Pub Date : 2025-10-24DOI: 10.1109/TEM.2025.3625427
Jialan Shan;Zhaohua Deng;Zihao Deng;Dan Song
The rapid diffusion of artificial intelligence (AI) is accelerating the adoption of mental health chatbots (MHCs) as scalable tools for psychological support. Grounded in media naturalness theory (MNT) and computers are social actors paradigm, this study empirically investigates how MHCs’ humanlike competencies—cognitive, relational, and emotional—influence users’ self-esteem (termed AI-enabled self-esteem), through the mediating mechanism of emotional resonance. We conducted an online survey in Credamo and obtained 451 valid responses from experienced MHC users. Using a hybrid approach that combines structural equation modeling (SEM) and necessary condition analysis, we found that all three humanlike competencies positively predict emotional resonance and are identified as its necessary conditions. Emotional resonance, in turn, is positively associated with AI-enabled self-esteem. Notably, relational competency demonstrates the strongest effect on emotional resonance, challenging the common emphasis on emotional competency in human–chatbot interaction (HCI) design. Furthermore, the ordinary least squares regression corroborates the SEM results, and mediation analyses indicate a partial mediating role of emotional resonance, validating the robustness of our results. This study advocates for the design and adoption of MHCs with humanlike competencies. It also contributes to theoretical discourse on HCI literature and offers actionable guidance for MHC design and development.
{"title":"Emotional Resonance and Self-Esteem: The Role of Humanlike Competencies From Mental Health Chatbots","authors":"Jialan Shan;Zhaohua Deng;Zihao Deng;Dan Song","doi":"10.1109/TEM.2025.3625427","DOIUrl":"https://doi.org/10.1109/TEM.2025.3625427","url":null,"abstract":"The rapid diffusion of artificial intelligence (AI) is accelerating the adoption of mental health chatbots (MHCs) as scalable tools for psychological support. Grounded in media naturalness theory (MNT) and computers are social actors paradigm, this study empirically investigates how MHCs’ humanlike competencies—cognitive, relational, and emotional—influence users’ self-esteem (termed AI-enabled self-esteem), through the mediating mechanism of emotional resonance. We conducted an online survey in Credamo and obtained 451 valid responses from experienced MHC users. Using a hybrid approach that combines structural equation modeling (SEM) and necessary condition analysis, we found that all three humanlike competencies positively predict emotional resonance and are identified as its necessary conditions. Emotional resonance, in turn, is positively associated with AI-enabled self-esteem. Notably, relational competency demonstrates the strongest effect on emotional resonance, challenging the common emphasis on emotional competency in human–chatbot interaction (HCI) design. Furthermore, the ordinary least squares regression corroborates the SEM results, and mediation analyses indicate a partial mediating role of emotional resonance, validating the robustness of our results. This study advocates for the design and adoption of MHCs with humanlike competencies. It also contributes to theoretical discourse on HCI literature and offers actionable guidance for MHC design and development.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4281-4293"},"PeriodicalIF":5.2,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1109/TEM.2025.3618762
Han Guo;Lei Song;Feng Yang;Xiaolong Guo
Purchasing and supply chain management (PSCM) is a subfield of supply chain management and focuses on the purchasing process. Relevant studies emphasize the importance of logistics, commodity flow, and information flow in the above process and make in-depth research. However, there are few studies on PSCM capital flow management, especially in terms of systematic review of the literature. This article adopts a systematic literature review (SLR) approach that focuses on the role of a common complementary capital flow instrument, supply chain finance (SCF), in driving PSCM. First, based on the focal point of credit risk during SCF operations, this article systematically categorizes the development of PSCM driven by SCF into three patterns: seller-driven, buyer-driven, and third-party-driven. Second, in the above categorization patterns, this study focuses on the influence mechanisms of SCF on the four main decisions (pricing, quantity, quality, and timing). By clustering the main decisions under the three patterns, the results show that financing risks and costs under SCF operations change lenders’ decisions (e.g., lending rates, credit cycles, etc.), which in turn change borrowers’ decisions (e.g., price, quantity, etc.) in the purchasing process, and ultimately drive the development of PSCM. This review establishes SCF as an active driver of PSCM, revealing its dual role as a cost optimizer and strategic resource enabler, while reinterpreting capital flow as a proactive “fourth driver” in supply chains to dynamically coordinate procurement decisions. Finally, we summarize these studies and make recommendations for future research.
