Pub Date : 2025-12-05DOI: 10.1109/TEM.2025.3640643
Minhao Gu;Peizhi Zhang;Rui Chang;WaiFong Boh;Baofeng Huo
Trade credit is a financing tool used in supply chain management. Blockchain can improve transparency among transaction parties and reduce transaction costs through consensus mechanisms and automation, offering a more efficient solution for managing trade credit. This study investigates how and to what extent blockchain affects trade credit. The empirical analysis is based on data from firms listed on the Shanghai and Shenzhen stock exchanges (A-share market) during the period 2015–2022. The results show that blockchain implementation reduces received trade credit from suppliers, whereas it increases provided trade credit to customers. A series of robustness procedures—including alternative variable constructions, lagged specifications, alternative identification strategies, and placebo-based Monte Carlo simulations—confirm the validity and stability of the empirical findings. This study further investigates the mechanisms of how blockchain implementation affects trade credit. The results show that blockchain implementation further reduces received trade credit from more centralized suppliers. In addition, the results also indicate that more trade credit will be provided to customers with a higher level of demand uncertainty. This study offers a comprehensive view of how firms utilize blockchain to improve trade credit efficiency. Managerial implications based on the research findings are also provided.
{"title":"The Impact of Blockchain Implementation on Received and Provided Trade Credit","authors":"Minhao Gu;Peizhi Zhang;Rui Chang;WaiFong Boh;Baofeng Huo","doi":"10.1109/TEM.2025.3640643","DOIUrl":"https://doi.org/10.1109/TEM.2025.3640643","url":null,"abstract":"Trade credit is a financing tool used in supply chain management. Blockchain can improve transparency among transaction parties and reduce transaction costs through consensus mechanisms and automation, offering a more efficient solution for managing trade credit. This study investigates how and to what extent blockchain affects trade credit. The empirical analysis is based on data from firms listed on the Shanghai and Shenzhen stock exchanges (A-share market) during the period 2015–2022. The results show that blockchain implementation reduces received trade credit from suppliers, whereas it increases provided trade credit to customers. A series of robustness procedures—including alternative variable constructions, lagged specifications, alternative identification strategies, and placebo-based Monte Carlo simulations—confirm the validity and stability of the empirical findings. This study further investigates the mechanisms of how blockchain implementation affects trade credit. The results show that blockchain implementation further reduces received trade credit from more centralized suppliers. In addition, the results also indicate that more trade credit will be provided to customers with a higher level of demand uncertainty. This study offers a comprehensive view of how firms utilize blockchain to improve trade credit efficiency. Managerial implications based on the research findings are also provided.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"467-480"},"PeriodicalIF":5.2,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830766","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 : 2025-12-05DOI: 10.1109/TEM.2025.3640397
Jacques Bughin
This study examines how dynamic capabilities interact with imperfect competition to shape the performance outcomes of corporate digital transformation. Building on an oligopoly model that integrates automation and digital innovation choices, we show analytically that market power and dynamic capabilities act as strategic complements, jointly amplifying the returns on digital investments. Using a global sample of 545 incumbent firms across seven industries, we find strong empirical support for this prediction: transformational capabilities and asymmetric market positions significantly increase the return on digital technologies, especially for early adopters and firms with an innovation-biased strategy. The study demonstrates research rigor by combining a micro-founded structural model with extensive econometric validation, including instrumental-variable estimation, multiple robustness checks, and industry- and geography-adjusted controls. Our results offer new insight into why digital returns are highly skewed across firms and explain why many incumbents experience limited performance gains despite large investments in digital technologies.
