Journal of Operations Management最新文献

Disasters affect hundreds of millions of people every year and the response of governments is crucial in alleviating the suffering of those affected. Despite the importance of contracting in response to disasters, research on this topic is conspicuous by its absence. This paper begins to address this gap by investigating the choice of procurement contract type by US federal agencies during disaster management operations. The research relies on 47,560 contracts issued by the US federal government in response to 14 major disasters between 2005 and 2016. We build on agency theory to investigate the choice of the contract type made by federal agencies at the different stages of a relief operation. This research provides empirical evidence of the key factors underpinning the choice of contract in the context of disaster management, namely the amount of spend per contract and the type of acquisition (product or service), and reveals the moderating role of the stage of the relief operation.

Appointing individuals drawn from suppliers and customers to a firm's board of directors is an increasingly popular practice that can enhance the interorganizational relationship and generate relational rents. Yet, such board members may act in the best interest of their primary employer rather than the shareholders of the firm whose board they serve on, thus creating potential agency conflicts. Drawing on the relational view and agency theory, we explore the tension between rent generation and agency costs and consider how a firm can design governance mechanisms to effectively leverage customer or supplier representation on the board of directors. The associated hypotheses are tested using a large panel dataset constructed from multiple archival sources, and our findings suggest that supplier and customer board members are a double-edged sword: While they generate value in some instances, they can also be associated with lower performance depending on the levels of two key governance mechanisms—the number of inside directors on the board and the proportion of outcome-based board member compensation.

This research examines the impact of leader disability status on the operational performance of teams that include individuals with disabilities (IWD) using longitudinal micro-data from an apparel manufacturing company in a competitive integrative employment environment. To aid in developing the research hypotheses and in interpreting the empirical findings, the quantitative analysis is complemented with qualitative data collected through interviews involving managers and workers with and without disabilities at the focal firm and two other large companies that employ IWD. A beneficial moderating effect of leader-worker disability status similarity on team performance is hypothesized and subsequently tested using Prais-Winsten regression. The results show that a leader with a disability has a potentially beneficial impact on team performance as the number of workers with disabilities in the team increases, resulting in improved productivity (measured in labor hours per garment) and quality (measured in operator defects per garment). The theoretical, managerial, and policy implications of the study provide actionable insights for the creation of an inclusive labor force.

As the US healthcare system transitions from volume to value, various value-based programs tie medical reimbursements to hospital performance relative to national top performers (i.e., benchmarks). However, prior studies report very limited results on how such benchmarks affect care delivery and patient outcomes across multiple performance fronts. This study examines how general acute care hospitals progress toward benchmarks measured by performance frontiers in technical efficiency, clinical quality, and patient experience over time, subjecting to external market conditions and internal focuses. Based on a panel dataset comprising hospitals in California from 2012 and 2019, our results find support for competitive-distance-driven progression rates, suggesting that hospitals' competitive positions measured by their distances to benchmarks drive performance improvements. Yet, the effect diminishes as they move closer to performance frontiers. In addition, we find that market competition reduces the progression rate of technical efficiency. Finally, our results also suggest that focus improves performance progression rates, yet its effects are curvilinear.

The increased digitalization of shop floors has provided unprecedented opportunities for real-time sharing of process and resource details. Visualization boards (VBs), which provide ubiquitous technology-enabled renderings of such details, salient to a local shop-floor setting, have the potential to play a significant role in this regard. Critical to the effectiveness of this role is the fit between VB design and shop-floor needs. In our study, we apply task-technology-fit theory in case examinations focused on identifying mismatch, implications of mismatch, and putative best practices in designs for future interventions. Our assessment capitalizes on both core operations management design principles as well as technology management design principles. We develop grounded propositions regarding guidelines that should be applied in future VB designs and deployments.

The world is witnessing more supply-base disruptions, where multiple suppliers of a buying firm simultaneously experience disturbed operations. Compared to single-supplier disruptions, supply-base disruptions create a more uncertain situation for a purchasing manager, yet they can also reveal improvement opportunities. Hence, it is theoretically and practically valuable to understand why a purchasing manager might not be willing to explore these opportunities. Adopting a sensemaking perspective, we investigate how two dimensions of supply-base disruption severity, breadth and depth, influence managers' perception of disruption severity and post-recovery action (i.e., suggesting supply-base restructuring ideas). We conducted multiple scenario-based experiments with practitioners and triangulated the experimental results with interviews, finding that both breadth and depth have diminishing, positive effects on perceived severity. Interestingly, depth is less influential than breadth. These findings reveal the circumstances under which the severity of a complex, disruptive situation could be misestimated. Our results also show that supply-base structural complexity (a cue of the task environment) amplifies the positive effect of perceived severity on a manager's inclination to walk into the unknown to propose supply-base restructuring ideas. These findings provide an explanation for management nonresponse after a supply-base disruption.

Treville, S., Browning, T. R., & Oliva, R. (2023). Empirically grounding analytics (EGA) research in the Journal of Operations Management. Journal of Operations Management, 69(2), 337–348.

This is to correct the attribution of citations to references in Tables 2 and 3 that became misaligned during the copyediting process.

The sixth row of Table 2 should refer to de Treville, Petty, et al. (2014).

The seventh row of Table 2 should refer to de Treville, Schürhoff, et al. (2014).

The second row of Table 3 should refer to de Treville, Bicer, et al. (2014).

We apologize for this error.

