Pub Date : 2025-02-13DOI: 10.1109/TEM.2025.3535771
Yujie Ma;Xin Xia;Jie Guo;Chen Zhang
Green laws make original equipment manufacturers responsible for full product lifecycle management, emphasizing remanufacturing. Research shows that remanufacturing technologies are complex and costly. Without product designs tailored for remanufacturing, achieving efficiency becomes a significant challenge. Therefore, it is imperative to consider remanufacturing during the initial product design stage. Existing literature primarily proposes either integrated or two-stage optimization methods for the decision-making of manufacturers and remanufacturers. However, they fail to describe the tradeoffs between the decisions of the two stakeholders. This article proposes a leader–follower interactive decision-making framework based on a Stackelberg game to explore the interaction between product design and remanufacturing and construct a bilevel interactive optimization (BIO) model. To solve it, we further develop a novel bilevel deep reinforcement learning framework, which can be applied to general BIO problems, particularly with multidimensional discrete decision variables and complex model constraints. We validate the proposed model and algorithm through case studies on laptops and electric vehicles, supported by comprehensive comparative experiments. Our results show that the product design considering the remanufacturing process improves manufacturers' utility per unit cost while reducing remanufacturers' costs.
{"title":"A Deep Reinforcement Learning Method Solving Bilevel Optimization for Product Design Considering Remanufacturing","authors":"Yujie Ma;Xin Xia;Jie Guo;Chen Zhang","doi":"10.1109/TEM.2025.3535771","DOIUrl":"https://doi.org/10.1109/TEM.2025.3535771","url":null,"abstract":"Green laws make original equipment manufacturers responsible for full product lifecycle management, emphasizing remanufacturing. Research shows that remanufacturing technologies are complex and costly. Without product designs tailored for remanufacturing, achieving efficiency becomes a significant challenge. Therefore, it is imperative to consider remanufacturing during the initial product design stage. Existing literature primarily proposes either integrated or two-stage optimization methods for the decision-making of manufacturers and remanufacturers. However, they fail to describe the tradeoffs between the decisions of the two stakeholders. This article proposes a leader–follower interactive decision-making framework based on a Stackelberg game to explore the interaction between product design and remanufacturing and construct a bilevel interactive optimization (BIO) model. To solve it, we further develop a novel bilevel deep reinforcement learning framework, which can be applied to general BIO problems, particularly with multidimensional discrete decision variables and complex model constraints. We validate the proposed model and algorithm through case studies on laptops and electric vehicles, supported by comprehensive comparative experiments. Our results show that the product design considering the remanufacturing process improves manufacturers' utility per unit cost while reducing remanufacturers' costs.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"573-590"},"PeriodicalIF":4.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667256","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}
Additive manufacturing (AM) has emerged as a promising solution for spare parts management. Given the possibility of producing spare parts close to the point of use, the literature generally asserts that decentralized AM production is more environmentally friendly than centralized AM production. However, when asserting this, the literature overlooks AM's high energy intensity and variable CO2,eq emissions from electricity generation in different countries. The current study addresses this problem by analyzing when centralized AM production is environmentally preferable to decentralized AM production, taking a lifecycle perspective. A mathematical model quantifies CO2,eq emissions for both strategies and determines which is environmentally preferable, and a decision tree analysis is used to develop a decision tree that suggests when centralized AM production is environmentally preferable. Interestingly, our results contradict the current literature, showing how centralized AM production can be a more environmentally friendly strategy than decentralized AM production, especially in countries with low CO2,eq emissions. Adopting centralized AM production when preferable would result in significant reductions of CO2,eq emissions that, considering the current carbon reduction schemes recently introduced, would lead to substantial economic savings (even up to 3000 USD/year per spare part). Moreover, considering future trends in sustainable energy sources and AM technology advancements, this study explores how the preferable AM production strategy might evolve, showing that this does not greatly affect the convenience of centralized AM production. Finally, a practical application of the decision tree in two case studies demonstrates its utility for two companies and the potential savings achievable.