{"title":"The Interaction of Market Power and Dynamic Capabilities in Shaping Digital Transformations Success","authors":"Jacques Bughin","doi":"10.1109/TEM.2025.3640397","DOIUrl":"https://doi.org/10.1109/TEM.2025.3640397","url":null,"abstract":"This study examines how dynamic capabilities interact with imperfect competition to shape the performance outcomes of corporate digital transformation. Building on an oligopoly model that integrates automation and digital innovation choices, we show analytically that market power and dynamic capabilities act as strategic complements, jointly amplifying the returns on digital investments. Using a global sample of 545 incumbent firms across seven industries, we find strong empirical support for this prediction: transformational capabilities and asymmetric market positions significantly increase the return on digital technologies, especially for early adopters and firms with an innovation-biased strategy. The study demonstrates research rigor by combining a micro-founded structural model with extensive econometric validation, including instrumental-variable estimation, multiple robustness checks, and industry- and geography-adjusted controls. Our results offer new insight into why digital returns are highly skewed across firms and explain why many incumbents experience limited performance gains despite large investments in digital technologies.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"612-625"},"PeriodicalIF":5.2,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830908","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}
Identifying product obsolescence factors is essential for guiding sustainable design and extending product longevity. Unlike prior studies, this research leverages online consumer reviews to explore product obsolescence factors. First, ChatGPT-4o, an advanced pretrained large language model, is utilized to identify these factors. User-generated content (UGC) time series-based product obsolescence indexes are then defined to quantify each factor's impact, offering a UGC-based complement to earlier methods that depended on expert judgment, supplier input, or survey data. By leveraging real-time customer insights, this approach aligns with Industry 4.0 principles, offering a UGC-based method that can support engineering managers to proactively address product obsolescence. It integrates factors' relative importance, determined through frequency–analytic hierarchy process (Freq-AHP), with their severity impact on consumers, assessed using the robustly optimized bidirectional encoder representations from transformers approach. This is further supported by a robustness check, where small perturbations were applied to sentiment intensities and all indices recalculated, confirming the aggregated obsolescence index remained stable across all product categories. This study focuses on consumer Internet of Things (IoT) devices, an area underexplored in existing literature, analyzing 47 695 online consumer reviews across nine product categories and selecting 4771 online obsolescence-related reviews for detailed analysis. Findings reveal 19 key factors and demonstrate a fundamental shift in obsolescence, indicating that product obsolescence of consumer IoT devices is increasingly driven by adaptability, interoperability, and digital resilience rather than physical durability. These insights demonstrate the potential of the proposed approach to inform product obsolescence mitigation strategies and guide more resilient, user-centered design in IoT ecosystems.
{"title":"A Consumer-Centric Framework for Measuring Product Obsolescence Using User-Generated Content and Large Language Models: Evidence From IoT Devices","authors":"Mohamadreza Azar Nasrabadi;Yvan Beauregard;Amir Ekhlassi","doi":"10.1109/TEM.2025.3640012","DOIUrl":"https://doi.org/10.1109/TEM.2025.3640012","url":null,"abstract":"Identifying product obsolescence factors is essential for guiding sustainable design and extending product longevity. Unlike prior studies, this research leverages online consumer reviews to explore product obsolescence factors. First, ChatGPT-4o, an advanced pretrained large language model, is utilized to identify these factors. User-generated content (UGC) time series-based product obsolescence indexes are then defined to quantify each factor's impact, offering a UGC-based complement to earlier methods that depended on expert judgment, supplier input, or survey data. By leveraging real-time customer insights, this approach aligns with Industry 4.0 principles, offering a UGC-based method that can support engineering managers to proactively address product obsolescence. It integrates factors' relative importance, determined through frequency–analytic hierarchy process (Freq-AHP), with their severity impact on consumers, assessed using the robustly optimized bidirectional encoder representations from transformers approach. This is further supported by a robustness check, where small perturbations were applied to sentiment intensities and all indices recalculated, confirming the aggregated obsolescence index remained stable across all product categories. This study focuses on consumer Internet of Things (IoT) devices, an area underexplored in existing literature, analyzing 47 695 online consumer reviews across nine product categories and selecting 4771 online obsolescence-related reviews for detailed analysis. Findings reveal 19 key factors and demonstrate a fundamental shift in obsolescence, indicating that product obsolescence of consumer IoT devices is increasingly driven by adaptability, interoperability, and digital resilience rather than physical durability. These insights demonstrate the potential of the proposed approach to inform product obsolescence mitigation strategies and guide more resilient, user-centered design in IoT ecosystems.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"448-466"},"PeriodicalIF":5.2,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11278478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-04DOI: 10.1109/TEM.2025.3632967
Thomas Clauss;Chanchai Tangpong;Matheus Franco;Ricarda B. Bouncken
Achieving joint product innovation in buyer–supplier relationships (BSRs) is a critical yet challenging endeavor that requires effective governance. While research has focused on how governance serves as a behavioral mechanism to align incentives and foster knowledge sharing, it has largely overlooked how governance can facilitate the more efficient path of knowledge integration while minimizing costly learning. Using survey data from 348 supplier firms in the sheet metal industry, we find that buyer directives have a positive effect on joint product innovation. We also find that the interaction between buyer directives and relational governance operates indirectly, enhancing joint product innovation by first fostering joint process innovation. This study contributes to BSR governance research in three ways. First, it reframes buyer directives as boundary objects that facilitate knowledge integration rather than as simple behavioral controls. Second, it specifies the role of relational governance in creating the collaborative context necessary for the enactment of these directives. Finally, it identifies joint process innovation as a concrete integrative mechanism linking operational collaboration to product innovation outcomes, challenging the view that they are separate phenomena.
