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Two questions facing motor carrier managers are (1) whether carriers should specialize in providing full truckload (TL) or less‐than‐truckload (LTL) services vis‐à‐vis offering mix of both and (2) whether this decision is contingent on carrier size. Yet, the literature provides little guidance because research to date has offered contradictory theoretical predictions and inconsistent empirical findings. Drawing on the theory of strategic purity and information processing theory, we explain why service specialization is likely to increase carriers' technical efficiency and why size will have a more pronounced effect on technical efficiency for carriers specializing in LTL services versus TL services. To test our theory, we assemble a panel data set from archival government sources regarding general freight motor carriers' provision of LTL and TL services. We measure carriers' technical efficiency using data envelopment analysis and test our hypotheses by fitting a series of panel data mixed‐effects models. Our results indicate that carriers are most technically efficient when they specialize in one service type. We also find that size positively affects technical efficiency but only for carriers specializing in LTL services; no returns to scale with regard to technical efficiency exist for carriers specializing in TL services.

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.

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Public procurement officials are bound by extensive policies, procedures, and laws. However, procurement professionals perpetually struggle to comply with these vast requirements — particularly in the acquisition of services. The purpose of this research is to explore knowledge-based factors affecting compliance of service contracts. A regression model using data acquired via survey from 219 U.S. Government procurement professionals reveals that the extent of compliance is affected by buyer experience, personnel turnover, the sufficiency with which service requirements are defined, post-award buyer-supplier communication, and the sufficiency of procurement lead time. From these results, implications for practice and theory are drawn. The study concludes with a discussion of limitations and directions for future research.