{"title":"Additive Manufacturing for Spare Parts Management: Is Decentralized Production Always Environmentally Preferable?","authors":"Mirco Peron;Luigi Panza;Enes Demiralay;Srinivas Talluri","doi":"10.1109/TEM.2025.3540938","DOIUrl":"https://doi.org/10.1109/TEM.2025.3540938","url":null,"abstract":"Additive manufacturing (AM) has emerged as a promising solution for spare parts management. Given the possibility of producing spare parts close to the point of use, the literature generally asserts that decentralized AM production is more environmentally friendly than centralized AM production. However, when asserting this, the literature overlooks AM's high energy intensity and variable CO<sub>2,eq</sub> emissions from electricity generation in different countries. The current study addresses this problem by analyzing when centralized AM production is environmentally preferable to decentralized AM production, taking a lifecycle perspective. A mathematical model quantifies CO<sub>2,eq</sub> emissions for both strategies and determines which is environmentally preferable, and a decision tree analysis is used to develop a decision tree that suggests when centralized AM production is environmentally preferable. Interestingly, our results contradict the current literature, showing how centralized AM production can be a more environmentally friendly strategy than decentralized AM production, especially in countries with low CO<sub>2,eq</sub> emissions. Adopting centralized AM production when preferable would result in significant reductions of CO<sub>2,eq</sub> emissions that, considering the current carbon reduction schemes recently introduced, would lead to substantial economic savings (even up to 3000 USD/year per spare part). Moreover, considering future trends in sustainable energy sources and AM technology advancements, this study explores how the preferable AM production strategy might evolve, showing that this does not greatly affect the convenience of centralized AM production. Finally, a practical application of the decision tree in two case studies demonstrates its utility for two companies and the potential savings achievable.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"634-650"},"PeriodicalIF":4.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667195","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 : 2025-02-10DOI: 10.1109/TEM.2025.3540270
Bin Xue;Kexin Chang;Yufeng Fan;Xingbin Chen;Tae Wan Kim;Bingsheng Liu
Uncertainty management in multidisciplinary decision making (MDM) involving stakeholders with discipline-specific expertise is imperative for the operations of developing urban infrastructure projects with multidimensional sustainability goals. Preference uncertainty and outcome uncertainty must be addressed simultaneously for theorizing and modeling in such MDM processes. Thus, in this article, we formalize an integrated MDM (iMDM) system to consistently mitigate preference uncertainty in decision alternative evaluation and expeditiously manage outcome uncertainty in decision alternative selection. Unlike the existing decision-making methods that often overlook different uncertainty characteristics in multidisciplinary operations management, the proposed system accounts for both uncertainties by specified information representation and integrated information optimization to enlarge decision spaces. Empirical evaluations in three real-world scenarios indicate that the iMDM system can mitigate and manage uncertainty to derive distinguishable alternative rankings and to generate optimized Pareto alternative sets. We further validate the effectiveness of the system using Charrette tests by quantifying the consistency and expeditiousness of both managing uncertainty and deriving desirable decision alternatives. Our contributions build upon the theoretical foundation of MDM under uncertainty and extend sustainable operations management science by clarifying decision information rationales from an uncertainty management perspective. Practically, findings benefit infrastructure operations’ managers and urban planners in making sustainability decisions in visualized, integrated, and automated manners.
{"title":"An Integrated Framework of Multidisciplinary Decision Making Under Uncertainty for Sustainable Infrastructure Development","authors":"Bin Xue;Kexin Chang;Yufeng Fan;Xingbin Chen;Tae Wan Kim;Bingsheng Liu","doi":"10.1109/TEM.2025.3540270","DOIUrl":"https://doi.org/10.1109/TEM.2025.3540270","url":null,"abstract":"Uncertainty management in multidisciplinary decision making (MDM) involving stakeholders with discipline-specific expertise is imperative for the operations of developing urban infrastructure projects with multidimensional sustainability goals. Preference uncertainty and outcome uncertainty must be addressed simultaneously for theorizing and modeling in such MDM processes. Thus, in this article, we formalize an integrated MDM (iMDM) system to consistently mitigate preference uncertainty in decision alternative evaluation and expeditiously manage outcome uncertainty in decision alternative selection. Unlike the existing decision-making methods that often overlook different uncertainty characteristics in multidisciplinary operations management, the proposed system accounts for both uncertainties by specified information representation and integrated information optimization to enlarge decision spaces. Empirical evaluations in three real-world scenarios indicate that the iMDM system can mitigate and manage uncertainty to derive distinguishable alternative rankings and to generate optimized Pareto alternative sets. We further validate the effectiveness of the system using Charrette tests by quantifying the consistency and expeditiousness of both managing uncertainty and deriving desirable decision alternatives. Our contributions build upon the theoretical foundation of MDM under uncertainty and extend sustainable operations management science by clarifying decision information rationales from an uncertainty management perspective. Practically, findings benefit infrastructure operations’ managers and urban planners in making sustainability decisions in visualized, integrated, and automated manners.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"751-767"},"PeriodicalIF":4.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667573","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 : 2025-02-07DOI: 10.1109/TEM.2025.3538913
Sebastian Kortmann;Barbara A. Bliss;Carsten Zimmermann;Josh Della Vedova
Reverse innovation is a growing area of interest in the academic literature and managerial practice. This “reversal” of innovation originates in the observation that products or services are sometimes first ideated, developed, prototyped, or adopted in emerging economies before being introduced to advanced economies. Prior research argues that adopting reverse innovation also heralds major organizational and global supply chain challenges and calls for more research into its antecedents and structures. Building on structural equation modeling and qualitative comparative analyses (fsQCA), we examine important antecedents and configurations for reverse innovation. Our study uses executive-level, cross-country data to emphasize the preceding role of ambidextrous supply chain strategies for value chain cocreation that drive reverse innovation.
