Robust Structural Equations for Designing and Monitoring Strategic International Facility Networks

Using predictive global sensitivity analysis, we develop a structural equations model to abstract from the details of a large‐scale mixed integer program (MIP) to capture essential design trade‐offs of global manufacturing and distribution networks. We provide a conceptual framework that describes a firm's network structure along three dimensions: market focus, plant focus, and network dispersion. Normalized dependent variables are specified that act as proxies for a company's placement into our conceptual network classification via the calculation of just a few key independent variables. We provide robust equation sets for eight cost structure clusters. Many different product types could be classified into one of these groups, which would allow managers to use the equations directly without needing to run the MIP for themselves. Our numerical tests suggest that the formulas representing the network structure drivers—economies of scale, complexity costs, transportation costs, and tariffs—may be sufficient for managers to design their strategic network structures, and perhaps more importantly, to monitor them over time to detect potential need for adjustment.     

Strategic Consumer Cooperation in a Name‐Your‐Own‐Price Channel

Supplier reluctance to openly advertise highly discounted products on the Internet has stimulated development of “opaque” name‐Your‐Own‐Price sales channels. Unfortunately (for suppliers), there is significant potential for online consumers to exploit these channels through collaboration in social networks. In this paper, we study three possible forms of consumer collaboration: exchange of bid result information, coordinated bidding, and coordinated bidding with risk pooling. We propose an egalitarian total utility maximizing mechanism for coordination and risk pooling in a bidding club and describe characteristics of consumers for whom participation in the club makes sense. We show that, in the absence of risk pooling, a plausible bidding club strategy using just information exchange gives almost the same benefits to consumers as coordinated bidding. In contrast, coordinated bidding with risk pooling can lead to significantly increased benefits for consumers. The benefits of risk pooling are highest for consumers with a low tolerance to risk. We also demonstrate that suppliers that actively adjust for such strategic consumer behavior can reduce the impact on their businesses and, under some circumstances, even increase revenues.     

A Noncooperative Model of Network Formation

We present an approach to network formation based on the notion that social networks are formed by individual decisions that trade off the costs of forming and maintaining links against the potential rewards from doing so. We suppose that a link with another agent allows access, in part and in due course, to the benefits available to the latter via his own links. Thus individual links generate externalities whose value depends on the level of decay/delay associated with indirect links. A distinctive aspect of our approach is that the costs of link formation are incurred only by the person who initiates the link. This allows us to formulate the network formation process as a noncooperative game. We first provide a characterization of the architecture of equilibrium networks. We then study the dynamics of network formation. We find that individual efforts to access benefits offered by others lead, rapidly, to the emergence of an equilibrium social network, under a variety of circumstances. The limiting networks have simple architectures, e.g., the wheel, the star, or generalizations of these networks. In many cases, such networks are also socially efficient.     

On the Benefits of Risk Pooling in Inventory Management

We analyze the benefits of inventory pooling in a multi‐location newsvendor framework. Using a number of common demand distributions, as well as the distribution‐free approximation, we compare the centralized (pooled) system with the decentralized (non‐pooled) system. We investigate the sensitivity of the absolute and relative reduction in costs to the variability of demand and to the number of locations (facilities) being pooled. We show that for the distributions considered, the absolute benefit of risk pooling increases with variability, and the relative benefit stays fairly constant, as long as the coefficient of variation of demand stays in the low range. However, under high‐variability conditions, both measures decrease to zero as the demand variability is increased. We show, through analytical results and computational experiments, that these effects are due to the different operating regimes exhibited by the system under different levels of variability: as the variability is increased, the system switches from the normal operation to the effective and then complete shutdown regimes; the decrease in the benefits of risk pooling is associated with the two latter stages. The centralization allows the system to remain in the normal operation regime under higher levels of variability compared to the decentralized system.     

