  Want t o s e e Summary  Graph  (YES o r NO) [NO  Enter  level  (1-30) [ 2 0 ]  desired  price  Enter desired Period With  quantity  7 h a s been  PBICE= 10  produced  )?  :  : 10  (1-70) [ 4 5 ]  : 45  simulated...  and QOANTITY=  45  your p r o f i t  was  Want t o s e e H i s t o r y  Report  (YES o r NO) [NO  ]?  :  Want t o s e e O r d e r e d  Report  (YES o r NO) [NO  ]?  :  Want t o s e e Summary  Graph  (YES o r NO) [NO  Enter desired  price  level  (1-30) [ 1 0 ]  Enter desired  quantity  Period  8 has been  With PRICE=  15  $39  produced  ]?  $55  :  ; 15  (1-70) [ 4 5 ]  ; 55  simulated...  and QUANTITY=  55  your  profit  was  Want t o s e e H i s t o r y  Report  (YES o r NO) [NO  ]?  :  Want t o s e e O r d e r e d  Report  (YES o r NO) [NO  ]?  :  Want t o s e e Summary  Graph  (YES o r NO) [NO  ]?  : Y  $30  94 30 29 28 27 26 25  Graph o f PROFIT/10  X X X X X X•* • •  vs  PRICE,QTY * •4** *  19 X 18 17 P 16 E 15 I . . . . 14 C 13 E 12 11 X 10 X... . 9 X 8 X 7 X 6 X 5 X• •• • 4 X 3 X 2 X IX XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX  *. *«  QO&NTITY  • •» »  XXXXXXXXXXXXXXXXXXXXXXXXX  12345678911111111112222222222333333333344444444445555£55555666666 012345678901234567890123 45678901234567890123 456789012345 Enter  desired price  Enter  desired quantity  Period  9 h a s been  w i t h PRICE=  15  level  {1-30) £ 15]  produced  :  {1-70) [ 5 5 ]  : 40  simulated.  and QUAHTITX= 40  your p r o f i t  was  $70  95 You a r e t h e G e n e r a l Manager f o r a s m a l l company c a l l e d XYZ (name d i s g u i s e d ) , w h i c h m a n u f a c t u r e s and s e l l s one p r o d u c t , W i d g e t s ( a g a i n d i s g u i s e d ) . I n y o u r c o n t i n u i n g e f f o r t s t o meet company o b j e c t i v e s - i . e . t o maximize p r o f i t (what e l s e ! ! ! ) - you r e c e n t l y h i r e d a n M.E.A. s t u d e n t , J o h n Doe, t o u n d e r t a k e some q u a n t i t a t i v e a n a l y s i s . J o h n was i n s t r u c t e d t o d e v e l o p a model and computer program t o h e l p f i n d t h e o p t i m a l R e t a i l P r i c e and P r o d u c t i o n Q u a n t i t y f o r W i d g e t s . A f t e r weeks o f d i l i g e n t work he has p r o d u c e d a v e r y " s o p h i s t i c a t e d " WATFIV program t o do t h e j o b . I t i s Monday m o r n i n g , and J o h n i s w a i t i n g f o r you when y o u a r r i v e a t t h e o f f i c e . He p r o u d l y p r e s e n t s h i s work t o you. U n f o r t u n a t e l y , b e i n g f r o m a famous E a s t e r n B u s i n e s s S c h o o l , he n e v e r t h o u g h t t o use t h e c o m p u t e r t o a c t u a l l y d e t e r m i n e t h e optimum a u t o m a t i c a l l y ; i n s t e a d , he d e s i g n e d a program w i t h which y o u c o u l d seek