Pub Date : 2026-01-30DOI: 10.1109/TEM.2026.3654578
Xiaowei Feng;Jiming Cao;Liang Liu;Cong Liu
This study introduces a colored network motif approach to systematically analyze microlevel collaboration patterns in public–private partnership (PPP) project networks from China's transportation sector. By distinguishing node types (e.g., contractors and investors) and tie strengths (e.g., strong versus weak collaboration), the analysis uncovers statistically significant triadic motifs that reveal structural dominance and evolutionary features. Using a longitudinal multiproject dataset (2014–2021) and degree-preserving randomized network benchmarks, the study ensures robust identification of overrepresented local structures. Key findings show that: 1) in terms of heterogeneous-node local relationship patterns, construction contractors emerge as dominant players, with fully connected triads and structural hole triads wherein dyads are different types of organizations identified as motifs; and 2) concerning heterogeneous-edge patterns, even though weak-tie subgraphs form the basic path of the networks, stable strong-tie subgraphs, representing collaboration alliances, become increasingly prevalent among organizations. This study contributes in three key ways. First, it advances project network analysis by shifting the analytical lens from macrolevel structures to microrelational patterns, enabling the identification of recurrent subgraph configurations among PPP actors. Second, it operationalizes colored motif detection to empirically capture both node- and edge-level heterogeneity in PPP networks. Third, it offers new theoretical and practical insights into the evolution of collaboration structures, showing how motifs such as structural holes reflect underlying governance logics.
{"title":"Using Colored Motifs to Characterize Relationship Patterns of Project Networks in Transportation Sectors","authors":"Xiaowei Feng;Jiming Cao;Liang Liu;Cong Liu","doi":"10.1109/TEM.2026.3654578","DOIUrl":"https://doi.org/10.1109/TEM.2026.3654578","url":null,"abstract":"This study introduces a colored network motif approach to systematically analyze microlevel collaboration patterns in public–private partnership (PPP) project networks from China's transportation sector. By distinguishing node types (e.g., contractors and investors) and tie strengths (e.g., strong versus weak collaboration), the analysis uncovers statistically significant triadic motifs that reveal structural dominance and evolutionary features. Using a longitudinal multiproject dataset (2014–2021) and degree-preserving randomized network benchmarks, the study ensures robust identification of overrepresented local structures. Key findings show that: 1) in terms of heterogeneous-node local relationship patterns, construction contractors emerge as dominant players, with fully connected triads and structural hole triads wherein dyads are different types of organizations identified as motifs; and 2) concerning heterogeneous-edge patterns, even though weak-tie subgraphs form the basic path of the networks, stable strong-tie subgraphs, representing collaboration alliances, become increasingly prevalent among organizations. This study contributes in three key ways. First, it advances project network analysis by shifting the analytical lens from macrolevel structures to microrelational patterns, enabling the identification of recurrent subgraph configurations among PPP actors. Second, it operationalizes colored motif detection to empirically capture both node- and edge-level heterogeneity in PPP networks. Third, it offers new theoretical and practical insights into the evolution of collaboration structures, showing how motifs such as structural holes reflect underlying governance logics.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1695-1709"},"PeriodicalIF":5.2,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223710","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}
With the rapid growth of the global economy and ongoing technological advancements, smart manufacturing has become a vital force driving industrial transformation. This study investigates how smart manufacturing capability influences business model innovation (BMI) in manufacturing enterprises. It further examines the mediating role of new productive forces and the moderating effect of patient capital in this relationship. Despite the significance of smart manufacturing, existing research offers limited insight into its impact on BMI. To address this gap, this study collected data from manufacturing firms across various industries through a questionnaire survey. The data were analyzed using structural equation modeling and hierarchical regression analysis. The results show that smart manufacturing capability significantly promotes BMI. This indicates that advancements in smart manufacturing can drive innovation by optimizing production processes, improving resource efficiency, and enhancing market responsiveness. Moreover, new productive forces serve as a key mediator in this relationship, suggesting that enhanced smart manufacturing capabilities improve firms’ production efficiency and innovation capacity, thereby facilitating business model transformation. Patient capital also plays a significant moderating role, demonstrating that long-term resource investment and strategic persistence amplify the positive effects of smart manufacturing on innovation. To ensure the rigor of the study, four robustness checks were conducted: substitute variable tests, subsample analyses, lag effect tests, and multicollinearity diagnostics. All results confirmed the stability of the core conclusions. This study provides a new theoretical perspective on the relationship between smart manufacturing and BMI. It also offers empirical support for research on technology enablement in engineering management and provides practical guidance for the digital transformation of manufacturing enterprises.
