Showing papers in "Decision Sciences in 2014"

Managing Imbalanced Supply Chain Relationships for Sustainability: A Power Perspective

Abstract: This study adopts a power perspective to investigate sustainable supply chain relationships and specifically uses resource dependence theory (RDT) to critically analyze buyer–supplier–supplier relationships. Empirical evidence is provided, extending the RDT model in this context. The concept of power relationships is explored through a qualitative study of a multinational company and agricultural growers in the UK food industry that work together to implement sustainable practices. We look at multiple triadic relationships involving a large buyer and its small suppliers to investigate how relative power affects the implementation of sustainable supply-management practices. The study highlights that power as dependence is relevant to understanding compliance in sustainable supply chains and to identifying appropriate relationship-management strategies to build more sustainable supply chains. We show the influences of power on how players manage their relationships and how it affects organizational responses to the implementation of sustainability initiatives. Power notably influences the sharing of sustainability-related risks and value between supply chain partners. From a managerial perspective, the study contributes to developing a better understanding of how power can become an effective way to achieve sustainability goals. This paper offers insights into the way in which a large organization works with small and medium size enterprises (SMEs) to implement sustainable practices and shows how power management—that is, the way in which power is used—can support or hinder effective cooperation around sustainability in the supply chain.

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

Abstract: 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.

The use of latent semantic analysis in operations management research

Abstract: In this article, we introduce the use of Latent Semantic Analysis (LSA) as a technique for uncovering the intellectual structure of a discipline. LSA is an emerging quantitative method for content analysis that combines rigorous statistical techniques and scholarly judgment as it proceeds to extract and decipher key latent factors. We provide a stepwise explanation and illustration for implementing LSA. To demonstrate LSA's ability to uncover the intellectual structure of a discipline, we present a study of the field of Operations Management. We also discuss a number of potential applications of LSA to show how it can be used in empirical Operations Management research, specifically in areas that can benefit from analyzing large volumes of unstructured textual data.

Encounter Satisfaction in E-tailing: Are the Relationships of Order Fulfillment Service Quality with its Antecedents and Consequences Moderated by Historical Satisfaction?

Abstract: This study focuses on whether historical satisfaction with an e-tailer (HSat) moderates baseline relationships in order fulfillment service quality models. HSat is defined as satisfaction with the e-tailer spanning all transactions except the current encounter. Encounter satisfaction (ESat) is defined as the consumer's satisfaction with the current transaction. In the baseline model, four order fulfillment service quality (OFSQ) dimensions managerially relevant to consumer e-tailing are examined: timeliness, availability, condition, and billing accuracy. The baseline structural model results support that OFSQ dimensions impact ESat, which in turn predicts two key consequences—repurchase intention and word-of-mouth. Adaptation theory is used to model the role of HSat, while controlling for transaction recency, vendor familiarity, and competitive pricing. HSat is shown to have pervasive main and interaction effects upon all baseline model relationships. These moderation effects have great managerial relevance. For example, the results illustrate a phenomenon similar to the service recovery paradox, wherein when a negative service encounter is followed by a highly positive service recovery event, previously dissatisfied consumers, as compared to previously satisfied consumers, respond with higher levels of current satisfaction. For managers, this finding is encouraging because policies that create highly positive events for consumers can thus supersede past negative experiences. Our results show however that HSat cannot be completely superseded by current OFSQ or current ESat.

Supplier selection behavior under uncertainty: : contextual and cognitive effects on risk perception and choice

Abstract: Buyers often make supplier selection decisions under conditions of uncertainty. Although the analytical aspects of supplier selection are well developed, the psychological aspects are less so. This article uses supply chain management and behavioral decision theories to propose that attributes of the purchasing situation (category difficulty, category importance, and contingent pay) affect cognition that, in turn, affects a supply manager's choice. We conducted a supplier selection behavioral experiment with practicing managers to test the model's hypotheses. When the context involves an important or difficult sourcing category, higher risk perceptions exist that increase preference for a supplier with more certain outcomes, even when that choice has a lower expected payoff. However, the presence of contingent pay decreases risk perceptions through higher perceived supplier control. We also find that a manager's risk propensity increases preferences for a supplier with less certain outcomes regardless of perceived risk. Our model and results provide a theoretical framework for further study into the cognitive aspects of supplier selection behavior and provide insight into biases that influence practicing supply chain managers.

