Technology in Society最新文献_第9页

Idea readability and complexity in online user innovation communities: Effects on implementation and advocacy 在线用户创新社区的创意可读性和复杂性：对实施和倡导的影响

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2026-02-06 DOI: 10.1016/j.techsoc.2026.103259

Mu Yang , Joseph Amankwah-Amoah , Chunjia Han

引用次数: 0

Artificial intelligence and corporate shadow banking: Evidence from distorted innovation 人工智能与企业影子银行：来自扭曲创新的证据

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2026-02-05 DOI: 10.1016/j.techsoc.2026.103256

Qingling Wu, Lihua Guo, Daming Li

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Teaching methods for building human capital for the twin transition: a skill-based approach 为双重转型建立人力资本的教学方法：以技能为基础的方法

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2025-11-21 DOI: 10.1016/j.techsoc.2025.103172

Adriana Hofmann Trevisan , Iskra Dukovska-Popovska , Federica Acerbi , Sergio Terzi , Claudio Sassanelli

{"title":"Teaching methods for building human capital for the twin transition: a skill-based approach","authors":"Adriana Hofmann Trevisan , Iskra Dukovska-Popovska , Federica Acerbi , Sergio Terzi , Claudio Sassanelli","doi":"10.1016/j.techsoc.2025.103172","DOIUrl":"10.1016/j.techsoc.2025.103172","url":null,"abstract":"<div><div>The growing demand for qualified professionals for the twin green and digital transition exceeds the supply of candidates, highlighting the urgency of effective educational methods for qualifying individuals in a circular economy (CE). However, despite the CE field having made several advances in terms of academic research and practical applications, teaching the CE has not received proper attention. Recently, the skills required in a twin transition have been defined, along with a framework identifying which of these skills should be fostered in new educational initiatives. However, it is still not clear which teaching methods are most suitable to support education in CE. This study, based on a systematic literature review, identifies 11 teaching methods, such as case studies, project-based learning, and gamification, that develop technical, digital and resilience skills. Given the continuous evolution and interdisciplinarity of the CE, particularly when combined with digital technologies, the delivery of knowledge necessitates appropriate and flexible approaches. By providing theoretical and practical implications, the study guides educators and policymakers in creating curricula aligned with market demands, promoting interdisciplinary education for the twin transition.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103172"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145623537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Who is lifting the green veil? Climate physical risks and supply chain spillovers of corporate carbon greenwashing 是谁揭开了绿色的面纱？气候物理风险和企业碳漂绿的供应链溢出效应

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2025-12-13 DOI: 10.1016/j.techsoc.2025.103203

Yun Zhong , Han Yan , Ziqian Xia

{"title":"Who is lifting the green veil? Climate physical risks and supply chain spillovers of corporate carbon greenwashing","authors":"Yun Zhong , Han Yan , Ziqian Xia","doi":"10.1016/j.techsoc.2025.103203","DOIUrl":"10.1016/j.techsoc.2025.103203","url":null,"abstract":"<div><div>Against the backdrop of intensifying global climate change, corporate greenwashing behavior is attracting widespread attention from regulators and academia. This paper investigates whether the climate physical risk faced by a customer is transmitted through the supply chain, influencing the supplier's selective disclosure of carbon information. Using a sample of Chinese A-share listed companies from 2008 to 2023, we find a significant result: Suppliers exhibit a markedly reduced level of carbon greenwashing when their principal customers are exposed to more severe climate physical risks. Mechanism analysis suggests that this inhibitory effect primarily operates through increased scrutiny on carbon reduction verification and a decline in the supplier management's future expectations. Furthermore, this effect is stronger under specific conditions: when customer concentration is higher, the customer's digital technology level is more advanced, and the supplier's financial flexibility is poorer. Collectively, these findings not only provide new evidence on the cross-firm transmission mechanism of climate risk but also offer important micro-level implications for achieving global climate governance goals.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103203"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Are AI and environmental technology innovations converging? 人工智能和环境技术创新正在融合吗？

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2026-01-06 DOI: 10.1016/j.techsoc.2026.103222

