The link between driver turnover and motor carrier safety
While it makes sense that an increase in driver turnover would have a negative effect on the carriers' safety, little is known about the exact nature of the relationship and about whether managers can take steps to mitigate those negative effects.
THE ARTICLE
"How does driver turnover affect motor carrier safety performance and what can managers do about it?" by Jason W. Miller of Michigan State University, John P. Saldanha of West Virginia University, Manus Rungtusanatham of The Ohio State University, and Michael Knemeyer of The Ohio State University. Published in the September 2017 issue of the Journal of Business Logistics.
THE UPSHOT
Truck driver turnover—the rate at which drivers voluntarily and involuntarily leave their jobs—and motor carrier safety are big concerns for the trucking industry and shippers who use trucking services. However, relatively little is known about the effect of turnover on safety. While it makes sense that an increase in driver turnover would have a negative effect on the carriers' safety, little is known about the exact nature of the relationship and about whether managers can take steps to mitigate those negative effects.
To answer those questions, Dr. Jason Miller of Michigan State University and his fellow researchers utilized a multimethod research design where they first surveyed managers at for-hire U.S. motor carriers, and then combined that information with data on carriers' safety violations that are publicly available from the U.S. Federal Motor Carrier Safety Administration (FMCSA). Analysis of the data found that the relationship between driver turnover and safety is not linear. Rather, a given percentage-point increase in driver turnover has a more pronounced negative effect on the rate of safety violations for a carrier with a low rate of driver turnover than it has on one with a high rate of driver turnover. The research also found that having formal rules and standard operating procedures for drivers and centralizing decision-making can mitigate the negative effect of driver turnover on some (but not all) facets of motor carrier safety.
Miller, the article's lead author, spoke with Supply Chain Quarterly Senior Editor Susan Lacefield about the practical implications of these findings.
What was the impetus for your research?
This research formed one of the three essays of my Ph.D. dissertation. I decided to examine the issue of how driver turnover related to motor carriers' rates of safety violations because 1) there has been limited empirical work on the topic despite its importance; 2) people have generally assumed that this relationship is linear, by which I mean a 1 percentage-point increase in turnover has the same negative effect on safety regardless of a carrier's baseline turnover rate; and 3) there is limited understanding concerning whether managers can mitigate the presumed negative consequences [of the relationship] between turnover and safety.
What did your research show about the link between driver turnover and motor carrier safety performance?
This research finds evidence that an increase in carriers' driver turnover rates results in worse performance for the "unsafe driving," "hours-of-service compliance," and "vehicle maintenance" safety metrics tracked by the FMCSA. However, for all three metrics, we find that the relationship is highly nonlinear, such that a 1 percentage-point increase in driver turnover has a far more pronounced negative effect when a carrier has a low baseline rate for turnover (for example, 20 percent annually) versus when a carrier has a high baseline rate for turnover (for example, 100 percent). We further found that when carriers determine how drivers execute work activities—what we term "activity control" in our paper—it helps to mitigate the negative consequences of increases in driver turnover on the unsafe driving measure.
Can you provide some examples of activity controls that can improve motor carrier safety?
Activity control represents the extent that the carriers' managers shape how drivers execute their tasks. This includes things such as scheduling work (for example, trying to prevent drivers from operating during the riskiest nighttime hours), establishing standard operating procedures for drivers to follow (for example, how pre-trip inspections should be conducted, how to alert dispatchers of drivers' locations, etc.), and determining what routes drivers should follow.
So companies that have such activity controls in place are able to reduce the negative consequences of turnover on some aspects of safety?
Activity control only mitigates the consequences of driver turnover on unsafe driving; it does not reduce the negative consequences of driver turnover on hours-of-service compliance or vehicle maintenance. In retrospect, this finding makes sense in that we would expect activity controls to more strongly influence drivers' in-cab operations, which are a direct cause of unsafe driving behaviors. In contrast, compliance with hours-of-service rules and maintenance are more directly influenced by carrier-level actions. Thus, activity control is not a panacea that can address all of the negative safety consequences arising from driver turnover.
Were there any other findings from the research that may be surprising or interesting to supply chain professionals?
One thing we found was that higher levels of driver turnover were negatively related to carrier safety for the three metrics tracked by the FMCSA (unsafe driving, hours-of-service compliance, and vehicle maintenance) that we utilized in our study. I had anticipated that this effect would only hold for unsafe driving and hours-of-service compliance, given that these two metrics are under the control of a carrier's drivers to a greater extent than vehicle maintenance is. This just goes to show the importance of addressing turnover.
The research also showed that driver turnover displayed a very strong nonlinear relationship with each of the safety metrics, which indicates that the carriers that should be most worried about a 1 percentage-point increase in turnover are, somewhat paradoxically, those with lower baseline turnover rates. The explanation we offered for this set of findings is that firms with a high baseline turnover rate are likely to have developed routines that help mitigate the consequences of turnover, such that a 1 percentage-point increase in turnover has limited impact on their operations. In contrast, for firms that tend to experience far lower turnover rates, a 1 percentage-point increase in turnover is far more disruptive.
