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When Diesel Prices Surge, What Happens to the Supply Chain?

MIT freight expert Chris Caplice explains why smaller carriers may feel the squeeze first, and what businesses can do about it

Oct 14, 2026

2 min

Diesel rarely gets the same public attention as gasoline, but its price can reverberate across almost every part of the economy.

Global diesel prices have climbed to record levels amid significant supply disruptions, putting additional pressure on trucking, agriculture, manufacturing and the movement of goods. The impact is raising an important question for businesses: When does a fuel-price spike become a genuine supply-chain problem?

Dr. Chris Caplice, founder and director of the MIT FreightLab at the MIT Center for Transportation and Logistics, says the freight industry has spent decades developing mechanisms to manage fuel volatility. But that doesn't mean every carrier experiences the impact equally.

“Smaller carriers not only have older equipment and are not getting fully reimbursed, they also have cash flow challenges.”

Caplice notes that fuel surcharge programs help shippers and carriers share the risk of changing diesel prices. However, carriers must pay for fuel immediately while surcharge payments can arrive 30 days or more later — creating particular pressure for smaller operators.

Dr. Chris Caplice serves as the Executive Director of the Massachusetts Institute of Technology’s Center for Transportation & Logistics (CTL) where he is responsible for the planning and management of the research, education, and corporate outreach programs for the center.

View his profile

The consequences can extend well beyond the trucking company.

According to Caplice, every 20-cent-per-gallon increase in diesel costs a shipper approximately three to four cents per mile. Rather than immediately redesigning supply chains, companies are more likely to look for operational efficiencies, including increasing truck utilization or shifting freight to intermodal transportation where practical.

So, what should businesses be watching?

Small-carrier vulnerability: Sustained fuel costs could create significant cash-flow pressure and contribute to some smaller trucking companies exiting the market.
More efficient freight: Companies may increasingly focus on fuller loads, better utilization and other measures that reduce unnecessary miles.
Intermodal opportunities: Higher trucking costs could make shifting appropriate freight between truck and rail more attractive.
Electric trucks: Persistently expensive diesel could strengthen the economic case for electric Class 8 trucks in some applications.
The six-month question: Caplice suggests duration matters. If elevated diesel prices persist for six months, businesses may have greater reason to view the situation as something more significant than temporary volatility.

The broader freight network has considerable capacity to adapt, Caplice says. But the longer high diesel prices persist, the more important efficiency, carrier stability and transportation strategy become for companies trying to manage costs and maintain resilient supply chains.

Dr. Chris Caplice is founder and co-director of the MIT FreightLab and Executive Director of the MIT Center for Transportation & Logistics. His research focuses on freight transportation, procurement, planning, performance and infrastructure.

If you’re interested in speaking with Dr. Caplice about rising diesel prices, freight transportation and what sustained fuel costs could mean for supply chains, simply click on his profile below to arrange an interview today.

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Chris Caplice, PhD

Executive Director | Senior Research Scientist | Founder and Director, MIT Freight Lab

Dr. Caplice's research focuses on improving the way freight transportation is designed, procured, and managed.

Transportation Planning and ModelingTransportation Procurement and BiddingOnline Education in Supply Chain ManagementFreight TransportationFreight and Logistics

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Oct 14, 2026

2 min

When Food Supply Chains Break: Why Traceability Matters

A foodborne illness outbreak can begin with a single contaminated product. Finding where that contamination occurred, however, can mean tracing a product backward through a complicated network of retailers, distributors, brokers, carriers, wholesalers and suppliers. That challenge has been brought into focus by the 2026 Cyclospora outbreak, which has disproportionately affected lettuce and resulted in thousands of confirmed cases and thousands more under investigation in the United States. Dr. Christopher Mejía Argueta, a Research Scientist at the MIT Center for Transportation and Logistics, compares tracing the source of a foodborne illness outbreak to a “criminal investigation. “After officials investigate that, they go back and identify where the retailers sold those potential products, and then they start going upstream in the supply chain.” The process starts with consumers who have been diagnosed and works backward through the supply chain, identifying where products were sold before moving upstream through distributors and brokers and ultimately toward suppliers and vendors. But the more complicated the supply chain becomes, the harder that investigation can be. “The more the complexity grows, the more difficult it is to identify where all of this happened.” Chris Mejía Argueta is a Senior Research Scientist at the MIT Center for Transportation and Logistics with 20 years of experience delivering applied research in 20+ countries. His work helps organizations turn complex supply chain challenges into practical strategies that improve competitiveness, efficiency, and flexibility. View his profile Mejía Argueta explains that contamination could potentially occur at several points, including at the carrier or wholesale level. With fresh produce often moving through numerous intermediaries before reaching consumers, each additional participant can add another layer to the investigation. Once a likely source is identified, recalls become an important tool for containing the outbreak. Potentially contaminated products must be located, brought back and destroyed, while supply chain stakeholders also need to consider the possibility of cross-contamination involving other products that came into contact with them. The 2026 Cyclospora outbreak raises broader questions about how food supply chains can improve visibility and traceability as they become increasingly complex. How can better traceability help investigators identify the source of contaminated food faster? What happens when products move through numerous distributors, brokers and carriers? Where can contamination occur as food moves through the supply chain? How do recalls work once a potentially contaminated product has been identified? What role does supply chain visibility play in limiting cross-contamination? How can food supply chains become better prepared to identify and contain future outbreaks? If you’re interested in speaking with Dr. Mejía Argueta about food supply chain traceability, the challenges of tracking contamination and what the 2026 Cyclospora outbreak reveals about supply chain visibility, simply click on his profile below to arrange an interview today.

