Pub Date : 2026-04-01Epub Date: 2026-01-14DOI: 10.1016/j.techfore.2026.124535
Isaac Ahakwa , Yi Xu , Evelyn Agba Tackie
Environmental degradation remains a critical challenge for resource-rich economies, where different forms of natural resources may exert heterogeneous environmental effects. This study evaluates how disaggregated natural resources, namely forest, oil, minerals, and natural gas, affect environmental degradation in Ghana, while assessing the moderating role of environmental taxes. Using a dynamic ARDL simulation approach, the analysis reveals that forest resources reduce environmental degradation, whereas oil, mineral, and natural gas resources intensify environmental degradation. Environmental taxes are found to mitigate the adverse environmental impacts associated with oil and mineral resource extraction, but are ineffective in offsetting degradation linked to natural gas and forest resources. These findings demonstrate that the environmental effects of resource exploitation and taxation are highly resource-specific, highlighting the heterogeneous dynamics between natural resources and environmental degradation.
{"title":"The role of environmental taxes in promoting sustainable utilization of disaggregated natural resources toward global greening: A novel dynamic ARDL simulation approach","authors":"Isaac Ahakwa , Yi Xu , Evelyn Agba Tackie","doi":"10.1016/j.techfore.2026.124535","DOIUrl":"10.1016/j.techfore.2026.124535","url":null,"abstract":"<div><div>Environmental degradation remains a critical challenge for resource-rich economies, where different forms of natural resources may exert heterogeneous environmental effects. This study evaluates how disaggregated natural resources, namely forest, oil, minerals, and natural gas, affect environmental degradation in Ghana, while assessing the moderating role of environmental taxes. Using a dynamic ARDL simulation approach, the analysis reveals that forest resources reduce environmental degradation, whereas oil, mineral, and natural gas resources intensify environmental degradation. Environmental taxes are found to mitigate the adverse environmental impacts associated with oil and mineral resource extraction, but are ineffective in offsetting degradation linked to natural gas and forest resources. These findings demonstrate that the environmental effects of resource exploitation and taxation are highly resource-specific, highlighting the heterogeneous dynamics between natural resources and environmental degradation.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124535"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-26DOI: 10.1016/j.techfore.2026.124550
Wanggi Jaung
As a general-purpose technology, artificial intelligence (AI) is increasingly shaping environmental outcomes, yet its alignment with environmental values remains unclear. We assess this alignment by comparing environmental valuations from three open-source AI models (Gemma 2, Llama 3.1, and Mistral) with those of human stakeholders. Using choice experiment studies from 21 countries, we drew on estimates of human marginal willingness to pay (MWTP) for environmental attributes and replicated the same designs with the AI models. Across countries and attributes, the models assigned consistently higher MWTP than humans, with larger gaps in Western countries and for non-use values such as existence and bequest values. These results suggest that prevailing human values may be an insufficient benchmark for evaluating AI alignment, even as adopting more stringent AI-driven environmental standards raises practical and ethical concerns. Differences across models further indicate that a diverse AI model ecosystem could support pluralistic rather than homogenized environmental values. Together, these findings provide a quantitative basis for understanding AI–environment value alignment and for designing environmentally responsible AI systems.