{"title":"The Impact of Smart Manufacturing Capabilities on Business Model Innovation in Manufacturing Enterprises","authors":"Tongtong Geng;Yueping Du;Jinghong Lan;Jiangyue Qu;Yong Jiang","doi":"10.1109/TEM.2026.3658192","DOIUrl":"https://doi.org/10.1109/TEM.2026.3658192","url":null,"abstract":"With the rapid growth of the global economy and ongoing technological advancements, smart manufacturing has become a vital force driving industrial transformation. This study investigates how smart manufacturing capability influences business model innovation (BMI) in manufacturing enterprises. It further examines the mediating role of new productive forces and the moderating effect of patient capital in this relationship. Despite the significance of smart manufacturing, existing research offers limited insight into its impact on BMI. To address this gap, this study collected data from manufacturing firms across various industries through a questionnaire survey. The data were analyzed using structural equation modeling and hierarchical regression analysis. The results show that smart manufacturing capability significantly promotes BMI. This indicates that advancements in smart manufacturing can drive innovation by optimizing production processes, improving resource efficiency, and enhancing market responsiveness. Moreover, new productive forces serve as a key mediator in this relationship, suggesting that enhanced smart manufacturing capabilities improve firms’ production efficiency and innovation capacity, thereby facilitating business model transformation. Patient capital also plays a significant moderating role, demonstrating that long-term resource investment and strategic persistence amplify the positive effects of smart manufacturing on innovation. To ensure the rigor of the study, four robustness checks were conducted: substitute variable tests, subsample analyses, lag effect tests, and multicollinearity diagnostics. All results confirmed the stability of the core conclusions. This study provides a new theoretical perspective on the relationship between smart manufacturing and BMI. It also offers empirical support for research on technology enablement in engineering management and provides practical guidance for the digital transformation of manufacturing enterprises.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1558-1572"},"PeriodicalIF":5.2,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175825","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 : 2026-01-28DOI: 10.1109/TEM.2026.3657965
Mohammad Nurul Hassan Reza;Sahadat Hossain;Abdullah Al Mamun;Angappa Gunasekaran;Chinnasamy Agamudai Malarvizhi;Uma Thevi Munikrishnan
The current state of research on the adoption of cloud computing (CC) is characterized by a lack of comprehensive reviews and classifications of existing studies. This systematic review addresses this gap by proposing a novel framework for CC adoption that integrates core influential antecedents, potential advantages, and challenges in sustainable business operations. Specifically, the framework links antecedents (inputs) to processes (positive outcomes/potential advantages), ultimately contributing to sustainable performance and resource efficiency (outputs). Using the Web of Science and Scopus databases, we selected 67 journal articles on CC adoption, published from 2011 to 2025. This study encompasses bibliometric and thematic analyses. Bibliometric analysis revealed a growing interest in publishing research on CC from various countries, with different sectors emphasized in pioneering journals. It also demonstrated a diverse approach, including methodologies, tools, techniques, and theories. Thematic analysis identified 24 antecedents—spanning perceived innovation-related, technological, organizational, and environmental—along with six potential advantages and six challenges influencing CC adoption, ultimately aiding sustainable business operations. Challenges are conceptualized as moderating variables in the adoption process. The findings contribute to theory by clarifying the interplay between adoption drivers, advantages, and challenges, and to practice by offering managers a diagnostic tool to facilitate CC adoption for improved efficiency and sustainable business performance.
