Forward collision warnings (FCW) are designed to warn drivers of potential collisions, but their effectiveness may vary based on driving conditions and driver responses. This study investigated driver behavior in response to real-world FCW alerts across various driving contexts with the aims of evaluating the prevalence and characteristics of FCW...
This study quantifies bidirectional gazing—when drivers and pedestrians look at one another—in a naturalistic setting. Understanding bidirectional gazing provides insights into the communication dynamics between pedestrians and drivers, and their relation to infrastructural support (e.g., a stop sign). Findings demonstrate that 36% of observed road crossings included at least one...
This research investigates how Artificial Intelligence (AI) and Machine Learning (ML) forecasting methodologies can be leveraged for cold chain capacity planning, specifically utilising Prophet and Seasonal Autoregressive Integrated Moving Average parametrised through grid search. In collaboration with Americold, the world's second-largest refrigerated logistic service provider, the study explores the challenges...
Although the potentialities of artificial intelligence (AI) are motivating its fast integration in organizations, our knowledge on how to capture organizational value out of these investments is still scarce. Relying on an approach to dynamic capabilities that focuses on the team level, we examine how humans and AI create interactions...
Renewable energy resources will play an essential role in the future. However, the understanding of their supply chains and their relationship to emerging technologies like the Internet of Things (IoT) has not been thoroughly investigated. Furthermore, integrating IoT technology can compute the impact on sustainable development goals and develop customized...
In the US, light- to heavy-duty vehicles account for the largest portion of total greenhouse gas emissions. A rapid transition to electric vehicles (EVs) is critical in achieving the Net Zero goal of cutting carbon emissions. Approximately 11% of new car sales are EVs but adoption of this technology is...
Under a relational contract, the value placed on expected future business must outweigh the short-term temptations to deviate for the buyer–supplier relationship to persist. Operational and relational factors that influence this trade-off have been explored, however, there is a considerable lack of research on the moderating effects of supplier and...
In January 2024, the Humanitarian Supply Chain Lab at the Massachusetts Institute of Technology held a roundtable on the theme of scaling construction capacity after disasters, convening individuals from academia, nonprofit, and public and private sector organizations. Participants brought varied perspectives, including considerations of supply chains, government policies, building codes, and private sector construction operations. To ensure candor, the event was held under Chatham House Rule. The roundtable used recent natural disasters and their housing challenges to frame discussions around two goals: (1) identify approaches to increase capacity for rapidly deployable housing solutions after disasters and (2) capture policy and operational constraints that hinder implementation of those rapidly deployable housing solutions. The event and this report seek to catalyze systemic research and provide discrete recommendations to address the challenges and opportunities to restore housing for disaster survivors.
The purpose of this study is twofold: investigating how omnichannel (OC) retailers manage e-fulfillment costs and establishing how these costs relate to the evolution of OC retailers' e-fulfillment strategies. Experts in e-fulfillment from 34 European OC retailers across various sectors participated in an exploratory survey. The study's results reveal that...
This pioneering work explores the main barriers to digitization in small, family-owned retailers (i.e., nanostores), in emerging markets. Given their informal status, shopkeepers tend to stay “under the radar” and distrust any form of digitization because they are concerned that their transactional records might become transparent to the tax authorities...
This paper delves into the critical aspect of demand forecasting within the broader context of optimizing drop trailer management in volatile networks, with a specific focus on a large pallet manufacturer’s supply chain operation. The study underscores the importance of accurate demand forecasting as a foundational element for informing subsequent optimization models.
To enhance understanding of congestion points at ports and provide visibility into the incoming goods flow into the USA, this study focuses on maritime ports, using the Port of Boston and New York/New Jersey as case studies. Based on the Automatic Information System (AIS) data, we aim to develop predictive models for port congestion status and the Estimated Time of Arrival (ETA) of container ships. Additionally, we analyze historical commodity flow data to forecast future values, weights, volumes and categories based on Harmonized System (HS) codes.
In response to the escalating challenges of global inflation, particularly in developing countries like Brazil, this study combines web scraping and machine learning to analyze inflation dynamics within the retail sector. By systematically real-time pricing and product data from a sponsor company and its four main competitors, we focus on...
This study investigates the United States full truckload procurement process and persistent issue of budget overruns faced by shippers during their budgeting. Despite planning through Requests for Proposals (RFPs) that forecast shipping volumes and secure contractual rates with carriers, shippers regularly confront unplanned expenses surpassing their budgets. The key problems...
The detrimental effects of global warming are increasingly evident, necessitating urgent action to reduce Greenhouse Gas emissions. This alarming situation has called for the collective contributions of all actors, i.e. nations, firms, and individuals, to limit the annual warming to below 2 degrees Celsius. Our sponsor company, with a global...
Recent global events, particularly the COVID-19 outbreak, highlighted vulnerabilities in supply chains and the need for resilience in maintaining essential services, emphasizing the requirement for a robust Business Continuity Management (BCM) Plan. The sponsor (A leading pharmaceutical company with a global presence) currently has a revenue-first approach to risk management...
The detrimental effects of global warming are increasingly evident, necessitating urgent action to reduce Greenhouse Gas emissions. This alarming situation has called for the collective contributions of all actors, i.e. nations, firms, and individuals, to limit the annual warming to below 2 degrees Celsius. Our sponsor company, with a global...
The water bottling company, an important player in the beverage industry, places significant emphasis on quantifying its supply chain responsiveness to meet dynamic market demands. This abstract dives into the various metrics employed by this company to enhance its supply chain responsiveness. By analyzing key performance indicators such as lead...
This project introduces a refined approach to cost allocation developed for our sponsor company, a manufacturer and commercializer of chemical solutions for the construction industry. Faced with the complexities of serving thousands of clients across North America, the company seeks to improve its volume-based allocation method to accurately identify profitable...
Food imports from Latin America via ocean transport are important for the U.S. food supply and economic growth. The resilience of the U.S. port network is fundamental in maintaining this supply. A disruption in one or more ports could compromise the network’s capacity to keep a smooth flow of perishable...
This project aims to assist a logistics-focused real estate investment company in proactively identifying underserved markets in the U.S. transportation sector. Utilizing a mix of data from public and private sources and machine learning methods, the goal is to develop a quantitative methodology that highlights potential market investment opportunities for...
The recent escalation in the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) world is adding unprecedented levels of complexity to businesses. Philip Morris International is no exception. Factors such as geopolitical conflicts, raw material shortages, rising inflation, and changes in country legislation are exerting pressure on PMI's supply chain. This pressure...
The freight brokerage industry is at a pivotal juncture, with digital platforms reshaping market dynamics and carrier preferences. This capstone project, undertaken in partnership with Nolan Transportation Group (NTG), employs a predictive machine learning model to decode and understand these evolving preferences. The study leverages a dataset comprising nearly 2...
In this capstone project, the complex relationship between Dell Technologies and its suppliers is examined, with a focus on how the suppliers’ supply chain impacts Dell's greenhouse gas (GHG) emissions. Facing the challenges of climate change, Dell is committed to achieving net-zero GHG emissions by 2050, with a significant focus...
Our capstone project focuses on forecasting sales of the sponsor company's Heat-not-Burn (HNB) products. We estimate future sales of consumables and kits in Italy by looking at monthly data between 2015 and 2023. Sales of the products have a solid positive trend, and regardless of any other parameter, we observe...
