DECISION SCIENCES最新文献

{"title":"Protecting data intangibly: How does control culture influence data breach risks?","authors":"Lirong Lu,&nbsp;Shan Liu,&nbsp;Hao Wang","doi":"10.1111/deci.70016","DOIUrl":"https://doi.org/10.1111/deci.70016","url":null,"abstract":"<p>As data have become the most valuable asset for many firms, the increasing frequency, scope, and cost of data breaches have had a significant impact on organizations. Traditionally, managers have focused primarily on tangible control measures to ensure information security and minimize data breach risks. However, a deeper understanding of intangible control measures remains limited. This study explores the impact of control culture—an intangible control measure—on different types of data breach risks within a firm: accidental internal, malicious external, and malicious internal breaches. Drawing on human factor theory and routine activity theory, we develop several hypotheses regarding the effect of control culture on these varying types of data breach risks. We collect data from multiple sources and construct a panel data set to empirically test these hypotheses. Our findings reveal that a stronger control culture significantly reduces the risk of accidental internal and malicious external data breaches. However, it does not reduce the risk of internal breaches with malicious intent. This research breaks new ground in addressing data breach risks from the perspective of control culture, providing valuable insights for both academics and practitioners.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"57 1","pages":"47-65"},"PeriodicalIF":2.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147566376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Talking terms: Agent information in LLM supply chain bargaining","authors":"Samuel N. Kirshner,&nbsp;Yiwen Pan,&nbsp;Jason Xianghua Wu,&nbsp;Alex Gould","doi":"10.1111/deci.70010","DOIUrl":"https://doi.org/10.1111/deci.70010","url":null,"abstract":"<p>We investigate the use of large language models as agents (LLM agents) in autonomous supply chain contract negotiations. Our objectives are to assess whether LLM agents exhibit human-like bargaining behaviors and to explore the impact of information on performance. To address these objectives, we conducted several experimental studies using LLM agents as participants and compared the results with human results from a benchmark study. Our experiments covered scenarios where supplier cost information was public, private, ambiguous, or deceptive. Overall, we found that LLM agents use simple heuristics to make decisions and generally exhibit human-like negotiating behavior. Contrasting humans, LLM agents are more inclined toward reaching agreement, leading to greater supply chain efficiency but potentially greater inequality compared to human negotiators. Deceiving LLM agents into believing they have higher costs can improve outcomes for the supplier at the expense of retailers and the supply chain's efficiency. We also show that tailored retrieval-augmented generation (RAG) configurations can enhance negotiation outcomes. Taken together, our results (1) provide timely insights into the integration of AI into supply chains, (2) raise ethical questions around the trade-off between inequality and efficiency and the use of deception with LLM agents, (3) highlight the effectiveness of tailoring RAG configurations to optimize specific objectives such as efficiency or stakeholder profitability, and (4) provide many avenues for future research into examining LLM agents as supply chain negotiators.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"57 1","pages":"9-23"},"PeriodicalIF":2.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147566006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning approach to synthetic data generation: Uncertainty generative model with neural attention","authors":"Martin Kang,&nbsp;Gary F. Templeton,&nbsp;Seong-Jong Joo,&nbsp;Han Kyul Kim","doi":"10.1111/deci.70021","DOIUrl":"https://doi.org/10.1111/deci.70021","url":null,"abstract":"<p>Data scarcity undermines the precision of empirical and analytical research by limiting sample sizes and reducing statistical power. In domains such as business operations, financial management, and information systems, failure data often arise from rare events, introducing substantial aleatoric and epistemic uncertainty. Existing synthetic data generation methods, including interpolation-based oversampling and generative models, face persistent challenges. They often fail to capture rare events, preserve temporal dependencies, or model multiple sources of uncertainty, leading to unrealistic samples and degraded performance in downstream tasks. This study introduces the uncertainty generative model with neural attention (UGMNA), a synthetic data generation approach that integrates attentive neural processes, the Heston stochastic volatility model, and stochastic differential equations within a continuous-time latent framework. UGMNA addresses data scarcity by generating synthetic samples that emulate the distributional characteristics of original datasets while explicitly