采用云计算的研究现状的特点是缺乏对现有研究的全面审查和分类。本系统综述通过提出一种新的CC采用框架来解决这一差距，该框架整合了可持续业务运营中的核心影响因素、潜在优势和挑战。具体而言，该框架将前因（投入）与过程（积极结果/潜在优势）联系起来，最终促进可持续绩效和资源效率（产出）。使用Web of Science和Scopus数据库，我们选择了2011年至2025年间发表的67篇关于CC采用的期刊文章。这项研究包括文献计量学和专题分析。文献计量学分析显示，各国对出版CC研究的兴趣日益浓厚，在开拓性期刊上强调不同的领域。它还展示了多种方法，包括方法、工具、技术和理论。专题分析确定了24个前因——涵盖与感知创新相关的、技术的、组织的和环境的——以及影响CC采用的6个潜在优势和6个挑战，最终有助于可持续的业务运营。挑战被定义为采用过程中的调节变量。这些发现通过阐明采用驱动因素、优势和挑战之间的相互作用来促进理论，并通过为管理人员提供诊断工具来促进采用CC以提高效率和可持续的业务绩效，从而有助于实践。
{"title":"Unlocking the Potential of Cloud Computing for Sustainable Business Operations: A Systematic Review of Antecedents, Advantages and Challenges","authors":"Mohammad Nurul Hassan Reza;Sahadat Hossain;Abdullah Al Mamun;Angappa Gunasekaran;Chinnasamy Agamudai Malarvizhi;Uma Thevi Munikrishnan","doi":"10.1109/TEM.2026.3657965","DOIUrl":"https://doi.org/10.1109/TEM.2026.3657965","url":null,"abstract":"The current state of research on the adoption of cloud computing (CC) is characterized by a lack of comprehensive reviews and classifications of existing studies. This systematic review addresses this gap by proposing a novel framework for CC adoption that integrates core influential antecedents, potential advantages, and challenges in sustainable business operations. Specifically, the framework links antecedents (inputs) to processes (positive outcomes/potential advantages), ultimately contributing to sustainable performance and resource efficiency (outputs). Using the Web of Science and Scopus databases, we selected 67 journal articles on CC adoption, published from 2011 to 2025. This study encompasses bibliometric and thematic analyses. Bibliometric analysis revealed a growing interest in publishing research on CC from various countries, with different sectors emphasized in pioneering journals. It also demonstrated a diverse approach, including methodologies, tools, techniques, and theories. Thematic analysis identified 24 antecedents—spanning perceived innovation-related, technological, organizational, and environmental—along with six potential advantages and six challenges influencing CC adoption, ultimately aiding sustainable business operations. Challenges are conceptualized as moderating variables in the adoption process. The findings contribute to theory by clarifying the interplay between adoption drivers, advantages, and challenges, and to practice by offering managers a diagnostic tool to facilitate CC adoption for improved efficiency and sustainable business performance.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1723-1738"},"PeriodicalIF":5.2,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223640","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 : 2026-01-28DOI: 10.1109/TEM.2026.3658843
Zhiyuan Chen;Qiaoyun Gong;Jianhong Zhou
Enabled by blockchain progress, initial coin offerings (ICOs) emerged as an alternative to traditional equity financing, with global investor reach, decentralized governance, and reduced transaction costs. However, the performance of ICOs under competitive product market conditions remains underexplored. This article develops a game theoretic Cournot competition model to compare firms' financing and operational strategies under two benchmark scenarios, depending on whether product value is insensitive or sensitive to managerial effort. The analysis examines how cost structure, market volatility, product substitutability, and managerial risk attitude jointly affect financing choices and production decisions. To ensure research rigor, we further analyze a generalized model and conduct robustness checks by varying key parameters, confirming the stability of the equilibrium outcomes beyond the benchmark settings. The results show that optimal financing choices depend critically on market structure. Greater product substitutability intensifies competition and widens the utility gap between financing modes, strengthening the dominance of the more suitable strategy. Equity financing is more favorable for risk averse firms or those operating in low innovation, high substitutability industries, such as manufacturing and utilities, due to its risk sharing and operational flexibility. In contrast, ICOs are better suited for innovation-driven ventures, such as DeFi and non-fungible tokens (NFTs), which benefit from incentive alignment and reduced equity dilution. This study provides managerial insights into the strategic selection of financing mechanisms under competition and contributes to a deeper understanding of token financing in modern capital markets.