Socially Responsible Practices: An Exploratory Study on Scale Development using Stakeholder Theory†

Abstract: Socially responsible practices of firms have evolved into an important area of research in operations management; however, it remains challenging to identify specific scales that capture multiple dimensions of such social practices. In this exploratory study, we use stakeholder theory to develop new multi-item measurement scales linked to multiple groups (i.e., internal, supplier, customer, and community stakeholders). Furthermore, we empirically test a higher order multidimensional construct that collectively assesses the socially responsible practices of a firm. Using these stakeholder-derived constructs as taxons in a cluster analysis, we identify important patterns in the way that multiple groups of stakeholders are engaged. Finally, we demonstrate that the set of social practices are complementary and concentrating on one group can yield spillover effects to other specific stakeholder groups.

Strategies for Appointment Policy Design with Patient Unpunctuality

Abstract: Appointment policy design is complicated by patients who arrive earlier or later than their scheduled appointment time. This article considers the design of scheduling rules in the presence of patient unpunctuality and how they are impacted by various environmental factors. A simulation optimization framework is used to determine how to improve performance by adjusting the schedule of appointments. Prior studies (that did not include patient unpunctuality) have found that a scheduling policy with relatively consistent appointment interval lengths in the form of a dome or plateau dome rule to perform well in a variety of clinic environments. These rules still perform reasonably well here, but it is shown that a combination of variable-length intervals and block scheduling are better at mitigating the effects of patient unpunctuality. In addition, performance improves if the use of this policy increases toward the end of the scheduling session. Survey and observational data collected at multiple outpatient clinics are used to add realism to the input parameters and develop practical guidelines for appointment policy decision making.

Theory Development in Operations Management: Extending the Frontiers of a Mature Discipline via Qualitative Research

Abstract: This invited paper discusses theory development in operations management. Many stellar researchers have made excellent contributions to theory development in our field. Operations management is a maturing discipline. Recently, theory driven empirical research has become common in top-tier journals in our field. Impelled by this trend and due to the path dependency of research, in general, researchers have examined operations phenomena using theories from management and organizational science. How do we extend the frontiers of knowledge in our maturing discipline? How do we develop theories within the field of operations management? In examining some of the seminal ideas that have shaped our field, a common characteristic is that they relied on observational studies and conceptual reasoning. Is it time for us to stress the usefulness of qualitative research methods in our field? Could this lead to an intellectual renewal in our field and extend the frontier of a maturing discipline? This paper explores these questions and advances the notion that qualitative analysis needs to be emphasized more than it has been in recent past. This paper is meant to provoke discussion among empirical researchers in operations management.

Quantitatively Representing Nonlinear Disaster Recovery

Abstract: This article provides a new technique for quantitatively characterizing the progress of recovery operations in the aftermath of a disaster event. The approach extends previous research on measuring dynamic, or adaptive, disaster resilience by developing a robust approach for characterizing nonlinear disaster recovery. In doing so, it enables a more accurate mathematical representation of di?erent categories of recovery behavior and provides support for a much broader application of existing theory. Because the new approach inherits the ability to compare the relative behavior of multiple scenarios simultaneously, it also can serve as the basis for analytically comparing the expected performance of different plans for recovery operations. Practical application of the technique is demonstrated and discussed in the context of recovering electrical power after Hurricane Sandy struck the New York metropolitan area.

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

Abstract: 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. © 2014 Decision Sciences Institute.