modeling both aleatoric and epistemic uncertainty. Its design enhances statistical power by augmenting limited datasets and ensures that synthetic data reflect key patterns, temporal dynamics, and complex distributions encountered in real-world scenarios. Experimental results across multiple case studies demonstrate that UGMNA reduces both types of uncertainty while preserving essential data patterns. Compared with conventional baselines and state-of-the-art generators, UGMNA consistently improves predictive accuracy, ranking performance, and model calibration in data-scarce, high-variance environments. These findings establish UGMNA as a robust framework for generating reliable synthetic data, offering practical utility for research and decision-making in contexts where data scarcity and uncertainty hinder model development.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"57 1","pages":"66-85"},"PeriodicalIF":2.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seeing the bigger picture: Pathways to carbon neutrality in the hard-to-abate sector–insights from a field study","authors":"Alok Raj,&nbsp;Sriram Narayanan,&nbsp;Samit Paul,&nbsp;Saroj Kumar Singh,&nbsp;Subodha Kumar","doi":"10.1111/deci.70017","DOIUrl":"https://doi.org/10.1111/deci.70017","url":null,"abstract":"<p>Reducing carbon emissions in the hard-to-abate sector is crucial yet challenging for achieving carbon neutrality. This study explores pathways to carbon neutrality in steel industry using Carbon Capture and Utilization (CCU) technology. Employing a design science research approach anchored in the Natural Resource-Based View (NRBV), this study examines the intervention, mechanisms, and outcomes of CCU technology implementation within a leading steel manufacturing facility. The intervention led to an average CO₂ reduction of around 9% and economic benefits of around $89,825 per month from the pilot project. This study extends to the cement, oil and gas, and fertilizer industries, enhancing the generalizability of its findings. It demonstrates that more than a technological shift, CCU technology adoption represents a comprehensive transformation, encompassing process, product, and administrative innovations. The research also highlights key challenges and trade-offs, including safety concerns, spatial constraints, and integrating new processes into existing frameworks. Emphasizing the need to build internal and external capabilities, it underscores process modifications, innovative ways of CO₂ utilization, and broad stakeholder collaboration as critical factors. Ultimately, this study advances the understanding of viable pathways for CO₂ emission reduction through CCU technology.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"57 1","pages":"24-46"},"PeriodicalIF":2.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147570018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A coordination mechanism between the emergency department and inpatient unit to mitigate hospital crowding","authors":"Jie Wang,&nbsp;Mengchuan Zou,&nbsp;Yong-Hong Kuo,&nbsp;Zuo-Jun Max Shen,&nbsp;Colin A. Graham","doi":"10.1111/deci.70014","DOIUrl":"https://doi.org/10.1111/deci.70014","url":null,"abstract":"<p>Emergency department (ED) crowding is a typical problem in hospitals across many countries, leading to numerous grievous consequences. One of the major causes of ED crowding is <i>ED boarding</i>, which refers to cases in which patients are delayed being admitted to inpatient wards (IW) due to bed shortages. Our research is motivated by the recent developments in hospital information systems and the introduction of a new operational unit to hospital management, known as the <i>capacity command center</i> or <i>coordination center</i>. This unit is tasked with monitoring real-time performance metrics across different hospital units and recommending operational actions. Enabled by this advancement in hospital information systems, our research considers a patient streaming strategy and proposes a coordination mechanism between ED and IW. With our proposed <i>system visibility</i>, both the system status and information about the operations are shared between the two units. To capture the dynamic updates of individual patient statuses, mixed-integer linear programming models are developed. Our proposed methodology is shown to be effective in improving computational efficiency. Coordination effects are evaluated with numerical experiments. Our results suggest that the coordination mechanism can improve the efficiency of both units significantly in terms of patient waiting time, boarding time, and length of stay. Lastly, we extend it to more complex scenarios and find that the coordination mechanism continues to perform well when treatment time is uncertain and dependent on patient's type and physician's workload, and streaming accuracy varies. The impacts of various factors are also investigated to derive managerial insights.