https://hdl.handle.net/1721.1/101403 Thu, 09 Apr 2026 05:01:08 GMT 2026-04-09T05:01:08Z https://hdl.handle.net/1721.1/153289 Modeling Causal Effects of Disasters and Disaster Relief Activity on Truckload Spot Rates Rana, Shraddha; Goentzel, Jarrod; Caplice, Chris Freight transportation is an important part of the US economy, of which 60% is movement of goods by trucks. We are particularly interested in full truckloads that move goods for a single customer, from a single origin to a single destination. During disasters, as the demand for truckload transportation increases to stock up and distribute emergency supplies, the ability decreases due to infrastructure damage. The increase in demand is not only from private sector but more importantly from public sector agencies for disaster relief. Moreover, as the public and private sector shippers compete for the same carrier resources, it can result in constrained truckload availability and consequently higher prices. With the increase in frequency of natural disasters it is important to model historical impact in order to be prepared for truckload procurement for future disasters. We contribute to disaster modeling and management literature by measuring causal effects of disasters on a critical system's performance. We quantify the magnitude, geographical spread, timing, and duration of the causal effects of disaster conditions (Hurricane Harvey and Hurricane Irma) and consequent public sector disaster relief activity on private sector truckload spot rates using a difference-in-differences methodology. We find that long-haul loads inbound to nodes near the hurricane's paths are most affected by both disaster conditions and disaster relief activity, experiencing a large magnitude of statistically significant increase in spot rates during hurricane periods. Moreover, the increase in spot rates is both localized and short-lived. Thu, 04 Jan 2024 00:00:00 GMT https://hdl.handle.net/1721.1/153289 2024-01-04T00:00:00Z https://hdl.handle.net/1721.1/143780 The Hidden Costs of Not-So-Friendly Ghost Lanes Acocella, Angela; Caplice, Chris Firms’ (shippers’) procurement of truckload (TL) transportation services is a costly, time-intensive process. The result of these months-long procurement events is typically thousands of contracts between the shipper and transportation service providers (carriers) covering each of the shipper’s lanes (origin-destination pairs) over which it distributes products. Due to TL supply and demand uncertainty, shippers often adopt a coverage strategy to ensure contracted capacity is secured on combinations of lanes on which demand is expected. However, this strategy leads to unnecessary costs and inefficiencies.We find that a large percentage of shippers’ lanes never end up being utilized. We refer to contracted lanes on which no business materializes as ghost lanes. In this study, we characterize ghost lanes to help shippers identify which lanes need not be contracted in the first place to reduce existing startup costs. When none of the expected business on ghost lanes materializes, this disrupts carriers’ network balance and operating efficiencies and impacts service levels to other customers. We empirically demonstrate how the disruptions from ghost lanes from a shipper in one year factor into carriers’ performance and pricing decisions the following year. Moreover, for the lanes that are characteristically ghost lanes but that do materialize, carrier rejection rates are high as are contract prices relative to spot market prices - in other words, shippers are overpaying anyway. We conclude by recommending that firms reconsider their coverage approach to TL transportation procurement by excluding lanes with high probability of becoming ghost lanes (in particular, new lanes) from the traditional annual procurement process. Mon, 04 Jul 2022 00:00:00 GMT https://hdl.handle.net/1721.1/143780 2022-07-04T00:00:00Z https://hdl.handle.net/1721.1/141352 Expanding the Freight Contract Portfolio: Index-Based Freight Contract Design Under Uncertainty Acocella, Angela; Caplice, Chris; Sheffi, Yossi Long-term, fixed-price contracts in the truckload transportation sector have been the prevailing relationship form between firms and their for-hire transportation service providers. While advantageous for planning and budgeting purposes, these contracts do not lend themselves well to contexts in which supply, demand, and market uncertainties are prevalent. We propose an alternative, market-based contract for the truckload sector to reduce the unanticipated costs and performance degradation that result from the standard fixed-price contract. With a uniquely detailed and expansive dataset that captures compounding uncertainties, we build empirical transportation provider decision models. We apply them to index-priced demand across a set of design, implementation, and segmentation strategies and present the those that offer Pareto improvements over the status quo fixed-price