{"title":"Does AI value the environment? Evaluation of AI value alignment","authors":"Wanggi Jaung","doi":"10.1016/j.techfore.2026.124550","DOIUrl":"10.1016/j.techfore.2026.124550","url":null,"abstract":"<div><div>As a general-purpose technology, artificial intelligence (AI) is increasingly shaping environmental outcomes, yet its alignment with environmental values remains unclear. We assess this alignment by comparing environmental valuations from three open-source AI models (Gemma 2, Llama 3.1, and Mistral) with those of human stakeholders. Using choice experiment studies from 21 countries, we drew on estimates of human marginal willingness to pay (MWTP) for environmental attributes and replicated the same designs with the AI models. Across countries and attributes, the models assigned consistently higher MWTP than humans, with larger gaps in Western countries and for non-use values such as existence and bequest values. These results suggest that prevailing human values may be an insufficient benchmark for evaluating AI alignment, even as adopting more stringent AI-driven environmental standards raises practical and ethical concerns. Differences across models further indicate that a diverse AI model ecosystem could support pluralistic rather than homogenized environmental values. Together, these findings provide a quantitative basis for understanding AI–environment value alignment and for designing environmentally responsible AI systems.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124550"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-19DOI: 10.1016/j.techfore.2026.124538
Pankaj C. Patel
Drawing on transaction cost economics and organizational information processing theory, we challenge the espoused benefits of AI in servitization by demonstrating that stock market reactions to service technology patents with high AI scores are negative. In a sample of 1306 service technology patents and 758,143 non-service technology patents from 3899 manufacturing firms (1980–2020), we find that idiosyncratic volatility mitigates this negative reaction, while tangibility shows no such effect. Decade-wise analysis reveals effects are significant only in the 2010s and 2020s, suggesting evolving market perceptions of AI-driven servitization. Results hold across matched-pair sampling, non-linear effects testing, fixed-effects individual slopes, and alternative moderator analyses. This study cautions against assuming short-term market value of AI service innovations in manufacturing.
{"title":"Navigating the gambit: Unfavorable market responses to AI-based service patents in manufacturing firms","authors":"Pankaj C. Patel","doi":"10.1016/j.techfore.2026.124538","DOIUrl":"10.1016/j.techfore.2026.124538","url":null,"abstract":"<div><div>Drawing on transaction cost economics and organizational information processing theory, we challenge the espoused benefits of AI in servitization by demonstrating that stock market reactions to service technology patents with high AI scores are negative. In a sample of 1306 service technology patents and 758,143 non-service technology patents from 3899 manufacturing firms (1980–2020), we find that idiosyncratic volatility mitigates this negative reaction, while tangibility shows no such effect. Decade-wise analysis reveals effects are significant only in the 2010s and 2020s, suggesting evolving market perceptions of AI-driven servitization. Results hold across matched-pair sampling, non-linear effects testing, fixed-effects individual slopes, and alternative moderator analyses. This study cautions against assuming short-term market value of AI service innovations in manufacturing.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124538"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-27DOI: 10.1016/j.techfore.2026.124564
Anders M.S.Ø. Jakobsen, Wim Vanhaverbeke
This study addresses the question of how user roles in Product Configuration Systems (PCS) function as socio-technical agents shaping operational efficiency, digital knowledge integration, and sustainable product customization in manufacturing. Grounded in socio-technical systems theory, the study analyses three years of PCS usage data from Grundfos—a global industrial pump manufacturer—to explore the socio-technical interplay between automated configuration processes and human expertise. Findings reveal that PCS effectiveness varies across Sales, Engineering, and Manufacturing roles: automation accelerates routine configurations, but human expertise remains crucial for complex cases. A regional analysis of global usage patterns indicates that highly automated regions achieve efficiency gains yet require expert oversight, whereas regions reliant on manual processes face digital adoption barriers that limit the system's optimization potential. Moreover, many PCS errors stem from misalignments between system constraints and user adaptations, underscoring the socio-technical nature of these challenges and the need for continuous human–technology alignment. Based on these insights, the study offers three key contributions to theory and practice: (1) a new conceptualization of PCS user roles as socio-technical agents; (2) a theoretical explanation of how user interactions shape PCS outcomes; and (3) a practical framework for embedding sustainability considerations into PCS workflows and decision-making.