The Effect of Board of Directors’ IT Awareness on CIO Compensation and Firm Performance

Abstract: Chief information officers (CIOs) play increasingly strategic roles in firms in this competitive global economy, which is now largely powered by information technology (IT). However, research has shown a lack of board of directors� oversight on CIO- and IT-related issues. Drawing on agency, resource dependence, and alignment theories, we investigate the effect of board of directors� IT awareness on CIO compensation structure and firm performance. We conduct cross-sectional time series analyses of data collected from various sources. Our study underlines three important findings. First, we show that some commonly known executive compensation determinants, such as individual characteristics and governance structure, do not have significant effects on CIO compensation structure. Second, with regard to CIO compensation structure, firms respond to increasing information asymmetry differently according to the level of IT awareness of their boards. Finally, firms perform better when their boards have higher levels of IT awareness, and this positive effect of IT awareness is considerably larger in IT intensive industries. Overall, our study provides empirical support for the important role of boards� IT awareness in shaping CIO compensation and improving firm performance. Our results suggest that boards with functional area knowledge�or higher IT awareness in this case�can more effectively monitor and better incentivize executives, and consequently lead to better firm performance.

Optimal Temporal Customer Purchasing Decisions Under Trade‐In Programs with Up‐Front Fees

Abstract: To entice customers to purchase both current and new generation products over time, many firms offer different trade-in programs including programs that require customers to pay an up-front fee. To examine the effectiveness of the trade-in programs, we develop a two-period model in which a firm sells the first generation product in the first period and the second generation product in the second period; however, the firm offers a trade-in program that customers can participate in when purchasing the first generation product in the first period. To participate, each customer has to pay a nonrefundable fee in the first period so that she has the option to trade-in her first generation product and receive a prespecified trade-in value to be used for the purchase of the second generation product in the second period. To capture market heterogeneity and market uncertainty, we examine the case when the valuation of the first generation product varies among customers and the valuation of the second generation product is uncertain a priori. By analyzing a two-period game, we determine the optimal purchasing behavior of each rational customer, and we show that the firm is always better off by offering its own trade-in programs. Also, our numerical analysis reveals that trade-in programs can benefit the firm significantly especially when (i) the residual value of the first generation product is high; (ii) the expected incremental value of the second generation product is high; or (iii) the valuation of the second generation product is highly uncertain.

Partially flexible operating rooms for elective and emergency surgeries

Abstract: In hospitals, the management of operating rooms faces a trade-off between the need to be responsive to emergency surgeries and to conduct scheduled elective surgeries efficiently. Operating rooms can be configured as flexible and handle both electives and emergencies, or as dedicated to focus on either electives or emergencies. With flexible rooms, the prioritization of emergencies over scheduled electives can lead to schedule disruptions. Focused rooms can lead to imbalances between capacity and surgery workload. Whereas hospital administrators typically handle this trade-off by employing either flexible rooms (complete flexibility) or dedicated rooms (complete focus), we investigate whether a combination of flexible and dedicated rooms (partial flexibility) could be a preferable alternative. The ensuing question is what is the right combination of flexible and dedicated rooms? A versatile simulation model is developed to evaluate different resource allocation policies under various environmental parameters and performance metrics, including patient wait time, staff overtime, and operating room utilization. The main result is that partial flexibility configurations outperform both complete flexibility and complete focus policies by providing solutions with improved values of expected wait time for both emergency and elective patients.

Point-of-use hybrid inventory policy for hospitals

Abstract: Modern point-of-use technology at hospitals has enabled new replenishment policies for medical supplies. One of these new policies, which we call the hybrid policy, is currently in use at a large U.S. Midwest hospital. The hybrid policy combines a low-cost periodic replenishment epoch with a high-cost continuous replenishment option to avoid costly stockouts. We study this new hybrid policy under deterministic and stochastic demand. We develop a parameter search engine using simulation to optimize the long-run average cost per unit time and, via a computational study, we provide insights on the benefits (reduction in cost, inventory, and number of replenishments) that hospitals may obtain by using the hybrid policy instead of the commonly used periodic policies. We also use the optimal hybrid policy parameters from the deterministic analysis to propose approximate expressions for the stochastic hybrid policy parameters that can be easily used by hospital management.