contract. Finally, we validate our models with a pilot study of indexed contracts implemented by a large agricultural firm in the US. We employ propensity score matching to quantify the causal effect of indexed pricing on transportation suppliers’ contract compliance and costs the firm incurs during a constrained market period. Wed, 23 Mar 2022 00:00:00 GMT https://hdl.handle.net/1721.1/141352 2022-03-23T00:00:00Z https://hdl.handle.net/1721.1/141351 The End of “Set It and Forget It” Pricing? Opportunities for Market-Based Freight Contracts Acocella, Angela; Caplice, Chris; Sheffi, Yossi In the for-hire truckload market, firms often experience unexpected transportation cost increases due to contracted transportation service provider (carrier) load rejections. The dominant procurement strategy results in long-term, fixed-price contracts that become obsolete as transportation providers’ networks change and freight markets fluctuate between times of over and under supply. We build behavioral models of the contracted carrier’s load acceptance decision under two distinct freight market conditions based on empirical load transaction data. With the results, we quantify carriers’ likelihood of sticking to the contract as their best known alternative priced load options increase and become more attractive; in other words, carriers’ contract price stickiness. Finally, we explore carriers’ contract price stickiness for different lane, freight, and carrier segments and offer insights for shippers to identify where they can expect to see substantial improvement in contracted carrier load acceptance as they consider alternative, market-based pricing strategies. Tue, 22 Mar 2022 00:00:00 GMT https://hdl.handle.net/1721.1/141351 2022-03-22T00:00:00Z https://hdl.handle.net/1721.1/130093 Two Quasi-Experiments Concerning Working Conditions of American Truck Drivers Correll, David; Caplice, Chris; Martens, Bobby Two quasi-experiments are presented concerning the working conditions of American long-haul truck drivers. Using driver weeks as the unit of analysis, we present several statistically significant differences between driver weeks that preceded a truck driver leaving their employer and those that did not, as well as significant behavioral differences between "soft" (low transportation price) and "tight" (high transportation price) market conditions. We also document consistent and predicable patterns in the weekly lives of truck drivers. These experiments provide new insights into the working conditions of America's increasingly scarce long-haul truck drivers. Fri, 05 Mar 2021 00:00:00 GMT https://hdl.handle.net/1721.1/130093 2021-03-05T00:00:00Z https://hdl.handle.net/1721.1/125591 A Discrete Simulation-Based Optimization Algorithm for the Design of Highly Responsive Last-Mile Distribution Networks Snoeck, Andre; Winkenbach, Matthias Online and omnichannel retailers are proposing increasingly tight delivery deadlines, moving closer towards instant on-demand delivery. To operate last-mile distribution systems with such tight delivery deadlines efficiently, defining the right strategic distribution network design is of paramount importance. However, this problem exceeds the complexity of the strategic design of traditional last-mile distribution networks for two main reasons: (1) the reduced time available for order handling and delivery, and (2) the absence of a delivery cut-off time that clearly separates order collection and delivery periods. This renders state-of-the-art last-mile distribution network design models inappropriate, as they assume periodic order fulfillment based on a delivery cut-off. In this study, we propose a metamodel simulation-based optimization (SO) approach to strategically design last-mile distribution networks with tight delivery deadlines. Our methodology integrates an in-depth simulator with traditional optimization techniques by extending a traditional black-box SO algorithm with an analytical model that captures the underlying structure of the decision problem. Based on a numerical study inspired by the efforts of a global fashion company to introduce on-demand distribution with tight delivery deadlines in Manhattan, we show that our approach outperforms contemporary SO approaches as well as deterministic and stochastic programming methods. In particular, our method systematically yields network designs with superior expected cost performance. Furthermore, it converges to good solutions with a lower computational budget and is more consistent in finding high-quality solutions. We show how congestion effects in the processing of orders at facilities negatively impact the network performance through late delivery of orders and reduced potential for consolidation. In addition, we show that the sensitivity of the optimal network design to congestion effects in order processing at the facilities increases as delivery deadlines become increasingly tight. https://hdl.handle.net/1721.1/125591 