{"title":"A socio-technical perspective on product configuration systems: Insights from Grundfos","authors":"Anders M.S.Ø. Jakobsen, Wim Vanhaverbeke","doi":"10.1016/j.techfore.2026.124564","DOIUrl":"10.1016/j.techfore.2026.124564","url":null,"abstract":"<div><div>This study addresses the question of how user roles in Product Configuration Systems (PCS) function as socio-technical agents shaping operational efficiency, digital knowledge integration, and sustainable product customization in manufacturing. Grounded in socio-technical systems theory, the study analyses three years of PCS usage data from Grundfos—a global industrial pump manufacturer—to explore the socio-technical interplay between automated configuration processes and human expertise. Findings reveal that PCS effectiveness varies across Sales, Engineering, and Manufacturing roles: automation accelerates routine configurations, but human expertise remains crucial for complex cases. A regional analysis of global usage patterns indicates that highly automated regions achieve efficiency gains yet require expert oversight, whereas regions reliant on manual processes face digital adoption barriers that limit the system's optimization potential. Moreover, many PCS errors stem from misalignments between system constraints and user adaptations, underscoring the socio-technical nature of these challenges and the need for continuous human–technology alignment. Based on these insights, the study offers three key contributions to theory and practice: (1) a new conceptualization of PCS user roles as socio-technical agents; (2) a theoretical explanation of how user interactions shape PCS outcomes; and (3) a practical framework for embedding sustainability considerations into PCS workflows and decision-making.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124564"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-07DOI: 10.1016/j.techfore.2025.124506
Mingyang Zou , Yang Yang
Does the application of artificial intelligence technology in enterprises bring all benefits and no harm? Most current work focuses on the positive effects of AI technology usage on businesses, while largely ignoring this issue. Focusing on signal theory, we test how the adoption of artificial intelligence affects the occurrence of corporate misconduct. We argue that due to the information asymmetry between large language models and businesses, the use of artificial intelligence (AI) technology may lead to increased corporate misconduct. Using data from 4144 listed companies in China, we find evidence supporting our argument. We also analyze the impact of industry digitization, enterprise digital technology use, and executive tone on this effect, and we further distinguish the effect of this effect in different situations through additional analyses. Enterprises can utilize these findings to identify their risk points in AI technology application and develop corresponding risk management strategies accordingly.
{"title":"Unveiling the impact of artificial intelligence on corporate misconduct, the perspective of information asymmetry","authors":"Mingyang Zou , Yang Yang","doi":"10.1016/j.techfore.2025.124506","DOIUrl":"10.1016/j.techfore.2025.124506","url":null,"abstract":"<div><div>Does the application of artificial intelligence technology in enterprises bring all benefits and no harm? Most current work focuses on the positive effects of AI technology usage on businesses, while largely ignoring this issue. Focusing on signal theory, we test how the adoption of artificial intelligence affects the occurrence of corporate misconduct. We argue that due to the information asymmetry between large language models and businesses, the use of artificial intelligence (AI) technology may lead to increased corporate misconduct. Using data from 4144 listed companies in China, we find evidence supporting our argument. We also analyze the impact of industry digitization, enterprise digital technology use, and executive tone on this effect, and we further distinguish the effect of this effect in different situations through additional analyses. Enterprises can utilize these findings to identify their risk points in AI technology application and develop corresponding risk management strategies accordingly.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124506"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145904109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-23DOI: 10.1016/j.techfore.2026.124553
Kalle Nuortimo , Janne Härkönen , Kristijan Breznik
Addressing global waste management challenges requires understanding not only the technical capabilities of products and technologies but also the factors shaping their development and deployment across the waste hierarchy. Deployment outcomes are strongly influenced by acceptance, reputation, and trust, distinct yet interrelated constructs whose dynamics remain insufficiently understood. Deepening this understanding can enhance stakeholder engagement and improve decision-making in waste management. This study examines waste-to-energy incineration as a representative case to investigate these dynamics across global, regional, and local levels. A multidisciplinary, data-driven approach is applied, combining artificial intelligence, big data analytics, opinion mining, Correspondence Analysis on Generalized Aggregated Lexical Tables, and content classification to assess acceptance, trust, and reputation in multiple knowledge domains. The analysis clarifies these constructs as interwoven but individually influential factors shaping technology deployment and explores their interplay with public perception. A novel method is also introduced for generating indicative reputation scores derived from sentiment analysis. The findings show that AI-enhanced analytical tools, when integrated with established methods, yield valuable insights into stakeholder sentiment and public discourse. These insights can inform more targeted stakeholder engagement and strategic communication in waste management planning. Overall, the study demonstrates the potential of emerging analytical tools to produce timely, structured indicators of trust, acceptance, and reputation, key dimensions for navigating the socio-political challenges of technology deployment in the waste sector.