The Diffusion of Wal‐Mart and Economies of Density

The rollout of Wal‐Mart store openings followed a pattern that radiated from the center outward, with Wal‐Mart maintaining high store density and a contiguous store network all along the way. This paper estimates the benefits of such a strategy to Wal‐Mart, focusing on the savings in distribution costs afforded by a dense network of stores. The paper takes a revealed preference approach, inferring the magnitude of density economies from how much sales cannibalization of closely packed stores Wal‐Mart is willing to suffer to achieve density economies. The model is dynamic with rich geographic detail on the locations of stores and distribution centers. Given the enormous number of possible combinations of store‐opening sequences, it is difficult to directly solve Wal‐Mart's problem, making conventional approaches infeasible. The moment inequality approach is used instead and works well. The estimates show the benefits to Wal‐Mart of high store density are substantial and likely extend significantly beyond savings in trucking costs.     

Catastrophe Risk Models for Evaluating Disaster Risk Reduction Investments in Developing Countries

Major natural disasters in recent years have had high human and economic costs, and triggered record high postdisaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low‐ and middle‐income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model‐based cost‐benefit analyses for DRR in developing countries.     

A Bayesian Network Estimation of the Service‐Profit Chain for Transport Service Satisfaction

Bayesian network methodology is used to model key linkages of the service‐profit chain within the context of transportation service satisfaction. Bayesian networks offer some advantages for implementing managerially focused models over other statistical techniques designed primarily for evaluating theoretical models. These advantages are (1) providing a causal explanation using observable variables within a single multivariate model, (2) analysis of nonlinear relationships contained in ordinal measurements, (3) accommodation of branching patterns that occur in data collection, and (4) the ability to conduct probabilistic inference for prediction and diagnostics with an output metric that can be understood by managers and academics. Sample data from 1,101 recent transport service customers are utilized to select and validate a Bayesian network and conduct probabilistic inference.     

Shifts of long run average cost curves: Theoretical and managerial implications

Economists have traditionally employed one of two alternative methods when analyzing economies of scale: The long run average cost curve (LRAC curve) and the production function. Only the production function concept, however, has been extended beyond a static framework for analysis of scale economies in a dynamic setting. This paper will extend the traditional, static LRAC curve concept by developing an appropriate dynamic framework. This framework will then be used to analyze the shifts of LRAC curves through time in three major American industries: steel making, cement manufacturing, and electric power generation.The empirical and theoretical topics explored in this study raise issues of both managerial and theoretical concern. These issues include: the relationship between economic plant life and plant size; the existence of scale biases in previous studies of scale economies and current depreciation practices; the accuracy and use of construction cost indexes; and the effects of technological change over extended periods of time. The dynamic framework developed in this study serves several useful purposes. For example, it constitutes a first step toward the development of theories that fill the void between the static theory of LRAC curves and the theories of increasing, decreasing, and constant cost industries. Furthermore, many questions, such as optimal plant or firm size, should be answered in a dynamic framework if appropriate managerial or anti-trust issues are to be considered. Finally, this dynamic framework shifts the emphasis of studies of scale economies back to costs and the use of this framework should result in improved corporate planning and decision making.     

PRODUCT OFFERING,PRICING, AND MAKE‐TO‐STOCK/MAKE‐TO‐ORDER DECISIONS WITH SHARED CAPACITY

In an era of mass customization, many firms continue to expand their product lines to remain competitive. These broader product lines may help to increase market share and may allow higher prices to be charged, but they also cause challenges associated with diseconomies of scope. To investigate this tradeoff, we considered a monopolist who faces demand curves, which for each of its potential products, decline with both price and response time (time to deliver the product). The firm must decide which products to offer, how to price them, whether each should be make‐to‐stock (mts) or make‐to‐order (mto), and how often to produce them. The offered products share a single manufacturing facility. Setup times introduce disceonomies of scope and setup costs introduce economies of scale. We provide motivating problem scenarios, model the monopolist's problem as a non‐linear, integer programming problem, characterize of the optimal policy, develop near‐optimal procedures, and discuss managerial insights.     

Global sourcing in integrated network structures: The case of hybrid purchasing organizations

An issue for companies in globally competitive markets is to adapt their organizational structures and governance in increasingly complex organizations. At the functional level of purchasing, companies are turning to hybrid purchasing organizations in order to leverage global sourcing benefits. One of the key challenges in this context is to distinguish between categories to be integrated across sites and those that are to remain under the authority of each purchasing location in order to maximize purchasing synergies.This paper presents a purchasing portfolio model that provides a comprehensive view of relevant global synergy dimensions. Based on a literature review, a theoretically-grounded purchasing portfolio model for global sourcing is developed. The theoretical basis stems from information processing theory, organizational buying behavior (OBB) and transaction cost economics. The validity of the model is explored by means of case study research. Complementing the extant literature, the theoretical contribution of the paper lies in not only addressing category selection criteria for exploiting economies of scale, but also for economies of information and learning and economies of process. Furthermore, it provides insights regarding integrated network coordination mechanisms at the functional level of purchasing.     