t h e o p t i mum y o u r s e l f (by s p e n d i n g p r e c i o u s t i m e a t a c o m p u t e r t e r m i n a l , s i m u l a t i n g the r e s u l t s of d i f f e r e n t P r i c e / Q u a n t i t y combinations). You r e f r a i n f r o m s t r a n g l i n g J o h n , a n d c a l m l y t h a n k h i m f o r h i s e f f o r t s ( w h i l e making a m e n t a l memo t o h i r e o n l y O.B.C. g r a d u a t e s i n t h e f u t u r e ) , You t h e n p r o c e e d t o t h e Computing C e n t r e t o t r y c u t t h e new program. As y o u a r r i v e a t t h e t e r m i n a l room, you r e c a l l y o u r m a r k e t i n g manager r e p o r t i n d i c a t i n g t h a t your f i r m ' s demand f u n c t i o n i s r a t h e r u n u s u a l . You make a m e n t a l n o t e n o t t o l e t y o u r i n t u i t i o n l e a d you a s t r a y , and then s t a r t r u n n i n g t h e program... ,  ***  THE PROGRAM ***  The s i m u l a t i o n i s d i r e c t e d by y o u , t h e u s e r . When t h e word "COMMAND :" a p p e a r s , e i t h e r e n t e r a command or j u s t p r e s s RETURN t o g e t a l i s t o f a v a i l a b l e commands., Remember; A l l commands may be t y p e d i n f u l l OR a b b r e v i a t e d a s you w i s h . Some h e l p f u l h i n t s : 1. The p o s s i b l e p r i c e r a n g e i s 1-30. 2. The p o s s i b l e q u a n t i t y r a n g e i s 1-70., 3. T h e r e i s one a n d o n l y o n e maximum p o i n t . 4. The game w i l l a u t o m a t i c a l l y s t o p a f t e r 25 m i n u t e s . 5. The game w i l l a l s o s t o p when you f i n d t h e optimum. 6. The optimum v a l u e s a r e d i f f e r e n t f o r e v e r y o n e ! 7. A f t e r a few p e r i o d s , be s u r e t o t r y a l l r e p o r t s i n o r d e r t o l e a r n what t h e y a r e . . . ,  ***** O n l y a v a i l a b l e PRICE QUANTITY SIMULATE HISTORY ORDERING GRAPH  COMMAND Enter  Set r e t a i l p r i c e f o r t h i s period Set production q u a n t i t y f o r t h i s Simulate t h i s period's r e s u l t s P r o v i d e H i s t o r y Report P r o v i d e Ordered H i s t o r y Report P r o v i d e Summary Graph  period  : PRICE  desired price  COMMAND  commands a r e :  level  (1-30) [ 1 0 ]  : 15  : QUANTITY  Enter d e s i r e d q u a n t i t y COMMAND  : SIMULATE  Period  1 has been  With PRICE= 15  produced  : PRICE  COMMAND  :  Period  2 h a s been  :  simulated...  and QUANTITY=  COMMAND  (1-70) [ 2 5 ]  25  your  profit  was $35  your  profit  was $39  your  profit  was $36  your  profit  was $45  15 QUANTITY 35  SIM  With PRICE= 15  simulated...  and QUANTITY^ 3 5  COMMAND  : P 15 Q 45 S  Period  3 h a s been  With PRICE= 15  simulated...  and QUANTITY=  COMMAND  : P 10 Q 35 S  Period  4 h a s been  With PBICE= 10  45  simulated...  