Local Resources and Procurement Practices in Humanitarian Supply Chains: An Empirical Examination of Large‐Scale House Reconstruction Projects

Different procurement decisions taken by relief organizations can result in considerably different implications in regards to transport, storage, and distribution of humanitarian aid and ultimately can influence the performance of the humanitarian supply chain and the delivery of the humanitarian aid. In this article, we look into what resources are needed and how these resources evolve in the delivery of humanitarian aid. Drawing on the resource‐based view of the firm, we develop a framework to categorize the impact of local resources on the configuration of humanitarian supply chains. In contrast to other papers, the importance of localizing the configuration of the humanitarian supply chain is not only conceptually recognized, but empirical investigations are also provided. In terms of methodology, this article is based on the analysis of secondary data from two housing reconstruction projects. Findings indicate that the use of local resources in humanitarian aid has positive effects on programs’ overall supply chain performance and these effects are not only related to the macroeconomic perspective, but benefits expand to improvements related to the use of knowledge. At the same time, it was found that local sourcing often comes with a number of problems. For example, in one of the cases, significant problems existed, which were related to the scarcity of local supplies. Both housing reconstruction projects have indicated the continuous need for changes throughout the programs as a dynamic supply chain configuration is important for the long‐term sustainability of reconstruction aid.     

Managing Engineering Design for Competitive Sourcing in Closed‐Loop Supply Chains

We examine the strategic interplay between a buyer's design decision and the ensuing competition between suppliers in a three‐tier closed‐loop supply chain setting with significant recycling considerations. The nature of the engineering design decision in our research entails choice of integral versus modular design that has direct implications for the input raw material waste and ensuing competition between suppliers (i.e., incumbent and new). Whereas the integral design requires a large blank and generates excessive material scrap, the modular design reduces the generated scrap, and enhances cut‐to‐fit modularity, but incurs joining cost and yield loss. The incumbent supplier who supports the status quo choice of integral design can effectively recycle excessive material waste, as it is strategically located close to the source of material. The engineering design team at our study firm is currently exploring the option to source from alternative suppliers that can support either integral or modular designs, but have significantly lower effectiveness in recycling scrap material. We characterize the buyer's price sensitivity levels, component characteristics, supply chain configurations, and virgin and scrap specialty material prices that yield various design and sourcing policy alternatives. The buyer's optimal policy choice, the ensuing price–demand dynamics, and the resulting recycling implications demonstrate that the buyer can benefit from strategically tailoring his design decisions to affect the suppliers' material requirements and costs. We show that utilizing an alternative supply option is particularly valuable for components made from a material with a low price differential in virgin and scrap forms in supply chains wherein the new supplier base can recycle effectively. In such cases, the buyer induces severe price competition by dual sourcing the integral design, and competition may negate the seemingly obvious benefits of operational improvements (e.g., higher scrap material return rate).      

Closed‐Loop Supply Chains: An Introduction to the Feature Issue (Part 2)

Closed‐loop supply chain management is the design, control and operation of a system to maximize value creation over the entire life‐cycle of a product with dynamic recovery of value from different types and volumes of returns over time. The research in this feature issue furthers our understanding of this rich area and serves as a starting point for another round of research which continues to dig deeper still into relevant industry issues.     

Closed‐Loop Supply Chains: An Introduction to the Feature Issue (Part 1)

Closed‐loop supply chains (CLSC) have product returns at the center of attention. Our view is that CLSC are best managed from a business perspective where organizations seek to maximize value recovery. The research in the feature issue, and our experiences, shows that there are still numerous, unresolved, managerially relevant issues that deserve further investigation. We also observe that there is a pressing need to validate the assumptions in our models using interdisciplinary, industry‐driven research. The time is right for production and operations management to play a central role in the sustainability movement slowly taking hold in practice.     