As scholars in the field of operations management (OM), we would like to suggest that our field fell short in terms of due diligence when transitioning from statistical process control (SPC) to Six Sigma—accepting without scrutiny, building theory around, and teaching heuristics and algorithms without recognizing its underlying statistical inaccuracies. It is our view that these incorrect heuristics and algorithms have introduced bias and inefficiencies in process improvement throughout the OM field, contributing to a disconnect between OM and knowledge development in data science more generally. We call for a return to first principles and the establishment of formal conceptual definitions for the theory and methods underlying Six Sigma. We urge the OM academic community to embrace the lessons from SPC and Six Sigma so that we prioritize our due-diligence role, beginning with a requirement that all algorithms and tools be vetted before entering our curricula and case-study repertoires, especially as we move forward into an age of big data and potentially further opaque algorithms and tools. We propose that our top journals be open to research that scrutinizes methods developed in practice, so that OM will continue to be the focal field for quality assurance—even when the “product” of a process is data.

The application of statistical methods to quality management has been a central theme in OM since Shewhart's seminal work at Western Electric's Hawthorne Works nearly a century ago (Shewhart, 1925; Shewhart, 1926). He studied process variation to determine “how and under what conditions observations may contribute to a rational decision to change or not a process to accomplish improvements” (W. Edwards Deming, p.i, in the foreword of the 1986 edition of Shewhart, 1931). His work fostered methods and tools to monitor, diagnose, measure, reduce, and control variation in the output of a process to increase its consistency and capability.

The capability of a process with respect to a process parameter hence can be defined as the number of standard deviations (“sigmas”) of the parameter that fit between the mean for that parameter and its specification limits. If the process is not centered between the specification limits, then the process capability is set using whichever specification limit is closer to the process center. Six Sigma moves the concept of process capability from descriptive to prescriptive. At the time that Motorola's process-improvement ideas were proposed by Bill Smith in 1986 (Harry, 1994), process capability was defined in terms of specification limits set three standard deviations from the process mean (a “3σ process”). Following Shewhart's logic, a centered and normally distributed 3σ process is expected to produce 2700 parts-per-million (ppm) pieces that are more than three standard deviations from the process mean.

Motorola quantified the “z

Many antecedents identified as essential to supply chain resilience (SCR) are often studied independently, without considering their synergistic effects. Based on a case study and resource orchestration theory, this article focuses on configurations of different antecedents regarding supply chain integration and big data analytics capability to develop proactive and reactive SCR. Using survey data from 277 Chinese manufacturing firms, we consider three dimensions of supply chain integration, information integration, operational integration and relational integration, and three dimensions of big data analytics capability, technical skills, managerial skills and data driven-decision culture, and conduct fuzzy-set qualitative comparative analysis (fsQCA) to explore antecedent configurations generating high proactive and reactive SCR. We find that multiple antecedent configurations can achieve high SCR and configurations for high proactive and reactive SCR are not identical, which may involve alternative effects across different antecedents. We further implement propensity score matching analysis and reveal that firms following these configurations for high SCR also have better economic and operational performance. Moreover, we check the robustness of findings by using secondary data and attributes analysis with machine learning. This article complements and extends existing SCR literature from the configurational perspective and provides practical insights for managers to build SCR.

Our 6 years at the helm of JOM have been a real pleasure—and a lot of work. In this editorial, we reflect on some of the developments during our time in office, provide insights on some current policies, and review some items of interest to the JOM community.

As we began our terms in 2018, our foremost challenge was to increase the number of high-quality submissions to the Journal. Our strategy for this centered on emphasizing underutilized regions of JOM's scope and widening the solution space for contributions (in terms of types, topics, and methods), developing authors and reviewers, and injecting our enthusiasm for OM into the scholarly community. We signaled our interest in additional types of submissions by creating new departments (Empirical Research Methods, Innovation and Project Management, Public Policy and Industry Studies) and broadening others (Design Science became Intervention-based Research, and Marketing and Retail became Operations Interfaces). Our initial editorial (Browning & de Treville, 2018) welcomed new and underrepresented types of submissions such as literature reviews, conceptual papers, and those contributing empirically grounded research questions. JOM's 40th anniversary in 2020 provided an ideal opportunity to reflect on where our field came from and where it could broadly and boldly go (Browning, 2020). We aimed to provoke discussions in our field about the nature and role of topics such as Lean (Browning & de Treville, 2021; Cusumano et al., 2021; Hopp & Spearman, 2021) and Six Sigma (de Treville, Browning, Holweg, & Shah, 2023), where stubborn gaps persist between theory, teaching, and practice. These developments and debates are not standing still; they continue to provide opportunities for our community to engage and move forward. We wrote and accepted editorials and Forum articles on topics such as intervention-based research (Chandrasekaran et al., 2020; Oliva, 2019), warranted claims (Ketokivi & Mantere, 2021), replication studies (Pagell, 2021), and empirically grounding analytics research (de Treville, Browning, & Oliva, 2023). Intervention-based research and the empirical grounding of analytics represent relatively unexplored territory whose development will dramatically contribute to the production of knowledge that will be highly relevant to practice. Building our contributions around warrant rather than futile attempts to “prove” a knowledge claim leads to sounder knowledge creation, as does ensuring the replicability of results. In contrast to calls for more replication, Pagell (2021) focused on the replication process, such that replication is built into ongoing research. Finally, everything that we have done has emphasized the use of formal conceptual definitions (Wacker, 2004