Robust supply chain strategies for recovering from unanticipated disasters

Recovering from unanticipated disasters is critical in today’s global market. This paper examines the effectiveness of popular recovery strategies used to address unpredictable disasters that derail supply chains. We create a formal model to portray dynamic operational performance among supply chain firms facing disruptions caused by natural and man-made disasters. Our analysis shows that a supply chain recovers best if member firms adopt a radical, rapid, costly recovery strategy that immediately resolves the disruption. This observation is robust to various resource consumption requirements. We apply our methodology in the case of Taiwan’s 2011 food contamination scandal and provide managerial insights.     

Lead time aggregation: A three-echelon supply chain model

In this paper, destructive effects of upstream aggregated stochastic lead times on the supply chain (SC) performance are analyzed. For this purpose, a three-echelon SC consisting of one producer, one distributor, and one retailer is modeled. Both the producer and distributor face stochastic lead times, which can be also aggregated to create a long unpredictable lead time. In order to scale down shortages at the retailer site, an incentive scheme is proposed to convince the upstream members to increase their reorder points. Applying the coordinated model considerably increases the total profit earned by the whole SC as well as all SC members.     

Dynamic impact on global supply chains performance of disruptions propagation produced by terrorist acts

Understanding disruptions and how their effects propagate through the supply chain is critical to promote security and efficient movement of goods. This research proposes a system dynamics model as an effective quantitative approach for analyzing the effects of the materialization and simultaneous propagation of disruptions produced by terrorist acts on global supply chains performance. The article shows that the impact on inventory levels in the supply chain can increase 600% compared to normal operating conditions as a result of increasing the security measures on international borders. Finally, useful conclusions for designing more resilient supply chains and future research are exposed.     

Designing a new supply chain for competition against an existing supply chain

We develop a bi-level model for designing an entrant supply chain (SC) in the presence of a pre-existing competing SC where demand is elastic with respect to price and distance. The model assumes dynamic competition between the new and pre-existing SCs in retailers’ level and probabilistic customers’ behavior. Strategic facility location and flow decisions are made while considering inventory carrying costs incurred on the operational level. We formulate the problem and propose exact and metaheuristic algorithms to solve it. The model is solved using data from a real-life case and also randomly generated test problems to extract managerial insights.     

Supplier hoarding,government intervention,and timing for post-disaster crop supply chain recovery

This work presents a multi-methodological approach to address the issue of post-disaster crop supply chain recovery under the influences of government intervention and supplier hoarding intention. A conceptual model which characterizes the antecedents of supplier hoarding intention is proposed, and validated using survey data. Grounded in the empirical study, an analytical model is then proposed for decision analysis of a two-tier crop supply chain recovering from post-disaster supply disruptions. Analytical results indicate that hoarding behavior reduces the time taken by supply chain members for supply recovery; and however, contributes to mixed effects on the expected profits of supply chain members.     

Post-disaster grain supply chain resilience with government aid

Assessing the disruption and resilience of the agricultural grain supply chain is critical to ensure grain supply and stabilize grain price in the final market. This research proposes a quantitative model to analyze how a grain processor regains robustness when supply is disrupted by a natural disaster upstream, and how this disruption affects grain retailers downstream. Two supply chain recovery methods, contingent sourcing and government aid, are considered for grain processor recovery. The results show that (1) a processor prefers timely full recovery, and (2) government aid as an intervention means is indispensable but cannot fully replace the backup supplier.     

Design and planning for green global supply chains under periodic review replenishment policies

We quantify the impact of jointly optimizing strategic network design and tactical inventory planning on the cost and CO₂ emissions of multi-echelon logistics networks. The obtained insights indicate that longer optimized replenishment cycles reduce a node’s transportation cost and CO₂ emissions but increase its inventory costs. Moreover, under a fixed replenishment cycle, a node’s service level increases when supplied by a satellite warehouse. Finally: (i) the costs of implementing optimal green network design decisions could be misleading if inventory planning is neglected, (ii) greening of supply chains could become expensive, (iii) current legislative CO₂ ton prices hardly influence logistics networks.     