Optimization and Coordination of Fresh Product Supply Chains with Freshness‐Keeping Effort

We consider a supply chain in which a distributor procures from a producer a quantity of a fresh product, which has to undergo a long‐distance transportation to reach the target market. During the transportation process, the distributor has to make an appropriate effort to preserve the freshness of the product, and his success in this respect impacts on both the quality and quantity of the product delivered to the market. The distributor has to determine his order quantity, level of freshness‐keeping effort, and selling price, by taking into account the wholesale price of the producer, the cost of the freshness‐keeping effort, the likely spoilage of the product during transportation, and the possible demand for the product in the market. The producer, on the other hand, has to determine the wholesale price based on its effect on the order quantity of the distributor. We develop a model to study this problem, and characterize each party's optimal decisions in both decentralized and centralized systems. We further develop an incentive scheme to facilitate coordination between the two parties. Computational results are reported to show the effects of freshness‐keeping efforts.     

Closed‐Loop Supply Chains: A Critical Review,and Future Research*

In this article, I present a review and tutorial of the literature on closed‐loop supply chains, which are supply chains where, in addition to typical forward flows, there are reverse flows of used products (postconsumer use) back to manufacturers. Examples include supply chains with consumer returns, leasing options, and end‐of‐use returns with remanufacturing. I classify the literature in terms of strategic, tactical, and operational issues, but I focus on strategic issues (such as when should an original equipment manufacturer (OEM) remanufacture, response to take‐back legislation, and network design, among others) and tactical issues (used product acquisition and disposition decisions). The article is written in the form of a tutorial, where for each topic I present a base model with underlying assumptions and results, comment on extensions, and conclude with my view on needed research areas.     

Positioning Inventory in Clinical Trial Supply Chains

As a result of slow patient recruitment and high patient costs in the United States, clinical trials are increasingly going global. While recruitment efforts benefit from a larger global footprint, the supply chain has to work harder at getting the right drug supply to the right place at the right time. Certain clinical trial supply chains, especially those supplying biologics, have a combination of unique attributes that have yet to be addressed by existing supply chain models. These attributes include a fixed patient horizon, an inflexible supply process, a unique set of service‐level requirements, and an inability to transfer drug supplies among testing sites. We provide a new class of multi‐echelon inventory models to address these unique aspects. The resulting mathematical program is a nonlinear integer programming problem with chance constraints. Despite this complexity, we develop a solution method that transforms the original formulation into a linear integer equivalent. By analyzing special cases and through numerical study of both real‐life and simulated examples, we demonstrate the effectiveness of the solution and develop insights into inventory positioning and the cost drivers in clinical trial supply chains.     

Evacuating People with Mobility‐Challenges in a Short‐Notice Disaster

In past disasters, arrangements have been made to evacuate people without their own transportation, requiring them to gather at select locations to be evacuated. Unfortunately, this type of plan does not help those people who are unable to move themselves to the designated meeting locations. In the United States, according to the Post‐Katrina Emergency Management Reform Act of 2006, state or local governments have the responsibility to coordinate evacuation plans for all populations. These include those with disabilities. However, few, if any, have plans in place for those who are mobility‐challenged. The problem of evacuating mobility‐challenged people from their individual locations in a short‐notice disaster is a challenging combinatorial optimization problem. In order to develop the model and select a solution approach, we surveyed related literature. Based on our review, we formulate the problem and develop an Ant Colony Optimization (ACO) algorithm to solve it. We then test two different versions of the ACO algorithm on five stylized datasets with several different parameter settings.     

Bubbles and Self‐Enforcing Debt

We characterize equilibria with endogenous debt constraints for a general equilibrium economy with limited commitment in which the only consequence of default is losing the ability to borrow in future periods. First, we show that equilibrium debt limits must satisfy a simple condition that allows agents to exactly roll over existing debt period by period. Second, we provide an equivalence result, whereby the resulting set of equilibrium allocations with self‐enforcing private debt is equivalent to the allocations that are sustained with unbacked public debt or rational bubbles. In contrast to the classic result by Bulow and Rogoff (1989a), positive levels of debt are sustainable in our environment because the interest rate is sufficiently low to provide repayment incentives.     

Distributed Decision‐Making in Supply Chains and Private E‐Marketplaces

This paper develops a distributed decision‐making framework for the players in a supply chain or a private e‐marketplace to collaboratively arrive at a global Pareto‐optimal solution. In this model, no player has complete knowledge about all the costs and constraints of the other players. The decision‐making framework employs an iterative procedure, based on the Integer L‐shaped method, in which a master problem is solved to propose global solutions, and each player uses his local problems to construct feasibility and optimality cuts on the master problem. The master problem is modeled as a mixed‐integer program, and the players' local problems are formulated as linear programs. Collaborative planning scenarios in private e‐marketplaces and in supply chains were formulated and solved for test data. The results show that this distributed model is able to achieve near‐optimal solutions considerably faster than the traditional centralized approach.     