{"title":"Waste management–related trust, acceptance, and reputation: A multidisciplinary big data analysis across knowledge domains","authors":"Kalle Nuortimo , Janne Härkönen , Kristijan Breznik","doi":"10.1016/j.techfore.2026.124553","DOIUrl":"10.1016/j.techfore.2026.124553","url":null,"abstract":"<div><div>Addressing global waste management challenges requires understanding not only the technical capabilities of products and technologies but also the factors shaping their development and deployment across the waste hierarchy. Deployment outcomes are strongly influenced by acceptance, reputation, and trust, distinct yet interrelated constructs whose dynamics remain insufficiently understood. Deepening this understanding can enhance stakeholder engagement and improve decision-making in waste management. This study examines waste-to-energy incineration as a representative case to investigate these dynamics across global, regional, and local levels. A multidisciplinary, data-driven approach is applied, combining artificial intelligence, big data analytics, opinion mining, Correspondence Analysis on Generalized Aggregated Lexical Tables, and content classification to assess acceptance, trust, and reputation in multiple knowledge domains. The analysis clarifies these constructs as interwoven but individually influential factors shaping technology deployment and explores their interplay with public perception. A novel method is also introduced for generating indicative reputation scores derived from sentiment analysis. The findings show that AI-enhanced analytical tools, when integrated with established methods, yield valuable insights into stakeholder sentiment and public discourse. These insights can inform more targeted stakeholder engagement and strategic communication in waste management planning. Overall, the study demonstrates the potential of emerging analytical tools to produce timely, structured indicators of trust, acceptance, and reputation, key dimensions for navigating the socio-political challenges of technology deployment in the waste sector.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124553"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-27DOI: 10.1016/j.techfore.2026.124534
Savvas Papagiannidis , Ewelina Lacka , Ariana Polyviou , Yann Truong , Ben Marder , Jonas Colliander , Ilias O. Pappas , Giray Gozgor
The metaverse promises to extend our physical world using AR and VR technologies. Virtual environments and immersive spaces have been described as antecedents of the metaverse and offer some insight into the potential socio-economic impact of a fully functional, persistent cross platform metaverse. Considering the renewed interest by big tech companies in metaverses and the investment in relevant technologies, it is important to reflect on the current state of play and assess the socio-economic impact that such transformative technologies could have. The empirical evidence provided by papers responding to the Special Issue call shed light on the impact metaverses have, offering valuable theoretical and practical insights into business and social opportunities and challenges.