Global supply chain design: A literature review and critique

In this paper, we review decision support models for the design of global supply chains, and assess the fit between the research literature in this area and the practical issues of global supply chain design. The classification scheme for this review is based on ongoing and emerging issues in global supply chain management and includes review dimensions for (1) decisions addressed in the model, (2) performance metrics, (3) the degree to which the model supports integrated decision processes, and (4) globalization considerations. We conclude that although most models resolve a difficult feature associated with globalization, few models address the practical global supply chain design problem in its entirety. We close the paper with recommendations for future research in global supply chain modeling that is both forward-looking and practically oriented.     

Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application

In this paper, we present a two-stage mixed integer programming (MIP) interdiction model in which an interdictor chooses a limited amount of elements to attack first on a given network, and then an operator dispatches trains through the residual network. Our MIP model explicitly incorporates discrete unit flows of trains on the rail network with time-variant capacities. A real coal rail transportation network is used in order to generate scenarios to provide tactical and operational level vulnerability assessment analysis including rerouting decisions, travel and delay costs analysis, and the frequency of interdictions of facilities for the dynamic rail system.     

Reprint of “Green supply chain decisions – Case-based performance analysis from the food industry”

Environmental impacts, such as GHC emissions, have been introduced to supply chain management as an additional parameter to traditional cost, lead-time and on-time delivery. Supply chain management represents a significant source of decisions affecting the eco-efficiency of many products. This paper analyses cases from the food industry, mainly order-picking, transportation, warehousing, and distribution aspects from the greening point of view. Three case examples of decisions in supply chain design in the food industry are considered. The results show dependencies between performance measures. Finally, a framework of decisions and their impact on performance is presented.     

Marrying supply chain sustainability and resilience: A match made in heaven

Sustainable supply chain management has become an integral part of corporate strategy for virtually every industry. However, little is understood about the broader impacts of sustainability practices on the capacity of the supply chain to tolerate disruptions. This article aims to explore the sustainability–resilience relationship at the supply chain design level. A multi-objective optimization model featuring a sustainability performance scoring method and a stochastic fuzzy goal programming approach is developed that can be used to perform a dynamic sustainability tradeoff analysis and design a “resiliently sustainable” supply chain. Important managerial and practical insights are obtained from an empirical case study.     

Uncertainty propagation in a supply chain or supply network

A supply chain is characterized by uncertain demands (demand-side uncertainty) and uncertainties associated with the performances of the production facilities (supply-side uncertainty). In this paper, a method is proposed to plan production in a supply chain with a multi-echelon supply process with unreliable production facilities working in markets with uncertain demand. In such a system it is necessary to consider the global and cumulative effects on the performance of the entire supply chain. We introduce the salient features of uncertainty propagation in supply chains and demonstrate their impact quantitatively using a test problem from the automotive industry.     

Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain

This study presents a mathematical model that designs a reliable multi-modal transportation network for a biofuel supply chain system, where intermodal hubs are subject to site-dependent probabilistic disruptions. The disruption probabilities of intermodal hubs are estimated by using a probabilistic model which is developed using real world data. We developed an accelerated Benders decomposition algorithm to solve this challenging NP-hard problem. Numerical analysis show that the model selects to use intermodal hubs located in areas with low disruption probabilities. In case of a disaster, the reliable solution results in 6.21% savings over the minimum cost solution.     

Reliable design of an integrated supply chain with expedited shipments under disruption risks

This paper studied the design of a two-echelon supply chain where a set of suppliers serve a set of terminals that receive uncertain customer demands. In particular, we considered probabilistic transportation disruptions that may halt product supply from certain suppliers. We formulated this problem into an integer nonlinear program to determine the optimal system design that minimizes the expected total cost. A customized solution algorithm based on Lagrangian relaxation was developed to efficiently solve this model. Several numerical examples were conducted to test the proposed model and draw managerial insights into how the key parameters affect the optimal system design.     

Aircraft and passenger recovery during an aircraft’s unexpected unavailability

Airlines design their initial schedules under the assumption that all resources will be available on time and flights will operate as planned. However, some disruptions occur due to mechanical failures and unexpected delays of maintenance, making the aircraft unavailable for a certain period of time. These deviations from the initial plan result in high operational costs in addition to the serious inconveniences experienced by passengers. In order to handle aircraft and passenger recovery problems simultaneously, we work on integrated networks at which aircraft routings and passenger itineraries are superimposed. Consequently, we could calculate the actual profit and cancellation cost by evaluating each passenger itinerary while considering the seat capacity limitations. In our computational results, we use a daily schedule of a major U.S. airline and clearly demonstrate that there is an optimal trade-off between operating and passenger-related costs.     

