Journal of Operations Management最新文献

{"title":"Spillover Effects From Health Information Systems Integration: Evidence From Prescription Drug Monitoring Programs","authors":"Yufei Shen,&nbsp;Dorothy Lianlian Jiang,&nbsp;Dimitrios A. Andritsos,&nbsp;Xitong Li","doi":"10.1002/joom.1367","DOIUrl":"https://doi.org/10.1002/joom.1367","url":null,"abstract":"<div>\u0000 \u0000 <p>To ease prescribers' burden in using statewide Prescription Drug Monitoring Programs (PDMPs), many US states have moved to better integrate PDMP data with patients' electronic health records (EHRs). While such PDMP-EHR integration is likely to reduce local formal prescription opioid consumption, in this paper, we explore the possibility that it induces individuals to seek opioids across state borders and/or at the local black market. We find that for a focal county, its neighboring state's PDMP-EHR integration leads to an increase in the focal county's consumption of prescription opioids, an undesirable cross-border spillover effect. Moreover, we find that this spillover effect is mitigated when prescribers in the focal county have access to the neighboring state's PDMP data via interstate PDMP data sharing. We also find nuanced evidence that a state's PDMP-EHR integration might induce an increase in its black-market prices of prescription opioids. While vertical information integration in a region (i.e., a state's PDMP-EHR integration) may fulfill its intended benefit, our findings suggest it may also result in a spillover effect on neighboring areas. Notably, a complementary horizontal information integration (in this case, interstate PDMP data sharing) could mitigate such an undesirable spillover effect. We discuss implications for the design of care delivery processes, particularly prescription processes, that rely on the studied health information systems.</p>\u0000 </div>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 2","pages":"176-196"},"PeriodicalIF":10.4,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147565967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operational Process and Agency Considerations in Managing Emerging Technologies in Healthcare","authors":"Elliot Bendoly,&nbsp;Meng Li,&nbsp;Jeffrey Smith,&nbsp;Paul A. Pavlou","doi":"10.1002/joom.70029","DOIUrl":"https://doi.org/10.1002/joom.70029","url":null,"abstract":"&lt;p&gt;In recent years, emerging technologies have seen explosive, and arguably unprecedented, growth in most industries. The healthcare industry has been no exception (Dai and Tayur &lt;span&gt;2020&lt;/span&gt;). We are at a crucial point where close consideration of the operational and strategic implications of emergent technologies in the healthcare industry is both observable and fully warranted. Emerging technologies, such as the internet of things (IoT), genetic technologies, 3D printing, advanced social platforms, as well as advanced analytics (e.g., artificial intelligence [AI] and other big data-driven analytics systems) are driving rapid growth and transformation in this industry (Gardner et al. &lt;span&gt;2015&lt;/span&gt;; Ganju et al. &lt;span&gt;2020&lt;/span&gt;; Xu et al. &lt;span&gt;2021&lt;/span&gt;; Adjerid et al. &lt;span&gt;2022&lt;/span&gt;; Rajpurkar et al. &lt;span&gt;2022&lt;/span&gt;). What is now needed are theoretical and practical insights to help identify new opportunities, operational challenges (and their solutions), arising from the advancement and adoption of these powerful emerging technologies in healthcare.&lt;/p&gt;&lt;p&gt;Consider some of the current opportunities in healthcare: Emerging technologies are empowering physicians and improving patient care in multiple ways (Ferrand et al. &lt;span&gt;2018&lt;/span&gt;; Mukherjee and Sinha &lt;span&gt;2020&lt;/span&gt;). Developments in AI capabilities have been perhaps most notable in public discourse. AI has been deployed to augment diagnostic, clinical, and even surgical functions, therapy selection, risk prediction, and disease stratification. Resulting benefits include reductions in medical errors and increases in case throughput (Kalis et al. &lt;span&gt;2018&lt;/span&gt;). 3D printing technology has now advanced to the point at which it can be used to produce a wide range of customized medical devices, prosthetics, and implants. It can also fill emergent needs in place of dedicated production capacity for healthcare products (Bendoly, Chandrasekaran, et al. &lt;span&gt;2024&lt;/span&gt;). Robotic surgery has also been leveraged to greatly increase the precision of complex surgical activities.