{"title":"Metaverse beyond the hype: Empirically assessing the future impact of metaverses","authors":"Savvas Papagiannidis , Ewelina Lacka , Ariana Polyviou , Yann Truong , Ben Marder , Jonas Colliander , Ilias O. Pappas , Giray Gozgor","doi":"10.1016/j.techfore.2026.124534","DOIUrl":"10.1016/j.techfore.2026.124534","url":null,"abstract":"<div><div>The metaverse promises to extend our physical world using AR and VR technologies. Virtual environments and immersive spaces have been described as antecedents of the metaverse and offer some insight into the potential socio-economic impact of a fully functional, persistent cross platform metaverse. Considering the renewed interest by big tech companies in metaverses and the investment in relevant technologies, it is important to reflect on the current state of play and assess the socio-economic impact that such transformative technologies could have. The empirical evidence provided by papers responding to the Special Issue call shed light on the impact metaverses have, offering valuable theoretical and practical insights into business and social opportunities and challenges.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124534"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-26DOI: 10.1016/j.techfore.2026.124552
Tao Wang , Kaifan Luo , Chao Yu
Institutional elements are crucial drivers of corporate green innovation. Although existing research has acknowledged the important role of institutional elements in corporate green innovation and explored their interrelations, a comprehensive understanding of their relative importance and nonlinear impacts remains limited. To address this gap, this study draws on institutional theory and employs multiple machine learning algorithms, along with SHAP value analysis, using data from Chinese A-share listed companies (2011−2022) to systematically assess the influence of regulative, normative, and cultural-cognitive elements on firms' green innovation. The findings reveal that, among institutional elements, cultural-cognitive elements exert the most significant influence on firm green innovation. Specifically, central inspections, public attention, and industry-level green orientation are the predominant factors within their respective institutional categories. Most institutional elements exhibit significant nonlinear relationships with green innovation. Further analysis indicates that cultural-cognitive elements can, under certain conditions, impede green innovation, whereas regulative and normative elements generally foster it. Moreover, the impact of institutional elements demonstrates considerable heterogeneity across different regions, industries, and firm sizes. This study highlights the importance and interplay of institutional elements in shaping firm green innovation, offering insights for emerging economies to tailor policies and support firms' sustainable transformation.
{"title":"Unlocking the institutional foundations of green innovation: A machine learning analysis","authors":"Tao Wang , Kaifan Luo , Chao Yu","doi":"10.1016/j.techfore.2026.124552","DOIUrl":"10.1016/j.techfore.2026.124552","url":null,"abstract":"<div><div>Institutional elements are crucial drivers of corporate green innovation. Although existing research has acknowledged the important role of institutional elements in corporate green innovation and explored their interrelations, a comprehensive understanding of their relative importance and nonlinear impacts remains limited. To address this gap, this study draws on institutional theory and employs multiple machine learning algorithms, along with SHAP value analysis, using data from Chinese A-share listed companies (2011−2022) to systematically assess the influence of regulative, normative, and cultural-cognitive elements on firms' green innovation. The findings reveal that, among institutional elements, cultural-cognitive elements exert the most significant influence on firm green innovation. Specifically, central inspections, public attention, and industry-level green orientation are the predominant factors within their respective institutional categories. Most institutional elements exhibit significant nonlinear relationships with green innovation. Further analysis indicates that cultural-cognitive elements can, under certain conditions, impede green innovation, whereas regulative and normative elements generally foster it. Moreover, the impact of institutional elements demonstrates considerable heterogeneity across different regions, industries, and firm sizes. This study highlights the importance and interplay of institutional elements in shaping firm green innovation, offering insights for emerging economies to tailor policies and support firms' sustainable transformation.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124552"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-29DOI: 10.1016/j.techfore.2025.124522
Eszter Lukács , Sabrine Mallek , Jiyang Cheng
The study focuses on understanding how the use of generative Artificial Intelligence (AI) can beneficially result in circular supply chain transformation while embedding design intelligence, ethical intelligence, and predictive intelligence within socio-technical systems. This study proposes and validates a model that integrates generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness, which collectively affect circular supply chain resilience and socio-environmental value realization, mediated by Sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To test the hypothesis, data were collected from 264 professionals in supply chain and technology-related industries in the USA. As the findings suggest, generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness significantly enhance sustainable process reconfiguration capability, which drives AI-enabled stakeholder co-creation. A serial mediation model indicates that Generative AI capabilities affect circular supply chain resilience and socio-environmental value realization via sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To our surprise, the regenerative policy ambidexterity negatively moderates the relationship between AI-enabled stakeholder co-creation and the realization of socio-environmental value. The results provide actionable advice for managers implementing generative AI in sustainable supply chains. Instead of focusing solely on algorithmic efficiency, if an organization can develop reconfiguration capability and engage stakeholders, it would generate systemic sustainability benefits.
