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PurposeThis paper aims to investigate the evolution of operations management (OM) research along two major dimensions from 1977 to 2003 and discusses possible paths for research progression in the future.Design/methodology/approachTo identify OM research papers, a careful definition of OM research was constructed based initially on earlier work and then more precisely extended through empirical analysis. The research on OM builds on a previous study that took snapshots of OM research in 1977 and 1987. It then extends and updates it through a content analysis of 593 articles published in 1995 and 2003 in five journals recognized for publishing OM research.FindingsThe overall results illustrate that OM has evolved from heavily rationalistic, axiomatic analyses based on artificial reconstructions of reality toward more interpretive analyses based on natural observations of reality.Research limitations/implicationsAs the OM field continues to evolve, it is important to monitor and reassess published research to discern its changing dimensions. While this effort is not an exhaustive review of all OM research and does not consider all relevant journals and years, it does offer the "big picture" perspective needed for analyzing changing research approaches in the field.Practical implicationsThe research provides an analysis of the evolution of knowledge creation within the field and possible paths for its future development. The practical implications are that as research becomes more interpretive and observation‐based, the findings will have more relevance for managers and the problems they face.Originality/valueWhile several authors have analyzed the OM field relative to select research methods and journals, this paper provides a broader and more encompassing view of OM research along two important research dimensions: the researcher's framework and the source of the data.

PurposeThe purpose of this paper is to assess and document the progress of postponement research, identify current gaps, and provide direction for future research efforts.Design/methodology/approachPostponement literature published from 1999 to 2006 was reviewed.FindingsThe review revealed a significant increase in the number of postponement research efforts, many of which at least partially addressed past challenges noted in previous research. Several opportunities to continue addressing these past challenges were identified. Future researchers are challenged to validate new postponement concepts and extend postponement research beyond its manufacturing context. Other challenges call for the continued assessment of the relationship between postponement and uncertainty and the investigation into the slow rate of postponement adoption among practitioners.Research limitations/implicationsThis effort is not an exhaustive review of all postponement research. This review does not consider unpublished papers, papers in non‐academic journals, or papers presented at conferences.Practical implicationsThis review is a useful resource for supply chain researchers interested in supply chain strategies and the evolution of postponement as a supply chain concept.Originality/valueThis paper uses the challenges of past research as a measure of the progress of postponement thought and theory. The gaps identified and challenges made will serve as a foundation upon which future researchers can build.

PurposeThe purpose of the paper is to provide a conceptual foundation to enhance the body of knowledge related to supplier selection in light of global supply chain disruptions and risk.Design/methodology/approachThe proposed tool is based on a multi‐criteria optimization framework, which will enable the user to gain a better understanding of how the consideration of each of these risk measures will affect the recommended solution/supply base. The model serves as a complement to existing supplier selection models by incorporating regional risks associated with potential suppliers' locations and density risks based on great circle distance measures.FindingsThe paper demonstrated the proposed model by using the great circle distance measure to calculate the density risk and two secondary data sources to capture environmental risk. One measure captures a variety of environmental issues such as political, legal, security, fiscal, labor, and regulatory issues. The other measure captures the historical effects of weather on dollar and human losses in each country of the world, which represents the potential for severe weather events and the country's ability to react to these events.Research limitations/implicationsAlthough the paper does not consider all possible risks, it augments prior research through the development of a decision support tool that offers supply risk mitigation when sourcing globally. Specifically, the tool allows for the analysis and mitigation of two key global risk measures, environmental risk and density risk, when selecting suppliers for mission‐critical parts. The model is able to support various sourcing strategies such as sole, multiple and cross sourcing and can be used in conjunction with other disruption mitigation strategies such as supply redundancy.Practical implicationsGlobal sourcing has provided significant performance enhancements, but has put firms in a vulnerable position relative to the potential devastating effects of supply disruptions. While supply managers are cognizant of the risks associated with global sourcing, limited knowledge and tools are available to allow them to mitigate these risks. Although it would need to be adapted to the nuances of company supply chains, it is believed that the tool provides value to managerial decision making relative to the sourcing of mission critical parts/products.Originality/valuePrior work in this area has not adequately incorporated contemporary issues and risks in global sourcing. The paper augments prior research through the development of a multi‐objective decision support model for strategic supplier selection that is focused on two important contemporary factors: environmental risk and density risk. The proposed model captures important interdependent relationships between these two factors that have not been considered in prior selection models.

ABSTRACTThe COVID‐19 pandemic paralyzed the world and revealed the critical importance of supply chain management—perhaps more so than any other event in modern history—in navigating crises. The extensive scope of disruption, massive spillover of effects across countries and industries, and extreme shifts in demand and supply that occurred during the COVID‐19 pandemic illustrate that pandemics are qualitatively different from typical disruptions. As such, pandemics require scholars to take a fresh look at what lenses offer understanding of supply chain phenomena in order to help supply chain managers better prepare for the next pandemic and foster transiliency (i.e., the ability to simultaneously restore some processes and change—often radically—others). To help scholars and managers achieve these aims, we offer an agenda for supply chain management research on pandemics by considering how the key tenets of well‐known and emergent theories can illuminate challenges and potential solutions. Specifically, we consider how resource dependence theory, institutional theory, resource orchestration theory, structural inertia, game theory, real options theory, event systems theory, awareness–motivation–capability framework, prospect theory, and tournament theory offer ideas that can help scholars build knowledge about pandemics' effects on supply chains as well as help managers formulate responses.

