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Journal article
A factor-analytic logit approach to truck driver turnover
Journal of business logistics, Vol.16(1), p.281
01/01/1995
Abstract
A combination of quantitative techniques is used to identify the reasons why truck drivers leave a particular company. Similar techniques have been used to model choices of mode, route, destination, and carrier using nominally scaled, binary dependent variables. The most common of these models is the LOGIT model. These models use sets of explanatory variables to predict the probability that an individual will choose a particular outcome. The explanatory variables constitute a utility function that influences the probability of choosing a particular outcome over other available outcomes. A model of driver turnover behavior is presented and empirically tested. The model may assist managers in controlling turnover. Also, an approach to choice modeling is demonstrated that alleviates some of the problems associated with multicollinearity. The approach combines factor analysis with LOGIT to predict probability of choice. The binary choice for the driver is either to leave or remain with the current employer. Results of this factor-analytic LOGIT approach are compared to those obtained by a LOGIT-only model.
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Details
- Title
- A factor-analytic logit approach to truck driver turnover
- Publication Details
- Journal of business logistics, Vol.16(1), p.281
- Resource Type
- Journal article
- Publisher
- Blackwell Publishing Ltd
- Identifiers
- 99380550690206600
- Academic Unit
- Commerce; Lewis Bear Jr. College of Business
- Language
- English