Customizing quality management practices: A conceptual and measurement framework

Abstract: Quality management (QM) has often been promoted as a universal remedy, where organizations adopt these practices to enhance performance. However, implementation of QM has led to mixed results with some high-profile failures. Some suggest that customizing QM practices to fit the organization's situational context can help avoid implementation failure and improve performance. However, research has not fully investigated how organizations should go about customizing quality practices. This article addresses this question by conceptualizing two fundamental yet different aspects of QM practices that have different learning objectives: quality exploitation (QEI) and quality exploration (QER). Drawing on experts and empirical data, we develop a reliable and valid set of measures for QEI and QER. Furthermore, the analysis shows the performance differences in the two sets of QM practices across different contextual settings. Specifically, the empirical results show that the benefits of different QM orientations depend on the level of competition and rate of product change. This research challenges prior conceptualizations of QM, and suggests a practical framework to guide decision makers in customizing QM practices.

Governance Choice, Sourcing Relationship Characteristics, and Relationship Performance

Abstract: Past work on exchange relationships has debated the efficacy of partnership versus arm's-length governance on performance of a buyer�supplier relationship However, how these governance approaches leverage key supplier specific relationship characteristics has not been examined In this study, we examine the moderating role of governance choice (arm's-length versus partnership governance) in leveraging key supplier specific characteristics to achieve superior performance for the buyer in a relationship Specifically, drawing from residual rights theory, we argue that the governance choice buyers make moderates the impact of supplier flexibility, supplier human capital and relationship dependency on performance Our findings suggest that, for a buyer, the benefits of supplier flexibility and relationship dependency are better realized in partnership governance as opposed to arm's-length governance Further, our findings suggest that although buyers choose a specific governance approach consistent with their outsourcing motivation, the choice of governance is critical to leveraging the impact of supplier characteristics due to the moderation effects studied We elaborate on these effects and discuss the implications of our findings

A decision support tool for predicting patients at risk of readmission : a comparison of classification trees, logistic regression, generalized additive models and multivariate adaptive regression splines

Abstract: This is the peer reviewed version of the following article: Eren Demir, “Classification Trees, Logistic Regression, Generalized Additive Models, and Multivariate Adaptive Regression Splines” Decision Sciences, Vol 45(5): 849-880, October 2014, which has been published in final form at doi: 10.1111/deci.12094. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. © 2014 Decision Sciences Institute

On the Issuing Policies for Perishable Items such as Red Blood Cells and Platelets in Blood Service

Abstract: Red blood cells (RBCs) and platelets are examples of perishable items with a fixed shelf life. Recent studies show that transfusing fresh RBCs may lead to an improvement of patient outcomes. In addition, to better manage their inventory, hospitals prefer to receive fresh RBCs and platelets. Therefore, as well as minimizing outdates and shortages, reducing the average age of issue is a key performance criterion for blood banks. The issuing policy in a perishable inventory system has a substantial impact on the age of issue and outdate and shortage rates. Although several studies have compared the last in first out (LIFO) and the first in first out (FIFO) policies for perishable products, only a few studies have considered the situation of blood banks where replenishment is not controllable. In this study, we examine various issuing policies for a perishable inventory system with uncontrollable replenishment, and outline a modified FIFO policy. Our proposed modified FIFO policy partitions the inventory into two parts such that the first part holds the items with age less than a threshold. It then applies the FIFO policy in each part and the LIFO policy between the parts. We present two approximation techniques to estimate the average age of issue, the average time between successive outdates and the average time between successive shortages of the modified FIFO policy. Our analysis shows in several cases that where the objective function is a single economic function, or it is formulated as a multiobjective model, the modified FIFO policy outperforms the FIFO and LIFO policies.

