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ABSTRACTIn an automotive supply chain, long production time and demand uncertainty lead to major challenges in meeting customer demand. To respond to these challenges, automotive supply chain incorporates flexibility in the order‐fulfillment process through vehicle trades. This study focuses on a new category of vehicle trades where dealers trade vehicles that are still under production (order‐trades) and in the delivery phase of the order‐fulfillment process (distribution‐trades). Using empirical data in an experimental design setting, order‐ and distribution‐trades are shown to improve flexibility in order fulfillment, with no additional costs for the manufacturer. Different managerial levers such as trade fees and trade caps are evaluated to develop insights for managing vehicle trades. The results show that the involvement of the manufacturer in planning order‐ and distribution‐trades helps in lowering inventory, reducing lost sales, and improving logistics costs for the entire supply chain.

PurposeThe purpose of this research is to investigate the contingent adoption of Additive Manufacturing (AM) and propose a typology to evaluate its adoption viability within a firm's supply chain.Design/methodology/approachBy conducting semi-structured interviews of practitioners with deep knowledge of AM and supply chains from diverse industries, this research explores the contingent factors influencing AM adoption and their interaction.FindingsWhile the AM literature is growing, there is a lack of research investigating how contingent factors influence AM adoption. By reviewing the extant literature on the benefits and barriers of AM, we explain the underlying contingencies that enact them. Further, we use an exploratory approach to validate and uncover underexplored contingent factors that influence AM adoption and group them into technological, organizational and strategic factors. By anchoring to a selected set of contingent factors, a typological framework is developed to explain when and how AM is a viable option.Research limitations/implicationsThis study focuses on specific industries such as automotive, machine manufacturing, aerospace and defense. Scholars are encouraged to explore the contextual factors affecting AM adoption in particular industries to expand our findings. The authors also acknowledge that the robustness of their framework can be enhanced by integrating the remaining contingent factors.Practical implicationsThe developed typological framework provides a pathway for practitioners to see how and when AM can be useful in their supply chains.Originality/valueThis is the first paper in the supply chain management literature to synthesize contingent factors and identify some overlooked factors for AM adoption. The research is also unique in explaining the interaction among selected factors to provide a typological framework for AM adoption. This research provides novel insights for managers to understand when and where to adopt AM and the key contingent factors involved in AM adoption.

AbstractUtilizing behavioral experiments involving approximately one thousand subjects, we empirically evaluate the relationship between volume flexibility and the Bullwhip Effect (BWE). We not only evaluate differences in the level of BWE, but also differences in associated system performance. We find that systems with hard capacity constraints are effective at limiting BWE, but also produce very poor customer service levels. However, systems with low levels of volume flexibility generate similar performance as fully flexible systems but do so while also generating a lower BWE. In a multi‐echelon setting, we show that having partial volume flexibility at the upstream echelon helps in reducing order variance, with no significant drop in service level in the supply chain. This is particularly useful in those manufacturing environments which prefer stable orders for production planning without affecting the downstream customer service level. Counterintuitively, both experiments uncovered instances of irrational behavior where participants invoked flexibility in ways that did not always enhance system performance. In addition, these experiments also established enhancements in BWE and system performance through introduction of incremental volume flexibility into upstream echelon of a supply chain.

AbstractHospitals are under tremendous pressure to improve multiple performance dimensions that may be at odds, including cost containment, clinical quality, and patient satisfaction. The need to improve performance on multiple fronts is compounded by sources of uncertainty that include upstream diversity of supply chain (SC) partners, internal diversity of clinical specialties provided, and downstream diversity of patient conditions. Information processing theory (IPT) suggests two strategies for dealing with uncertainty: reduce the amount of information elevated to higher levels for processing and accommodate the amount of information by increasing information processing at other levels. We apply IPT to investigate (i) the relationship between the two information processing strategies in a hospital's SC and its cost containment, clinical quality, and patient satisfaction performance, and (ii) how these relationships may be moderated by diversity in the hospital's SC partners, clinical specialties, and patients, the common sources of uncertainty in hospital SCs. These questions were examined using regression analysis of primary data from acute care hospitals matched with secondary data from the Centers for Medicare and Medicaid Services, American Hospital Association and the Agency for Healthcare Research and Quality measuring hospital operating characteristics and performance. The analysis yielded several important findings: (i) while a slack resources strategy (uncertainty reduction) is effective for improving patient satisfaction performance, it is ineffective for reducing cost, (ii) a lateral relations strategy (uncertainty accommodation) is effective in improving all three performance dimensions, and (iii) these relationships are moderated differentially by the three diversity dimensions only for lateral relations. These findings offer important managerial insights about hospitals' efforts to improve potentially conflicting performance outcomes and suggest interesting opportunities for future research applying IPT to this important topic.