and QUANTITY=  35  97 COMMAND  : P 20 S  Period  5 h a s been  W i t h PBICE= 20  Please If  simulated...  and Q U A N T I T ¥ =  35  your  profit  CAREFULLY answer t h e f o l l o w i n g t h r e e  was $12  questions:  100 o t h e r p e o p l e were p l a y i n g t h i s game r i g h t now, how many would be c l o s e r t o t h e optimum than y o u (0-100)?  How would y o u r a t e t h e " u s a b i l i t y " o f t h i s proqram; from 1 t o 9, where ^ f r u s t r a t i n g , 9 = c o n v e n i e n t (1-9)? How would y o u d e s c r i b e y o u r p r e s e n t a t t i t u d e t o w a r d t h i s game; 1=bored, 9 = e n j o y i n g i t (1-9)?  COMMAND  : 9  :  ***** Only PRICE QUANTITY SIMULATE HISTORY ORDERING GRAPH  available  commands a r e :  Setr e t a i l price f o r t h i s period S e tproduction quantity f o r this S i m u l a t e t h i s p e r i o d s' r e s u l t s P r o v i d e H i s t o r y Report P r o v i d e Ordered H i s t o r y Report P r o v i d e Summary Graph 1  COMMAND  : HIST  History  Report  f o r most r e c e n t  25 periods.  PEBIOD  PBICE  QTY  PROFIT  1 2 3 4 5  15 15 15 10 20  25 35 45 35 35  35 39 36 45 12  period  : 7  : 25  98 COMMAND  : GBDEBING  History Beport PEBIOD  PBICE  QTY  4 2 3 1 5  10 15 15 15 20  35 35 45 25 35  COMMAND  30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1  - ordered  by P r o f i t . PBOFIT 45 39 36 35 12  :G  Graph o f PBOEIT/10  v s . PBICE,QTY  X X X X X X X X X p B c E X X X X X X X X X [XXXXXXXXXXXXXXXXXXXXXXXXXXX QUANTITY XXXXXXXXXXXXXXXXXXXXXXXXX 12345678911111111112222 22222233333333 33444 44444445555555555666666 01234567890123456789012345678901234567890123456789012345  99  Appendix  D  PBOFJT FUNCTION A the  one-quarter portion  computer game program) a p p e a r s  highest is  profit  i n each  along  function, the l e f t  "four-arm thus,  global  simply  edge and t h e n  mountain" monotone  participant  -  entire  two d i m e n s i o n s ,  thinking.  page  edge, y i e l d i n g a  The p r o f i t  yet  the  the function  t h e m a t r i x on t h e n e x t  in  maxima  page, w i t h  Clearly,  a l o n g t h e bottom  increasing  ( r e a d i n by  To r e c r e a t e t h e  w i t h t h e peak a t 80.  maximum and no l o c a l  enough t o keep e a c h  ridge."  reflect  function  on t h e n e x t  row u n d e r l i n e d .  simply a "winding mountain  profit  is,  o f the profit  i s  still  function w i t h one complex  100  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 3 3 3 3 5 5 5 5 5 5 9 9 9 10 14 14 15 21 22 23 30 31 39 41 50 60 70 80  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 2 3 4 4 4 4 7 7 7 8 8 8 11 12 13 13 18 19 20 26 27 28 36 36 46 48 57 67 76 78  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 2 1 2 2 3 2 3 2 3 4 5 4 6 4 6 6 8 6 8 6 9 7 9 9 12 10 