Quantity Flexibility Contract in the Presence of Discount Incentive

Abstract: We design a new contract, which we refer to as the QFi contract, that combines the quantity flexibility (QF) mechanism and the price-only discount incentive. Under the QF contract, the buyer does not assume full responsibility for the forecast, yet the supplier guarantees the availability of the forecasted quantity and extra buffer inventory. In contrast, the price-only discount contract places full inventory burden on the buyer. We show that the proposed QFi contract effectively balances the inventory risk for both the buyer and the supplier considering both the QF and discount mechanisms. We also show that the QFi contract is able to achieve supply chain coordination. More importantly, the QFi contract's coordinating price scheme does not require knowledge of demand distribution. We identify areas where the buyer and supplier may both benefit from implementing the QFi contract as opposed to the extant QF or price-only (wholesale) discount contractual decisions in a decentralized supply chain. We also specify the conditions under which supply chain coordination can be achieved in a win-win manner. We conclude with managerial implications and provide directions for future research.

Emergency Department Staff Planning to Improve Patient Care and Reduce Costs

Abstract: In the face of high staffing costs, uncertain patient arrivals, and patients unsatisfied with long wait times, staffing of medical emergency departments (EDs) is a vexing problem. Using empirical data collected from three active EDs, we develop an analytic model to provide an effective staffing plan for EDs. Patient demand is aggregated into discrete time buckets and used to model the stochastic distribution of patient demand within these buckets, which considerably improves model tractability. This model is capable of scheduling providers with different skill profiles who work either individually or in teams, and with patients of varying acuity levels. We show how our model helps to balance staffing costs and patient service levels, and how it facilitates examination of important ED staffing policies.

Adoption of Mobile Telephony in Rural India: An Empirical Study

Abstract: Mobile telephony has become one of the major factors driving the social and economic development of a country. The objective of this article is to identify factors affecting the adoption of mobile telephony in rural India and examine their impact on its adoption. An explanatory empirical methodology with sequential design was used for this purpose, and new factors that affect users� decisions to adopt mobile telephony in rural India were identified. We extended the technology acceptance model by integrating new factors for a developing nation. This study found that ensuring service transparency and identifying opinion leaders in the local community are key requirements for increasing the speed of adoption in the rural India. The findings of this study will provide insights for service providers and policy makers to develop strategies and policies that will enhance mobile telephony adoption in rural India.

Green Purchasing by MNC Subsidiaries: The Role of Local Tailoring in the Presence of Institutional Duality

Abstract: To examine the essential determinants of green purchasing by multinational corporations� (MNC) subsidiaries, this study takes institutional theory as a foundation and focuses on the institutional duality associated with localization and globalization. Specifically, we develop a model to explain subsidiaries� green purchasing and empirically test the model with data from 141 purchasing managers and senior purchasing staff members from subsidiaries in 39 countries. Our results suggest that pressures from headquarters and the local environment do not affect subsidiaries� green purchasing directly; rather, they exert indirect influences through local tailoring. This study contributes to extant literature by revealing the significance of local tailoring in an MNC context. In addition, our findings offer several implications for practice by providing a roadmap for disseminating green purchasing across the subsidiaries of an MNC, as well as highlighting the importance of both clear communication about the benefits of green purchasing and internal audits.

The Importance of Social Embeddedness: Churn Models at Mobile Providers

Abstract: This article argues the importance of social embeddedness at mobile providers by exam- ining the effects of customers’ network topological properties on churn probability—the probability of a customer switching from one telecommunication provider to another. This article uses data from regional snowball sampling—the only practically feasible network sampling method—to identify groups with significantly different churn ratios for customers with different network topological properties. Clear evidence indicates that individual network characteristics (node-level metrics) have considerable impact on churn probabilities. The inclusion of network-related measures in the churn model allows a longer-term projection of churners and improves the predictive power of the model. With no possibility to carry out repeated sampling, sample stability was checked through simulation results. On the one hand, this article highlights the importance and effectiveness of the provider’s tailored marketing campaigns by showing that customers targeted by direct marketing campaigns are less threatened by churn than nontargeted customers. On the other, this article shows that social embeddedness blocks the impact of the very same marketing efforts. This article forwards the idea that social embeddedness, also prevalent in vendor switching, can be extended to understanding the development of professional societies threatened by membership churn. [Submitted: January 12, 2012. Revised: July 30, 2012; March 31, 2013. Accepted: April 12, 2013.]