What are some ways managers—both those who work for motor carriers and those who hire motor carriers—can apply the findings of your research?
Motor carrier managers can gain a better understanding of how reducing driver turnover is likely to improve their safety as well as a better understanding of when increases in turnover are likely to be the most detrimental to safety. Shippers can use carriers' data on driver turnover to develop better forward-looking projections of carriers' safety.
Our research further lends credence to the recent report by the National Academies of Sciences, Engineering, and Medicine (NASEM) that urged the FMCSA to collect more detailed information regarding carriers' operating characteristics that could affect their safety. Driver turnover was mentioned in this report as an area warranting data collection. The findings reported in our research corroborate the NASEM's recommendation.
What do you think the key takeaway from your research is for practitioners?
Driver turnover negatively affects carriers' safety across a variety of safety dimensions measured by the Federal Motor Carrier Safety Administration as part of the Compliance, Safety, and Accountability (CSA) program. But this relationship is highly nonlinear, in that a 1 percentage-point increase in driver turnover has a more pronounced negative effect on safety for carriers that have lower baseline rates of driver turnover. Thus, when practitioners evaluate the benefits from reducing turnover, they need to also incorporate costs that stem from lower safety compliance in addition to recruitment and training costs.
Editor's Note: CSCMP members can access JBL articles by clicking on the "Develop" tab at cscmp.org, selecting "Journal of Business Logistics," and using the secure link to the Wiley Online Library.
The launch is based on “Amazon Nova,” the company’s new generation of foundation models, the company said in a blog post. Data scientists use foundation models (FMs) to develop machine learning (ML) platforms more quickly than starting from scratch, allowing them to create artificial intelligence applications capable of performing a wide variety of general tasks, since they were trained on a broad spectrum of generalized data, Amazon says.
The new models are integrated with Amazon Bedrock, a managed service that makes FMs from AI companies and Amazon available for use through a single API. Using Amazon Bedrock, customers can experiment with and evaluate Amazon Nova models, as well as other FMs, to determine the best model for an application.
Calling the launch “the next step in our AI journey,” the company says Amazon Nova has the ability to process text, image, and video as prompts, so customers can use Amazon Nova-powered generative AI applications to understand videos, charts, and documents, or to generate videos and other multimedia content.
“Inside Amazon, we have about 1,000 Gen AI applications in motion, and we’ve had a bird’s-eye view of what application builders are still grappling with,” Rohit Prasad, SVP of Amazon Artificial General Intelligence, said in a release. “Our new Amazon Nova models are intended to help with these challenges for internal and external builders, and provide compelling intelligence and content generation while also delivering meaningful progress on latency, cost-effectiveness, customization, information grounding, and agentic capabilities.”
The new Amazon Nova models available in Amazon Bedrock include:
Amazon Nova Micro, a text-only model that delivers the lowest latency responses at very low cost.
Amazon Nova Lite, a very low-cost multimodal model that is lightning fast for processing image, video, and text inputs.
Amazon Nova Pro, a highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks.
Amazon Nova Premier, the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models
Amazon Nova Canvas, a state-of-the-art image generation model.
Amazon Nova Reel, a state-of-the-art video generation model that can transform a single image input into a brief video with the prompt: dolly forward.
Economic activity in the logistics industry expanded in November, continuing a steady growth pattern that began earlier this year and signaling a return to seasonality after several years of fluctuating conditions, according to the latest Logistics Managers’ Index report (LMI), released today.
The November LMI registered 58.4, down slightly from October’s reading of 58.9, which was the highest level in two years. The LMI is a monthly gauge of business conditions across warehousing and logistics markets; a reading above 50 indicates growth and a reading below 50 indicates contraction.
“The overall index has been very consistent in the past three months, with readings of 58.6, 58.9, and 58.4,” LMI analyst Zac Rogers, associate professor of supply chain management at Colorado State University, wrote in the November LMI report. “This plateau is slightly higher than a similar plateau of consistency earlier in the year when May to August saw four readings between 55.3 and 56.4. Seasonally speaking, it is consistent that this later year run of readings would be the highest all year.”
Separately, Rogers said the end-of-year growth reflects the return to a healthy holiday peak, which started when inventory levels expanded in late summer and early fall as retailers began stocking up to meet consumer demand. Pandemic-driven shifts in consumer buying behavior, inflation, and economic uncertainty contributed to volatile peak season conditions over the past four years, with the LMI swinging from record-high growth in late 2020 and 2021 to slower growth in 2022 and contraction in 2023.
“The LMI contracted at this time a year ago, so basically [there was] no peak season,” Rogers said, citing inflation as a drag on demand. “To have a normal November … [really] for the first time in five years, justifies what we’ve seen all these companies doing—building up inventory in a sustainable, seasonal way.
“Based on what we’re seeing, a lot of supply chains called it right and were ready for healthy holiday season, so far.”
The LMI has remained in the mid to high 50s range since January—with the exception of April, when the index dipped to 52.9—signaling strong and consistent demand for warehousing and transportation services.