{"title":"Supply Chain Finance: A Strategic Enabler for Purchasing and Supply Chain Management","authors":"Han Guo;Lei Song;Feng Yang;Xiaolong Guo","doi":"10.1109/TEM.2025.3618762","DOIUrl":"https://doi.org/10.1109/TEM.2025.3618762","url":null,"abstract":"Purchasing and supply chain management (PSCM) is a subfield of supply chain management and focuses on the purchasing process. Relevant studies emphasize the importance of logistics, commodity flow, and information flow in the above process and make in-depth research. However, there are few studies on PSCM capital flow management, especially in terms of systematic review of the literature. This article adopts a systematic literature review (SLR) approach that focuses on the role of a common complementary capital flow instrument, supply chain finance (SCF), in driving PSCM. First, based on the focal point of credit risk during SCF operations, this article systematically categorizes the development of PSCM driven by SCF into three patterns: seller-driven, buyer-driven, and third-party-driven. Second, in the above categorization patterns, this study focuses on the influence mechanisms of SCF on the four main decisions (pricing, quantity, quality, and timing). By clustering the main decisions under the three patterns, the results show that financing risks and costs under SCF operations change lenders’ decisions (e.g., lending rates, credit cycles, etc.), which in turn change borrowers’ decisions (e.g., price, quantity, etc.) in the purchasing process, and ultimately drive the development of PSCM. This review establishes SCF as an active driver of PSCM, revealing its dual role as a cost optimizer and strategic resource enabler, while reinterpreting capital flow as a proactive “fourth driver” in supply chains to dynamically coordinate procurement decisions. Finally, we summarize these studies and make recommendations for future research.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4208-4224"},"PeriodicalIF":5.2,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-02DOI: 10.1109/TEM.2025.3616029
Tian Liu;Bipan Zou;Linzi Zhang;Guohu Xu
Warehouses recently are increasingly using autonomous robots and compact structures to handle fluctuating demands in a cost-efficient way. While organizing items in a compact cube can save floor space cost, it sacrifices the operational efficiency due to reshuffling and robot detouring to get target items. This study investigates this trade-off in three typical robotic storage and retrieval systems (RS/RSs), including a compact structure that organizes stacks in a grid (RCS/RS), a disperse structure that establishes vertical aisles for robot traveling (VRS/RS), and a structure with an aisle between any two adjacent racks for robot traveling (AVS/RS). We first build an expected travel time model of retrieval transactions, and validate the accuracy of the model by simulation. Then, with the objective of minimizing the expected retrieval travel time of robots, we derive the optimal configuration for three systems. Finally, we construct a cost minimization model of the system with a required throughput capacity obtained by a closed queuing network. We derive the minimum system cost by determining optimal system configuration and the numbers of robots and workstations. The comparison results show that the AVS/RS is the most efficient in robot travel time. The VRS/RS needs the least investment to reach a required throughput capacity, and the AVS/RS is the most expensive. Moreover, when the budget for system configuration, robots and workstations is limited, the VRS/RS can provide the largest throughput capacity.
{"title":"Expected Retrieval Time Comparison Among Robotic Storage and Retrieval Systems With Various Structures","authors":"Tian Liu;Bipan Zou;Linzi Zhang;Guohu Xu","doi":"10.1109/TEM.2025.3616029","DOIUrl":"https://doi.org/10.1109/TEM.2025.3616029","url":null,"abstract":"Warehouses recently are increasingly using autonomous robots and compact structures to handle fluctuating demands in a cost-efficient way. While organizing items in a compact cube can save floor space cost, it sacrifices the operational efficiency due to reshuffling and robot detouring to get target items. This study investigates this trade-off in three typical robotic storage and retrieval systems (RS/RSs), including a compact structure that organizes stacks in a grid (RCS/RS), a disperse structure that establishes vertical aisles for robot traveling (VRS/RS), and a structure with an aisle between any two adjacent racks for robot traveling (AVS/RS). We first build an expected travel time model of retrieval transactions, and validate the accuracy of the model by simulation. Then, with the objective of minimizing the expected retrieval travel time of robots, we derive the optimal configuration for three systems. Finally, we construct a cost minimization model of the system with a required throughput capacity obtained by a closed queuing network. We derive the minimum system cost by determining optimal system configuration and the numbers of robots and workstations. The comparison results show that the AVS/RS is the most efficient in robot travel time. The VRS/RS needs the least investment to reach a required throughput capacity, and the AVS/RS is the most expensive. Moreover, when the budget for system configuration, robots and workstations is limited, the VRS/RS can provide the largest throughput capacity.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4184-4207"},"PeriodicalIF":5.2,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1109/TEM.2025.3613494