Assessing Antecedents of Socially Responsible Supplier Selection in Three Global Supply Chain Contexts

Abstract: A number of highly publicized, controversial lapses in social responsibility within global supply chains have forced managers and scholars to reexamine long-held perspectives on supplier selection. Extending Carter and Jennings� department-level study of purchasing social responsibility, our research assesses the role of supply managers� ethical intentions and three key antecedents that drive socially responsible supplier selection. Comparing evidence from firms operating in China, the United States, and the United Arab Emirates, we identify three key drivers of supply managers� ethical intentions and examine both their direct and indirect impacts on socially responsible supplier selection. We find differential support for the predictor relationships on supply manager ethical intentions across national contexts and mediated versus nonmediated models. These observations bear important implications for firms conducting global supply management.

Pricing of Full-Service Repair Contracts with Learning, Optimized Maintenance, and Information Asymmetry

Abstract: This article considers the optimal pricing of full-service (FS) repair contracts by taking into account learning and maintenance efficiency effects, competition from service , and asymmetric information. We analyze on-call service (OS) and FS contracts in a market where customers exhibit heterogeneous risk aversion. While the customers minimize their disutility over the equipment lifetime, the service provider maximizes expected profits arising from the portfolio of OS and FS contracts. We show that the optimal FS price depends inter alia on the customer's prior cost experience and on OS repair and maintenance costs. The optimal FS price is shown to increase as fewer OS customers are lost to competition, whereas improved repair learning enabled by FS reduces the optimal price. A numerical study based on data from a manufacturer of forklifts highlights the importance of learning in maintenance operations, which constitutes the key benefit of FS contracts; 81% of the customers select the FS option and are willing to pay an insurance premium of around 1.5% of total OS cost against volatility of repair costs.

Exploiting Technological Indicators for Effective Technology Merger and Acquisition (M&A) Predictions

Abstract: Mergers and acquisitions (M&A) play increasingly important roles for contemporary business, especially in high-tech industries that conduct M&As to pursue complementarity from other companies and thereby preserve or extend their competitive advantages. The appropriate selection (prediction) of M&A targets for a given bidder company constitutes a critical first step for an effective technology M&A activity. Yet existing studies only employ financial and managerial indicators when constructing M&A prediction models, and select candidate target companies without considering the profile of the bidder company or its technological compatibility with candidate target companies. Such limitations greatly restrict the applicability of existing studies to supporting technology M&A predictions. To address these limitations, we propose a technology M&A prediction technique that encompasses technological indicators as independent variables and accounts for the technological profiles of both bidder and candidate target companies. Forty-three technological indicators are derived from patent documents and an ensemble learning method is developed for our proposed technology M&A prediction technique. Our evaluation results, on the basis of the M&A cases between January 1997 and May 2008 that involve companies in Japan and Taiwan, confirm the viability and applicability of the proposed technology M&A prediction technique. In addition, our evaluation also suggests that the incorporation of the technological profiles and compatibility of both bidder and candidate target companies as predictors significantly improves the effectiveness of relevant predictions.

Looking Inside Glitch Mitigation Capability: The Effect of Intraorganizational Communication Channels

Abstract: Manufacturers can reduce the occurrence of glitches in their operations by building capabilities to prevent them, yet mitigation capabilities are also needed to contain the effects of the glitches that will still inevitably occur every now and then. We examine the glitch mitigation capability of a production process from an information-processing perspective and propose that (i) the impact of operational glitches on delivery performance is contingent on the formalization of intrafirm communication channels and (ii) this effect is stronger when formal communication channels are complemented with informal channels. We test our model in a sample of 163 make-to-order production processes and find support for the first hypothesis and partial support for the second hypothesis. The statistical analyses also reveal nonhypothesized empirical regularities, which we explore through an additional qualitative study based on 34 site visits and 30 interviews with production planners. The results have practical implications for the design of intraorganizational communication channels, and they also contribute to the research on organizational resilience and communications by showing that when coping with disruptions, the formal communication channels have advantages that are seldom discussed in the literature or recognized by practitioners.