{"title":"Initial Coin Offerings Versus Equity Financing Strategies Under Cournot Competition","authors":"Zhiyuan Chen;Qiaoyun Gong;Jianhong Zhou","doi":"10.1109/TEM.2026.3658843","DOIUrl":"https://doi.org/10.1109/TEM.2026.3658843","url":null,"abstract":"Enabled by blockchain progress, initial coin offerings (ICOs) emerged as an alternative to traditional equity financing, with global investor reach, decentralized governance, and reduced transaction costs. However, the performance of ICOs under competitive product market conditions remains underexplored. This article develops a game theoretic Cournot competition model to compare firms' financing and operational strategies under two benchmark scenarios, depending on whether product value is insensitive or sensitive to managerial effort. The analysis examines how cost structure, market volatility, product substitutability, and managerial risk attitude jointly affect financing choices and production decisions. To ensure research rigor, we further analyze a generalized model and conduct robustness checks by varying key parameters, confirming the stability of the equilibrium outcomes beyond the benchmark settings. The results show that optimal financing choices depend critically on market structure. Greater product substitutability intensifies competition and widens the utility gap between financing modes, strengthening the dominance of the more suitable strategy. Equity financing is more favorable for risk averse firms or those operating in low innovation, high substitutability industries, such as manufacturing and utilities, due to its risk sharing and operational flexibility. In contrast, ICOs are better suited for innovation-driven ventures, such as DeFi and non-fungible tokens (NFTs), which benefit from incentive alignment and reduced equity dilution. This study provides managerial insights into the strategic selection of financing mechanisms under competition and contributes to a deeper understanding of token financing in modern capital markets.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1587-1601"},"PeriodicalIF":5.2,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175817","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 : 2026-01-26DOI: 10.1109/TEM.2026.3655220
Yanji Duan;Qingyun Zhu;Joseph Sarkis
This study investigates whether combining blockchain and artificial intelligence (AI) enhances consumer value and creates synergies in reverse logistics operations in a retail setting. Using a behavioral experiment with 250 participants on a simulated e-commerce platform featuring blockchain only, AI only, or their combination while searching for returned product-logistics information. Two dimensions of consumer outputs were assessed: perceptual outcomes—attitude toward the firm and repurchase intention—and experiential outcomes—task completion time and accuracy. Results indicate a clear perceptual complementarity. Integrating blockchain's verifiable transparency with AI-driven personalization significantly strengthened consumer sustainability perceptions and willingness to repurchase relative to single-technology conditions. Differently, experiential effects diverged. Combining both technologies increased task completion time, and did not significantly improve accuracy, revealing performance substitutability rather than synergy. These findings refine complementarity theory by demonstrating that a technology bundle can simultaneously yield positive perceptual spillovers and negative experiential tradeoffs. Retailers are therefore advised to adopt the blockchain–AI pairing when strategic objectives center on trust and brand perceptions but to simplify the interface when operational speed is important. Robustness checks were completed to further establish rigor in the results. Our study also provides actionable insights for managers, emphasizing the prioritization of technology adoption, the importance of bundling blockchain with AI, and the differentiation between perceptual and experiential synergies to maximize consumer value in retail operations.