{"title":"Generative AI-driven transition to circular and responsible supply chains: Unpacking the dynamics of eco-centric design intelligence and ethical responsiveness","authors":"Eszter Lukács , Sabrine Mallek , Jiyang Cheng","doi":"10.1016/j.techfore.2025.124522","DOIUrl":"10.1016/j.techfore.2025.124522","url":null,"abstract":"<div><div>The study focuses on understanding how the use of generative Artificial Intelligence (AI) can beneficially result in circular supply chain transformation while embedding design intelligence, ethical intelligence, and predictive intelligence within socio-technical systems. This study proposes and validates a model that integrates generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness, which collectively affect circular supply chain resilience and socio-environmental value realization, mediated by Sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To test the hypothesis, data were collected from 264 professionals in supply chain and technology-related industries in the USA. As the findings suggest, generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness significantly enhance sustainable process reconfiguration capability, which drives AI-enabled stakeholder co-creation. A serial mediation model indicates that Generative AI capabilities affect circular supply chain resilience and socio-environmental value realization via sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To our surprise, the regenerative policy ambidexterity negatively moderates the relationship between AI-enabled stakeholder co-creation and the realization of socio-environmental value. The results provide actionable advice for managers implementing generative AI in sustainable supply chains. Instead of focusing solely on algorithmic efficiency, if an organization can develop reconfiguration capability and engage stakeholders, it would generate systemic sustainability benefits.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124522"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Resilience is crucial as entrepreneurial organizations have often been viewed as fragile systems, leading to their reactive approach to disruptions. However, there is a lack of clarity regarding the role of unique organizational capabilities in interpreting emerging disruptions, managing the aftereffects of disruptions, and achieving antifragility. We explore how entrepreneurial organizations proactively thrive during disruption, with a specific focus on the unique role of varied organizational capabilities at three distinct stages of disruption: the pre-disruption stage, the emergence of disruption, and the post-disruption stage. Our qualitative study investigated responses from managers working in thirty-six entrepreneurial organizations, highlighting the concurrent role of digital capabilities, social capital, and ambidexterity during different stages of disruption. The findings indicate that leveraging social capital is crucial in activating organizational resilience during the various stages of a crisis. Digital technologies enable entrepreneurial organizations to anticipate the potential ramifications of disruptions and engage in collaborations during the post-disruption phase, thereby building antifragility. Another implication is the role of ambidexterity as an organizational capability in responding positively to continuous disruptions and thriving post disruptions.
{"title":"Moving beyond resilience: Building antifragility using digital technologies in entrepreneurial organizations","authors":"Yaning Zhang , Sanjay Chaudhary , Safiya Mukhtar Alshibani , Yanzhe Yuan , Bhumika Gupta","doi":"10.1016/j.techfore.2025.124514","DOIUrl":"10.1016/j.techfore.2025.124514","url":null,"abstract":"<div><div>Resilience is crucial as entrepreneurial organizations have often been viewed as fragile systems, leading to their reactive approach to disruptions. However, there is a lack of clarity regarding the role of unique organizational capabilities in interpreting emerging disruptions, managing the aftereffects of disruptions, and achieving antifragility. We explore how entrepreneurial organizations proactively thrive during disruption, with a specific focus on the unique role of varied organizational capabilities at three distinct stages of disruption: the pre-disruption stage, the emergence of disruption, and the post-disruption stage. Our qualitative study investigated responses from managers working in thirty-six entrepreneurial organizations, highlighting the concurrent role of digital capabilities, social capital, and ambidexterity during different stages of disruption. The findings indicate that leveraging social capital is crucial in activating organizational resilience during the various stages of a crisis. Digital technologies enable entrepreneurial organizations to anticipate the potential ramifications of disruptions and engage in collaborations during the post-disruption phase, thereby building antifragility. Another implication is the role of ambidexterity as an organizational capability in responding positively to continuous disruptions and thriving post disruptions.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124514"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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