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 5","pages":"489-508"},"PeriodicalIF":2.5,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining the use of analytics in healthcare operations management: A systematic and narrative literature review","authors":"Bogdan Bichescu,&nbsp;Randy V. Bradley,&nbsp;David D. Dobrzykowski,&nbsp;Iana Shaheen,&nbsp;Antoinette Smith","doi":"10.1111/deci.70011","DOIUrl":"https://doi.org/10.1111/deci.70011","url":null,"abstract":"<p>Healthcare delivery is data intensive and data dependent, but hospitals have struggled to leverage data to improve operational performance. At the same time, healthcare researchers have been advancing the use of analytics in our publications. Unfortunately, there appears to be a substantial gap between the insights that we as researchers have produced and the actual adoption of analytics among healthcare organizations. We attempt to provide a starting point to close that gap by conducting a systematic review of 414 studies published in five top operations management (OM) journals between 2010 and 2024. We provide a systematic and narrative review of the literature applying analytics approaches in healthcare OM (HOM) studies. Our stream-, journal-, and author-level analyses underpin several important contributions. We begin by identifying key publication and methodological trends by journal. Next, we identify and describe six key topics using Latent Dirichlet Allocation (LDA) topic modeling and syntheses by the authors. We juxtapose the LDA topics by journal to identify nuanced journal preferences within the broader literature. Finally, we identify the most active researchers in HOM in general, by topic and journal, and discuss future research directions. Collectively, these contributions ought to support practitioners in accessing our research and scholars in their efforts to develop relevant research questions, design and position their studies, and ultimately more clearly articulate compelling contributions to the HOM literature using analytics approaches.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 5","pages":"449-470"},"PeriodicalIF":2.5,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical countermeasures during public health emergencies—Does information sharing among health system coalition help?","authors":"Sukrit Pal,&nbsp;Anand Nair","doi":"10.1111/deci.70007","DOIUrl":"https://doi.org/10.1111/deci.70007","url":null,"abstract":"<p>Challenged by constrained healthcare resources, hospitals encounter barriers to accommodating patient demand during public health emergencies. Building on a comprehensive literature review of information and knowledge exchange in healthcare, disaster management, and humanitarian operations management, this study explores the influence of treatment-based medical countermeasures (T-MCM) on ICU bed utilization during the Covid-19 pandemic, investigating whether participation in a regional health registry (HReg) facilitates better management of care capacities. We use a difference-in-differences approach with propensity score weighting to analyze a panel dataset of 735 observations from Michigan hospitals, finding that health systems that used T-MCMs experienced modest reductions of 1.8% of ICU bed utilization. However, the reduction increased by an additional 27.1% among hospitals that participated in the HReg. Hospitals that used T-MCMs without HReg participation experienced a 10.8% increase in ICU bed utilization, suggesting resource overload. These results underscore the importance of adaptive learning and strategic investment in information-sharing infrastructures to optimize healthcare delivery during crises. We discuss theoretical, managerial, and policy implications when managing healthcare capacity during pandemics.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 6","pages":"622-637"},"PeriodicalIF":2.5,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145824547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Late payments, higher prices? An experimental investigation of competitive procurement","authors":"Matthew J. Walker,&nbsp;Kyle Hyndman","doi":"10.1111/deci.70006","DOIUrl":"https://doi.org/10.1111/deci.70006","url":null,"abstract":"<p>The decision to pay one's supplier late is commonplace across global supply chains and, arguably, a key challenge for many businesses. In a multiple-methods study, we contribute to the literature by documenting important empirical and anecdotal features about the likelihood and severity of late payments, formulating and solving a theoretical model grounded in these features, which suggests a policy tool to reduce late payments and then validating the model through a rigorous laboratory experiment. Grounded in our direct interactions with buyer-side and supplier-side organizations and our analysis of regulatory payment reports, we construct a game-theoretic model to analyze the qualitative effect through which uncertainty about the date payment will be received influences suppliers’ pricing decisions. We then examine whether an economic incentive (penalty for late payment) deters buyers from reneging upon an announced payment term. The effectiveness of introducing a penalty for late payment is not obvious because some buyers may choose to circumvent the penalty by announcing a longer payment term up front, and the penalty may influence suppliers’ bidding strategies. We find analytically and validate experimentally that setting the highest penalty for late payment is an effective deterrent mechanism and leads to the highest expected buyer profit through its effect on supplier competition. Thus, establishing a credible commitment to pay one's suppliers within a shorter payment term is a cost-effective managerial strategy for buyers. However, a welfare loss arises if the penalty is not set high enough because it fails to align incentives for a subset of buyers.