Journal of Operations Management最新文献

Multiparty alliances (MPAs) are increasingly used to deliver large utilities infrastructure projects on-time, on-budget, and to specified quality. In theory, MPAs should help buyers to coordinate suppliers, enable concurrent scheduling, and create process innovations. On the other hand, these governance structures are inherently less stable than dyadic relationships due to their additional complexity and greater opportunities for free riding. We conduct a multi-source, longitudinal study, investigating how a buyer actively manages the dynamics between competition and cooperation during the formation of an MPA consisting of a lead organization and directional relationships between all partners. We contribute to MPA and coopetition literature by exploring cooperation and competition dynamics that are associated with the MPA structure that would largely be absent in dyads, and unpack the process by which a buyer orchestrates these dynamics by sequentially introducing new initiatives that seek to balance coopetition. MPAs have been recommended by governments and industry bodies as one solution for time and cost overruns in the utilities infrastructure sector, our study also provides guidance to buyers on the management of the alliance during the critical formation stage of the relationship lifecycle.

The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as observational data lacks the benefit of random treatment assignment, estimating causal effects poses challenges. In the specific scenario where one can reasonably assume that all confounding factors are observed—referred to as selection on observables—matching methods and synthetic controls can assist researchers to replicate a randomized experiment, the most desirable setting for drawing causal inferences. In this paper, we first present an overview of matching methods and their utilization in the OM literature. Subsequently, we establish the framework and provide pragmatic guidance for propensity score matching and coarsened exact matching, which have garnered considerable attention in recent OM studies. Following this, we conduct a comprehensive simulation study that compares diverse matching algorithms across various scenarios, providing practical insights derived from our findings. Finally, we discuss synthetic controls, a method that offers unique advantages over matching techniques in specific scenarios and is expected to become even more popular in the OM field in the near future. We hope that this paper will serve as a catalyst for promoting a more rigorous application of matching and synthetic control methodologies.

Embedded in networks of relationships, firms are who they buy from and sell to. As a result, a firm's corporate social responsibility (CSR) practices can be influenced by CSR practices of its customers and suppliers—known as CSR diffusion. This study examines how CSR diffuses in a supply chain that encompasses a focal firm, its suppliers, and customers. Adopting a relational view, this research hypothesizes that a firm's CSR is influenced by its customer-base CSR differently than its supply-base CSR. By analyzing panel data consisting of 1972 firm-year observations integrated from multiple data sources, the results offer evidence for a positive impact of customer-base CSR and a negative impact of supply-base CSR on firm CSR. Interestingly, when customers and suppliers of a focal firm establish direct business connections (i.e., customer–supplier closure), the positive follow-suit effect of customer-base CSR is enhanced. In contrast, the negative free-ride effect of supply-base CSR is diminished. This suggests that a focal firm is more likely to embrace CSR practices from CSR-active supply chain partners when embedded in closed triads. This research shows the need to consider the directionality and closure of relationships in understanding the diffusion of voluntary, ill-defined, costly operational practices within a supply chain.

Hospital administrators are shifting care delivery models toward an approach that uses more caregivers in the form of mid-level providers (MLPs), such as nurse practitioners, physician assistants, and clinical nurse specialists. To date, however, healthcare operations management (OM) literature remains ambiguous about longitudinal empirical associations between mid-level providers and hospital costs, quality, and other performance measures. We analyze how the extent of MLP employment used by a hospital is associated with hospital operational outcomes, as reflected by hospital cost per discharge and Triple Aim Performance (TAP) efficiency metrics. Our findings indicate percent MLP usage is positively associated with efficiency metrics for hospital clinical quality, technical efficiency, and patient experience, but not associated with hospital costs. We also find percent MLP usage is associated with the likelihood that hospitals excel on all TAP metrics simultaneously. Post-hoc exploratory analyses suggest the associations exhibit differential outcomes across hospital efficiency quantiles, while sub-sample analyses motivate boundary conditions for some hypothesized MLP associations. We contribute to healthcare OM research by providing one of the first panel data analyses of MLPs, improving insights relative to extant work. By giving key stakeholders useful findings about outcomes associated with hospital staffing trends, our managerial contribution helps hospital administrators understand empirical consequences of the increasing use of MLPs.