Xu Ouyang;Sai-Ho Chung
In the past five years, the logistics and service sectors struggled for disruptions in multiple dimensions, particularly since the COVID-19 pandemic. Lockdown, travel restriction, geopolitical tension, extreme weather, and the trade war imposed critical challenges to operations. The resulting disruptions impacted both the upstream (e.g., production and supply) and the downstream (e.g., final-mile delivery and customer service) throughout the industries negatively. It is thus meaningful to identify critical operational problems arising from these disruptions and to derive insights on how to hedge against their adverse impacts. This article provides a focused review of the latest literature on logistics and service operations under disruptions. We identify the primary sources of recent disruptions and classify their effects on operational uncertainties. Then, we demonstrate how classic operational problems (e.g., vehicle routing and inventory management) are developed to adapt to disruptions, as well as some emerging issues (e.g., network design under tariff uncertainty). According to application contexts, we review several representative methodologies (e.g., stochastic programming, robust optimization, game theory, and machine learning), which are widely applied in modeling and solving these problems. Last, we conclude this review by summarizing our findings and proposing a three-fold research agenda to inspire future studies on this vital topic.
{"title":"Logistics and Service Operations Under Disruptions: Recent Development Under the DT Taxonomy","authors":"Xu Ouyang;Sai-Ho Chung","doi":"10.1109/TEM.2025.3613494","DOIUrl":"https://doi.org/10.1109/TEM.2025.3613494","url":null,"abstract":"In the past five years, the logistics and service sectors struggled for disruptions in multiple dimensions, particularly since the COVID-19 pandemic. Lockdown, travel restriction, geopolitical tension, extreme weather, and the trade war imposed critical challenges to operations. The resulting disruptions impacted both the upstream (e.g., production and supply) and the downstream (e.g., final-mile delivery and customer service) throughout the industries negatively. It is thus meaningful to identify critical operational problems arising from these disruptions and to derive insights on how to hedge against their adverse impacts. This article provides a focused review of the latest literature on logistics and service operations under disruptions. We identify the primary sources of recent disruptions and classify their effects on operational uncertainties. Then, we demonstrate how classic operational problems (e.g., vehicle routing and inventory management) are developed to adapt to disruptions, as well as some emerging issues (e.g., network design under tariff uncertainty). According to application contexts, we review several representative methodologies (e.g., stochastic programming, robust optimization, game theory, and machine learning), which are widely applied in modeling and solving these problems. Last, we conclude this review by summarizing our findings and proposing a three-fold research agenda to inspire future studies on this vital topic.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4225-4236"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-30DOI: 10.1109/TEM.2025.3616130
Cong Cheng;Jian Dai;Lulu Yan
Selecting the right merger and acquisition (M&A) target is a critical yet challenging endeavor, as the success of these strategic initiatives depends mainly on identifying compatible firms. This study draws upon the theoretical perspectives of strategic fit and organizational search to propose and validate a novel, two-stage M&A target recommendation approach designed as a managerial decision support system. Initially, the method facilitates a focused search in which acquirers define explicit criteria for identifying a highly relevant initial target within a knowledge graph (KG). It then employs a similarity-based search expansion using advanced KG embedding models to recommend additional targets that exhibit latent structural similarities. The efficacy of this approach is validated on a large-scale U.S. M&A dataset (2010–2022). Our key findings are threefold. First, our model demonstrates statistically significant superiority over benchmarks, confirmed through robustness checks, including tenfold cross-validation and temporal validation. Second, in an experiment on deals by experienced acquirers, our model is more effective at identifying these targets, quantitatively demonstrating its superior recommendation quality. Third, our analysis uncovers counterintuitive patterns, revealing that machine-identified structural similarities can be more potent predictors of fit than traditional human-centric filters, such as geography. It further explores the tool’s boundary conditions, showing that it is more effective in complex, high-tech sectors. This KG-based methodology offers a more informed, strategically refined, and empirically validated tool to enhance the quality of M&A decisions.