The LMI is a monthly survey of logistics managers from across the country. It tracks industry growth overall and across eight areas: inventory levels and costs; warehousing capacity, utilization, and prices; and transportation capacity, utilization, and prices. The report is released monthly by researchers from Arizona State University, Colorado State University, Rochester Institute of Technology, Rutgers University, and the University of Nevada, Reno, in conjunction with the Council of Supply Chain Management Professionals (CSCMP).
Specifically, 48% of respondents identified rising tariffs and trade barriers as their top concern, followed by supply chain disruptions at 45% and geopolitical instability at 41%. Moreover, tariffs and trade barriers ranked as the priority issue regardless of company size, as respondents at companies with less than 250 employees, 251-500, 501-1,000, 1,001-50,000 and 50,000+ employees all cited it as the most significant issue they are currently facing.
“Evolving tariffs and trade policies are one of a number of complex issues requiring organizations to build more resilience into their supply chains through compliance, technology and strategic planning,” Jackson Wood, Director, Industry Strategy at Descartes, said in a release. “With the potential for the incoming U.S. administration to impose new and additional tariffs on a wide variety of goods and countries of origin, U.S. importers may need to significantly re-engineer their sourcing strategies to mitigate potentially higher costs.”
Grocers and retailers are struggling to get their systems back online just before the winter holiday peak, following a software hack that hit the supply chain software provider Blue Yonder this week.
The ransomware attack is snarling inventory distribution patterns because of its impact on systems such as the employee scheduling system for coffee stalwart Starbucks, according to a published report. Scottsdale, Arizona-based Blue Yonder provides a wide range of supply chain software, including warehouse management system (WMS), transportation management system (TMS), order management and commerce, network and control tower, returns management, and others.
Blue Yonder today acknowledged the disruptions, saying they were the result of a ransomware incident affecting its managed services hosted environment. The company has established a dedicated cybersecurity incident update webpage to communicate its recovery progress, but it had not been updated for nearly two days as of Tuesday afternoon. “Since learning of the incident, the Blue Yonder team has been working diligently together with external cybersecurity firms to make progress in their recovery process. We have implemented several defensive and forensic protocols,” a Blue Yonder spokesperson said in an email.
The timing of the attack suggests that hackers may have targeted Blue Yonder in a calculated attack based on the upcoming Thanksgiving break, since many U.S. organizations downsize their security staffing on holidays and weekends, according to a statement from Dan Lattimer, VP of Semperis, a New Jersey-based computer and network security firm.
“While details on the specifics of the Blue Yonder attack are scant, it is yet another reminder how damaging supply chain disruptions become when suppliers are taken offline. Kudos to Blue Yonder for dealing with this cyberattack head on but we still don’t know how far reaching the business disruptions will be in the UK, U.S. and other countries,” Lattimer said. “Now is time for organizations to fight back against threat actors. Deciding whether or not to pay a ransom is a personal decision that each company has to make, but paying emboldens threat actors and throws more fuel onto an already burning inferno. Simply, it doesn’t pay-to-pay,” he said.
The incident closely followed an unrelated cybersecurity issue at the grocery giant Ahold Delhaize, which has been recovering from impacts to the Stop & Shop chain that it across the U.S. Northeast region. In a statement apologizing to customers for the inconvenience of the cybersecurity issue, Netherlands-based Ahold Delhaize said its top priority is the security of its customers, associates and partners, and that the company’s internal IT security staff was working with external cybersecurity experts and law enforcement to speed recovery. “Our teams are taking steps to assess and mitigate the issue. This includes taking some systems offline to help protect them. This issue and subsequent mitigating actions have affected certain Ahold Delhaize USA brands and services including a number of pharmacies and certain e-commerce operations,” the company said.
Editor's note:This article was revised on November 27 to indicate that the cybersecurity issue at Ahold Delhaize was unrelated to the Blue Yonder hack.
The new funding brings Amazon's total investment in Anthropic to $8 billion, while maintaining the e-commerce giant’s position as a minority investor, according to Anthropic. The partnership was launched in 2023, when Amazon invested its first $4 billion round in the firm.
Anthropic’s “Claude” family of AI assistant models is available on AWS’s Amazon Bedrock, which is a cloud-based managed service that lets companies build specialized generative AI applications by choosing from an array of foundation models (FMs) developed by AI providers like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself.
According to Amazon, tens of thousands of customers, from startups to enterprises and government institutions, are currently running their generative AI workloads using Anthropic’s models in the AWS cloud. Those GenAI tools are powering tasks such as customer service chatbots, coding assistants, translation applications, drug discovery, engineering design, and complex business processes.
"The response from AWS customers who are developing generative AI applications powered by Anthropic in Amazon Bedrock has been remarkable," Matt Garman, AWS CEO, said in a release. "By continuing to deploy Anthropic models in Amazon Bedrock and collaborating with Anthropic on the development of our custom Trainium chips, we’ll keep pushing the boundaries of what customers can achieve with generative AI technologies. We’ve been impressed by Anthropic’s pace of innovation and commitment to responsible development of generative AI, and look forward to deepening our collaboration."