Geopolitical conflicts, particularly economic ones, introduce significant uncertainties into the global supply chain. The impact of these conflicts on cross-border buyer–supplier transactions remains underexplored, as does the capability of global suppliers to mitigate such risks by locking in their foreign buyers. Employing a combined perspective of resource dependence theory and transaction cost economics, we examine a natural experiment to investigate the effects of the 2018 U.S.–China trade war on the transactional relationships between Chinese suppliers and their U.S. buyers. Our study reveals that the trade war generally adversely affected these buyer–supplier transactional relationships, leading to a negative abnormal transaction value in the affected dyads, which amounted to 18.42% of their pre-event level. However, we find that this adverse impact can be attenuated when Chinese suppliers demonstrate superior innovation capabilities, higher corporate social responsibility performance, or fewer local political ties. These findings yield insights for international suppliers and buyers on strategies to maintain buyer–supplier transactions and minimize the detrimental effects on global supply chain relationships during geopolitical conflicts.

Project-based interorganizational networks are temporary and dynamic, and significantly different from stable networks for mass production. However, empirical studies on project-based interorganizational networks are scant. Drawing upon the network literature and distinguishing between production and distribution networks, we investigate how the centrality of a project in industry networks and tie strength of the project's member firms affect project performance in terms of product quality and sales. Using data of 821 Chinese movie projects during 2015–2018, we find empirical evidence that a project's centrality in the production network enhances product quality and that in the distribution network elevates product sales. Interestingly, weak ties in the production team contribute to product quality while strong ties in the distribution team improve product sales. This study advances the literature on project-based industries and interorganizational networks. It highlights the distinction between production and distribution networks in project-based industries and sheds light on the differential roles of a project's centrality and tie strength in both networks. These findings also offer novel insights to managers in project-based industries.

Across universities, agencies and corporate institutions, attention is often drawn to the value of interdisciplinary translational research. For good reason. Interdisciplinary approaches can provide the means by which to accomplish the most impactful and practical of academic, social and commercial advancements. They imply a capitalization on integrative problem-solving, benefiting from the insights of various perspectives and knowledge bases. While motivating and coordinating such collaborations can be challenging, at the core of the argument for interdisciplinary effort is the presumption that individual disciplines bring unique value to the table. Just as interdisciplinary research cannot exist without unique disciplinary contributions, individual disciplines have no hope of advancing their unique contributions without a clear understanding of their identity relative to other disciplines. In other words, they need to know and hold-to their own ‘true North.’

Although the Journal of Operations Management (JOM) is open to diversity in empirical approaches, methods, and epistemologies, the journal's Aims and Scope are clear in articulating that at the core of the work that JOM aims to publish is empirical research motivated by relevant operations management problems. Indeed, historically, the journal has published everything from ethnographic work to econometric studies of secondary data. It has showcased interview-based field work, case studies, field and lab experimental work, as well as intervention studies. Developmentally, the work has ranged from exploratory research reporting new regularities to formal testing of established hypotheses.

Good research design would have us assemble the data required to develop, test, and refine our hypotheses or to answer our research questions. Recent developments in information technology and governmental reporting requirements, however, have created a wealth of data, to the point that it is now sensible for researchers to consider how to leverage it. At the same time, this availability of easily accessible data, together with the desirability of interdisciplinary work, has yielded an increasing number of submissions out of the journal's scope. While we recognize the potential usefulness of these data to explore and expand the boundaries and interfaces of Operations Management with other disciplines, we believe it is important to remind ourselves of our own ‘true North.’

