Technological Forecasting and Social Change最新文献_第4页

The role of environmental taxes in promoting sustainable utilization of disaggregated natural resources toward global greening: A novel dynamic ARDL simulation approach 环境税在促进分类自然资源可持续利用、实现全球绿化中的作用：一种新的动态ARDL模拟方法

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-14 DOI: 10.1016/j.techfore.2026.124535

Isaac Ahakwa , Yi Xu , Evelyn Agba Tackie

{"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}

引用次数: 0

Does AI value the environment? Evaluation of AI value alignment 人工智能重视环境吗？评估人工智能的价值一致性

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-26 DOI: 10.1016/j.techfore.2026.124550

Wanggi Jaung

{"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}

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Navigating the gambit: Unfavorable market responses to AI-based service patents in manufacturing firms 引导策略：制造企业对基于人工智能的服务专利的不利市场反应

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-19 DOI: 10.1016/j.techfore.2026.124538

Pankaj C. Patel

引用次数: 0

A socio-technical perspective on product configuration systems: Insights from Grundfos 产品配置系统的社会技术视角：格兰富的见解

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-27 DOI: 10.1016/j.techfore.2026.124564

Anders M.S.Ø. Jakobsen, Wim Vanhaverbeke

{"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}

引用次数: 0

Unveiling the impact of artificial intelligence on corporate misconduct, the perspective of information asymmetry 揭示人工智能对企业不当行为的影响，信息不对称的视角

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-07 DOI: 10.1016/j.techfore.2025.124506

Mingyang Zou , Yang Yang

引用次数: 0

Waste management–related trust, acceptance, and reputation: A multidisciplinary big data analysis across knowledge domains 废物管理相关的信任、接受和声誉：跨知识领域的多学科大数据分析

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.techfore.2026.124553

Kalle Nuortimo , Janne Härkönen , Kristijan Breznik

{"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}

引用次数: 0

Metaverse beyond the hype: Empirically assessing the future impact of metaverses 超越炒作的虚拟世界：对虚拟世界未来影响的实证评估

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-27 DOI: 10.1016/j.techfore.2026.124534

Savvas Papagiannidis , Ewelina Lacka , Ariana Polyviou , Yann Truong , Ben Marder , Jonas Colliander , Ilias O. Pappas , Giray Gozgor

引用次数: 0

Unlocking the institutional foundations of green innovation: A machine learning analysis 解锁绿色创新的制度基础：机器学习分析

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-26 DOI: 10.1016/j.techfore.2026.124552

Tao Wang , Kaifan Luo , Chao Yu

{"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}

引用次数: 0

Generative AI-driven transition to circular and responsible supply chains: Unpacking the dynamics of eco-centric design intelligence and ethical responsiveness 生成式人工智能驱动的向循环和负责任供应链的过渡：揭示以生态为中心的设计智能和道德响应的动态

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.techfore.2025.124522

Eszter Lukács , Sabrine Mallek , Jiyang Cheng

{"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}

引用次数: 0

Evaluating the use of structural equation modeling in online purchase intention research: A comprehensive review (2000−2023) 评价结构方程模型在在线购买意愿研究中的应用：综述（2000 - 2023）

IF 13.3 1区管理学

Technological Forecasting and Social Change Pub Date : 2026-04-01 Epub Date: 2026-01-12 DOI: 10.1016/j.techfore.2025.124512

René Abreu-Ledón , Darkys E. Luján-García , Pedro Garrido-Vega , Jose A.D. Machuca , Yodaira Borroto-Pentón

{"title":"Evaluating the use of structural equation modeling in online purchase intention research: A comprehensive review (2000−2023)","authors":"René Abreu-Ledón , Darkys E. Luján-García , Pedro Garrido-Vega , Jose A.D. Machuca , Yodaira Borroto-Pentón","doi":"10.1016/j.techfore.2025.124512","DOIUrl":"10.1016/j.techfore.2025.124512","url":null,"abstract":"<div><div>Technological advances—and, more recently, the COVID-19 pandemic—have accelerated the growth of online purchasing, prompting a surge in empirical research on online consumer behavior. A substantial share of these studies rely on structural equation modeling (SEM) for data analysis. However, inadequate or improper application of SEM can produce unreliable results and misleading conclusions, undermining scientific progress and managerial decision-making. To address this critical concern, the present study provides, to the best of our knowledge, the first comprehensive assessment of SEM applications—encompassing both covariance-based structural equation modeling (CB-SEM) and partial least squares structural equation modeling (PLS-SEM)— in online purchase intention (OPI) research. Our review covers 120 empirical articles published between 2000 and 2023 and reveals that methodological requirements of SEM are often overlooked, which risks invalidating both theoretical contributions and managerial implications. In response, we offer practical recommendations and a results-based guide to assist researchers and reviewers in enhancing the rigor, reliability, and decision-oriented value of SEM studies in this field.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124512"},"PeriodicalIF":13.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980365","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}

引用次数: 0