Altruism in Networks

We provide the first analysis of altruism in networks. Agents are embedded in a fixed network and care about the well‐being of their network neighbors. Depending on incomes, they may provide financial support to their poorer friends. We study the Nash equilibria of the resulting game of transfers. We show that equilibria maximize a concave potential function. We establish existence, uniqueness of equilibrium consumption, and generic uniqueness of equilibrium transfers. We characterize the geometry of the network of transfers and highlight the key role played by transfer intermediaries. We then study comparative statics. A positive income shock to an individual benefits all. For small changes in incomes, agents in a component of the network of transfers act as if they were organized in an income‐pooling community. A decrease in income inequality or expansion of the altruism network may increase consumption inequality.     

Benefits of Hybrid Lateral Transshipments in Multi‐Item Inventory Systems under Periodic Replenishment

Lateral transshipments are a method of responding to shortages of stock in a network of inventory‐holding locations. Conventional reactive approaches only seek to meet immediate shortages. The study proposes hybrid transshipments which exploit economies of scale by moving additional stock between locations to prevent future shortages in addition to meeting immediate ones. The setting considered is motivated by retailers who operate networks of outlets supplying car parts via a system of periodic replenishment. It is novel in allowing non‐stationary stochastic demand and general patterns of dependence between multiple item types. The generality of our work makes it widely applicable. We develop an easy‐to‐compute quasi‐myopic heuristic for determining how hybrid transshipments should be made. We obtain simple characterizations of the heuristic and demonstrate its strong cost performance in both small and large networks in an extensive numerical study.     

The Economics of Public Beta Testing

A growing number of software firms now rely on public beta testing to improve the quality of their products before commercial release. While the benefits resulting from improved software reliability are well recognized, some important market‐related benefits have not been studied. Through word‐of‐mouth, public beta testers can accelerate the diffusion of a software product after its release. Additionally, because of network effects, public beta testers can increase users’ valuation of a product. In this study, we consider both reliability‐related and market‐related benefits, and develop models to determine the optimal number of public beta testers and the optimal duration of testing. Our analyses show that public beta testing can be profitable even if word‐of‐mouth and network effects are the only benefits. Furthermore, when both benefits are considered, there is significant “economies of scope”—the net profit increases at a faster rate when both word‐of‐mouth and network effects are significant than when only one benefit is present. Finally, our sensitivity analyses demonstrate that public beta testing remains highly valuable to software firms over a wide range of testing and market conditions. In particular, firms will realize greater profits when recruiting public beta testers who are interested in the software but unable to afford it.     

When and How to Pursue Corporate Social Responsibility with Core Competencies

We first establish that the pursuit of corporate social responsibility (CSR) can enhance the society's welfare when both market and government imperfections occur, and demonstrate this is likely in most locales across the world. Second, we show that CSR initiatives are most likely successful and sustainable when a firm accurately identifies the benefits and costs of potential CSR initiatives and implements them consistent with its core competencies. We provide three reasons for a firm to focus CSR initiatives on core competencies: to reap economies of scale and scope in building company‐wide knowledge and skills; to promote worker productivity that is integral to the firm; and to exploit the fixed costs associated with managing workers. Each reason provides a distinct way to minimize the costs and increase the gains from pursuing CSR initiatives and provides implications for implementing CSR initiatives.     

Risk Finance for Catastrophe Losses with Pareto‐Calibrated Lévy‐Stable Severities

For catastrophe losses, the conventional risk finance paradigm of enterprise risk management identifies transfer, as opposed to pooling or avoidance, as the preferred solution. However, this analysis does not necessarily account for differences between light‐ and heavy‐tailed characteristics of loss portfolios. Of particular concern are the decreasing benefits of diversification (through pooling) as the tails of severity distributions become heavier. In the present article, we study a loss portfolio characterized by nonstochastic frequency and a class of Lévy‐stable severity distributions calibrated to match the parameters of the Pareto II distribution. We then propose a conservative risk finance paradigm that can be used to prepare the firm for worst‐case scenarios with regard to both (1) the firm's intrinsic sensitivity to risk and (2) the heaviness of the severity's tail.     