Kyle S. Herman , Tatiana Gaitan Amortegui , Steve Griffiths

{"title":"Are AI and environmental technology innovations converging?","authors":"Kyle S. Herman , Tatiana Gaitan Amortegui , Steve Griffiths","doi":"10.1016/j.techsoc.2026.103222","DOIUrl":"10.1016/j.techsoc.2026.103222","url":null,"abstract":"<div><div>Artificial intelligence (AI) is increasingly invoked as a means of advancing climate and environmental solutions, yet how it shapes environmental technology (ET) development remains poorly understood. This study addresses that gap by asking: To what extent are AI and ETs converging, and which specific domains are driving this integration? To investigate these questions, we have constructed a new dataset of nearly 8000 AI-environmental (AI-ENVI) patents filed at the USPTO from 2003 through 2023. Drawing on this dataset, we perform semantic reclassification followed by forward citation mapping to identify influential innovations and to evaluate prominent domains of technological convergence. We find that three fields dominate: renewable energy optimization, electric vehicles, and fossil fuel efficiency/industrial decarbonization. To probe further, we examine metrics of novelty, disruptiveness, and generality. Novelty is highest in grid-level energy storage optimization; disruptiveness peaks in blockchain-based energy trading; and generality is strongest in the former as well as energy demand forecasting. Evidence that AI applications for incumbent industries attract high forward citations, and that carbon capture and storage (CCS) emerges as a disruptive subcategory, underscores the need for appropriate policy mechanisms to avoid carbon lock-in within the ET–AI nexus.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103222"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital transformation, open innovation and circular business model transition: The role of effectual logic 数字化转型、开放式创新与循环商业模式转型：有效逻辑的作用

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2026-01-05 DOI: 10.1016/j.techsoc.2026.103223

Safiya Mukhtar Alshibani , Sanjay Chaudhary , Snigdha Dash , Raj V. Mahto

{"title":"Digital transformation, open innovation and circular business model transition: The role of effectual logic","authors":"Safiya Mukhtar Alshibani , Sanjay Chaudhary , Snigdha Dash , Raj V. Mahto","doi":"10.1016/j.techsoc.2026.103223","DOIUrl":"10.1016/j.techsoc.2026.103223","url":null,"abstract":"<div><div>Despite the theorized role of open innovation in shaping circular business models, there remains ambiguity about how open innovation can accelerate the transition toward circularity. Transition towards a circular business model typically presents obstacles for entrepreneurial organizations because they lack access to resources. Ambiguity remains on how organizations transitioning to a circular business model deploy open innovation strategies and what decision-making mechanisms underpin the value co-creation processes. We address the research question: How do organizations deploy open innovation in circular business models? We explore how open innovation is integrated with circular business models. Based on a qualitative analysis of forty-three open-ended online interviews and Gioia’s methodology, the findings reveal that effectual logic supports organizations in effectively deploying open innovation while pursuing a circular business model. The transition towards circularity raises dilemmas about leveraging collaborations, and effectuctual logic assists in integrating an open innovation strategy into the circular business model. By minimizing resource commitment, collaborating with diverse stakeholders, and continuously refining processes, managers pursuing circularity can effectively address the challenges encountered during the transition to circularity.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103223"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How AI shapes entrepreneurial processes in social enterprises: A model of augmented and centric pathways 人工智能如何塑造社会企业的创业过程：增强和中心路径的模型

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2025-11-29 DOI: 10.1016/j.techsoc.2025.103181

Shouxiang Qiu , Bingjie Li , Zhao Duan

{"title":"How AI shapes entrepreneurial processes in social enterprises: A model of augmented and centric pathways","authors":"Shouxiang Qiu , Bingjie Li , Zhao Duan","doi":"10.1016/j.techsoc.2025.103181","DOIUrl":"10.1016/j.techsoc.2025.103181","url":null,"abstract":"<div><div>To tackle complex societal challenges, social entrepreneurship is increasingly leveraging Artificial Intelligence (AI). However, the existing literature often treats AI as a static technological input, leaving the dynamic, unfolding process of its integration into social enterprises critically underexplored. Furthermore, this perspective treats technology as monolithic, overlooking how specific digital representations and depth of integration reconfigure the entrepreneurial process. To address this gap, this study develops a process model of AI integration in social entrepreneurship. Adopting a longitudinal, multiple-case study methodology, we examine how AI integration shapes the three processes of social entrepreneurship: opportunity recognition, opportunity development, and opportunity exploitation. Our findings identify two strategic pathways: AI-augmented social entrepreneurship, where AI is instrumentally adopted to enhance an existing social business model, and AI-centric social entrepreneurship, where a novel AI capability fundamentally creates the social value proposition. Our primary contribution is a process framework elucidating how entrepreneurial activities, strategic priorities, and developmental dynamics diverge across AI-augmented and AI-centric pathways. This model advances the theoretical understanding of technology integration in social entrepreneurship and offers practical guidance for leveraging AI to create and scale social value.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103181"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145690544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital industrial agglomeration and breakthrough technological innovation: Evidence from business registration data 数字产业集聚与突破性技术创新：来自工商登记数据的证据

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2025-11-13 DOI: 10.1016/j.techsoc.2025.103161