The identity of the Operations Management discipline can occasionally appear nebulous to those outside the field. Though supply chain disruptions have made numerous headlines in the recent years, the field hasn't benefited from the many decades of notoriety and personal exposure that other management fields have. Adults with experience filing taxes, maintaining bank accounts, applying for and paying off loans, and investing for retirement all have some sense, as skewed as it may be, of disciplines s

We investigate the impact of performance feedback delivered to front-line workers through new digital technologies in the manufacturing sector. Our study takes place in a globally operating manufacturing company that employs smartwatches for real-time control on the shop floor. In a large-scale and multi-site field experiment, we examine 29,669 machine status reports to assess the productivity effects of providing near real-time feedback to workers via smartwatches. We develop our hypotheses drawing on construal-level theory and its central idea of psychological distance. Initially, we observe production without feedback to establish comparability between treatment groups. Subsequently, we allocate various combinations of feedback to workers in four separate areas in two manufacturing plants. We manipulate whether the feedback is targeted at individuals with psychologically close feedback (“you did…”) or targeted at the team with relatively psychologically distant feedback (“your team did…”). Furthermore, we vary the message framing: positive framing emphasizes completed tasks, while negative framing emphasizes unfinished tasks. Our findings indicate that positively framed feedback, targeting individuals directly, enhances productivity more than other feedback combinations. Our study contributes new theoretical insights into the interplay between feedback framing and targets in fast-paced and highly automated batch production environments.

The use of part-time employees to support operations has been a contentious topic in the literature. While part-time employees add cost-effective flexibility to operations, their impact on operational outcomes has largely been documented as negative. However, there are a number of sectors (e.g., non-profit) which rely heavily on part-time employees, with anecdotal evidence supporting their role in improving outcomes. Through this research, we seek to shed light on these contradicting perspectives. We do so by investigating the impact of the percentage of part-time employees in the workforce dedicated to the Supplemental Nutrition Assistance Program (SNAP) outreach efforts at United States (U.S.) food banks on the effectiveness of this initiative. SNAP is the largest domestic hunger program in the U.S., assisting over 42 million individuals, and food banks play a critical role in outreach and enrollment for SNAP. We utilize data on the operational characteristics and SNAP activities of food banks that are members of the Feeding America network and U.S. Census data on the demographic characteristics of their service area. We find that an increased percentage of part-time FTEs (full-time equivalent) in a food bank's workforce dedicated to SNAP outreach efforts increases its effectiveness, particularly in relation to operational and contextual factors that can benefit from a more flexible workforce. Based on these findings and our review of the literature, we propose a conceptual framework on the effectiveness of part-time employees in different settings.

This study empirically examines how induced learning through adopting a set of best practices and learning-by-doing improved a hospital's care of ischemic stroke patients using ad hoc teams. While previous studies in healthcare operations management conducted in ad hoc team environments predominantly focused on volume-based learning (learning by doing, team familiarity via interactions among team members), our study focuses on induced learning in ad hoc teams through best practice adoptions. The analysis uses secondary data (Data period: January 2009–March 2017) about stroke patients from a comprehensive stroke center (CSC) in a U.S. tertiary teaching hospital as it adopted the U.S. American Heart Association/American Stroke Association (AHA/ASA) Target:Stroke best practices. The ad hoc stroke teams provide the initial care and their performance is measured using “Door-to-Needle (DTN)” time and its sub-time segments. The DTN time is measured as the time elapsed between the stroke patient's arrival at the hospital's emergency department (ED) and the appropriate infusion of “Tissue Plasminogen Activator (TPA)” (i.e., a thrombolytic medication informally referred to as a “clot buster”). We found that adopting these best practices improved ischemic stroke care beyond improvement due to repetition. We also found that the neurologist's recent experience providing stroke care for the prior patient is positively associated with meeting the time performance goal for the current patient. This study provides insights into the use of management mechanisms to adopt and sustain best practices in healthcare that are generalizable to other organizations with ad hoc team environments.