Sourcing Decisions with Competitive Suppliers and Imperfect Information

Abstract: Manufacturers often must choose between outsourcing and producing internally. This choice is complex and influenced by a variety of factors, including the costs and capabilities of the potential suppliers. In addition, if the manufacturer outsources, he must design the sourcing process. We study the manufacturer's outsourcing decision, with a focus on the impact of the sourcing process on that decision. We consider a setting in which the manufacturer has imperfect information regarding the suppliers' costs and capabilities, and we assume that the manufacturer uses a two-stage sourcing process. The first stage is the qualification stage, in which the manufacturer seeks to reduce the uncertainty regarding the suppliers' capabilities. The second stage is the supplier selection stage, in which the manufacturer selects among the qualified suppliers on the basis of price. We first characterize the optimal design of the two-stage process, and then consider the outsourcing decision. We demonstrate several trade-offs. Vertical integration enables the manufacturer to reduce uncertainty and extract all of the profits of production. However, outsourcing enables the manufacturer to take advantage of the (potentially) lower costs and higher capabilities of the suppliers, particularly if competition between suppliers can be encouraged. We find that the manufacturer is more likely to vertically integrate when the warranty cost and the cost of exerting effort during qualification are large, and when there is significant uncertainty regarding the suppliers' capabilities. The manufacturer is more likely to outsource when the suppliers' costs (capabilities) are low (high), and when the number of suppliers is large.

Failure Risk and Quality Cost Management in Single versus Multiple Sourcing Decision

Abstract: The advantage of multiple sourcing to protect against supplier failures arising from undependable products due to latent defects is examined using a model with non-linear external failure costs. Prior research has focused only on supplier failures arising from unreliable supply, such as late/insufficient/no delivery. I derive a closed-form characterization of the optimal production quota allocation for the LUX (Latent defect-Undependable product-eXternal failure) setting. The allocation determines the optimal supply base, with intuitive properties that hold under a mild requirement. The requirement includes the special case of equal procurement costs charged by suppliers but also allows unequal costs without any particular order. The key result of the paper is a necessary and sufficient condition determining whether single or multiple sourcing is optimal. Another condition is obtained to determine the exact size of the optimal supply base, provided the mild requirement holds. With minor modifications, the results also hold when a buyer-initiated procurement contract can be used to elicit private information on the suppliers’ unit variable production costs.

Role of Random Capacity Risk and the Retailer in Decentralized Supply Chains with Competing Suppliers

Abstract: This research considers a supply chain under the following conditions: (i) two heterogeneous suppliers are in competition, (ii) supply capacity is random and pricing is endogenous, (iii) consumer demand, with and without an intermediate retailer, is price dependent. Specifically, we examine how uncertainty in supply capacity affects optimal ordering and pricing decisions, supplier and retailer profits, and the incentives to reduce such uncertainty. When two suppliers sell through a monopolistic retailer, supply uncertainty not only affects the retailer's diversification strategy for replenishment, but also changes the suppliers� wholesale price competition and the incentive for reducing capacity uncertainty. In this dual-sourcing model, we show that the benefit of reducing capacity uncertainty depends on the cost heterogeneity between the suppliers. In addition, we show that a supplier does not necessarily benefit from capacity variability reduction. We contrast this incentive misalignment with findings from the single-supplier case and a supplier-duopoly case where both suppliers sell directly to market without the monopolistic retailer. In the latter single-supplier and duopoly cases, we prove that the unreliable supplier always benefits from reducing capacity variability. These results highlight the role of the retailer's diversification strategy in distorting a supplier's incentive for reducing capacity uncertainty under supplier price competition.