{"title":"A Knowledge Graph-Based Target Recommendation Approach for Mergers and Acquisitions","authors":"Cong Cheng;Jian Dai;Lulu Yan","doi":"10.1109/TEM.2025.3616130","DOIUrl":"https://doi.org/10.1109/TEM.2025.3616130","url":null,"abstract":"Selecting the right merger and acquisition (M&A) target is a critical yet challenging endeavor, as the success of these strategic initiatives depends mainly on identifying compatible firms. This study draws upon the theoretical perspectives of strategic fit and organizational search to propose and validate a novel, two-stage M&A target recommendation approach designed as a managerial decision support system. Initially, the method facilitates a focused search in which acquirers define explicit criteria for identifying a highly relevant initial target within a knowledge graph (KG). It then employs a similarity-based search expansion using advanced KG embedding models to recommend additional targets that exhibit latent structural similarities. The efficacy of this approach is validated on a large-scale U.S. M&A dataset (2010–2022). Our key findings are threefold. First, our model demonstrates statistically significant superiority over benchmarks, confirmed through robustness checks, including tenfold cross-validation and temporal validation. Second, in an experiment on deals by experienced acquirers, our model is more effective at identifying these targets, quantitatively demonstrating its superior recommendation quality. Third, our analysis uncovers counterintuitive patterns, revealing that machine-identified structural similarities can be more potent predictors of fit than traditional human-centric filters, such as geography. It further explores the tool’s boundary conditions, showing that it is more effective in complex, high-tech sectors. This KG-based methodology offers a more informed, strategically refined, and empirically validated tool to enhance the quality of M&A decisions.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4113-4126"},"PeriodicalIF":5.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-29DOI: 10.1109/TEM.2025.3615542
Kerem Kayabay;Mert Onuralp Gökalp;Atilla Kılınç;Ebru Gökalp;Tugrul Daim
Many organizations struggle to keep their artificial intelligence (AI) systems aligned with operational data and computing resources in today’s volatile landscape. Data science roadmapping (DSR) embeds data layers into planning scenarios and enables a human-centric process. While DSR is effective for creating data science roadmaps, it lacks a clear implementation framework. This research advances DSR as a continuous AI alignment platform through three phases: 1) a multivocal literature review of academic and grey sources identifies gaps and tools; 2) synthesis of these findings adapts DSR for ongoing AI alignment; 3) a retrospective case study evaluates the adapted process. Initial results show the effectiveness of agile modifications to the DSR framework and the integration of a real-time platform for roadmap implementation and monitoring. Case study participants strongly supported a dedicated roadmapping operations team, especially to manage communication, detect AI deviations, and ensure compliance. This underscores how the operationalization of roadmapping can strengthen data and AI governance.
{"title":"Data Science Roadmapping for AI Alignment: Insights From a Multivocal Literature Review and a Retrospective Case Study","authors":"Kerem Kayabay;Mert Onuralp Gökalp;Atilla Kılınç;Ebru Gökalp;Tugrul Daim","doi":"10.1109/TEM.2025.3615542","DOIUrl":"https://doi.org/10.1109/TEM.2025.3615542","url":null,"abstract":"Many organizations struggle to keep their artificial intelligence (AI) systems aligned with operational data and computing resources in today’s volatile landscape. Data science roadmapping (DSR) embeds data layers into planning scenarios and enables a human-centric process. While DSR is effective for creating data science roadmaps, it lacks a clear implementation framework. This research advances DSR as a continuous AI alignment platform through three phases: 1) a multivocal literature review of academic and grey sources identifies gaps and tools; 2) synthesis of these findings adapts DSR for ongoing AI alignment; 3) a retrospective case study evaluates the adapted process. Initial results show the effectiveness of agile modifications to the DSR framework and the integration of a real-time platform for roadmap implementation and monitoring. Case study participants strongly supported a dedicated roadmapping operations team, especially to manage communication, detect AI deviations, and ensure compliance. This underscores how the operationalization of roadmapping can strengthen data and AI governance.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4171-4183"},"PeriodicalIF":5.2,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145315460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-25DOI: 10.1109/TEM.2025.3614554
Soumya Prakash Patra;Rohit Agrawal;Rajesh Kumar Singh;Qile He
Blockchain technology (BCT) is emerging as a disruptive innovation in increasingly globalized business ventures. It is believed to offer important benefits to international entrepreneurs, such as reducing transaction cost and risk of fraud, creating better transactional trust, and avoiding exploitation by business partners. However, BCT can bring changes to the business world only if it gets adopted by industries across all spectrums. International entrepreneurs are amongst the critical groups of adopters of BCT. Based on multiple theoretical perspectives, this article identifies and categorizes key barriers to adopting BCT by international entrepreneurs. A survey of BCT field experts was conducted to validate 15 key barriers to BCT adoption. Furthermore, based on pairwise comparison data collection with three groups of international entrepreneurs from India and U.K., a decision-making methodology was adopted to identify the relative importance and the causal relationships among the key barriers. This study develops a framework of strategic solutions to address barriers of BCT adoption by international entrepreneurs. This study offers stakeholders of BCT to better understand the patterns of BCT adoption by international entrepreneurs and will support the development of more targeted and multifaceted BCT adoption strategies.