&lt;/p&gt;&lt;p&gt;Emerging technologies are also changing the social reach and special opportunities for healthcare delivery (Bavafa et al. &lt;span&gt;2018&lt;/span&gt;). The interest in facilitating physically separate service engagement between patients and physicians, prompted in part by the COVID-19 pandemic, has prompted large-scale adoptions of telehealth technologies, often termed telemedicine, through which patients can access medical care remotely. Online consultations and live medical streaming are becoming normal experiences for many, permitting patients to obtain physical and mental health support virtually. Advanced wearables bring forth additional implications for such engagement. Ambulatory facilities, often located close to where patients live in suburban or rural areas, are becoming more valuable for patients when integrated with the aid of Electronic Health Record (EHR) systems. Robotic surgical options","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 2","pages":"164-175"},"PeriodicalIF":10.4,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing Generative AI for Value Co-Creation: An Intervention-Based Randomized Field Experiment in a Healthcare Context","authors":"Yanwu Song,&nbsp;Tingting Yan,&nbsp;Fu Jia,&nbsp;Lujie Chen,&nbsp;Hao Li","doi":"10.1002/joom.70012","DOIUrl":"https://doi.org/10.1002/joom.70012","url":null,"abstract":"<div>\u0000 \u0000 <p>Owing to limited healthcare resources, there has been increased demand for artificial intelligence (AI) interventions to treat mental health problems of chronic disease patients in developing countries. However, it is challenging to overcome the AI trust crisis in the healthcare context and develop AI that improves the patient's personalized experience and the quality of care. Elaborating on the value co-creation theory using an actor–network theory (ANT) approach, this study examines how generative artificial intelligence (GenAI) can improve post-discharge care for patients with cardiovascular disease in resource-limited settings. Using an intervention-based research approach in collaboration with a major hospital in China, researchers co-designed a GenAI intervention with potential users and various stakeholders. Through a randomized controlled trial, we further evaluated the impact of a co-created GenAI intervention on the post-discharge self-confidence and quality of care of 114 patients. Compared with the standard post-discharge care process, chronically ill patients who received the GenAI intervention experienced a 6.049-point (out of a total of 80 points) decrease in state anxiety and an 87.8% decrease in the 30-day readmission risk. The insights gained from the intervention process, as interpreted using the ANT approach, expand the generic framework of value co-creation to include a more GenAI-mediated network of human and non-human objects. Results reveal GenAI's boundary-spanning and integrating roles as a critical node in the emerging, dynamic, value-creating actor network. The inclusion of “a nonparticipant observe” allows us to offer cognitive explanations for why GenAI works. Overall, this study contributes to healthcare operations management by designing a process for developing and implementing GenAI to improve healthcare operations.</p>\u0000 </div>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 2","pages":"197-232"},"PeriodicalIF":10.4,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147562751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking Privacy in Healthcare: The Impact of Explanations on Privacy Concerns and Self-Disclosure to Conversational Technologies","authors":"Hashai Papneja,&nbsp;Sarv Devaraj","doi":"10.1002/joom.70026","DOIUrl":"https://doi.org/10.1002/joom.70026","url":null,"abstract":"<p>While artificial intelligence (AI)-based conversational technologies offer exciting prospects in healthcare, the lack of transparency and elevated privacy concerns in using such technologies remain a challenge and make much-needed information difficult to obtain while administering patient care. Approaches that emphasize transparency and interpretability of AI systems provide a promising avenue to address these concerns. In this study, we explore the role of transparency-enhancing explanations as a way for caregivers to elicit truthful disclosure of otherwise private information from patients. Specifically, we explore how automated explanations provisioned by conversational technologies can help reduce the user's privacy concerns and bring about self-disclosure, thus helping to improve key outcomes such as accurate diagnosis and effective treatment. Through an online experiment with 556 participants in a healthcare context, we uncover the mediating effects of two critical factors, informational justice and perceived relevance, on privacy concerns. We find that explanations foster perceptions of informational justice and perceived relevance in the user, which help reduce privacy concerns and bring about self-disclosure. The study's findings have implications for researchers as well as practitioners who leverage conversational technologies in healthcare and other service contexts.