Sep 18, 2026

3 min

Where Will AI Change Work First?

Artificial intelligence is changing the workplace, but predicting which jobs will disappear may be the wrong place to start. A recent Boston Globe article looks at new research from Pierre Bouquet, a PhD candidate and research assistant at the MIT Center for Transportation & Logistics (MIT CTL), and Luca Mouchel, a visiting student at MIT CTL completing his master’s thesis in affiliation with MIT. Their AI Labor Exposure Map examines the specific tasks that make up different occupations and measures which of those tasks can already be performed or accelerated by AI. The distinction matters. AI exposure does not mean that a job is about to disappear. It can mean that certain parts of a job are becoming easier to automate while other responsibilities, particularly those involving judgment, oversight and human interaction, remain firmly in human hands. (news.mit.edu) “It’s not a forecast. It’s a measurement.” Pierre Bouquet, MIT Center for Transportation & Logistics, speaking to The Boston Globe (ctl.mit.edu) That idea is central to the broader work Bouquet and Mouchel are doing at MIT CTL. Bouquet’s doctoral research focuses on the future of work and measuring AI’s impact on labor markets, organizations and society. Mouchel’s work focuses on quantifying workforce exposure to AI. Together, their research contributes to MIT CTL’s broader effort to understand how technology changes work at the level of individual tasks. (ctl.mit.edu) Their work is part of the Work Analytics Lab at MIT CTL, which studies AI exposure, job design, productivity and workforce planning. The goal is to give employers and policymakers better information about where AI may automate work, where it may augment people and how jobs themselves could evolve. That approach produces a more nuanced picture of the future of work. Exposure varies considerably across occupations and regions. Knowledge-intensive jobs can contain highly exposed tasks, while many service and physical roles remain less affected by current AI capabilities. Even within an exposed occupation, the parts of the job requiring human judgment, management and interpersonal skills may remain essential. For employers, the question may therefore be less about which jobs AI will replace and more about which parts of work should change. That creates an opportunity to think differently about workforce planning, job redesign, training and how organizations divide responsibilities between people and technology. Story Ideas AI exposure is not job loss: Why measuring tasks gives a clearer picture of workforce risk. Which jobs will AI change first? The occupations and regions showing the greatest exposure. What should stay human? Identifying the tasks where judgment and human interaction still matter most. The entry-level AI question: How automation could reshape the early stages of professional careers. Redesigning work around AI: How companies can use task-level data to rethink jobs, training and productivity. Read the Boston Globe article: AI’s impact on jobs? It’s all over the map. Visit MIT CTL to learn more about their work at the MIT Center for Transportation & Logistics are conducting on on AI, labor markets, workforce planning and the changing nature of work.

Sep 18, 2026

3 min

From Automation to Autonomy: AI’s Next Role in the Supply Chain.

Artificial intelligence is creating new possibilities across global supply chains, but the bigger story may be how far companies are prepared to rethink the way their supply chains actually operate. A recent Financial Times article, “How AI is reshaping supply chains” looks at how AI is changing supply chain planning, logistics and decision making as organizations search for better ways to manage growing complexity and disruption. Among the experts featured is Dr. Maria Jesús Sáenz of the MIT Center for Transportation & Logistics (MIT CTL). At MIT CTL, Dr. Sáenz leads work focused on digital supply chain transformation and serves as Executive Director of the MIT Supply Chain Management master's program. Her research examines how AI and digital technologies are changing collaboration, decision making and performance across supply chains. MIT CTL has long been at the forefront of supply chain research and education, working at the intersection of industry, technology and some of the most pressing challenges facing global supply networks. Today, that increasingly includes understanding where AI can have a meaningful impact and what organizations need to do to put it to work effectively. MIT CTL describes Dr. Sáenz’s insights as part of its ongoing leadership in research spanning AI, digital transformation and supply chain innovation. For Dr. Sáenz, the potential of AI goes well beyond making existing processes faster. It points toward supply chains that can become increasingly autonomous, learn from changing conditions and adapt the way they operate. "It is more automated, more autonomous, more self-learning, self-correcting, more resilient." But technology alone will not create that transformation. Dr. Sáenz emphasizes the importance of redesigning processes, investing in digital capabilities and establishing a clear strategic vision before organizations deploy new technologies. That raises some important questions for supply chain leaders: How autonomous should supply chains become? Where should people remain firmly involved in decision making? Are organizations redesigning their operations around the capabilities of AI, or simply adding new technology to existing processes? These questions are becoming more important as companies explore the next generation of intelligent supply chains. Dr. Sáenz’s research at MIT CTL provides a valuable perspective on what separates incremental automation from deeper supply chain transformation. Her broader research includes intelligent and autonomous supply chains, AI in supply chains and the ways humans and AI can work together more effectively. Story Ideas Are autonomous supply chains actually within reach?: What AI can manage today and where human judgment remains essential. What comes after automation?: How self-learning and increasingly autonomous systems could change supply chain planning and execution. AI without the groundwork: Why companies may struggle to realize the benefits of AI without the right data, processes, digital capabilities and strategy. Human and AI decision making: How organizations can determine which supply chain decisions should be automated, supported by AI or left to people. Can AI make supply chains more resilient?: How intelligent systems could help organizations identify changing conditions and respond more quickly to disruption. Beyond the AI pilot: What separates organizations experimenting with AI from those using it to fundamentally rethink supply chain operations. Read the Financial Times article: How AI is reshaping supply chains Connect with Dr. Maria Jesús Sáenz to learn more about her research at the MIT Center for Transportation & Logistics on AI, digital transformation, human and AI collaboration, and intelligent supply chains.