ABSTRACTFollowing supplier‐induced disruptions, suppliers may undertake recovery actions in hopes of reducing damage to the focal exchange with buyers. While research shows that the absence of suppliers' recovery actions almost always leads to a deteriorated relationship, it is less clear if—or more likely when—the presence of suppliers' recovery actions restores a relationship. Accordingly, we examine a specific set of suppliers' recovery actions in light of important considerations—that is, disruption severity, suppliers' dependence, and buyers' supply chain risk uncertainty. Through the lens of signaling theory, we frame supplier‐induced disruptions as negative signals from suppliers (signalers) to buyers (receivers) and suppliers' recovery actions as positive signals. We theorize that these mixed signals unfold in different buyers' perceptions due to the aforementioned contextual considerations. Using the critical incident technique to capture disruption events, we find that the messages of suppliers conveyed through their recovery actions may or may not be "loud and clear," depending on the context. In doing so, our results reveal substantive guidance for suppliers' use of recovery actions to combat the negative perception of supplier‐induced disruptions. Likewise, the results are also promising for buying companies seeking to develop (i.e., improve) supplier performance.

ABSTRACTDespite recent attention to closed‐loop supply chains and remanufacturing, there is scant information about what drives the re‐make versus buy decision for original equipment manufacturers (OEMs) engaging in remanufacturing. Based on the extant remanufacturing literature and transaction cost economics, we formulated hypotheses related to the drivers of in‐house versus contracted remanufacturing operations. The hypotheses were investigated via quantitative and qualitative data, thus offering a rich test of the formulated relationships. Consistent with the theory, the quantitative results showed that intellectual property, operational assets, and remanufacturing frequency are significant drivers of the re‐make versus buy decision. However, counter to the theory, the quantitative results did not support the significance of brand reputation, technological uncertainty, condition uncertainty, product complexity, and volume uncertainty. The qualitative results were used to enrich these findings by providing theoretical extensions and pragmatic insights of the remake versus buy decision in remanufacturing.

ABSTRACTSupply chain risk uncertainty can create severe repercussions, thus it is not surprising that research interest in supply chain risk has been growing. While extant inquiry is informative, there is a lack of investigations that center on supply chain investment decisions when facing high levels of risk uncertainty. Given the potential dollar value involved in these decisions, an understanding of how these supply chain decisions are made is of significant theoretical and practical importance. Real options theory, with its focus on decision making under conditions of uncertainty, is an appealing theoretical lens for this endeavor. In essence, real options theory asserts that managerial decisions center on creating and then exercising or not exercising certain opportunities. To date, theorizing about and investigations of real options have used firms as their focus. Not yet examined are real options within supply chains that cross firm boundaries and drive much of the competitive activity in the modern economy. Accordingly, we extend real options theory to the supply chain context by examining how different types of options are approached relative to supply chain project investments. Specifically, we theorize how the options will be related to perceived value under conditions of high supply chain risk uncertainty. Overall, our investigation builds knowledge by extending real options theory to the supply chain context and by providing evidence suggesting some options operate differently in supply chains than they do in firms.

ABSTRACTSupply chain disruptions and the associated operational and financial risks represent the most pressing concern facing firms that compete in today's global marketplace. Extant research has not only confirmed the costly nature of supply chain disruptions but has also contributed relevant insights on such related issues as supply chain risks, vulnerability, resilience, and continuity. In this conceptual note, we focus on a relatively unexplored issue, asking and answering the question of how and why one supply chain disruption would be more severe than another. In doing so, we argue, de facto, that supply chain disruptions are unavoidable and, as a consequence, that all supply chains are inherently risky. Employing a multiple‐method, multiple‐source empirical research design, we derive novel insights, presented as six propositions that relate the severity of supply chain disruptions (i) to the three supply chain design characteristics of density, complexity, and node criticality and (ii) to the two supply chain mitigation capabilities of recovery and warning. These findings not only augment existing knowledge related to supply chain risk, vulnerability, resilience, and business continuity planning but also call into question the wisdom of pursuing such practices as supply base reduction, global sourcing, and sourcing from supply clusters.

ABSTRACTMany 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.

PurposeThe purpose of the paper is to provide a conceptual/theoretical foundation to enhance the body of knowledge related to supply chain interdependence and technology‐enabled coordination.Design/methodology/approachThe paper heavily engaged itself in the theory/literature related to coordination theory, interdependence theory, interdependence, coordination and supply chain technologies to formulate the theoretical propositions.FindingsFrom the literature/theoretical bases, the paper derived a total (include sub‐components) of eight theoretical propositions related to interdependence, coordination and technology enablers.Research limitations/implicationsWhile technology enabled‐coordination is central to supply chain management, there is a lack of a prescriptive view present in the literature. By deriving insights from the rich literature related to coordination theory and interdependence theory, we provide a theoretical foundation for future research to enhance the body of knowledge related to the systematic application of technology to foster the appropriate coordination strategy.Practical implicationsAlthough empirical support is warranted, the proposed concepts related to technology‐enabled coordination offer pragmatic advice to managers.Originality/valueThe paper provides a theoretical foundation for future research to enhance the body of knowledge related to the systematic application of technology to foster the appropriate coordination strategies.