{"title":"Fostering Reverse Innovation With Value Chain Cocreation","authors":"Sebastian Kortmann;Barbara A. Bliss;Carsten Zimmermann;Josh Della Vedova","doi":"10.1109/TEM.2025.3538913","DOIUrl":"https://doi.org/10.1109/TEM.2025.3538913","url":null,"abstract":"Reverse innovation is a growing area of interest in the academic literature and managerial practice. This “reversal” of innovation originates in the observation that products or services are sometimes first ideated, developed, prototyped, or adopted in emerging economies before being introduced to advanced economies. Prior research argues that adopting reverse innovation also heralds major organizational and global supply chain challenges and calls for more research into its antecedents and structures. Building on structural equation modeling and qualitative comparative analyses (fsQCA), we examine important antecedents and configurations for reverse innovation. Our study uses executive-level, cross-country data to emphasize the preceding role of ambidextrous supply chain strategies for value chain cocreation that drive reverse innovation.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"768-783"},"PeriodicalIF":4.6,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667433","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 : 2025-02-06DOI: 10.1109/TEM.2025.3539799
{"title":"2024 Index IEEE Transactions on Engineering Management Vol. 71","authors":"","doi":"10.1109/TEM.2025.3539799","DOIUrl":"https://doi.org/10.1109/TEM.2025.3539799","url":null,"abstract":"","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15595-15792"},"PeriodicalIF":4.6,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10877711","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143361066","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 : 2025-02-05DOI: 10.1109/TEM.2025.3538945
Tong Su;Boqiang Lin
Although green bonds are rapidly growing to be a mature financing tool, the debate over whether there are benefits to be gained by issuers’ stocks has yet to be resolved, especially in the emerging market context. Issuing green bonds, as a financing procedure targeted to green engineering projects and demonstrating the issuers’ environmentally friendly attitude, does and how does it affect the issuers’ stock prices, liquidity, and risk? We address this issue by paying attention to the Chinese green bond issuance events. Utilizing the event study method, research shows that investors react positively to green bond issuance events. However, this reaction is only sensitive to green bond listing events, but not to announcements. Investor responses can be reflected in the abnormal changes in stock prices and liquidity. Both the stock systematic risk and idiosyncratic risk show little change after firms issue green bonds, which illustrates that green bond issuance cannot shape the inherent investors’ value judgments on issuer companies, thereby only producing temporary impacts. This study suggests that the green premium of corporate stocks induced by green bond issuance events may be sourced from investors’ optimistic predictions about green transformation, rather than investors’ subjective willingness to promote environmental sustainability.