Timing and Self‐Control

The standard dual‐self model of self‐control, with a shorter‐run self who cares only about the current period, is excessively sensitive to the timing of decisions and to the interpolation of additional “no‐action” time periods in between the dates when decisions are made. We show that when the shorter‐run self is not completely myopic, this excess sensitivity goes away. To accommodate the combination of short time periods and convex costs of self‐control, we introduce a cognitive resource variable that tracks how the control cost depends on the self‐control that has been used in the recent past. We consider models with both linear and convex control costs, illustrating the theory through a series of examples. We examine when opportunities to consume will be avoided or delayed, and we consider the way in which the marginal interest declines with delay.     

The Impact of Product Lifecycle on Capacity Planning of Closed‐Loop Supply Chains with Remanufacturing

Product recovery operations in reverse supply chains face rapidly changing demand due to the increasing number of product offerings with reduced lifecycles. Therefore, capacity planning becomes a strategic issue of major importance for the profitability of closed‐loop supply chains. This work studies a closed‐loop supply chain with remanufacturing and presents dynamic capacity planning policies developed through the methodology of System Dynamics. The key issue of the paper is how the lifecycles and return patterns of various products affect the optimal policies regarding expansion and contraction of collection and remanufacturing capacities. The model can be used to identify effective policies, to conduct various “what‐if” analyses, and to answer questions about the long‐term profitability of reverse supply chains with remanufacturing. The results of numerical examples with quite different lifecycle and return patterns show how the optimal collection expansion/contraction and remanufacturing contraction policies depend on the lifecycle type and the average usage time of the product, while the remanufacturing capacity expansion policy is not significantly affected by these factors. The results also show that the collection and remanufacturing capacity policies are insensitive to the total product demand. The insensitivity of the optimal policies to total demand is a particularly appealing feature of the proposed model, given the difficulty in obtaining accurate demand forecasts.     

Strongly Consistent Self‐Confirming Equilibrium

Fudenberg and Levine (1993a) introduced the notion of self‐confirming equilibrium, which is generally less restrictive than Nash equilibrium. Fudenberg and Levine also defined a concept of consistency, and claimed in their Theorem 4 that with consistency and other conditions on beliefs, a self‐confirming equilibrium has a Nash equilibrium outcome. We provide a counterexample that disproves Theorem 4 and prove an alternative by replacing consistency with a more restrictive concept, which we call strong consistency. In games with observed deviators, self‐confirming equilibria are strongly consistent self‐confirming equilibria. Hence, our alternative theorem ensures that despite the counterexample, the corollary of Theorem 4 is still valid.     

Self‐Selective Social Choice Functions Verify Arrow and Gibbard‐Satterthwaite Theorems

This paper introduces a new notion of consistency for social choice functions, called self‐selectivity, which requires that a social choice function employed by a society to make a choice from a given alternative set it faces should choose itself from among other rival such functions when it is employed by the society to make this latter choice as well. A unanimous neutral social choice function turns out to be universally self‐selective if and only if it is Paretian and satisfies independence of irrelevant alternatives. The neutralunanimous social choice functions whose domains consist of linear order profiles on nonempty sets of any finite cardinality induce a class of social welfare functions that inherit Paretianism and independence of irrelevant alternatives in case the social choice function with which one starts is universally self‐selective. Thus, a unanimous and neutral social choice function is universally self‐selective if and only if it is dictatorial. Moreover, universal self‐selectivity for such functions is equivalent to the conjunction of strategy‐proofness and independence of irrelevant alternatives or the conjunction of monotonicity and independence of irrelevant alternatives again.     