13 10 13 10 14 10 14 11 14 15 19 16 20 17 21 18 22 23 28 24 29 25 30 31 37 33 38 34 39 42 48 4 4 50 53 59 55 62 65 70 73 71 74 68 72 64  0 0 0 0 0 0 0 0 0 0 1 2 2 3 3 5 5 5 7 7 8 11 11 11 12 15 16 16 17 17 18 23 24 25 26 32 34 35 42 43 45 54 56 64 67 68 66 61 56  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 2 2 2 4 3 4 4 6 4 6 6 8 6 9 7 9 9 12 10 12 10 13 13 16 14 17 14 17 15 18 18 22 19 22 20 23 20 24 21 24 22 25 27 30 28 32 29 34 31 35 37 42 39 43 40 45 47 51 4 9 53 51 55 58 56 61 56 62 57 62 55 63 56 58 51 53 46 48 40  0 0 0 0 0 0 0 1 1 2 3 5 5 7 8 10 11 11 14 15 15 19 19 20 21 25 25 26 27 28 29 34 36 38 40 45 47 49 50 49 51 52 50 51 48 49 44 38 32  0 0 0 0 0 0 1 1 2 3 5 7 7 9 10 12 13 14 17 17 18 21 22 23 24 28 29 30 30 31 32 37 39 41 <J3 44 43 45 46 43 45 46 44 45 11 42 36 30 24  0 0 0 0 0 1 1 2 3 4 6 8 9 11 12 14 15 16 19 20 21 24 25 26 27 30 31 32 33 34 35 36 36 38 40 41 3S 40 41 38 3S 40 38 38 34 35 29 23 18  0 0 0 0 0 1 2 3 4 6 8 10 10 13 14 16 17 18 21 22 23 26 27 28 29 29 29 30 30 31 32 33 32 34 35 36 34 35 36 33 34 34 31 32 27 28 22 17 12  0 0 0 0 1 2 3 4 5 7 9 11 12 15 16 18 19 20 23 24 25 25 25 26 27 27 25 26 27 28 29 30 28 29 31 32 29 30 31 27 28 29 25 25 21 21 16 11 8  0 0 0 1 1 2 3 5 7 9 11 13 14 17 18 20 21 22 22 22 23 23 22 23 24 24 22 23 24 24 25 26 24 25 26 27 24 25 26 22 23 23 19 19 15 16 11 8 4  0 1 1 1 2 3 5 6 8 10 12 15 16 18 19 19 19 20 20 20 21 21 19 20 21 21 19 20 20 21 22 22 20 21 22 23 19 20 21 16 17 17 14 14 10 10 7 4 0  1 1 1 2 3 4 6 7 9 11 14 16 17 17 18 18 17 18 18 17 18 18 17 17 18 18 16 16 17 17 18 18 16 17 18 18 14 15 15 12 13 13 9 10 7 7 4 0 0  1 1 2 2 4 5 7 9 11 13 15 15 16 16 16 16 15 16 16 15 15 15 14 14 15 15 13 13 14 14 14 15 12 13 13 14 11 11 12 8 8 9 6 6 3 3 0 0 0  1 2 2 3 5 6 8 10 12 14 14 14 14 14 14 14 13 14 14 12 13 13 11 11 12 12 10 10 10 10 11 11 9 9 10 10 7 8 8 5 6 6 3 3 0 0 0 0 0  2 2 3 4 6 7 9 11 13 13 13 12 12 12 12 12 11 11 11 10 10 10 8 9 9 9 7 7 8 8 8 8 6 6 7 7 5 5 5 3 3 3 0 0 0 0 0 0 0  2 3 4 5 6 8 10 12 12 12 11 11 10 10 10 10 9 9 9 7 8 8 6 6 7 7 5 5 5 5 5 6 4 4 4 5 2 3 3 0 0 0 0 0 0 0 0 0 0  2 4 4 6 7 9 11 11 1 1 1 1 10 9 9 9 8 8 6 7 7 6 6 6 4 4 4 4 3 3 3 3 4 4 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0  3 4 5 7 8 10 10 10 10 9 9 8 7 7 6 6 5 5 5 4 4 4 3 3 3 3 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0  101  Appendix  E  SAMPLE PROGRAM OUTPUT A player  listing appears  preceded is  o f t h e computer qame o u t p u t on  by a 0,  the r e s u l t s  the next  page.  On  that  f o r an  paqe, i f a  of  another  is  termination information.  QTY, labels  PROFIT, should  to the l i n e s  The  preceded  The  i f by  l a b e l s a t the bottom by  a 1.  The  #HISTORYS, #ORDERS, tGRAPHS, and be o b v i o u s .  