{"title":"Adoption of Blockchain Technology in International Entrepreneurship: Strategic Framework for Managing Roadblocks","authors":"Soumya Prakash Patra;Rohit Agrawal;Rajesh Kumar Singh;Qile He","doi":"10.1109/TEM.2025.3614554","DOIUrl":"https://doi.org/10.1109/TEM.2025.3614554","url":null,"abstract":"Blockchain technology (BCT) is emerging as a disruptive innovation in increasingly globalized business ventures. It is believed to offer important benefits to international entrepreneurs, such as reducing transaction cost and risk of fraud, creating better transactional trust, and avoiding exploitation by business partners. However, BCT can bring changes to the business world only if it gets adopted by industries across all spectrums. International entrepreneurs are amongst the critical groups of adopters of BCT. Based on multiple theoretical perspectives, this article identifies and categorizes key barriers to adopting BCT by international entrepreneurs. A survey of BCT field experts was conducted to validate 15 key barriers to BCT adoption. Furthermore, based on pairwise comparison data collection with three groups of international entrepreneurs from India and U.K., a decision-making methodology was adopted to identify the relative importance and the causal relationships among the key barriers. This study develops a framework of strategic solutions to address barriers of BCT adoption by international entrepreneurs. This study offers stakeholders of BCT to better understand the patterns of BCT adoption by international entrepreneurs and will support the development of more targeted and multifaceted BCT adoption strategies.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4127-4140"},"PeriodicalIF":5.2,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-17DOI: 10.1109/TEM.2025.3609983
Qingguo Bai;Lei Xu
With the introduction of buy-online-and-pickup-in-store (BOPS) services, it has been unclear whether physical stores should have their own online channels when overconfident behavior, carbon abatement, and incomplete demand information are considered in the manufacturer’s operations. This practical issue motivates us to investigate an overconfident manufacturer under a cap-and-offset policy who sells products through the omnichannel retail model. Three types of customers in this model are classified, and only the expectation and variance of stochastic demand are captured. The operational stages related to production, inventory, and transportation contribute to carbon emissions. We first consider the self-operated online channel and the independent channel and develop two corresponding distributionally robust newsvendor models. The analytic expression of the optimal robust manufacturing quantity for each model is solved. We compare the operational efficacy of an overconfident manufacturer in the self-operated online system with that in the independent system. The results show that the net profit from selling each unit item to online customers is a significant factor in comparing the profit and carbon emissions of overconfident manufacturers in the two omnichannel retail systems. Numerical experiments are conducted to complement the theoretical models and examine the effects of several major parameters on the two systems in the omnichannel retail model. This article provides the manufacturer with valuable knowledge of the robust manufacturing strategy and integration between the online and offline channels under the omnichannel retail model.