Recovering costs through price and service differentiation: Accounting for exogenous information on attribute processing strategies in airline choice

The entry of low cost airlines has thrown out a challenge to all airlines to find ways of attracting passengers, through a mix of fare discounting, greater frequency, improved flight times and no-frill's levels of on-board service. These competitive strategies have an impact on cost recovery. As airlines seek business in an increasingly heterogeneous passenger market, a greater understanding of what matters to potential passengers in choosing an airline grows in importance. Traditional studies of passenger airline choice assume that all attributes matter, but some to a lesser extent. What happens to the empirical evidence on willingness to pay when specific attributes are totally ignored by particular passengers? In this paper, we examine the impact of individual-specific attribute processing strategies (APS) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of airline service and fare level choice. Modelling practice assumes that whilst respondents may exhibit preference heterogeneity, they employ a homogenous APS with regards to how they process the presence/absence of attributes of stated choice (SC) experiments. We demonstrate how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute of the SC task may be used in the estimation process, and how such information may be used to provide outputs that are attribute processing strategies segment specific.     

The redesign of a warranty distribution network with recovery processes

A warranty distribution network provides aftersales warranty services to customers and resembles a closed-loop supply chain network with specific challenges for reverse flows management like recovery, repair, and reflow of refurbished products. We present here a nonlinear and nonconvex mixed integer programming model for the design of the warranty distribution network of a semiconductor company which is operated by an outsourced third party logistics service provider. The application of the model to the real-life case provides an improved distribution network flow and rearranged warehouse and recovery locations, and resulted in weekly cost savings of 3.4% for the considered item.     

A method for quantifying travel productivity for corporate travel managers

For large corporations with significant travel budgets, the efficiency in execution of employee travel is critical to the productivity of the enterprise. Air travel disruptions (i.e. delays, cancellations, missed connections) prevent employees from performing enterprise related tasks resulting in lost billable revenue and unbudgeted Indirect costs (e.g. unplanned overnight stays for stranded passengers, and idle time charges). Since travel disruption data is not readily available to Corporate Travel Managers, the Indirect charges cannot be included in budgets, and the magnitude of lost billable revenue is not known. Further, without measuring the travel delays and their impact, it is not possible to understand the underlying causes of the delays to improve the process.This paper describes a method for providing Corporate Travel Departments travel disruption statistics and their impact on revenue and profits. The method overcomes the problem of the absence of data by deriving travel delay statistics for corporate travel from publicly available historic airline flight data-bases. The method also uses a travel delay cost model to estimate the financial impact of travel disruptions. The implications of these results on Corporate Travel Management (CTM) productivity improvement strategies, corporate travel and indirect budgets, contracts with travel providers, and travel insurance are discussed.     

Fulfillment source allocation,inventory transshipment,and customer order transfer in e-tailing

We consider an inventory fulfillment-allocation and transshipment problem in an e-tailing environment. For a typical e-tailer, each customer demand is fulfilled from the closest fulfillment center if there are enough inventories. Otherwise, the e-tailer would transship stock from a nearby facility or transfer the customer order so it is fulfilled from another facility, depending on the economics of transportation. We develop a mixed-integer programming model to help e-tailers optimally fulfill customer orders while minimizing logistics costs. We propose a Benders decomposition-based approach to efficiently find optimal solutions. Our computational results demonstrate the importance of considering inventory transshipments in online deliveries.     

Cooperatives for fruits and vegetables in emerging countries: Rationalization and impact of decentralization

We develop a (noncooperative) game theoretic model for a decentralized setting wherein fringe farmers compete with a two-tier cooperative network involving network farmers and a coordinator. We examine the roles of the coordinator and profit sharing in allocating costs/benefits of externalities in enhancing network efficiency and stability. Our main finding is that using profit sharing based mechanism the coordinator can overcome inherent inefficiency and instability of decentralization and noncooperative behavior of the network farmers. The roles of the coordinator and profit sharing are particularly important when it is economical for both network and fringe farmers to supply the product.