What about policy research?

Every year, roughly 27% of all jobs in the truck transportation sector (NAICS 484) are reshuffled across motor carriers as existing carriers grow or shrink, new entrants begin operations, and existing firms exit. We take a first look at job gain and job loss dynamics in truck transportation, with a special emphasis on the roles of carrier age and job gain and loss dynamics in the manufacturing sector, the source for most trucking ton‐miles. In doing so, we draw on and extend theory in both supply chain management and economics. We test our predictions using archival administrative data covering 1995 through 2019 from the Census Bureau's Business Dynamics Statistics program that tracks the universe of truck transportation firms with employees. Results from fitting a series of mixed effects models provide strong evidence that job gain and job loss dynamics at trucking firms decline rapidly as carriers age. We further find these age‐related dynamics are moderated by employment dynamics in the manufacturing sector. Robustness testing shows job gains and losses dynamics in manufacturing are more predictive than the same dynamics in the distribution sector (wholesaling, retailing, and warehousing). We discuss implications of these findings for theory and practice.

Section: Introductionmentioning

confidence: 85%

Job gain and job loss dynamics in the truck transportation industry

Miller,

Phares,

Burks

2024

“…By contrast, our theory and empirics suggest unannounced inspection blitzes would better target driver-related phenomena, which is precisely the opposite strategy the FMCSA implemented during our five-year period. Thus, our work contributes to the supply chain policy space (Richey & Davis-Sramek, 2022) by advising policymakers how to best pull levers to improve safety compliance. Furthermore, this responds to Douglas' (2021) call for researchers to better explain the interaction between carriers and regulators by leveraging exogenous variation in the probability of inspection, thus allowing for clear causal identification (Angrist & Pischke, 2009).…”

Section: Motor Carrier Safetymentioning

confidence: 98%

How do trucking companies respond to announced versus unannounced safety crackdowns? The case of government inspection blitzes

Balthrop

Scott

Miller

2023

Ensuring motor carriers comply with safety rules is critical to the efficient workings of supply chains and the safety of the motoring public. However, little is understood regarding how carriers respond to changes in the likelihood of inspection (a.k.a., “crackdowns”) undertaken by the Department of Transportation. Drawing on the regulatory compliance and criminology literature, we extend the rational cheater explanation that undergirds carrier safety research by incorporating principles from attention‐based theory to devise new theoretical predictions regarding how carriers respond to announced versus unannounced inspection crackdowns. To test our theory, we rely on exogenous variation in the probability of inspection from the DOT's use of announced and unannounced inspection “blitzes.” We test predictions using a longitudinal dataset of nearly 10 million truck inspections from 2012 to 2016. We find firms with lower costs of compliance, and higher costs of avoiding inspections improve compliance prior to and during announced blitzes. Small firms with lower costs of avoidance tend to avoid announced blitzes. Unannounced blitzes result in no changes in compliance or avoidance, providing evidence that awareness is driving our results.

“…Furthermore, exploring policy dynamics should facilitate the formulation of guidelines that can foster responsible innovation, safeguarding against potential disruptions or exploitation (Richey & Davis‐Sramek, 2022c). It might be pertinent to study how policies can be structured to encourage transparency and accountability in AI operations within the sector, facilitating an environment of trust and collaboration (Clayton, 2023).…”

Section: Level 1: Factors Contributing To the Ai Adoptionmentioning

confidence: 99%

Artificial intelligence in logistics and supply chain management: A primer and roadmap for research

Richey,

Chowdhury,

Davis‐Sramek

et al. 2023

Self Cite

The dawn of generative artificial intelligence (AI) has the potential to transform logistics and supply chain management radically. However, this promising innovation is met with a scholarly discourse grappling with an interplay between the promising capabilities and potential drawbacks. This conversation frequently includes dystopian forecasts of mass unemployment and detrimental repercussions concerning academic research integrity. Despite the current hype, existing research exploring the intersection between AI and the logistics and supply chain management (L&SCM) sector remains limited. Therefore, this editorial seeks to fill this void, synthesizing the potential applications of AI within the L&SCM domain alongside an analysis of the implementation challenges. In doing so, we propose a robust research framework as a primer and roadmap for future research. This will give researchers and organizations comprehensive insights and strategies to navigate the complex yet promising landscape of AI integration within the L&SCM domain.