{"title":"Is 1+1 Greater Than 2? The Synergistic Effect of Blockchain and Artificial Intelligence on Consumer Perceptual and Experiential Needs","authors":"Yanji Duan;Qingyun Zhu;Joseph Sarkis","doi":"10.1109/TEM.2026.3655220","DOIUrl":"https://doi.org/10.1109/TEM.2026.3655220","url":null,"abstract":"This study investigates whether combining blockchain and artificial intelligence (AI) enhances consumer value and creates synergies in reverse logistics operations in a retail setting. Using a behavioral experiment with 250 participants on a simulated e-commerce platform featuring blockchain only, AI only, or their combination while searching for returned product-logistics information. Two dimensions of consumer outputs were assessed: perceptual outcomes—attitude toward the firm and repurchase intention—and experiential outcomes—task completion time and accuracy. Results indicate a clear perceptual complementarity. Integrating blockchain's verifiable transparency with AI-driven personalization significantly strengthened consumer sustainability perceptions and willingness to repurchase relative to single-technology conditions. Differently, experiential effects diverged. Combining both technologies increased task completion time, and did not significantly improve accuracy, revealing performance substitutability rather than synergy. These findings refine complementarity theory by demonstrating that a technology bundle can simultaneously yield positive perceptual spillovers and negative experiential tradeoffs. Retailers are therefore advised to adopt the blockchain–AI pairing when strategic objectives center on trust and brand perceptions but to simplify the interface when operational speed is important. Robustness checks were completed to further establish rigor in the results. Our study also provides actionable insights for managers, emphasizing the prioritization of technology adoption, the importance of bundling blockchain with AI, and the differentiation between perceptual and experiential synergies to maximize consumer value in retail operations.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1652-1666"},"PeriodicalIF":5.2,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175819","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 : 2026-01-26DOI: 10.1109/TEM.2026.3657884
Qinglong Gou;Jia Li;Lei Song;Juzhi Zhang
Third-party logistics (3 PLs) providers with low service quality often face delivery uncertainty risks, leading to decreased consumer satisfaction and resulting in refunds. Retailers can mitigate the negative effects of these uncertainties by incorporating high-quality 3 PLs. However, the strategic implications of introducing high-quality 3 PLs for both retailers and low-quality 3 PLs remain underexplored. To address this gap, we develop a Stackelberg game-theoretic model to investigate the effect of introducing a high-quality 3 PL on retailer and high-quality 3 PL decision-making. Using backward induction to obtain the Nash equilibrium, we analyze strategic interactions under two scenarios: without and with the high-quality 3 PL. The results show that, under certain conditions—namely, when the retailer faces a moderate proportion of first shipment with the low-quality 3 PL and the transportation price of the high-quality 3 PL is low, or when the proportion of first shipment with the low-quality 3 PL is high—the introduction of the high-quality 3 PL can create a win–win–win outcome for the retailer, the low-quality 3 PL, and consumers. Furthermore, the introduction of the high-quality 3 PL leads to both the higher retail price for the retailer and the higher transportation price for the low-quality 3 PL. With the high-quality 3 PL, the transportation price of the low-quality 3 PL decreases as the transportation price of the high-quality 3 PL increases. In addition, we find that when considering an uncertainty penalty for the low-quality 3 PL, the introduction can also achieve a win–win–win result for all three parties. Finally, we extend other possible scenarios in the appendix to verify the robustness of our conclusions.
{"title":"Effect of High-Quality Thirty-Party Logistics on a Retailer With Delivery Uncertainty","authors":"Qinglong Gou;Jia Li;Lei Song;Juzhi Zhang","doi":"10.1109/TEM.2026.3657884","DOIUrl":"https://doi.org/10.1109/TEM.2026.3657884","url":null,"abstract":"Third-party logistics (3 PLs) providers with low service quality often face delivery uncertainty risks, leading to decreased consumer satisfaction and resulting in refunds. Retailers can mitigate the negative effects of these uncertainties by incorporating high-quality 3 PLs. However, the strategic implications of introducing high-quality 3 PLs for both retailers and low-quality 3 PLs remain underexplored. To address this gap, we develop a Stackelberg game-theoretic model to investigate the effect of introducing a high-quality 3 PL on retailer and high-quality 3 PL decision-making. Using backward induction to obtain the Nash equilibrium, we analyze strategic interactions under two scenarios: without and with the high-quality 3 PL. The results show that, under certain conditions—namely, when the retailer faces a moderate proportion of first shipment with the low-quality 3 PL and the transportation price of the high-quality 3 PL is low, or when the proportion of first shipment with the low-quality 3 PL is high—the introduction of the high-quality 3 PL can create a win–win–win outcome for the retailer, the low-quality 3 PL, and consumers. Furthermore, the introduction of the high-quality 3 PL leads to both the higher retail price for the retailer and the higher transportation price for the low-quality 3 PL. With the high-quality 3 PL, the transportation price of the low-quality 3 PL decreases as the transportation price of the high-quality 3 PL increases. In addition, we find that when considering an uncertainty penalty for the low-quality 3 PL, the introduction can also achieve a win–win–win result for all three parties. Finally, we extend other possible scenarios in the appendix to verify the robustness of our conclusions.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1544-1557"},"PeriodicalIF":5.2,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175913","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 : 2026-01-22DOI: 10.1109/TEM.2026.3657042