{"title":"Enabling Joint Product Innovation in Buyer–Supplier Relationships: Roles of Buyer Directives, Relational Governance, and Joint Process Innovation","authors":"Thomas Clauss;Chanchai Tangpong;Matheus Franco;Ricarda B. Bouncken","doi":"10.1109/TEM.2025.3632967","DOIUrl":"https://doi.org/10.1109/TEM.2025.3632967","url":null,"abstract":"Achieving joint product innovation in buyer–supplier relationships (BSRs) is a critical yet challenging endeavor that requires effective governance. While research has focused on how governance serves as a behavioral mechanism to align incentives and foster knowledge sharing, it has largely overlooked how governance can facilitate the more efficient path of knowledge integration while minimizing costly learning. Using survey data from 348 supplier firms in the sheet metal industry, we find that buyer directives have a positive effect on joint product innovation. We also find that the interaction between buyer directives and relational governance operates indirectly, enhancing joint product innovation by first fostering joint process innovation. This study contributes to BSR governance research in three ways. First, it reframes buyer directives as boundary objects that facilitate knowledge integration rather than as simple behavioral controls. Second, it specifies the role of relational governance in creating the collaborative context necessary for the enactment of these directives. Finally, it identifies joint process innovation as a concrete integrative mechanism linking operational collaboration to product innovation outcomes, challenging the view that they are separate phenomena.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"558-571"},"PeriodicalIF":5.2,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830918","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 : 2025-12-03DOI: 10.1109/TEM.2025.3639939
Tsung-Sheng Chang;Hung-Yung Hsu
Rising cyber threats have prompted enterprises to prioritize information security and adopt cyber threat intelligence (CTI) platforms to safeguard against cyber threats and crimes and improve their information security. Using the resource-based view (RBV) and CTI capability frameworks, this study identifies and evaluates the critical factors that affect the successful implementation of CTI platforms. A hybrid methodological approach, integrating the fuzzy analytic hierarchy process (Fuzzy AHP) and a combined compromise solution (CoCoSo), was used to assess expert judgments. The findings indicate that practitioners consider Top managers’ support as the most critical factor, followed by an emphasis on institutional innovation. Regarding CTI capabilities, organizations prioritize employees’ abilities to resolve cyber threats, followed by their ability to analyze information security intelligence. This study extends the research scope of RBV and CTI capabilities and provides practical decision-making views. When practitioners understand their organizational resources and defects, along with the critical factors to consider when introducing CTI platforms, it will help them to smoothly improve the security of computers.
{"title":"Critical Resource Factors for Cyber Threat Intelligence Implementation in Enterprises","authors":"Tsung-Sheng Chang;Hung-Yung Hsu","doi":"10.1109/TEM.2025.3639939","DOIUrl":"https://doi.org/10.1109/TEM.2025.3639939","url":null,"abstract":"Rising cyber threats have prompted enterprises to prioritize information security and adopt cyber threat intelligence (CTI) platforms to safeguard against cyber threats and crimes and improve their information security. Using the resource-based view (RBV) and CTI capability frameworks, this study identifies and evaluates the critical factors that affect the successful implementation of CTI platforms. A hybrid methodological approach, integrating the fuzzy analytic hierarchy process (Fuzzy AHP) and a combined compromise solution (CoCoSo), was used to assess expert judgments. The findings indicate that practitioners consider Top managers’ support as the most critical factor, followed by an emphasis on institutional innovation. Regarding CTI capabilities, organizations prioritize employees’ abilities to resolve cyber threats, followed by their ability to analyze information security intelligence. This study extends the research scope of RBV and CTI capabilities and provides practical decision-making views. When practitioners understand their organizational resources and defects, along with the critical factors to consider when introducing CTI platforms, it will help them to smoothly improve the security of computers.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"432-447"},"PeriodicalIF":5.2,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830936","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 : 2025-12-02DOI: 10.1109/TEM.2025.3639355
Hailan Guo;Zhen Shen;Hu Chen;Ming Dong;Katherine Y. Dong
In this article, we aim to explore the complex interactions that surround supply chain risk complexity (SCRC) and its effects on both financial and environmental, social, and governance (ESG) performance in the chip industry. It seeks to demonstrate how SCRC, influenced by supply chain concentration, impacts firm performance metrics. Drawing on resource dependence theory and the resource-based view, this study constructs a panel of 364 Chinese-listed semiconductor firms for 2013–2022 and creates a novel SCRC index using natural language processing. Ordinary least squares, fixed effects, and an event-study specification centered on the 2018 export control shock confirm that the patterns persist after controlling for unobserved heterogeneity and time effects. The analysis reveals a complex relationship wherein increased supply chain concentration heightens SCRC, which in turn has a dual impact: enhancing financial performance while negatively affecting ESG outcomes. Furthermore, SCRC serves as a significant mediator between supply chain concentration and performance metrics, showcasing the important role of risk disclosure in strategic supply chain configurations. The findings provide semiconductor executives with a clear framework: minimize dependence on any single partner, institutionalize comprehensive risk-disclosure practices, implement predictive digital tools, and preserve ESG resources to achieve efficiencies driven by concentration without compromising sustainability credentials.
