Understanding econo-political risks: impact of sanctions on an automotive supply chain

Purpose - The purpose of this paper is to introduce econo-political risks (EPRs) to supply chains (SCs). Based on case data from an automotive SC, this research identifies the mechanisms through which a subset of EPRs influences Sc operations and outcomes. Design/methodology/approach - An exploratory case study method is employed for theory development. Interviews with SC professionals of three case companies were the primary data source. Company documents, archival records, and direct observation provided further insights into how EPRs are perceived, how they impact a SC, how SC actors react to them, and what the overall performance results are. Findings - The research identifies EPRs in terms of scope (flow of material, money, and knowledge) and time, and provides concrete examples, along with the channels through which their impact unfolds, and the responses available to SC actors. The authors find secondary impacts of EPRs through economic and regulatory channels to be significant, and bankruptcy, strategic reorientation, and single sourcing are common outcomes. By elaborating on the mechanisms through which sanctions impact upon SCs, and the feasible response trajectories, this research can assist SC actors with more effective management of EPRs. Originality/value - This paper is novel for three reasons: first, it introduces EPRs to research into supply chain risk management (SCRM); second, it addresses SC risks in a developing country, a topic largely missing from the literature; and finally, this research focuses on post-event SC risks, whereas the bulk of SCRM literature focuses on the pre-event phase

Mixed network design using hybrid scatter search

This research proposes a bi-level model for the mixed network design problem (MNDP). The upper level problem involves redesigning the current road links’ directions, expanding their capacity, and determining signal settings at intersections to optimize the reserve capacity of the whole system. The lower level problem is the user equilibrium traffic assignment problem. By proving that the optimal arc flow solution of the bi-level problem must exist in the boundary of capacity constraints, an exact line search method called golden section search is embedded in a scatter search method for solving this complicated MNDP. The algorithm is then applied to some real cases and finally, some conclusions are drawn on the model's efficiency.postprin

​Resilient supply chain network design under competition : a case study

This research, motivated by a real-life case study in a highly competitive automobile supply chain, experimentally studies the impact of disruption on the competitiveness of supply chains. The studied supply chain faces two major risks: disruption of suppliers and tough competition from competitors. Any disruption in upstream level of the supply chain leads to an inability to meet demand downstream and causes market share to be lost to the competitors. For such a setting, a resilient topology is redesigned that can recover from and react quickly to any disruptive incidents. To this aim, we speculate there are three policies that can be used to mitigate the disruption risk, namely keeping emergency stock at the retailers, reserving back-up capacity at the suppliers, and multiple-sourcing. The problem is addressed using a mixed integer non-linear model to find the most profitable network and mitigation policies. We design a piecewise linear method to solve the model. Based on the data extracted from an automotive supply chain, practical insights of the research are extracted in a controlled experiment. Our analysis suggests that implementing risk mitigation policies not only work to the advantage of the supply chain by sustaining and improving its market share but also benefit customers by stabilizing retail prices in the market. Using the case study, we analyze the contribution of each risk strategy in stabilizing the supply chain's profit, market share, and retail price. Our analysis reveals that downstream “emergency stock” is the most preferable risk mitigation strategy if suppliers are unreliable

Link-based multi-class hazmat routing-scheduling problem : a multiple demon approach

This paper addresses a hazmat routing and scheduling problem for a general transportation network with multiple hazmat classes when incident probabilities are unknown or inaccurate. A multi-demon formulation is proposed for this purpose. This formulation is link-based (i.e., the decision variables are link flows) and can be transformed into other forms so that a wide range of solution methods can be used to obtain solutions. This paper also proposes a solution strategy to obtain route flow solutions without relying on exhaustive route enumeration and route generation heuristics. Examples are set up to illustrate the problem properties, the method of obtaining route flows from link flows, and the computational efficiency of the solution strategy. Moreover, a case study is used to illustrate our methodology for real-life hazmat shipment problems. From this case study, we obtain four key insights. First, to have the safest shipment of one type of hazmat, different trucks carrying the same type of hazmat need to take different routes and links. Second, in case of multiple-hazmat transportation, it is recommended to use different routes and links for the shipment of different hazmat types. This may increase travel time but can result in safer shipment. Third, if the degree of connectivity in a transportation network is high, the shipment company may have multiple solutions. Fourth, the hazmat flows on critical links (whose removal would make the network disconnected) must be distributed or scheduled over different periods to have safer shipment

Prevention of terrorism : an assessment of prior POM work and future potentials

© 2020 Production and Operations Management Society In this study, we review POM-based research related to prevention of terrorism. According to the Federal Emergency Management Agency (FEMA) terrorist attacks have the potential to be prevented. Consequently, the focus of this study is on security enhancement and improving the resiliency of a nation to prevent terrorist attacks. Accordingly, we review articles from the 25 top journals, [following procedures developed by Gupta et al. (2016)], in the fields of Production and Operations Management, Operations Research, Management Science, and Supply Chain Management. In addition, we searched some selected journals in the fields of Information Sciences, Political Science, and Economics. This literature is organized and reviewed under the following seven core capabilities defined by the Department of Homeland Security (DHS): (1) Intelligence and Information Sharing, (2) Planning, (3) Interdiction and Disruption, (4) Screening, Search, and Detection, (5) Forensics and Attribution, (6) Public Information and Warning, and (7) Operational Coordination. We found that POM research on terrorism is primarily driven by the type of information that a defending country and a terrorist have about each other. Game theory is the main technique that is used in most research papers. Possible directions for future research are discussed

Disaster management from a POM perspective : mapping a new domain

We have reviewed disaster management research papers published in major operations management, management science, operations research, supply chain management and transportation/ logistics journals. In reviewing these papers our objective is to assess and present the macro level “architectural blue print” of disaster management research with the hope that it will attract new researchers and motivate established researchers to contribute to this important field. The secondary objective is to bring this disaster research to the attention of disaster administrators so that disasters are managed more efficiently and more effectively. We have mapped the disaster management research on the following five attributes of a disaster: (1) Disaster Management Function (decision making process, prevention and mitigation, evacuation, humanitarian logistics, casualty management, and recovery and restoration), (2) Time of Disaster (before, during and after), (3) Type of Disaster (accidents, earthquakes, floods, hurricanes, landslides, terrorism and wildfires etc.), (4) Data Type (Field and Archival data, Real data and Hypothetical data), and (5) Data Analysis Technique (bidding models, decision analysis, expert systems, fuzzy system analysis, game theory, heuristics, mathematical programming, network flow models, queuing theory, simulation and statistical analysis). We have done cross tabulations of data among these five parameters to gain greater insights in disaster research. Recommendations for future research are provided