{"title":"Robust Decisions of Omnichannel Retail Operations for an Overconfident Manufacturer Considering Short Life-Cycle Products and Cap-and-Offset Policy","authors":"Qingguo Bai;Lei Xu","doi":"10.1109/TEM.2025.3609983","DOIUrl":"https://doi.org/10.1109/TEM.2025.3609983","url":null,"abstract":"With the introduction of buy-online-and-pickup-in-store (BOPS) services, it has been unclear whether physical stores should have their own online channels when overconfident behavior, carbon abatement, and incomplete demand information are considered in the manufacturer’s operations. This practical issue motivates us to investigate an overconfident manufacturer under a cap-and-offset policy who sells products through the omnichannel retail model. Three types of customers in this model are classified, and only the expectation and variance of stochastic demand are captured. The operational stages related to production, inventory, and transportation contribute to carbon emissions. We first consider the self-operated online channel and the independent channel and develop two corresponding distributionally robust newsvendor models. The analytic expression of the optimal robust manufacturing quantity for each model is solved. We compare the operational efficacy of an overconfident manufacturer in the self-operated online system with that in the independent system. The results show that the net profit from selling each unit item to online customers is a significant factor in comparing the profit and carbon emissions of overconfident manufacturers in the two omnichannel retail systems. Numerical experiments are conducted to complement the theoretical models and examine the effects of several major parameters on the two systems in the omnichannel retail model. This article provides the manufacturer with valuable knowledge of the robust manufacturing strategy and integration between the online and offline channels under the omnichannel retail model.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4020-4035"},"PeriodicalIF":5.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-16DOI: 10.1109/TEM.2025.3610266
Xiutian Shi;Qiaoli Lai;Ciwei Dong;Siru Chen
Supplier greenwashing behaviors in corporate social responsibility (CSR) have become increasingly notable, often involving exaggerated claims about CSR initiatives or diverting resources to conceal violations. In this article, we develop a game-theoretic model to investigate the motivation of greenwashing and its intricate economic and social consequences, and explore whether blockchain technology can effectively enhance CSR efforts. We find that the tradeoff between exaggeration and concealment inherent in greenwashing plays a significant role in CSR strategy selection and corresponding performances. Specifically, if the exaggerating effect dominates greenwashing, the supplier has an incentive to adopt blockchain for self-certification in CSR activities. Conversely, when the concealment effect prevails, opportunistic behavior is more likely to occur. However, the integrative greenwashing coefficient has polarized impacts on the optimal CSR effort level, retailer’s profit, and consumer surplus. We unveil that blockchain implementation achieves the highest social welfare when the exaggeration of greenwashing plays a more prominent role, particularly when the CSR violation penalty is relatively subtle for both firms. Interestingly, we observe that greenwashing, despite its negative connotations, can eventually stimulate CSR efforts due to the incremental demand induced by exaggerated disclosures, ultimately leading to the highest social welfare.
{"title":"Exaggeration or Concealment: Corporate Social Responsibility Strategy in the Blockchain Era","authors":"Xiutian Shi;Qiaoli Lai;Ciwei Dong;Siru Chen","doi":"10.1109/TEM.2025.3610266","DOIUrl":"https://doi.org/10.1109/TEM.2025.3610266","url":null,"abstract":"Supplier greenwashing behaviors in corporate social responsibility (CSR) have become increasingly notable, often involving exaggerated claims about CSR initiatives or diverting resources to conceal violations. In this article, we develop a game-theoretic model to investigate the motivation of greenwashing and its intricate economic and social consequences, and explore whether blockchain technology can effectively enhance CSR efforts. We find that the tradeoff between exaggeration and concealment inherent in greenwashing plays a significant role in CSR strategy selection and corresponding performances. Specifically, if the exaggerating effect dominates greenwashing, the supplier has an incentive to adopt blockchain for self-certification in CSR activities. Conversely, when the concealment effect prevails, opportunistic behavior is more likely to occur. However, the integrative greenwashing coefficient has polarized impacts on the optimal CSR effort level, retailer’s profit, and consumer surplus. We unveil that blockchain implementation achieves the highest social welfare when the exaggeration of greenwashing plays a more prominent role, particularly when the CSR violation penalty is relatively subtle for both firms. Interestingly, we observe that greenwashing, despite its negative connotations, can eventually stimulate CSR efforts due to the incremental demand induced by exaggerated disclosures, ultimately leading to the highest social welfare.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"4264-4280"},"PeriodicalIF":5.2,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-15DOI: 10.1109/TEM.2025.3609246
Usama Awan;Ismail Golgeci;Anne-Laure Mention
Manufacturing firms are facing the complex challenge of deploying information technology (IT) alignment and establishing market agility to drive business model innovation (BMI). While existing literature has established a link between organizational sensemaking and BMI, the interaction between market agility and organizational sensemaking for BMI remains unexamined. Drawing from a knowledge base view, this study addresses this research gap by examining the moderating effect of IT alignment on the mediating role of market agility in the relationship between sensemaking capability and BMI. Our data, collected from 232 engineering manufacturers, along with the application of PLS-SEM to test the conceptual model, reveal that the effect of organizational sensemaking capability on BMI through market agility depends on IT alignment. These findings enhance our understanding of IT alignment’s role in a firm’s development of BMI via market agility, providing valuable implications for managerial practices by underscoring the importance of IT alignment for BMI. By grasping this interaction, managers can unlock the potential for more effective and innovative business models, fostering enhanced competitiveness and sustained growth.
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