Francesco Otello Buccoliero;Angelo Corallo;Anna Maria Crespino;Vito Del Vecchio;Marianna Lezzi;Alessandra Spennato
The smart manufacturing paradigm involves the integration of Internet of Things, big data (BD), and artificial intelligence with digital twins, enabling the design of data-driven architectures. In this context, shopfloor digital twin (SDT) frameworks allow for real-time representation, simulation, monitoring, and prediction of shop floor entities, enabling the smarter and sustainable management of production processes. Different SDT frameworks were provided in the literature, but few empirical experimentations were present in real manufacturing scenarios. This issue is more evident when modeling a BD process-oriented SDT, which is the gap this article aims to narrow. Through a case study, based on the adoption of the hexadimensional shop floor digital twin (HexaSFDT) framework and using both qualitative and quantitative primary empirical data, in this article, we provide an original implementation of a process-oriented and BD-driven SDT in the shopfloor of a manufacturing aerospace company and, specifically, within the critical material-handling process. First, by modeling the material-handling process-oriented SDT, technological issues and domain tips (e.g., key performance indicators) are highlighted by experts for a better management of materials. Second, the case study shows the design and implementation of the big data analytics pipeline and how to close the loop. Third, best practices related to innovative empirical experimentation of HexaSFDT framework are emphasized, supporting companies in understanding the potential of SDT for better performance and more effective decision making.
{"title":"Modeling a Process Shop Floor Digital Twin in Smart Manufacturing: Best Practices From a Case Study","authors":"Francesco Otello Buccoliero;Angelo Corallo;Anna Maria Crespino;Vito Del Vecchio;Marianna Lezzi;Alessandra Spennato","doi":"10.1109/TEM.2026.3657042","DOIUrl":"https://doi.org/10.1109/TEM.2026.3657042","url":null,"abstract":"The smart manufacturing paradigm involves the integration of Internet of Things, big data (BD), and artificial intelligence with digital twins, enabling the design of data-driven architectures. In this context, shopfloor digital twin (SDT) frameworks allow for real-time representation, simulation, monitoring, and prediction of shop floor entities, enabling the smarter and sustainable management of production processes. Different SDT frameworks were provided in the literature, but few empirical experimentations were present in real manufacturing scenarios. This issue is more evident when modeling a BD process-oriented SDT, which is the gap this article aims to narrow. Through a case study, based on the adoption of the hexadimensional shop floor digital twin (HexaSFDT) framework and using both qualitative and quantitative primary empirical data, in this article, we provide an original implementation of a process-oriented and BD-driven SDT in the shopfloor of a manufacturing aerospace company and, specifically, within the critical material-handling process. First, by modeling the material-handling process-oriented SDT, technological issues and domain tips (e.g., key performance indicators) are highlighted by experts for a better management of materials. Second, the case study shows the design and implementation of the big data analytics pipeline and how to close the loop. Third, best practices related to innovative empirical experimentation of HexaSFDT framework are emphasized, supporting companies in understanding the potential of SDT for better performance and more effective decision making.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1667-1680"},"PeriodicalIF":5.2,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175813","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 : 2026-01-21DOI: 10.1109/TEM.2026.3656529
Xinyu Wang;Xinya Liu;Shuhua Zhang
Technological advances have substantially enhanced production flexibility in wind farm operations. This study examines how sponsors facing credit risk choose between flexible and rigid production policies and determine their expansion strategies. We develop a multiscenario optimal stopping model based on real options to characterize sponsors' decisions regarding production suspension, resumption, or default. Our findings indicate that flexible policies are preferred when credit risk is low, whereas higher credit risk makes rigid policies more advantageous. Enhancing production flexibility expands the range in which flexible policies remain optimal. Moreover, lower credit risk incentivizes earlier investment and expansion. Greater flexibility not only reinforces this effect but also promotes mode switching. Notably, under flexible policies, expansion can dynamically align with price signals and credit risks, whereas under rigid policies it relies solely on price fluctuations. Finally, a case study of China Datang New Energy validates the model's applicability. Robustness checks through comparative statics reveal that higher uncertainty suppresses mode switching but stimulates investment and expansion. These tests consistently confirm that flexible policies enable earlier investment and expansion, smaller capacity scales, and higher returns than rigid policies, regardless of volatility or credit risk levels. Overall, this study provides new managerial insights into balancing production flexibility and credit risk under uncertainty.