{"title":"The Impact of Supply Chain Risk Complexity and Concentration on Financial and ESG Performance in China's Semiconductor Industry","authors":"Hailan Guo;Zhen Shen;Hu Chen;Ming Dong;Katherine Y. Dong","doi":"10.1109/TEM.2025.3639355","DOIUrl":"https://doi.org/10.1109/TEM.2025.3639355","url":null,"abstract":"In this article, we aim to explore the complex interactions that surround supply chain risk complexity (SCRC) and its effects on both financial and environmental, social, and governance (ESG) performance in the chip industry. It seeks to demonstrate how SCRC, influenced by supply chain concentration, impacts firm performance metrics. Drawing on resource dependence theory and the resource-based view, this study constructs a panel of 364 Chinese-listed semiconductor firms for 2013–2022 and creates a novel SCRC index using natural language processing. Ordinary least squares, fixed effects, and an event-study specification centered on the 2018 export control shock confirm that the patterns persist after controlling for unobserved heterogeneity and time effects. The analysis reveals a complex relationship wherein increased supply chain concentration heightens SCRC, which in turn has a dual impact: enhancing financial performance while negatively affecting ESG outcomes. Furthermore, SCRC serves as a significant mediator between supply chain concentration and performance metrics, showcasing the important role of risk disclosure in strategic supply chain configurations. The findings provide semiconductor executives with a clear framework: minimize dependence on any single partner, institutionalize comprehensive risk-disclosure practices, implement predictive digital tools, and preserve ESG resources to achieve efficiencies driven by concentration without compromising sustainability credentials.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"390-401"},"PeriodicalIF":5.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830874","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 : 2025-12-02DOI: 10.1109/TEM.2025.3639264
Yu Liu;Manman Wang;Feng Yang
Motivated by technology licensing practices in emerging technology industries with high demand uncertainty, we investigate firms’ production timing decisions and technology licensing strategies in a supply chain consisting of two original equipment manufacturers (OEMs) and a common supplier. Both manufacturers source their key components from the common supplier, and the innovative manufacturer can license its quality-improving technology to the supplier. Considering the demand variability of quality-improving innovation, firms may adopt an ex-post production scheme (PS) to avoid market risk and choose an ex-ante production scheme (AS) to obtain market leadership. Our findings reveal that firms’ production timing and technology licensing decisions depend on the demand variability and the market potential difference. Interestingly, if a low-quality manufacturer implements AS, the innovative manufacturer may benefit from AS under no licensing. However, neither firm will obtain more benefits if both implement AS under technology licensing. When the innovative manufacturer adopts AS and its competitor adopts PS, the technology licensing will hurt the common supplier. Technology licensing makes low-quality OEMs more cautious and prefer PS, while high-quality OEMs are more aggressive and prefer AS. Moreover, the innovative OEM and supplier can reach a technology licensing agreement when the difference in market potential is greater than a small threshold. The intensity of competition among two manufacturers will raise the threshold for technology licensing. The extended model of innovation costs and licensing fees verifies the robustness of production timing decisions and licensing strategy choices. Our study provides novel insights and contributes to the growing literature on technology licensing under demand uncertainty.