https://hdl.handle.net/1721.1/125416 A Systems-Level Technology Policy Analysis of the Truck-and-Drone Cooperative Delivery Vehicle System Gaba, Farri; Winkenbach, Matthias This paper concerns a systems-level assessment of the truck-and-drone cooperative delivery system and its integration into urban environments. The analysis is grounded in an assessment of the regulatory environment currently applicable to truck-and-drone logistics, with a particular focus on the state of small unmanned aerial vehicle regulation in the United States. This is followed by a broad discussion of the social, environmental and operational implications of such a system deployed at scale and its potential impact on society. The paper concludes with an appraisal of the compatibility between today's relevant regulation and the evolving truck-and-drone system technology. A proposal for an adaptive regulatory framework to guide the safe, responsible development and deployment of this emerging technology is then proposed that suits the technology's various stakeholders; citizens, municipalities, relevant regulatory bodies and logistics firms. https://hdl.handle.net/1721.1/125416 https://hdl.handle.net/1721.1/124451 Forecasting Long Haul Truckload Spot Market Rates Rana, Shraddha; Caplice, Chris The objective of this paper is to predict long haul truckload spot market rates for the near future. Short term spot rate forecasts help with making operational decisions, estimating budgets for shippers and cash flow for carriers. First, we check if the weekly spot rates time series is a Random Walk process. In which case a Naïve forecast is better than other auto-regressive time series models and thus we use it as our base forecast. We then use exogenous economic indicators as inputs to a Linear Regression model, fit using Elastic Net Regularization, to check if there are leading indicators for truckload spot rates. An important aspect of the truckload spot market is the periodic cycles of soft (decreasing market rates) and tight (increasing market rates) markets. Such changes in the time series, or concept drift, make old forecasting models irrelevant. We thus use two implicit and one explicit concept drift handling methods to retrain our forecasting models. We create forecasts for 1, 4, 8 and 12 weeks into the future and compare MAPEs of the models to conclude that Naïve model outperforms them in each case. We also discuss how explicit detection of concept drift provides useful information on changes in the market cycle for the stakeholders. Mon, 23 Mar 2020 00:00:00 GMT https://hdl.handle.net/1721.1/124451 2020-03-23T00:00:00Z https://hdl.handle.net/1721.1/123694 Elephants or Goldfish?: An Empirical Analysis of Carrier Reciprocity in Dynamic Freight Markets Acocella, Angela J. (Angela Josephine); Caplice, Chris; Sheffi, Yossi Dynamic macroeconomic conditions and non-binding truckload freight contracts enable both shippers and carriers to behave opportunistically. We present an empirical analysis of carrier reciprocity in the US truckload transportation sector to demonstrate whether consistent performance and fair pricing by shippers when markets are in their favor result in maintained primary carrier tender acceptance when markets turn. The results suggest carriers have short memories: they do not remember shippers’ previous period pricing or tendering consistency when making freight acceptance decisions. However, carriers appear to be myopic and respond to shippers’ current market period behaviors, ostensibly without regard to shippers’ previous behaviors. A later version of this working paper has been published in a peer-reviewed journal and can be access here: https://doi.org/10.1016/j.tre.2020.102073 Thu, 23 Jan 2020 00:00:00 GMT https://hdl.handle.net/1721.1/123694 2020-01-23T00:00:00Z https://hdl.handle.net/1721.1/122668 Corporate Supply Chain Disclosures and Factors Determining the Disclosure Approaches: A Palm Oil Case Study Lee, Yin Jin; Bateman, Alexis H Palm oil is one of four big commodities contributing to rapid deforestation. Companies face stakeholder pressure to produce and source palm oil sustainably and to disclose their commitments and actions. This study analyses companies' disclosures to understand the state of disclosure practice, identify typical disclosure profiles, examine the complementarity between commitments and sustainable sourcing practices, understand the factors influencing companies' disclosure profiles, and identify ways to encourage companies to act sustainability and disclose their supply chain information. Data were collected from publicly available documents such as websites, annual reports, and sustainability reports. Methods used include content analysis, means clustering and multinomial logit regression. The resulting disclosure profiles can be used as a guide for companies towards to understand the state of disclosures and ideally, select more aggressive supply chain sustainability approaches. The estimated model quantified