Journal of Operations Management最新文献

Large government projects involving public–private collaborations inherently suffer from setbacks such as delays, cost overruns, or failure to meet contracted performance. Such setbacks may effectively be addressed through adjustments to contractual and relational governance; yet to date, the dynamics of governance adjustments and their interplay in addressing setbacks is not well understood. This research presents a dynamic theory of how parties can effectively address project setbacks through adjustments to contractual and relational governance. The dynamic theory was generated using longitudinal case data from two large public–private projects in the Netherlands that faced comparable project setbacks but deployed opposing governance adjustments, leading to drastically different project outcomes (i.e., collapse vs. recovery). This theory was then elaborated through two more cases and evidence from the literature. A system dynamics simulation model was then built that reproduces the different governance adjustments and outcomes observed in the four projects and serves to extend theory building. The refined theory not only shows under what conditions adjustments to contractual or relational governance are most effective, but also that governance adjustment interplay may trigger unintended side effects. As such, the theory explains why the careful balancing of governance adjustments is critical to project outcomes.

Despite the operational nature of enterprise system (ES) implementation and use, individual employees or work groups may deploy technology workarounds to circumvent inflexibility in or obstacles to using the ES. However, our understanding of the multilevel nature of technology workarounds and their performance implications remains limited. Drawing upon the multilevel theory of system usage and adaptive structuration theory, the current study examines the conditions under which group technology workarounds affect group performance, individual technology workarounds, and individual performance. Based on two studies with different research designs, we find that group technology workarounds have distinctive effects on short- and on long-term group performance. Specifically, while the impact of group technology workarounds on group performance is significantly positive in the short term, such effect diminishes over time. System failure and competition intensity strengthen the positive effect of group technology workarounds on short-term performance, whereas system failure and task nonroutineness lessen the negative effect of group technology workarounds on long-term performance. Our study further confirms the multilevel nature of technology workarounds, finding that group technology workarounds can influence individual technology workarounds and thereby individual performance. Our results support the view that technology workarounds as a group action should be considered alongside individual technology workarounds, as well as their positive and negative effects on both group and individual performance, in both the short- and long-term.

As suppliers' emissions contribute to a significant portion of the global environmental footprint, achieving supply chain wide carbon neutrality largely depends on suppliers' greenhouse gas (GHG) emissions reductions. Although suppliers' customers are increasingly signaling their commitment to tackling climate change through environmental disclosure, whether this signal contributes to supplier emissions reduction remains a question. Using signaling theory, this research proposes an emissions-reducing effect of customer base environmental disclosure on a supplier's GHG emissions level. Using a 2010–2017 panel dataset from multiple sources, we find empirical evidence supporting the upstream emissions-reducing effect of customer base environmental disclosure. Further, we identify two customer-base characteristics that affect this relationship: customer base climate innovation and competition. These findings contribute to the sustainable supply chain management literature by illustrating the effects of the customer base on supplier emissions performance. Specifically, customers could motivate a supplier's engagement in emissions reduction by collectively signaling their environmental commitment through enhanced disclosure. However, the effectiveness of this signaling effect can be contingent on the green innovation and competitive dynamics of the customer base.

We examine the role of platform sponsors and program managers in evolving a platform to stimulate inter-organizational collaboration in large research programs. Through a 5-year longitudinal case study, we analyzed a large inter-organizational collaborative research program in England, underpinned by the CLAHRC platform, sponsored by the NIHR. The research program attracted clinical academics in universities and clinical practitioners in a range of healthcare providers to collaborate in an ensemble of projects to drive evidence-based care for patients with long-term health conditions. Program managers struggled to facilitate collaboration through the platform, despite a highly decentralized governance approach. Our study identifies three mechanisms through which the platform sponsor and program managers revised the platform's governance strategies to enhance collaboration: (i) they instituted “interruptive events,” which routinely stopped projects, and analyzed if and why organizations struggle to collaborate; (ii) they expanded, rather than restricted, access rules for collaboration through “platform renting”; (iii) they re-distributed, rather than re-centralized, governance, to reduce unnecessary interdependences across collaborators attracted by the platform.

During software product development, the combination of digital resources (such as application programming interfaces and software development kits) establishes loose and tight edges between nodes, which form a software product network (SPN). These edges serve as observable conduits that may help practitioners and researchers better understand how vulnerabilities diffuse through SPNs. We apply network theory to analyze data from over 12 years of records extracted from the National Vulnerability Database. We contribute novel measures established using machine learning to gauge the properties influencing vulnerability diffusion within an SPN. We observed an SPN having a discernable shape that changed over time via network updates. We propose hypotheses and find empirical evidence that vulnerability diffusion is influenced by edge dynamics, developer responses, and their interaction. Implications for practice are that increased developer responses reduce software vulnerability diffusion attributed to edge dynamics.

Digital technology has enabled significant productivity gains in many industries. Manufacturers have benefited from robotics, and service businesses have benefited from self-service technologies. An area that has seen only meager productivity gains is professional services, such as healthcare, consulting, legal services, and higher education. Despite the emergence of artificial intelligence (AI) and other new technologies, professional services continue to be labor intensive with high labor costs. In 2021, Sampson published an empirically-based framework suggesting that emerging technologies would allow professional services to improve productivity by automating some tasks with self-service technologies, outsourcing some tasks to remote professionals, and delegating some tasks to semiprofessional workers. The underlying theory was that this restructuring hinges on the creative and interpersonal skill requirements of various tasks. Our research builds on Sampson's framework by modeling a professional service operation and studying the influence of task offloading on costs and quality. Our model involves discrete event simulation parameterized by empirical data. We consider labor costs, managerial costs, delay costs (including customer balking), and assessment costs. Results show contexts wherein increased task offloading can reduce costs with negligible impact on quality, suggesting great opportunities for reengineering professional services through increased automation, offshore outsourcing, and task delegation.

The cost of medical supplies represents a significant portion of hospital spending. Hospitals manage different types of medical supplies, such as general medical supplies and physician preference items. General medical supplies tend to be numerous and relatively low cost, while physician preference items tend to be less numerous and more expensive. Strong physician preference for certain medical supplies can limit the options available to reduce inventory costs. The use of consignment inventory is one way in which hospitals seek to reduce inventory costs for both general supplies as well as physician preference items. However, the use of consignment reduces the level of oversight that hospitals have on consigned inventories, thereby potentially increasing the likelihood of shrinkage. The impact of consignment on shrinkage cost has received limited attention. We investigate this issue by drawing upon the precepts of agency theory and by analyzing hospital data that span multiple years. Our results suggest that the use of consignment increases shrinkage and spend. We develop empirically informed analytical models to better understand the impact of an unforeseen increase in shrinkage on the cost associated with general and physician preference items. The analytical investigation suggests that the impact on general and physician preference items differ depending on the type of consignment contract negotiated between a hospital and a vendor. We discuss the theoretical and managerial implications of our findings.