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 2","pages":"316-351"},"PeriodicalIF":10.4,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond Discrete-Time Hazard Regression: Bayesian Regularization for Dynamic Churn Modeling","authors":"Ping Chou,&nbsp;Yen-Chun Chou,&nbsp;Howard Hao-Chun Chuang","doi":"10.1002/joom.70027","DOIUrl":"https://doi.org/10.1002/joom.70027","url":null,"abstract":"<div>\u0000 \u0000 <p>Discrete-time hazard regression is widely applied to firm-level time-to-event analyses and increasingly to individual churn behaviors. While the discrete logit hazard model for panel data remains the workhorse in OM, both fixed-effects and random-effects specifications have key limitations. The Grassia(II)-Geometric (G2G) model—allowing for dynamic churn and asymmetric heterogeneity—offers a compelling alternative for hazard regression and churn prediction. To address high-dimensional data, we propose Bayesian sparsity modeling via spike-and-slab LASSO (SSL) that enables simultaneous regularization and inference—both crucial for explanatory hypothesis testing. Simulation studies show that even when data are generated from logit functions with additive heterogeneity, asymmetric heterogeneity undermines logit regression, whereas G2G-SSL achieves stronger out-of-sample fit with lower false discovery rates. We further validate its predictive power in an empirical study on voluntary employee turnover at a Fortune 500 manufacturer. The proposed approach outperforms a range of advanced methods, improving both churn time prediction and cost efficiency for prescriptive workforce planning. Finally, we outline methodological extensions and provide a modeling procedure for discrete hazard regression analysis. By importing insights from marketing and Bayesian statistics, our work enables OM scholars to move beyond traditional hazard models and better capture real-world heterogeneity across a broad range of contractual churn scenarios.</p>\u0000 </div>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 1","pages":"131-158"},"PeriodicalIF":10.4,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One Step Forward, Two Steps Back: Managing Uncertainties in Outcomes, Deliverables, and Means in Behavioral Intervention Development Projects","authors":"Philip Cash,&nbsp;Melanie E. Kreye,&nbsp;Tyson R. Browning","doi":"10.1002/joom.70024","DOIUrl":"https://doi.org/10.1002/joom.70024","url":null,"abstract":"<p>We take an extended perspective on project success that includes <i>post-project</i> outcomes as well as <i>at-end</i> and <i>during-project</i> success. To manage projects accordingly, we conceptualize three corresponding orders of uncertainty (<i>outcomes</i>, <i>deliverables</i>, and <i>means uncertainties</i>). We study 11 cases of behavioral intervention development (BID) projects to explore how managers handle each of the three orders of uncertainty to achieve post-project success—fully, partially, or not at all. Our analysis suggests several key insights. The hierarchical nature of multi-order uncertainty management implies that decreasing a higher-order uncertainty (e.g., outcomes) increases the next-lower order (e.g., deliverables). In the studied cases, reducing <i>outcomes uncertainty</i> tended to increase <i>deliverables</i> and <i>means uncertainties</i>—causing one step forward to seem like two steps backward. Thus, the sequence of uncertainty-management activities matters, with post-project success linked to reducing <i>outcomes uncertainty</i> before <i>deliverables</i> and <i>means uncertainties</i>. Violations of this sequencing were associated with <i>uncertainty masking</i>, a failure to acknowledge uncertainty that misdirected uncertainty-management activities. Moreover, the uncertainty-management activities must be timely, lest they become misaligned with other project activities. These findings elaborate the theorized relationships between uncertainty management and project success. We further outline how project managers can manage uncertainty by <i>reframing</i> outcomes, <i>rescoping</i> deliverables, and <i>replanning</i> means.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 1","pages":"81-107"},"PeriodicalIF":10.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Model of Hospital Patient Engagement for Value Co-Creation: Does It Affect Performance? A U.S. Hospital Industry Study","authors":"Shawnee K. Vickery,&nbsp;Matthew J. Castel,&nbsp;Sriram Narayanan,&nbsp;Mariana L. Nicolae","doi":"10.1002/joom.70019","DOIUrl":"https://doi.org/10.1002/joom.70019","url":null,"abstract":"<p>A holistic model encompassing a hospital patient engagement system and its relationship to the quality of provider-patient interactions is presented. Based on service-dominant logic, the study examined whether the effects on hospital performance of providers' systemic patient engagement efforts to enable value co-creation are fully mediated by experiential quality (realized patient engagement). The research model was tested via 2SLS regressions using survey data matched with secondary data. Mediation hypotheses were tested using bootstrapping. The results showed that experiential quality fully mediates the beneficial effects of a hospital patient engagement system on patient recommendation, readmission rate, return on assets, and excess margin. Post hoc tests confirmed the broad applicability of a hospital patient engagement system for reputational and financial advantage.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"71 8","pages":"1222-1248"},"PeriodicalIF":10.