{"title":"Modeling Investor Responses to Green Bond Issuance: Multidimensional Perspectives and Evidence From China","authors":"Tong Su;Boqiang Lin","doi":"10.1109/TEM.2025.3538945","DOIUrl":"https://doi.org/10.1109/TEM.2025.3538945","url":null,"abstract":"Although green bonds are rapidly growing to be a mature financing tool, the debate over whether there are benefits to be gained by issuers’ stocks has yet to be resolved, especially in the emerging market context. Issuing green bonds, as a financing procedure targeted to green engineering projects and demonstrating the issuers’ environmentally friendly attitude, does and how does it affect the issuers’ stock prices, liquidity, and risk? We address this issue by paying attention to the Chinese green bond issuance events. Utilizing the event study method, research shows that investors react positively to green bond issuance events. However, this reaction is only sensitive to green bond listing events, but not to announcements. Investor responses can be reflected in the abnormal changes in stock prices and liquidity. Both the stock systematic risk and idiosyncratic risk show little change after firms issue green bonds, which illustrates that green bond issuance cannot shape the inherent investors’ value judgments on issuer companies, thereby only producing temporary impacts. This study suggests that the green premium of corporate stocks induced by green bond issuance events may be sourced from investors’ optimistic predictions about green transformation, rather than investors’ subjective willingness to promote environmental sustainability.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"651-663"},"PeriodicalIF":4.6,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667532","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 : 2025-02-04DOI: 10.1109/TEM.2025.3538586
Xin Zhao;Zhengwei Li;Yifeng Liu
The real-time and extensive interactive interfaces of social media platforms have reshaped the internal and external knowledge synergy modes of enterprises, bringing many opportunities for enterprises to overcome inertia and realize breakthrough innovation. Introducing the organizational inertia perspective, in this article, we explore the differentiated mechanisms of two social media affordances for breakthrough innovation in enterprises. The results show that internal synergy-oriented social media use (ISM) promotes breakthrough innovation by reducing routine rigidity. Meanwhile, external interaction-oriented social media use (ESM) enhances breakthrough innovation by overcoming resource rigidity. In addition, internal entrepreneurial orientation and external competitive pressure play a moderating role. The higher the entrepreneurial orientation is, the greater the negative effect of ISM on routine rigidity, and the greater the negative effect of ESM on resource rigidity. The higher the competitive pressure is, the less negative the effect of ISM on routine rigidity and the less negative the effect of ESM on resource rigidity. This study extends the existing literature on the nexus between social media use and breakthrough innovation through the lens of organizational inertia. Furthermore, by elucidating the underlying pathways and contingent factors, this research offers a guidance for enterprises to optimize their social media technologies.
{"title":"Outward and Inward Communication: A Study on the Driving Mechanism of Social Media Use for Breakthrough Innovation","authors":"Xin Zhao;Zhengwei Li;Yifeng Liu","doi":"10.1109/TEM.2025.3538586","DOIUrl":"https://doi.org/10.1109/TEM.2025.3538586","url":null,"abstract":"The real-time and extensive interactive interfaces of social media platforms have reshaped the internal and external knowledge synergy modes of enterprises, bringing many opportunities for enterprises to overcome inertia and realize breakthrough innovation. Introducing the organizational inertia perspective, in this article, we explore the differentiated mechanisms of two social media affordances for breakthrough innovation in enterprises. The results show that internal synergy-oriented social media use (ISM) promotes breakthrough innovation by reducing routine rigidity. Meanwhile, external interaction-oriented social media use (ESM) enhances breakthrough innovation by overcoming resource rigidity. In addition, internal entrepreneurial orientation and external competitive pressure play a moderating role. The higher the entrepreneurial orientation is, the greater the negative effect of ISM on routine rigidity, and the greater the negative effect of ESM on resource rigidity. The higher the competitive pressure is, the less negative the effect of ISM on routine rigidity and the less negative the effect of ESM on resource rigidity. This study extends the existing literature on the nexus between social media use and breakthrough innovation through the lens of organizational inertia. Furthermore, by elucidating the underlying pathways and contingent factors, this research offers a guidance for enterprises to optimize their social media technologies.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"815-826"},"PeriodicalIF":4.6,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621886","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}
Previous studies related to the blood supply chain under blockchain technology have concentrated solely on the managerial role of blockchain technology in this chain, and no systematic examination has been conducted using quantitative modeling methods. In this article, we focus on developing a blood supply chain based on blockchain technology using a simulation–optimization approach that integrates optimization techniques into simulation modeling and analysis for the first time. In the system dynamics approach, by examining factors, such as service quality, and social aspects that impact donors’ behavior, the main decisions, including the total amount of platelets that are distributed to all hospitals and the number of donors, are simulated under blockchain technology. Various policies are explored to evaluate their effect on the blood supply and demand. Then, this study introduces a biobjective mathematical model utilizing data envelopment analysis (DEA) to optimize the fair distribution of platelets to hospitals based on their efficiency. The outputs of the dynamics model (total platelets distributed to hospitals) and the DEA model (efficiency of selected hospitals) are entered into the biobjective model as parameters. The integration of blockchain technology allows managers to improve traceability at every stage, and the system with blockchain technology increases donor participation by 6%, 3%, and 12%.