the importance of media influence and regulations in encouraging greater corporate supply chain sustainability and disclosures. Sun, 29 Sep 2019 00:00:00 GMT https://hdl.handle.net/1721.1/122668 2019-09-29T00:00:00Z https://hdl.handle.net/1721.1/122268 Quantifying the impact of urban road networks on the efficiency of local trips Merchan, Daniel; Snoeck, Andre; Matthias, Winkenbach City-level circuity factors have been introduced to quantify and compare the directness of vehicular travel across different cities. While these city-level factors help to improve the quality of distance approximation functions for city-wide vehicle movements, more granular factors are needed to obtain accurate shortest path distance approximations for last- mile transportation systems that are typically characterized by local trips. More importantly, local circuity factors encode valuable information about the efficiency and complexity of the urban road network, which can be leveraged to inform policy and practice. In this paper, we quantify and analyze local network circuity leveraging contemporary traffic datasets. Using the city of Sao Paulo as our primary case study and a combination of supervised and un-supervised machine learning methods, we observe significant heterogeneities in local network circuity, explained by dimensional and topological properties of the road network. Locally, real trip distances are about twice as long as distances predicted by the L1 norm. Results from Sao Paulo are compared to seven additional urban areas in Latin America and the United States. At a coarse-grained level of analysis, we observe similar correlations between road network properties and local circuity across these cities Wed, 31 Jul 2019 00:00:00 GMT https://hdl.handle.net/1721.1/122268 2019-07-31T00:00:00Z https://hdl.handle.net/1721.1/114146 Revenue Mangement in Last-Mile Delivery: State-of-the-Art and Future Research Directions Snoeck, Andre; Merchan, Daniel; Winkenbach, Matthias This paper explores future avenues of research for revenue management in last-mile delivery. First, we review earlier efforts in this field, which have focused primarily on the problem of attended home deliveries (AHD) of groceries. Second, based on a topological classification of last-mile delivery characteristics, we identify relevant extensions inspired in current industry trends. Finally, we outline how existing models should be extended for these new problems and discuss promising streams of future research. Tue, 13 Mar 2018 00:00:00 GMT https://hdl.handle.net/1721.1/114146 2018-03-13T00:00:00Z https://hdl.handle.net/1721.1/113244 A Framework for Implementing Blockchain Technologies to Improve Supply Chain Performance Debabrata, Ghosh; Albert, Tan The objective of this paper is to describe the contemporary issues that supply chains face using the information sharing dimension and analyze blockchain technology’s capabilities to address these issues. We discuss select issues in managing contemporary supply chains from an information sharing perspective namely, information coordination challenges, effect of product and service manifestation on information complexity, effect of customer demand manifestation on information flow, outsourcing and globalization effects on information flow, and new emerging threats to supply chains by affecting information vulnerability. These issues are further categorized into- confidentiality and trust issues, inability to share information between supply chain partners, limitations of IT systems and lack of data standards. To address these issues, a unifying framework describing the applicability of blockchain has been presented that will guide companies in designing and implementing potential blockchain solutions to address issues in information exchange among supply chain partners. Blockchain based research is in nascent stages and this paper aims to add to this emerging research paradigm by analyzing blockchain technology through the information sharing dimension of supply chains. (this record is metadata only) Fri, 19 Jan 2018 00:00:00 GMT https://hdl.handle.net/1721.1/113244 2018-01-19T00:00:00Z https://hdl.handle.net/1721.1/109375 Internet of Things and Supply Chains: A Framework for Identifying Opportunities for Improvement and Its Application Phadnis, Shardul Management and technology experts believe that the internet of things (IoT) has the potential to radically transform today’s supply chains. Several practice-focused publications describe various ways in which IoT capabilities can affect the supply chains in positive and negative ways. However, no generic framework describing the peculiar effects of IoT on supply chains has yet emerged. This study presents a theoretical framework to articulate the distinct ways in which the IoT can influence the management of supply chains. The use of this framework is illustrated by applying it to identify opportunities for improving two supply chains: the supply chain described in