Exploring Longitudinal Industry‐Level Large Truckload Driver Turnover

Abstract

D river turnover remains a pervasive challenge for truckload (TL) motor carriers. For more than two decades, carriers in this segment have faced the deleterious effects brought on by a persistently high driver turnover rate, including increased costs, decreased productivity, and the erosion of safety performance. In light of these issues, logistics scholars have conducted numerous driver-level and carrier-level investigations to better understand the antecedents of TL driver turnover. Yet, since driver turnover is an industry-wide issue, critical industry-level questions remain unanswered. This paper seeks to complement prior work by adopting labor economic theory and methods to investigate how the industry-level driver turnover rate evolves over time. In particular, we focus on how changing industry employment and wages impact the TL driver turnover rate across large carriers. We test our theory of industry-level turnover using the American Trucking Association's proprietary turnover data for large TL carriers as well as governmental archives on industry and economic conditions obtained from the U.S. Bureau of Labor Statistics and the U.S. Federal Reserve. Estimation results from time-series regression modeling corroborate our theoretical arguments and hold important implications for TL motor carriers, shippers, and other industry stakeholders.

Expanding supply chain management and logistics research: A year in review

“…They offer additional insight and knowledge related to transportation, purchasing, and L&SCM technology. This issue reflects the traditional logistics-focused phenomena that remain the foundation for JBL (Miller et al 2021a(Miller et al , 2021b. It also highlights our desire to expand the Journal's focus to upstream issues that have been everpresent in firms but outside of JBL's traditional focus (Ellram & Tate, 2021).…”

“…Further use of primary data was reflected in quantitative studies that employed the Delphi technique (Durach et al 2021;Kurpjuweit et al 2021), a traditional survey approach (Iyengar et al 2021), a scenario-based role-playing experiment (Falcone et al 2021), and a natural experiment (Wallenburg et al 2021). Archival data were utilized to construct complex network structures (Wiedmer & Griffis, 2021), offer time series analysis (Miller et al 2021a(Miller et al , 2021b, and examine outcomes using a difference-in-differences technique . Finally, Volume 42 offered empirically grounded modeling approaches (Ambra et al 2021;Li et al 2021;Sternberg & Denizel, 2021).…”

Investigating the role of competing wage opportunities in truck driver occupational choice

“…Burks and Monaco (2019) study the effects of hours and earnings on the probability of entering or exiting trucking between periods, but they aggregate earnings across all blue-collar occupations and do not examine the effect of specific-industry wages on the cross-sectional distribution of employment. Miller et al (2020) focus on the effect of industry employment and wages on industry turnover using a time-series research design, which provides an understanding of industry-level turnover behavior but does not assess the behavior of specific individuals. Given the importance of the effects of industry-level and cross-industry factors over time, investigating the impact of these factors on repeated decisions can provide insight into how variation of industry and cross-industry wages affect turnover over time.…”

“…Further, we demonstrate that the wage effect varies across industries. In particular, the majority of studies of driver retention and intention to leave highlight the importance of pecuniary benefits within the truck driving job in predicting satisfaction (Johnson et al, 2009), job perception (Keller, 2002), retention (Prockl et al, 2017), and intention to leave (Williams et al, 2017); however, few studies have investigated the importance of industry wages (Miller et al, 2020) and wages in other industries (Burks & Monaco, 2019) in affecting these turnover dimensions. This study contributes to and extends this nascent literature base by confirming the importance of cross‐industry wages in occupational choice and demonstrating how this effect varies between industries.…”

The Effect of Truckload Driver Turnover on Truckload Freight Pricing

“…To test our hypotheses, we rely on time series modeling techniques (Enders 2015), a research design not often seen in the supply chain literature ( c.f., Miller et al 2020a; Swanson et al 2016). To do so, we collect several industry‐level, longitudinal data series from government and private‐sector sources.…”