ABSTRACTIn recent years, there have been increasing calls from the government and other organizations to provide easy public access to student evaluations of teaching. Indeed, the increasing ease of displaying and viewing large quantities of information, and competition among universities and majors for students, makes it likely that an era of greater transparency of this type of information is at hand. While students' evaluation of teaching (SET) is one quantitative metric that rates the instructor, it may be influenced by factors that are often beyond the instructor's control. In this study, we analyze a longitudinal data set from both engineering and business schools of a large public university, and identify factors that influence SET. We show which factors have the highest influence on overall SET scores, and contrast these between engineering and business colleges. Colleges within the same university may have differences in the factors affecting SET, and recognition of this is important in effectively and fairly evaluating SET scores. We also provide recommendations regarding information that should be displayed along with the SET, particularly when SET scores are made public, so that instructors are not unduly penalized when their evaluations can be influenced by factors over which they have no control.

PurposeDrawing on transaction cost economics (TCE) theory and organizational information processing theory (OIPT), this study investigates how the alignments between the characteristics of service (i.e. task complexity and measurement ambiguity) and governance mechanisms (i.e. contract specificity and monitoring) can affect service performance.Design/methodology/approachThe paper uses a rigorously designed survey to collect data from professionals who manage service outsourcing contracts in various industries. The respondent pool consists of randomly selected members of the Institute of Supply Management (ISM). The authors' research question is analyzed using 261 completed and useable responses. Structural equation modeling is adopted to examine the data and test the proposed hypotheses.FindingsThe authors find that both contract specificity and monitoring have a positive impact on supplier performance. Further, for high task complexity services, contract specificity is more effective than monitoring, and for high measurement ambiguity services, the opposite is true. Moreover, the effect of contract specificity is mediated by monitoring.Practical implicationsService outsourcers should use both contract specificity and monitoring in governing outsourced services and know that the former depends on the latter during execution. Facing resource constraints, they can prioritize crafting detailed contract provisions over implementing monitoring for highly complex services but consider monitoring as the primary governance tool in services whose outcomes are difficult to measure.Originality/valueThis study is the first to couple TCE with OPIT and consider the nature of outsourced services in the choice of governance mechanisms and empirically test the simultaneous effects of contract specificity and monitoring in the context of service outsourcing.

PurposeThe purpose of this paper is to review the literature to describe the current practices and research trends in managing supply chains in crisis. This paper also provides directions for future research in supply chain crisis management.Design/methodology/approachArticles published prior to August 2008 are analyzed and classified.FindingsA unique five‐dimensional framework to classify the literature is provided. The study reveals that there has been extensive research done in this area in recent years. Much of the research is focused on proactive approaches to crisis in supply chains. Management during various internal crises such as supplier bankruptcy or loss of key clients is a new, challenging area that requires further investigation.Research limitations/implicationsThis paper does not include articles that are not peer‐reviewed.Practical implicationsThis paper will serve as a guide to supply chain managers who would like to know how crises, disasters, and disruptions in supply chains have been handled in existing academic literature.Originality/valueTo the best of the authors' knowledge, this is the first literature review in the area of managing supply chains during crisis that looks at both SCM and operations research/management science journals. This paper identifies the various methods that have been used to handle crisis situations and provides a framework to classify the literature. Additionally, this paper identifies gaps in the literature that can provide ideas for future research in this area.