{"title":"Production Timing and Technology Licensing Under Competition and Demand Uncertainty","authors":"Yu Liu;Manman Wang;Feng Yang","doi":"10.1109/TEM.2025.3639264","DOIUrl":"https://doi.org/10.1109/TEM.2025.3639264","url":null,"abstract":"Motivated by technology licensing practices in emerging technology industries with high demand uncertainty, we investigate firms’ production timing decisions and technology licensing strategies in a supply chain consisting of two original equipment manufacturers (OEMs) and a common supplier. Both manufacturers source their key components from the common supplier, and the innovative manufacturer can license its quality-improving technology to the supplier. Considering the demand variability of quality-improving innovation, firms may adopt an ex-post production scheme (PS) to avoid market risk and choose an ex-ante production scheme (AS) to obtain market leadership. Our findings reveal that firms’ production timing and technology licensing decisions depend on the demand variability and the market potential difference. Interestingly, if a low-quality manufacturer implements AS, the innovative manufacturer may benefit from AS under no licensing. However, neither firm will obtain more benefits if both implement AS under technology licensing. When the innovative manufacturer adopts AS and its competitor adopts PS, the technology licensing will hurt the common supplier. Technology licensing makes low-quality OEMs more cautious and prefer PS, while high-quality OEMs are more aggressive and prefer AS. Moreover, the innovative OEM and supplier can reach a technology licensing agreement when the difference in market potential is greater than a small threshold. The intensity of competition among two manufacturers will raise the threshold for technology licensing. The extended model of innovation costs and licensing fees verifies the robustness of production timing decisions and licensing strategy choices. Our study provides novel insights and contributes to the growing literature on technology licensing under demand uncertainty.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"342-359"},"PeriodicalIF":5.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830764","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 : 2025-12-01DOI: 10.1109/TEM.2025.3639114
Zhongsheng Hua;Yuxuan You
Data collected from different channels that describe the condition of the same object may differ in their reliability and sampling costs. For example, online sensor tracking data of an object may be less reliable but much cheaper than offline field inspection data. This provides chances of fusing multichannel data to accurately monitor the condition of an object at low costs. In the article, we formulate a model of dynamically fusing easily achieved online data with costly offline sampled data (abbreviated as DFO2). In DFO2, we consider a dynamic decision process where a decision-maker observes online data and then decides whether to acquire a new piece of offline data. Offline data are costly to acquire, but it is accurate and can yield a reward in correcting errors in online data. A nonlinear contextual bandit method is then proposed to estimate the expected reward of offline sampling decisions, and an offline sampling policy is obtained by maximizing the expected reward. Theoretical analysis indicates that DFO2 achieves a sublinear regret bound, which means that the reward of DFO2 asymptotically approaches that of the optimal policy over time. To demonstrate the wide applicability of DFO2, experiments are performed across two distinct domains—healthcare and power systems. Results show that DFO2 has a better performance in trading off sampling cost and information accuracy compared to the benchmarks. Comparative experiments under different conditions also reveal the robustness of the method performance. Overall, this article provides a practical framework for unifying multichannel data to realize cost-effective monitoring.
{"title":"A Cost-Effective Data Sampling Strategy by Unifying Online Data With Offline Data","authors":"Zhongsheng Hua;Yuxuan You","doi":"10.1109/TEM.2025.3639114","DOIUrl":"https://doi.org/10.1109/TEM.2025.3639114","url":null,"abstract":"Data collected from different channels that describe the condition of the same object may differ in their reliability and sampling costs. For example, online sensor tracking data of an object may be less reliable but much cheaper than offline field inspection data. This provides chances of fusing multichannel data to accurately monitor the condition of an object at low costs. In the article, we formulate a model of dynamically fusing easily achieved online data with costly offline sampled data (abbreviated as DFO<sup>2</sup>). In DFO<sup>2</sup>, we consider a dynamic decision process where a decision-maker observes online data and then decides whether to acquire a new piece of offline data. Offline data are costly to acquire, but it is accurate and can yield a reward in correcting errors in online data. A nonlinear contextual bandit method is then proposed to estimate the expected reward of offline sampling decisions, and an offline sampling policy is obtained by maximizing the expected reward. Theoretical analysis indicates that DFO<sup>2</sup> achieves a sublinear regret bound, which means that the reward of DFO<sup>2</sup> asymptotically approaches that of the optimal policy over time. To demonstrate the wide applicability of DFO<sup>2</sup>, experiments are performed across two distinct domains—healthcare and power systems. Results show that DFO<sup>2</sup> has a better performance in trading off sampling cost and information accuracy compared to the benchmarks. Comparative experiments under different conditions also reveal the robustness of the method performance. Overall, this article provides a practical framework for unifying multichannel data to realize cost-effective monitoring.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"527-542"},"PeriodicalIF":5.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830855","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 : 2025-11-27DOI: 10.1109/TEM.2025.3638123
Perboli Guido;Simionato Nadia;Vandoni Chiara
This article investigates how Web3 technologies, such as blockchain, NFTs, and the metaverse, can drive business model innovation by enabling new forms of value creation, delivery, and capture. While the strategic potential of Web3 has been widely discussed, there remains a lack of operational tools to guide its implementation in real-world business contexts. To address this gap, we introduce the Web3 value exploitation design model, a step-by-step framework grounded in the GUEST methodology. The model is designed to support engineering managers in assessing Web3 readiness, aligning stakeholders, and developing decentralized business models. The framework is empirically validated through a real-world case study in the agrifood sector, offering actionable insights into how organizations can leverage Web3 to transition from centralized to decentralized, participatory ecosystems. The study contributes both theoretically and practically by bridging the gap between conceptual exploration and structured application of Web3 in business transformation.