the famed “Beer Distribution Game” and a revised version of that supply chain. This framework, grounded in the foundation of organizational information processing theory, can be of practical use in guiding organizations envision novel ways to improve the performance of their supply chains by deploying the IoT capabilities. Fri, 26 May 2017 00:00:00 GMT https://hdl.handle.net/1721.1/109375 2017-05-26T00:00:00Z https://hdl.handle.net/1721.1/106930 Financing the SME Value Chains Asad, Ata; Manish, Shukla; Mahender, Singh This research work is built upon case studies from Malaysia and India and surveys conducted on the supply and demand of SME finance in Malaysia. Addressing SMEs’ needs for finance, it is assessed that formal financial lending organizations represent a weak link in the financial supply chain for SMEs in the region. A lack of collateral and limited access to venture and growth capital are some of the obstacles that SME owners face when seeking finance for their businesses. This lack of affordable financing options stymies the growth of SMEs in Asia. This work classifies nine areas of demand for SME capital and suggests that banks in the region need to redesign their lending portfolios to better evaluate and manage the SME’s needs for finance. To help clarify the risks, this paper shows how the different sources of SME financing could be weighted with the so-called 5Cs framework viz. capacity, capital, character, collateral and condition. It suggests that the lending organizations should adopt more innovative ways to analyze SME loans, and gain a deeper understanding of how these enterprises fund their supply chains. Eleven key devices or mechanisms are discussed to leverage the lending process. Tue, 14 Feb 2017 00:00:00 GMT https://hdl.handle.net/1721.1/106930 2017-02-14T00:00:00Z https://hdl.handle.net/1721.1/104928 Estimating Demand for Substitutable Products when Inventory Records are Unreliable Steeneck, Daniel; Eng-Larsson, Fredrik; Jauffred, Francisco We present a procedure for estimating demand for substitutable products when the inventory record is unreliable and only validated infrequently and irregularly. The procedure uses a structural model of demand and inventory progression, which is estimated using a modified version of the Expectation Maximization-method. The procedure leads to asymptotically unbiased estimates without any restrictive assumptions about substitution patterns or that inventory records are periodically known with certainty. The procedure converges quickly also for large product categories, which makes it suitable for implementation at retailers or manufacturers that need to run the analysis for hundreds of categories or stores at the same time. We use the procedure to highlight the importance of considering inventory reliability problems when estimating demand, first through simulation and then by applying the procedure to a data set from a major US retailer. The results show that for the product category in consideration, ignoring inventory reliability problems leads to demand estimates that on average underestimate demand by 5%. It also results in total lost sales estimates that account for only a fraction of actual lost sales. Fri, 21 Oct 2016 00:00:00 GMT https://hdl.handle.net/1721.1/104928 2016-10-21T00:00:00Z https://hdl.handle.net/1721.1/104649 A Decision Making Framework for Reverse Logistics Network Design Tan, Albert; Chanchaichujit, Janya The main objective of this research is to answer the following research question “How should a company design their reverse logistics network in a more efficient or responsive way?” In this research, a conceptual framework has been developed based on several key factors for network design. Through the analysis of each key factor affecting network design decision, we have built a conceptual framework for reverse logistics network for companies to decide on whether to centralize versus decentralize their reverse logistics operations, and whether to outsource or insource some of their operations? Some existing studies are able to fit well in our proposed framework, giving us better insights to decision making in reverse logistics network design. The proposed conceptual framework is helpful for the companies or organizations to make better decisions when designing their reverse logistics operations to achieve a lean or responsive network. Wed, 05 Oct 2016 00:00:00 GMT https://hdl.handle.net/1721.1/104649 2016-10-05T00:00:00Z https://hdl.handle.net/1721.1/104095 A proposed set of criteria for supply chain strategy evaluation Perez-Franco, Roberto This note explores the applicability of evaluation criteria to the problem of evaluating the supply chain strategy of an organization. A discussion of supply chain strategy evaluation is relevant today, as the validity of the dominant approach – proposed two decades ago and based on matching types – has come into question. While evaluation criteria have a long history in other disciplines, they