Network Game and Capacity Investment Under Market Uncertainty

This paper investigates the impacts of competition and market uncertainty on airlines' network structures and capacity investment. The airlines choose their network structures and construct capacities while demands are unknown. After uncertainty is resolved, they determine the total number of seats to offer in each leg constrained by their capacities built earlier. We conclude that market uncertainty is the driving force of hub‐and‐spoke networks, whereas the market mean is the driving force of point‐to‐point networks. Which of the two countervailing forces dominates determines the equilibrium network structures. Moreover, we find that the airlines' total expected profits in the mixed equilibrium in which the airlines employ different networks are larger than in the pure hub‐and‐spoke network equilibrium in which each airline employs the hub‐and‐spoke network. However, the mixed equilibrium does not necessarily yield larger profits than the pure point‐to‐point equilibrium in which each airline employs the point‐to‐point network.     

Supply Network Structure,Visibility, and Risk Diffusion: A Computational Approach

Understanding and managing supply chain risks is a critical functional competency for today's global enterprises. A lack of this competency can have significant negative outcomes, including costly production and delivery delays, loss of future sales, and a tarnished corporate image. The ability to identify and mitigate risks, however, is complicated as supply chains are becoming increasingly global, complex, and interconnected. Drawing on the complex systems and epidemiology literature, and using a computational modeling and network analysis approach, we examine the impact of global supply network structure on risk diffusion and supply network health and demonstrate the importance of supply network visibility. Our results show a significant association between network structure and both risk diffusion and supply network health. In particular, our results indicate that small‐world supply network topologies consistently outperform supply networks with scale‐free characteristics. Theoretically, our study contributes to our understanding of risk management and supply networks as complex networked systems using a computational approach. Managerially, our study illustrates how decision makers can benefit from a network analytic approach to develop a more holistic understanding of system‐wide risk diffusion and to guide network governance policies for more favorable health level outcomes. The article concludes by highlighting the main findings and discussing possibilities of future research directions.     

Lead Time Management through Expediting in a Continuous Review Inventory System

We consider a continuous review inventory system where delivery lead times can be managed by expediting in‐transit orders shipped from the supplier. First, we propose an ordering/expediting policy and derive expressions for evaluating the operating characteristics of such systems. Second, using extensive numerical experiments, we quantify the benefits of such an expediting policy. Third, we investigate a number of managerial issues. Specifically, we analyze the impact of the number of expediting hubs and their locations along the shipment network on the performance of such systems and offer insights into the design of the shipment network. We show (i) a single expediting hub that is optimally located in a shipment network can capture the majority of cost savings achieved by a multi‐hub system, especially when expediting cost is not low or demand variability is not high; (ii) when expediting time is proportional to the time to destination, for small‐enough or large‐enough demand variations, a single expediting hub located in the middle of the shipment network can capture the majority of cost savings of an optimally located hub; and (iii) in general, hubs close to the retailer significantly drive down costs, whereas hubs close to the supplier may not offer much cost savings.     

Upgrading local operations for global arbitrage

This study shows that upgrading sales operations in host countries towards production allows MNCs to perform global arbitrage in their networks of foreign subsidiaries and thereby contributes to a strategy of reaping the benefits of multinationality. We predict and find that operation upgrades follow opportunities of improving resource flows in the subsidiary network to exploit the advantages of host countries in tax rates, investment incentives, and technological knowledge across borders. Performance effects on the level of the MNC network give evidence of these benefits from global arbitrage.     

A Sequential Selection Problem*

In this study we formulate a sequential selection problem. In a setting where a choice sequence among candidates is established for filling a job position, the analysis explicitly takes into account the benefits from the hiring, the risk of rejection of the job offer, and the costs due to delays in filling the position. The proposed solution, which is both intuitive and simple, is able to capture analytically the decision process. We also illustrate the versatility of the analysis by considering several other relevant sequential selection settings.