Re-Examining The Mortality Function Of Carriers In The Transition To A Deregulated Trucking Industry: Are There Organizational Properties Of Carriers That Affect Their Mortality Function In The Transitional Period?
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Type of WorkText
ProgramMaster of Arts
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The deregulation of the trucking industry in 1980 resulted in over-entry of carriers, which in turn spurred intense competition and ultimately led to mortality of many trucking carriers. This thesis studies the factors that led to carriers' exit from the industry, and aims to provide evidence that groups of carriers with varying operational characteristics could be affected differently by the predicting factors of exit, and as such may not share a single exit function as previous research suggests. Several approaches are used to identify differences in the exit functions of motor carriers. The analysis begins by identifying predicting variables that may affect groups of carriers differently. Next, tests are conducted to analyze the differences in probability of exit between cohorts, as well as to analyze how well the pooled model does in predicting exit rates of cohorts of carriers. Additional tests are conducted to compare the means of predicting factors across groups with the notion that if all trucking carriers share the same exit function, then the variables that increase the chances of exit are expected to have higher means for cohorts that are more likely to exit, and vice versa. Furthermore, contingency tables and chi-square tests are used to draw inferences as to whether the exit model for trucking carriers should be pooled. Results show that the pooled logistic regression loses information when used to predict exits for separate groups of carriers. Specifically, separate estimations seem to be able to track the signs of most coefficients, except the organizational choice variables. Also, inconsistencies are observed in comparing the means of predicting factors across groups, as positive variables in the pooled model did not necessarily exhibit higher means for groups with higher exit rates. Results suggest that firms with different operational characteristics may be served by different sets of best practices for survival.