are new to supply chain strategy evaluation. To help supply chain scholars assess the applicability of evaluation criteria to supply chain strategy, this note proposes a tentative set of criteria and provides insights derived from the authors’ recent experience with their use in two projects. We propose that the use of criteria for the evaluation of supply chain strategy may be a useful alternative, or at least a complement, to the dominant approach. We invite the empirical validation of these proposed criteria by third parties. Fri, 09 Sep 2016 00:00:00 GMT https://hdl.handle.net/1721.1/104095 2016-09-09T00:00:00Z https://hdl.handle.net/1721.1/104094 Eliciting and representing a supply chain strategy Perez-Franco, Roberto Purpose. The purpose of this paper is two-fold: first, to propose a framework that can be used to represent a supply chain strategy for a business unit in a clear and actionable manner; second, to propose a method that can be used to elicit the factual as is supply chain strategy that a business unit currently has in place. Approach. A framework to represent a supply chain strategy for a business unit was developed through an inductive theory-generation approach. A method to elicit the current as is supply chain strategy of a business unit was developed through collaborative management research projects and validated by several third party projects. Findings. The proposed method and framework were used to elicit the as is supply chain strategy of business units in nine different projects, mostly conducted by third parties. In every case, the validity of the result was confirmed by the business unit. Research limitations. The proposed framework and method have limited scalability beyond a single business unit. Also, they may be less useful when the supply chain strategy is undergoing a dramatic transformation. Originality. The paper proposes a novel way to characterize the supply chain strategy of a business unit as a conceptual system. The paper also proposes an innovative approach to tap into the tacit knowledge of the organization to reveal the patterns of decisions underpinning its current supply chain strategy. Fri, 09 Sep 2016 00:00:00 GMT https://hdl.handle.net/1721.1/104094 2016-09-09T00:00:00Z https://hdl.handle.net/1721.1/102234 Rethinking your supply chain strategy: a brief guide Perez-Franco, Roberto Rethinking a supply chain strategy is not a trivial problem. Supply chains tend to be rather complex entities, and the act of thinking strategically about them, what we call supply chain 'strategizing', reflects this complexity. The absence of an established answer in the supply chain management literature regarding how to rethink the supply chain strategy of an organization further compounds what is already a daunting problem. Between 2006 and 2016, a team of researchers at MIT’s Center for Transportation and Logistics (CTL) explored the problem of supply chain strategizing, as part the Supply Chain 2020 Project. After a decade of research in collaboration with world-class organizations, significant progress was made. Many questions remain open, and will continue to be explored by an offshoot of the SC2020 Project, called the MIT Supply Chain Strategy Lab. But we feel it is time to share with the community of supply chain managers the insights we have derived so far on how to re-think the supply chain strategy of an organization. That is the purpose of this text. Sun, 10 Apr 2016 00:00:00 GMT https://hdl.handle.net/1721.1/102234 2016-04-10T00:00:00Z https://hdl.handle.net/1721.1/101616 Rethinking supply chain strategy as a conceptual system Perez-Franco, Roberto; Phadnis, Shardul; Caplice, Chris; Sheffi, Yossi Changes to the strategy, context or environment of a business unit may necessitate a revision of its supply chain strategy. However, rethinking a supply chain strategy is not an easy problem, and has no clear answer in the specialized literature. Some fundamental questions about supply chain strategizing - i.e., the process of doing supply chain strategy - have been largely ignored, while others have been answered with overly-simplistic type- and-match approaches of unclear validity. In this paper, we present a holistic approach to supply-chain strategizing, called Conceptual System Assessment and Reformulation (CSAR), we have developed through a series of collaborative management research projects over a decade. This paper presents the key ideas of CSAR, and explains how it can be used to capture, evaluate and reformulate the supply chain strategy of a business unit. We argue that these ideas can serve as a first step towards a theory of supply chain strategy. Finally, we demonstrate the practical merits of CSAR by presenting the case of a large world-class corporation that used the approach as a starting point for an initiative to rethink the supply chain strategy of most of its business units. Mon, 07 Mar 2016 00:00:00 GMT https://hdl.handle.net/1721.1/101616 2016-03-07T00:00:00Z