Supply Chain Knowledge and Performance: A Meta‐Analysis

Many firms make significant investments into developing and managing knowledge within their supply chains. Such investments are often prudent because studies indicate that supply chain knowledge (SCK) has a positive influence on performance. Key questions still surround the SCK–performance relationship, however. First, what is the overall relationship between SCK and performance? Second, under what conditions is the relationship stronger or weaker? To address these questions, we applied meta‐analysis to 35 studies of the SCK–performance relationship that collectively include more than 8,400 firms. Our conservative estimate is that the effect size of the overall relationship is  = .39. We also find that the SCK–performance relationship is stronger when (i) examining operational performance, (ii) gathering data from more than one supply chain node, (iii) gathering data from multiple countries, (iv) examining service industries, and (v) among more recently published studies. We also found that studies that embraced a single theory base (as opposed to using multiple ones) had a stronger SCK–performance relationship. Looking to the future, our meta‐analysis highlights the need for studies to (i) include lags between the measurement of SCK and performance, (ii) gather upstream data when examining innovation, (iii) examine SCK within emerging countries, and (iv) provide much more information relative to the nuances of the SCK examined.     

Controversial Role of GPOs in Healthcare‐Product Supply Chains

This paper examines the controversial role that Group Purchasing Organizations (GPOs) play in the supply chains for healthcare products. Among the controversies, perhaps the most fundamental one is whether or not GPOs reduce purchasing costs for their members. However, the fiercest controversy is around the “contract administration fees (CAFs)” that GPOs charge to manufacturers. We examine these and other controversies using a Hotelling duopoly model. Among our conclusions: GPOs increase competition between manufacturers and lower prices for healthcare providers. However, GPOs reduce manufacturers' incentives to introduce innovations to existing products. We also demonstrate that the existence of lower off‐contract prices is not, per se, evidence of anticompetitive behavior on the part of GPOs. Indeed, we demonstrate that, under certain circumstances, the presence of a GPO lowers off‐contract prices. We also examine the consequences of eliminating the “safe harbor” provisions that permit healthcare GPOs to charge CAFs to manufacturers, and conclude that it would not affect any party's profits or costs.     

Self‐Control and the Theory of Consumption

To study the behavior of agents who are susceptible to temptation in infinite horizon consumption problems under uncertainty, we define and characterize dynamic self‐control (DSC) preferences. DSC preferences are recursive and separable. In economies with DSC agents, equilibria exist but may be inefficient; in such equilibria, steady state consumption is independent of initial endowments and increases in self‐control. Increasing the preference for commitment while keeping self‐control constant increases the equity premium. Removing nonbinding constraints changes equilibrium allocations and prices. Debt contracts can be sustained even if the only feasible punishment for default is the termination of the contract.     

Supply Chains in Sub‐Saharan Africa: A Decision Support System for Small‐Scale Seed Entrepreneurs*

It is necessary to infuse a consistent supply of improved seed varieties into local sub‐Saharan African crop production to improve low crop yields. The best distribution channel for the improved seed varieties may be small‐scale commercial seed companies, but local entrepreneurs struggle to determine whether such businesses are viable. Using a multi‐echelon supply chain approach, a decision support system (DSS) was designed to help African seed entrepreneurs make informed decisions about small‐scale seed chain businesses. Specifically, entrepreneurs make decisions about where to locate seed enterprises, with which farmers to contract, and where to store seed. Optimization and simulation modeling are used to evaluate infrastructure variables such as distance, transportation cost, and storage loss and cost in three development level areas. Currently, the decision tool is used in Mozambique, Malawi, Kenya, and Tanzania. The model has supported the start‐up of at least 17 small seed companies that are now introducing improved seed varieties into villages and farms. The DSS applies decision science research in a humanitarian application and offers important managerial implications about supply chain infrastructure to nongovernmental organizations and humanitarian groups. Such applications are vital as groups such as USAID, the Gates Foundation, and the International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT) continue to move toward micro‐enterprise, value chain, and market‐oriented development programs.     

A Purchasing Framework for B2B Pricing Decisions and Risk‐sharing in Supply Chains*

This paper presents a common modelling structure for (i) the implementation of operational policies by individual purchasing managers of risk‐sharing agreements among supply‐chain partners, and (ii) the integration of brick and click purchasing policies in a B2B. The problem of price uncertainty created within these two environments is modelled as a stochastic repetitive‐sales problem, applicable to any probability distribution. The model identifies sufficient conditions for regenerative ordering cycles, which allows for the use of the renewal reward theorem. The end result is a two‐price purchasing policy, which may substantially ease implementation problems across a global corporation's purchasing managers world‐wide and across B2B markets.