{"title":"Operational and Expansion Strategies of Wind Farms Under Uncertainty: The Impact of Credit Risk and Production Flexibility","authors":"Xinyu Wang;Xinya Liu;Shuhua Zhang","doi":"10.1109/TEM.2026.3656529","DOIUrl":"https://doi.org/10.1109/TEM.2026.3656529","url":null,"abstract":"Technological advances have substantially enhanced production flexibility in wind farm operations. This study examines how sponsors facing credit risk choose between flexible and rigid production policies and determine their expansion strategies. We develop a multiscenario optimal stopping model based on real options to characterize sponsors' decisions regarding production suspension, resumption, or default. Our findings indicate that flexible policies are preferred when credit risk is low, whereas higher credit risk makes rigid policies more advantageous. Enhancing production flexibility expands the range in which flexible policies remain optimal. Moreover, lower credit risk incentivizes earlier investment and expansion. Greater flexibility not only reinforces this effect but also promotes mode switching. Notably, under flexible policies, expansion can dynamically align with price signals and credit risks, whereas under rigid policies it relies solely on price fluctuations. Finally, a case study of China Datang New Energy validates the model's applicability. Robustness checks through comparative statics reveal that higher uncertainty suppresses mode switching but stimulates investment and expansion. These tests consistently confirm that flexible policies enable earlier investment and expansion, smaller capacity scales, and higher returns than rigid policies, regardless of volatility or credit risk levels. Overall, this study provides new managerial insights into balancing production flexibility and credit risk under uncertainty.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1512-1527"},"PeriodicalIF":5.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175821","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 : 2026-01-21DOI: 10.1109/TEM.2026.3656422
Siqi Wang;Zhen Li;Jianwei Liu;Xiaofei Zhang;Kee-Hung Lai
Strategically introducing artificial intelligence (AI) chatbots into online health communities (OHCs) to foster user engagement has become increasingly common, but it also creates competitive pressure and replacement risks for professional counselors who make similar prosocial contributions. We investigate how module-targeted AI chatbot deployment affects professional counselors’ prosocial contributions across a focal module (with AI deployment) and another neighbor module (without AI deployment). We developed a theoretical framework by integrating Protection Motivation Theory with the displacement effect, validating our conjectures using a longitudinal dataset from a leading Chinese OHC. Utilizing a difference-in-differences (DID) approach with rigorous robustness checks, we find that AI deployment significantly bolstered counselors’ prosocial contributions in the focal module, while neighbor module activity remained stable. The key mechanism underlying counselors’ heterogeneous responses lies in individual competence rather than economic incentives. Specifically, high-competence counselors exhibited a pronounced bifurcated response: they amplified both the quantity and semantic quality of their contributions in the focal module, while simultaneously retrenching along both dimensions in the neighbor module. Our findings reveal how counselors adapt their prosocial efforts when AI is deployed in a specific module and the displacement effects caused by such asymmetric intervention, providing practical insights for platform managers to deploy module-targeted AI chatbots effectively.