a  is  1, i t  p e r i o d o f s i m u l a t i o n ; i f by a 2, i t  a s e t o f a t t i t u d e q u e s t i o n n a i r e outcomes; and  refer  line  i t i s i n t r o d u c t o r y i n f o r m a t i o n ; i f by  is  output  individual  other l i n e s  a  3, i t  of  the  PERIOD, PRICE, SECS*10  (time)  are:  #GETLITS - # o f s t r i n q l i t e r a l s i n p u t t e d from t h e u s e r #GETLINS - # o f t i m e s a new i n p u t l i n e was t y p e d by t h e u s e r #CCBEANDS - # o f commands e x e c u t e d by t h e u s e r #DEFAULTS - # o f commands h a v i n q d e f a u l t r e s p o n s e s a v a i l a b l e TERRORS - # o f e r r o r s mad by t h e u s e r MAXCHARS - maximum # o f c h a r a c t e r s t h e u s e r c o u l d have t y p e d NUMCHARS - a c t u a l # o f c h a r a c t e r s t h e u s e r d i d t y p e #-GETNUMS - # o f numbers i n p u t t e d from t h e u s e r #HELPS - # o f t i m e s a h e l p messaqe was d i s p l a y e d #MCNADEF - # o f a l p h a b e t i c d e f a u l t s n e t a c c e p t e d by t h e u s e r #NCWNDEF - # o f n u m e r i c d e f a u l t s n o t a c c e p t e d by t h e u s e r  MX= 16 P B I C E - 10  O H A H I: = S A H P L E O H O D I ;=2 ( C H D )  1 1 1 2 1 3 1 4 1 5 2 50 1 6 1 7 1 8 1 9 1 10 1 1 1 1 12 1 13 1 14 1 15 210 0 1 16 1 17 1 18 1 19 1 20 3 1 L I N  P E B  E  I C  C  0 D E  C  1 3 5 9 13 5 15 15 15 15 15 15 15 20 20 10 7 10 10 5 10 8 30 P B I C E  1 3 5 9 13 9 35 40 45 50 30 25 20 35 40 35 9 40 45 40 45 40 40 Q  T Y  m  ^9  Q T Y = ;25  BZ = 1.196 DEF =YES  1 2 2 1 15  9 5 5 5 5  7 1 1 1 1  3 3 3 3 3  0 0 0 0 0  020 021 021 021 02 1  3 3 3 3 3  2 2 2 2 2  0 0 0 0 0  •0 0 0 0 0  0 0 0 0 0  100 5379 000 342 000 287 000 138 000 626  60 38 60 59 59 45 32 22 4 63  7 5 5 5 5 5 5 5 5 6  3 1 1 1 1 1 1 1 1 2  4 3 3 3 3 3 3 3 3 4  0 0 0 0 0 0 0 0 0 0  026 021 021 021 021 021 021 021 021 026  4 3 3 3 3 3 3 3 3 4  2 2 2 2 2 2 2 2 2 2  0 0 0 0 0 0 0 0 0 0  0 0 c 0 0 0 0 0 0 0  0 1 1 1 1 1 1 0 1 0  001 1069 000 178 000 241 000 322 000 194 000 190 000 105 000 188 134 000 001 440  86 63 76 63 95 8  5 5 5 5 7 9  1 1 2 1 3 1  3 3 3 3 4 1  0 0 0 0 0 9  021 021 021 021 026 9 1  3 3 3 3 4  2 2 2 2 2  0 0 0 0 0  0 0 c 0 0  1 1 0 0 0  000 000 000 000 001  P B  # . # # # # M H # # # # ###  0  G E  G E  E I  T L  T L  T  I  I N  T S  S  C  D  0  E F A  M  a A N D  s  0 L T S  E B B  0 B S  A U X «r C c H H A A B B S S  N  G E  H E  0  T N  L P  A  0 M  S  S  N  0 E F  s  N  HOG 0 IBB N SDA N TEP D E F S  OBH  ass I S  130 177 185 191 418  S E C S  *  1 0  103  Appendix F SAMPLE Three examples o f user next  three  position  pairs the  whether  were s i m u l a t e d  vertical axis,  good f e e l  axis).,  protocol  theses profit;  diagrams  diagrams, below  t h e o r d e r i n which  (imagine  price  running  and g u a n t i t y r u n n i n g By  connecting  from  s i x f o r further details).  