以往与区块链技术下的血液供应链相关的研究仅集中于区块链技术在该链条中的管理作用，尚未使用定量建模方法进行系统研究。本文采用仿真优化方法，首次将优化技术融入仿真建模和分析中，重点研究基于区块链技术的血液供应链的发展。在系统动力学方法中，通过研究影响献血者行为的服务质量和社会方面等因素，在区块链技术下模拟了主要决策，包括分配给所有医院的血小板总量和献血者数量。探讨了各种政策，以评估其对血液供求的影响。然后，本研究引入了一个利用数据包络分析（DEA）的生物目标数学模型，以优化基于效率的医院血小板公平分配。动态模型的输出（分配给医院的血小板总量）和 DEA 模型的输出（选定医院的效率）作为参数输入生物目标模型。区块链技术的集成使管理者能够提高每个阶段的可追溯性，采用区块链技术的系统使捐赠者的参与率分别提高了 6%、3% 和 12%。
{"title":"Impact of Blockchain Technology on Social Aspects of Blood Supply Chain: A Simulation–Optimization Approach","authors":"Pegah Norouzian-Maleki;Seyyed-Mahdi Hosseini-Motlagh;Saeed Yaghoubi","doi":"10.1109/TEM.2025.3535815","DOIUrl":"https://doi.org/10.1109/TEM.2025.3535815","url":null,"abstract":"Previous studies related to the blood supply chain under blockchain technology have concentrated solely on the managerial role of blockchain technology in this chain, and no systematic examination has been conducted using quantitative modeling methods. In this article, we focus on developing a blood supply chain based on blockchain technology using a simulation–optimization approach that integrates optimization techniques into simulation modeling and analysis for the first time. In the system dynamics approach, by examining factors, such as service quality, and social aspects that impact donors’ behavior, the main decisions, including the total amount of platelets that are distributed to all hospitals and the number of donors, are simulated under blockchain technology. Various policies are explored to evaluate their effect on the blood supply and demand. Then, this study introduces a biobjective mathematical model utilizing data envelopment analysis (DEA) to optimize the fair distribution of platelets to hospitals based on their efficiency. The outputs of the dynamics model (total platelets distributed to hospitals) and the DEA model (efficiency of selected hospitals) are entered into the biobjective model as parameters. The integration of blockchain technology allows managers to improve traceability at every stage, and the system with blockchain technology increases donor participation by 6%, 3%, and 12%.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"591-603"},"PeriodicalIF":4.6,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667531","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 : 2025-01-27DOI: 10.1109/TEM.2025.3534088
Ali B. Mahmoud;V Kumar;Stavroula Spyropoulou
In an era where generative AI (GenAI) is reshaping industries, public understanding of this phenomenon remains limited. This study addresses this gap by analyzing public beliefs about GenAI using the Technology Acceptance Model and Diffusion of Innovations Theory as frameworks. We adopted a big-data approach, utilizing machine-learning techniques to analyze 21,817 public comments extracted from an initial set of 32,707 on 44 YouTube videos discussing GenAI. Our investigation surfaced six pivotal themes: concerns over job and economic impacts, GenAI's potential to revolutionize problem-solving, its perceived shortcomings in creativity and emotional intelligence, the proliferation of misinformation, existential risks, and privacy decay. Emotion analysis showed that negative emotions dominated at 58.46%, including anger (22.85%) and disgust (17.26%). Sentiment analysis echoed this negativity, with 70% negative. The triangulation of thematic, emotional, and sentiment analyses highlighted a polarized public stance: recognition of GenAI's transformative potential is tempered by significant concerns about its implications. The findings offer actionable insights for engineering managers and policymakers. Strategies such as awareness-building, transparency, public engagement, balanced communication, governance, and human-centered development can address polarization and build trust. Ongoing research into public opinion remains essential for aligning technological advancements with societal expectations and acceptance.