{"title":"Module-Targeted AI Chatbot Deployment and Counselors’ Prosocial Contributions in Online Health Community","authors":"Siqi Wang;Zhen Li;Jianwei Liu;Xiaofei Zhang;Kee-Hung Lai","doi":"10.1109/TEM.2026.3656422","DOIUrl":"https://doi.org/10.1109/TEM.2026.3656422","url":null,"abstract":"Strategically introducing artificial intelligence (AI) chatbots into online health communities (OHCs) to foster user engagement has become increasingly common, but it also creates competitive pressure and replacement risks for professional counselors who make similar prosocial contributions. We investigate how module-targeted AI chatbot deployment affects professional counselors’ prosocial contributions across a focal module (with AI deployment) and another neighbor module (without AI deployment). We developed a theoretical framework by integrating Protection Motivation Theory with the displacement effect, validating our conjectures using a longitudinal dataset from a leading Chinese OHC. Utilizing a difference-in-differences (DID) approach with rigorous robustness checks, we find that AI deployment significantly bolstered counselors’ prosocial contributions in the focal module, while neighbor module activity remained stable. The key mechanism underlying counselors’ heterogeneous responses lies in individual competence rather than economic incentives. Specifically, high-competence counselors exhibited a pronounced bifurcated response: they amplified both the quantity and semantic quality of their contributions in the focal module, while simultaneously retrenching along both dimensions in the neighbor module. Our findings reveal how counselors adapt their prosocial efforts when AI is deployed in a specific module and the displacement effects caused by such asymmetric intervention, providing practical insights for platform managers to deploy module-targeted AI chatbots effectively.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1500-1511"},"PeriodicalIF":5.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175814","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 : 2026-01-20DOI: 10.1109/TEM.2026.3656330
Gongbing Bi;Dang Wang;Pingfan Wang
Product deterioration poses significant challenges to inventory management and profitability. Highlighting the importance of effective promotion strategies, this article investigates two countermeasures for deteriorating goods: price promotion (price discount) and trade credit promotion (credit period extension), analyzing their differential impacts on mitigating value loss. While both strategies alleviate deterioration effects, their cost structures diverge: price promotion directly erodes marginal profit, whereas trade credit promotion incurs cash opportunity cost from deferred payments. Our findings reveal that both price and trade credit promotions can help mitigate the impact of deterioration and enhance the retailer’s profitability with different scopes of application. Specifically, trade credit promotion results in higher retailer profitability when the unit cash opportunity cost falls below a certain threshold; otherwise, price promotion becomes the more favorable strategy. This threshold inversely correlates with the selling price and positively relates to the sensitivity of market demand to the credit period. Furthermore, we find that the more profitable strategy—whether price promotion or trade credit promotion—not only enhances the retailer’s profitability but also improves consumer surplus, thereby creating a win-win outcome. An extended model accounting for consumer indifference to product deterioration reaffirms the distinct impacts of both promotion strategies while validating the robustness of the baseline model. This article offers managerial insights into how retailers choose and implement promotion strategies when selling deteriorating products.
{"title":"Optimal Promotion Strategies for Deteriorating Products: Price Discount Versus Credit Period Extension","authors":"Gongbing Bi;Dang Wang;Pingfan Wang","doi":"10.1109/TEM.2026.3656330","DOIUrl":"https://doi.org/10.1109/TEM.2026.3656330","url":null,"abstract":"Product deterioration poses significant challenges to inventory management and profitability. Highlighting the importance of effective promotion strategies, this article investigates two countermeasures for deteriorating goods: price promotion (price discount) and trade credit promotion (credit period extension), analyzing their differential impacts on mitigating value loss. While both strategies alleviate deterioration effects, their cost structures diverge: price promotion directly erodes marginal profit, whereas trade credit promotion incurs cash opportunity cost from deferred payments. Our findings reveal that both price and trade credit promotions can help mitigate the impact of deterioration and enhance the retailer’s profitability with different scopes of application. Specifically, trade credit promotion results in higher retailer profitability when the unit cash opportunity cost falls below a certain threshold; otherwise, price promotion becomes the more favorable strategy. This threshold inversely correlates with the selling price and positively relates to the sensitivity of market demand to the credit period. Furthermore, we find that the more profitable strategy—whether price promotion or trade credit promotion—not only enhances the retailer’s profitability but also improves consumer surplus, thereby creating a win-win outcome. An extended model accounting for consumer indifference to product deterioration reaffirms the distinct impacts of both promotion strategies while validating the robustness of the baseline model. This article offers managerial insights into how retailers choose and implement promotion strategies when selling deteriorating products.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1602-1618"},"PeriodicalIF":5.2,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175818","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}
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