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145646526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Dual Brokerage Role of Digital Platforms in the Transition to a Circular Economy","authors":"Quynh Do,&nbsp;Mark Stevenson","doi":"10.1002/joom.70025","DOIUrl":"https://doi.org/10.1002/joom.70025","url":null,"abstract":"<p>The transition to a circular economy hinges on effective brokerage—the work of intermediaries in connecting innovative closed-loop recyclers (the niche) with the established waste network (the regime). While brokerage theory and its classical <i>tertius iungens/gaudens</i> typology explain how a broker's strategic intent shapes their behaviors, it offers limited insight into how brokers operate at the niche-regime interface, a context defined by inherent tensions. This inductive study of a digital platform intermediary in the post-industrial textile waste contexts of Bangladesh and India addresses this by theorizing brokerage as a set of tension-derived strategies. Our empirical findings identify three tensions: network structure, operational capability, and socially sustainable capability tensions. We then show how the platform addresses these tensions through a dual role: <i>structural brokerage</i>, via semi-disintermediation, and <i>capability brokerage</i>, via standardization and legitimization. In addition, the platform engages in identity work to overcome its own challenge of being a new network actor. We contribute a novel <i>contingent perspective</i> on brokerage by unpacking a broker's response to inherent tensions in a transition period. The research also shows how technology-based intermediaries can be deployed to manage reverse flows, and it furthers understanding of how informal actors can be integrated into formal supply chains.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 1","pages":"108-130"},"PeriodicalIF":10.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of a Buyer's Incentives and Organizational Structure on Suppliers' Quality","authors":"Anupam Agrawal,&nbsp;Ujjal Kumar Mukherjee","doi":"10.1002/joom.70020","DOIUrl":"https://doi.org/10.1002/joom.70020","url":null,"abstract":"<p>Changes in a buyer organization's incentives and structure can have a significant impact on supply chain performance, such as the quality of sourced components. We examine this relationship using data from a unique quasi-experiment where one of the two plants of a buyer introduced long-term quality improvement incentives and a more organic structure for supply chain engineers, while the other plant did not. Analyzing longitudinal component quality data from suppliers to both plants using difference-in-differences and triple-differences methods, we find that (i) the changes in incentives and structure led to differential improvements in supplier quality across the two plants, and (ii) suppliers did not easily transfer quality knowledge gained from one buyer relationship to others. Our paper contributes by showing that organizational redesign by a buyer focused on implicit incentives along with a supportive organic organizational structure can create a learning environment at its suppliers that can help improve the quality of sourced components and the learning generated does not necessarily spill over to other buyers.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"71 8","pages":"1185-1221"},"PeriodicalIF":10.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.70020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145646628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Help or Hindrance? The Role of Familiarity in Product Development Teams","authors":"Karthik Ramachandran,&nbsp;Necati Tereyağoğlu,&nbsp;Murat Unal","doi":"10.1002/joom.70022","DOIUrl":"https://doi.org/10.1002/joom.70022","url":null,"abstract":"<p>For products developed through a collaboration of specialized groups, success requires craft and engineering ingenuity from designers who focus on specific attributes, coupled with synchronized coordination between various design groups. Although shared work experience in the team—or familiarity—can improve coordination, it can deter creativity. We empirically study the impact of team familiarity on market performance of products by focusing on product development in the video game industry by coupling a granular database of development credits with sales data for video games. Although familiarity among coordinators has a positive effect on performance, familiarity among designers has a negative effect. Further, the positive (negative) effect of familiarity among coordinators (designers) is present even if familiarity is built through roles other than coordination (design). Overall, team familiarity is associated with a decrease in the product's market performance. Our results suggest that infusing fluidity in design roles and maintaining stability in coordination roles could improve the performance of new products.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"72 1","pages":"4-20"},"PeriodicalIF":10.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.70022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}