{"title":"A Replicable Framework to Drive Business Model Innovation Enabled by Web3: A Case Study in the Agrifood Sector","authors":"Perboli Guido;Simionato Nadia;Vandoni Chiara","doi":"10.1109/TEM.2025.3638123","DOIUrl":"https://doi.org/10.1109/TEM.2025.3638123","url":null,"abstract":"This article investigates how Web3 technologies, such as blockchain, NFTs, and the metaverse, can drive business model innovation by enabling new forms of value creation, delivery, and capture. While the strategic potential of Web3 has been widely discussed, there remains a lack of operational tools to guide its implementation in real-world business contexts. To address this gap, we introduce the Web3 value exploitation design model, a step-by-step framework grounded in the GUEST methodology. The model is designed to support engineering managers in assessing Web3 readiness, aligning stakeholders, and developing decentralized business models. The framework is empirically validated through a real-world case study in the agrifood sector, offering actionable insights into how organizations can leverage Web3 to transition from centralized to decentralized, participatory ecosystems. The study contributes both theoretically and practically by bridging the gap between conceptual exploration and structured application of Web3 in business transformation.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"818-831"},"PeriodicalIF":5.2,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11270235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1109/TEM.2025.3637530
Grazielle Fatima Gomes Teixeira;Anderson Luis Szejka;Osiris Canciglieri Júnior
This article presents a semi-systematic literature review of innovation helix models (triple, quadruple, and quintuple), examining their conceptual evolution, empirical applications, and emerging trends. The mixed-methods approach combining bibliometric mapping and thematic analysis identified five core domains: actor interaction, framework development, entrepreneurship, efficiency and effectiveness, and historical perspectives. The findings delineate the state of the art, while simultaneously exposing underlying divergences and conceptual lacunae. These gaps are articulated through a set of prospective research questions, systematically organized by model perspectives, actors, and salient characteristics. Findings confirm the predominance of the triple helix, while highlighting theoretical limitations that have motivated the development of higher order models. Although the quadruple and quintuple helices introduce societal and ecological dimensions, their operationalization remains limited. On this basis, the study advances a structured synthesis designed not only to orient subsequent scholarly inquiry but also to enhance the practical deployment of innovation helix models in engineering and technology management.
{"title":"Innovation Helix Models: Theory, Practice, and Emerging Trends","authors":"Grazielle Fatima Gomes Teixeira;Anderson Luis Szejka;Osiris Canciglieri Júnior","doi":"10.1109/TEM.2025.3637530","DOIUrl":"https://doi.org/10.1109/TEM.2025.3637530","url":null,"abstract":"This article presents a semi-systematic literature review of innovation helix models (triple, quadruple, and quintuple), examining their conceptual evolution, empirical applications, and emerging trends. The mixed-methods approach combining bibliometric mapping and thematic analysis identified five core domains: actor interaction, framework development, entrepreneurship, efficiency and effectiveness, and historical perspectives. The findings delineate the state of the art, while simultaneously exposing underlying divergences and conceptual lacunae. These gaps are articulated through a set of prospective research questions, systematically organized by model perspectives, actors, and salient characteristics. Findings confirm the predominance of the triple helix, while highlighting theoretical limitations that have motivated the development of higher order models. Although the quadruple and quintuple helices introduce societal and ecological dimensions, their operationalization remains limited. On this basis, the study advances a structured synthesis designed not only to orient subsequent scholarly inquiry but also to enhance the practical deployment of innovation helix models in engineering and technology management.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"374-389"},"PeriodicalIF":5.2,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830801","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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