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 6","pages":"598-621"},"PeriodicalIF":2.5,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145843021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Browse more, return less: Managing online returns through interactions with browsings and purchases","authors":"Quan Zhang,&nbsp;Zhuping Liu,&nbsp;Subodha Kumar,&nbsp;Shuai Yang","doi":"10.1111/deci.70005","DOIUrl":"https://doi.org/10.1111/deci.70005","url":null,"abstract":"<p>The surge in online returns has become a significant concern for online retailers, leading to substantial financial losses. Despite its pivotal role in online shopping, limited research has examined returns as an integral component of the consumer shopping process. We fill the gap by investigating the interactions among consumers' browsings, purchases, and returns on a large online shopping platform. Utilizing a rich data set capturing consumers' activity streams, we introduce an <i>augmented shopping process</i> that incorporates returns into the consumer “purchase funnel” and reveal insightful findings. First, consumers who browse higher priced items or engage in extensive research are less inclined to make returns. Second, purchases of more expensive products or a higher quantity are more prone to returns, whereas purchases with higher discounts are less likely returned. Third, returning a purchase with a higher total amount is likely followed by another purchase, but a return of highly discounted items is not. Motivated by these findings, we illustrate two strategies retailers can use to mitigate online returns and enhance operational performance. Our study facilitates a better understanding of returns in online shopping and offers actionable implications for retailers seeking to effectively manage returns.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 6","pages":"578-597"},"PeriodicalIF":2.5,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing product information access in physical retail operations: How do Scan & Go technologies affect consumers' in-store purchases?","authors":"Tingting Song,&nbsp;Zenan Zhou,&nbsp;Xianghua Lu,&nbsp;Tian Lu","doi":"10.1111/deci.70001","DOIUrl":"https://doi.org/10.1111/deci.70001","url":null,"abstract":"<p>With the remarkable transformation of the retail industry driven by online channels, physical retailers have increasingly employed in-store mobile technologies that integrate online features to remain competitive in their daily operations. In this study, we focus on the emerging <i>Scan &amp; Go</i> (<i>S&amp;G</i>) mobile technologies, which offer consumers in-store access to online product reviews and tutorials for scanned products. While these technologies seemingly provide the benefits of integrating online and offline information, their real-world effects on in-store purchases remain uncertain due to the <i>information attention reallocation effect</i>. Specifically, consumers may allocate more attention to the products they scan via <i>S&amp;G</i>, potentially increasing their purchases of these items, while reducing attention to surrounding products, possibly leading to fewer purchases of those items. Our empirical study leverages a unique data set to assess the comprehensive effects of consumers' <i>S&amp;G</i> adoption on their in-store purchasing behaviors, focusing on both transaction features and purchased product features. The findings reveal that consumers who adopt <i>S&amp;G</i> technologies tend to place more orders, spend more overall, and exhibit greater expenditures per order. In addition, they also show a preference for high-value items and diversify their purchases across product categories, while simultaneously purchasing fewer hedonic products. Further analysis investigates various <i>S&amp;G</i> app usage behaviors to validate the <i>information attention reallocation effect</i>, providing deeper insights into how this technology influences consumers' shopping patterns. At the forefront of empirical research on emerging <i>S&amp;G</i> technologies, this study provides valuable theoretical and practical implications for both researchers and practitioners in the field of retail operations. It emphasizes the need for strategic adaptation to innovative in-store technologies and underscores the importance of operational adjustments within the physical retail environment to remain competitive in the evolving retail landscape.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 6","pages":"553-577"},"PeriodicalIF":2.5,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145848102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}