on  i t is  t h e optimum. <price, from  the  indicates the  diagram,  The  quantity>  1 t o 30 a l o n g  1 t o 70 a l o n g t h e  the p o i n t s ,  f o r what t h e o r i g i n a l p a r t i c i p a n t  c f chapter  appear  •**»  the  or not t h e s u b j e c t found  numbers i n d i c a t e  horizontal  end  On  o f t h e optimum  indicated 2-digit  pages.  PBCTOCOLS  one c a n g e t a  was up t o ( s e e t h e  S A M P L E  -  ' S Y S T E M A T I C  P R O T O C O L *  F I N I S H E D  o  S A M P L E  S O T  .  " S T R U C T U R E D  F I N I S H E D  T R I A L  A N D  E R R O R "  107  Appendix G SUMMARY OF RESULTS This  last  statistical thesis next  appendix  tests  of  summarizes  the  26  hypotheses  (see c h a p t e r s i x f o r d e t a i l s ) . pages,  the  hypotheses  whenever n e c e s s a r y . each  hypothesis  based  upon whether  was a c c e p t e d  are  In the l a s t  was  rejected  results  I n t h e summary  broken  or accepted  down i n t o  the  noted  on  the  subparts whether  {i.e. supported),  hypothesis  respectively.  of  contained i n t h i s  column, i t i s  or n o t t h e n u l l  or rejected,  the  {of  equality)  HYP.  DEPENDENT VARIABLE  IND.  1.  Minutes/Period  2.  SIGH.  A/R  Mode Exp Style Risk  ns 0.09 ns 0.05  Bel acc Re j acc  Termination  Mode Exp Style Risk  ns 0.00 ns ns  Eej Acc Ie j Re j  3.  Confidence  Mode Exp Style Risk  ns 0.01 0.08 0.11  Rej Acc Acc acc  4.  Game  Min/Per. Term, Confid.  ns ns ns  Rej Rej Rej  5.  Experience  Min/Per. Term. Confid.  0.04 0.00 0.00  Acc Acc Acc  6.  Cognitive  Min/Per. Term. Confid.  0.15 0.05 0.01  Acc ACC Acc  7.  Bisk  Min/Per. Terra. Confid.  0.02 0. 11 0.03  Acc Acc Acc  8.  Error  Mode/Exp  ns  Rej  9.  Opening  Version  Level  Style  attitude  Rate  10.  YES/MO  11.  Acc,  12.  Extent  13.  Defaults  VAR.  —,  Defaults  Acc ns  Acc  Exp Style Bisk  ns 0.05 ns  Be j Acc Rej  Mode Exp Style Risk  0.01 ns ns 0.04  Acc Eej Rej Acc  abbreviation  Length  0. 00  ACC  14.  Ccmp. o v e r Time  Min/Per.  0.00  Acc  15.  Comp. o v e r Time  Confid.  ns  Rej  16.  Ccmp. o v e r Time  Usability  0.09  Acc  17.  Comp. o v e r Time  Abbrev.  0.01  Acc  of Defaults  o f Abbrev.  18.  Cemp. o v e r  Time  Histories  0.00  Ace  19.  Comp. o v e r  Time  Grd-Hist  ns  R«1  20. ,  Comp. o v e r  Time  Graphs  0.02  Acc  21.  History  Reports  Mode Exp Style Risk  0.00 0. 03 ns ns  Acc Acc Bej Bej  22.  Ordered  Hist.  Mode Exp Style Bisk  0. 01 ns ns ns  Acc Sej Bej Bej  23.  Graphs  Mode Exp Style Bisk  ns 0. 11 0. 15 ns  Bej Acc Acc Bej  24. .  Protocol  structure  Exp Style Bisk  0. 13 0.03 ns  Acc Acc Bej  25. ,  Protocol  Dispersion  Exp Style Bisk  0. 07 ns ns  Acc Re j Bej  Reports  

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