UBC Theses and Dissertations
Level of automation in industry and the propensity to strike in certain industries in the United States Thong, Gregory Tin Sin
One of the consequences arising out of the increasing use of automation in industry has been considered to be the effect of this on the trade union's ability to stage a successful strike. In this study, the null hypothesis is tested to determine whether there is a relationship between the level of automation in industry and the propensity to strike in certain industry groups in the United States. Data from two periods is analyzed; Period 1 between 1951 and 1959, and Period 2 between 1960 and 1965. The measurement of the level of automation in industry is made on the assumption that the level of automation is equivalent to the level of application of process control employing electronic computers in these industries. The measurement of propensity to strike is determined by comparing the ranking of the man-days idle due to work stoppages with the ranking of the annual average production worker employment levels among the industries. Secondary data has been adapted for use in the test of the null hypothesis. The data has been extracted mainly from the trade journal, Control Engineering, published by the McGraw-Hill Book Company, and from Analysis of Work Stoppages and the Employment and Earnings Statistics for the United States, published by the United States, Department of Labor, Bureau of Labor Statistics. The results indicated that at the level of significance, a = .05, the test on the null hypothesis indicated that there is no relationship between the level of automation in industry and the propensity to strike for Period 1. For Period 2, the test indicated that there is a relationship between the two variables, under the same level of significance. Further analysis of the results for Period 2 indicated that industries that have achieved or maintained a high or low level of automation are associated with high propensity to strike. The high propensity to strike in high level of automation industries tend to be caused by a small number of strikes of long duration on the average. On the other hand, industries that have maintained a low level of automation have been associated with high propensity to strike in general as a result of a large number of strikes of short duration on the average. A model has been developed to explain the relationship between the two variables. It is concluded that the results of the study, due to the short time spans of the periods studied, may only indicate the short-run or transitory trend. It is possible that these results will be dissimilar to those derived from a long-run study, when equilibrium has set in.
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