{"title":"Identifying the Public's Beliefs About Generative Artificial Intelligence: A Big Data Approach","authors":"Ali B. Mahmoud;V Kumar;Stavroula Spyropoulou","doi":"10.1109/TEM.2025.3534088","DOIUrl":"https://doi.org/10.1109/TEM.2025.3534088","url":null,"abstract":"In an era where generative AI (GenAI) is reshaping industries, public understanding of this phenomenon remains limited. This study addresses this gap by analyzing public beliefs about GenAI using the Technology Acceptance Model and Diffusion of Innovations Theory as frameworks. We adopted a big-data approach, utilizing machine-learning techniques to analyze 21,817 public comments extracted from an initial set of 32,707 on 44 YouTube videos discussing GenAI. Our investigation surfaced six pivotal themes: concerns over job and economic impacts, GenAI's potential to revolutionize problem-solving, its perceived shortcomings in creativity and emotional intelligence, the proliferation of misinformation, existential risks, and privacy decay. Emotion analysis showed that negative emotions dominated at 58.46%, including anger (22.85%) and disgust (17.26%). Sentiment analysis echoed this negativity, with 70% negative. The triangulation of thematic, emotional, and sentiment analyses highlighted a polarized public stance: recognition of GenAI's transformative potential is tempered by significant concerns about its implications. The findings offer actionable insights for engineering managers and policymakers. Strategies such as awareness-building, transparency, public engagement, balanced communication, governance, and human-centered development can address polarization and build trust. Ongoing research into public opinion remains essential for aligning technological advancements with societal expectations and acceptance.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"827-841"},"PeriodicalIF":4.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667254","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 : 2025-01-27DOI: 10.1109/TEM.2025.3534433
Shan Yin;Jun Lin
Digital platform markets are emerging rapidly with technological innovation, creating new market opportunities and unique challenges. In response, platforms in such markets compete aggressively through high subsidies for market dominance, leveraging network effects to achieve success. We examine such aggressive subsidy wars between new competitors and dominant incumbents, where the one that first runs out of funds risks market expulsion or marginalization. Our analysis incorporates consumer heterogeneity in network effects to evaluate subsidy strategies from a cost-effectiveness perspective. That is digital platforms, whether serve as suppliers or channels in platform-based supply chains, optimize either per acquisition cost or total subsidy expenditure. Our findings reveal that it is optimal for the dominant platform to protect its market dominance when the competitor's market share reaches a certain level, varying in distinct competitive contexts. Specifically, for channel platforms connecting buyers and suppliers, subsidy allocation must be balanced between user groups. We find that new competitors should typically subsidize the side with lower market share, while dominant platforms maintain equal market shares on both sides by adjusting subsidies in most cases. Interestingly, our findings demonstrate that a dominator's larger market shares cannot guarantee its competitive advantage in subsidy wars, which is influenced by the factors such as cost structure, competitor's financial capabilities, network effect strength, and product differentiation. We also identify critical conditions for new competitors to successfully win market dominance through initiating subsidy wars, while offering strategic guidance for dominant incumbents to defend their positions.
{"title":"Subsidy Wars for Market Dominance in Emerging Digital Platform Markets","authors":"Shan Yin;Jun Lin","doi":"10.1109/TEM.2025.3534433","DOIUrl":"https://doi.org/10.1109/TEM.2025.3534433","url":null,"abstract":"Digital platform markets are emerging rapidly with technological innovation, creating new market opportunities and unique challenges. In response, platforms in such markets compete aggressively through high subsidies for market dominance, leveraging network effects to achieve success. We examine such aggressive subsidy wars between new competitors and dominant incumbents, where the one that first runs out of funds risks market expulsion or marginalization. Our analysis incorporates consumer heterogeneity in network effects to evaluate subsidy strategies from a cost-effectiveness perspective. That is digital platforms, whether serve as suppliers or channels in platform-based supply chains, optimize either per acquisition cost or total subsidy expenditure. Our findings reveal that it is optimal for the dominant platform to protect its market dominance when the competitor's market share reaches a certain level, varying in distinct competitive contexts. Specifically, for channel platforms connecting buyers and suppliers, subsidy allocation must be balanced between user groups. We find that new competitors should typically subsidize the side with lower market share, while dominant platforms maintain equal market shares on both sides by adjusting subsidies in most cases. Interestingly, our findings demonstrate that a dominator's larger market shares cannot guarantee its competitive advantage in subsidy wars, which is influenced by the factors such as cost structure, competitor's financial capabilities, network effect strength, and product differentiation. We also identify critical conditions for new competitors to successfully win market dominance through initiating subsidy wars, while offering strategic guidance for dominant incumbents to defend their positions.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"689-702"},"PeriodicalIF":4.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667255","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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