Hong Zhao , Xiaoxi Cao , Tao Ma

{"title":"Digital industrial agglomeration and breakthrough technological innovation: Evidence from business registration data","authors":"Hong Zhao , Xiaoxi Cao , Tao Ma","doi":"10.1016/j.techsoc.2025.103161","DOIUrl":"10.1016/j.techsoc.2025.103161","url":null,"abstract":"<div><div>Promoting breakthrough technological innovation (BTInnovation) through digital industrial agglomeration (DIAgg) is a crucial component of achieving technological self-reliance and constructing a modern industrial system. Existing studies have focused on the impact of agglomeration on innovation, yet there is a lack of discussion regarding the effect of DIAgg on BTInnovation. Based on county-level panel data from 2003 to 2021, this study employs business registration data to measure the development level of DIAgg and analyzes its impact on BTInnovation. The findings reveal that DIAgg significantly enhances BTInnovation, a conclusion that remains robust under several robustness checks. The primary mechanisms driving the main effect are the labor pool and the technological spillover effect. Heterogeneity analysis reveals a stronger main effect in counties with superior market potential, a better business environment, greater attention to digital technology, lower intra-county competition and a specialized agglomeration model. Further analysis demonstrates that the promotional effect of DIAgg on BTInnovation in China primarily stems from specialized agglomeration. There findings contribute to the theoretical understanding of how industrial agglomeration affects innovation in the digital era and offer valuable implications for developing countries seeking to advance DIAgg and achieve high-quality development.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103161"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Can artificial intelligence drive enterprise green management innovation? A new perspective on harnessing intelligence 人工智能能否推动企业绿色管理创新？利用智力的新视角

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2025-11-08 DOI: 10.1016/j.techsoc.2025.103156

Shuai Che , Chen Liu , Jie Wang , Jun Wang

{"title":"Can artificial intelligence drive enterprise green management innovation? A new perspective on harnessing intelligence","authors":"Shuai Che , Chen Liu , Jie Wang , Jun Wang","doi":"10.1016/j.techsoc.2025.103156","DOIUrl":"10.1016/j.techsoc.2025.103156","url":null,"abstract":"<div><div>Amid the dual pressures of environmental pollution and resource constraints, enterprises are compelled to pursue green innovation to confront novel management challenges, and artificial intelligence emerges as a critical enabler by endowing enterprise green management innovation with advanced technological capabilities. Using data from Chinese enterprises spanning 2008–2023, this study comprehensively assesses artificial intelligence's catalytic role, revealing that artificial intelligence significantly enhances green management innovation efficiency. Local state-owned enterprises, firms with strong brand and content innovation capabilities, and industries such as water conservancy, public facilities management, wholesale, and retail gain disproportionate benefits. Artificial intelligence's green influence intensifies over time with a notable poverty alleviation effect at the 40th percentile and enhances productivity, resolving the productivity paradox. Theoretically, this study advances understanding by identifying digital, financing, operational, and R&D empowerment as key transmission mechanisms through which artificial intelligence drives green management innovation, collectively helping enterprises overcome high-pollution dilemmas. This research provides a basis for global enterprises to accelerate green management transformation and unleash the power of intelligent technologies in the digital age.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103156"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Out of gratification or fears? A dual model to explore drivers of generative artificial intelligence adoption 出于满足还是恐惧？探索生成式人工智能采用驱动因素的双重模型

IF 12.5 1区社会学

Technology in Society Pub Date : 2026-06-01 Epub Date: 2025-11-20 DOI: 10.1016/j.techsoc.2025.103177

Chien-Hsiang Liao , Yu-Hui Fang , Chia-Ying Li

{"title":"Out of gratification or fears? A dual model to explore drivers of generative artificial intelligence adoption","authors":"Chien-Hsiang Liao , Yu-Hui Fang , Chia-Ying Li","doi":"10.1016/j.techsoc.2025.103177","DOIUrl":"10.1016/j.techsoc.2025.103177","url":null,"abstract":"<div><div>Generative artificial intelligence (GenAI) has emerged as a transformative force reshaping how individuals work, live, and interact with their environments. Despite its rapid diffusion, research has yet to clarify the psychological mechanisms driving individual-level GenAI adoption and resistance. This study addresses this critical gap by proposing a dual-path model grounded in Uses and Gratifications Theory (UGT) and an extended Protection Motivation Theory (PMT) framework. UGT explains the positive, need-fulfilling motivations for GenAI use, incorporating novel gratification constructs such as serendipity, perceived diagnosticity, tangibility, curiosity fulfillment, and enjoyment. In contrast, the enhanced PMT framework captures both traditional and extended pathways of perceived threats. By including fear of losing power (FLP) and fear of missing out (FoMO) as internal psychological mechanisms, this study offers a more comprehensive account of GenAI adoption and resistance. Trait competitiveness and AI self-efficacy are introduced as moderators, delineating how individual differences shape protective responses. Using data from a two-wave longitudinal survey of 1271 ChatGPT users, the findings reveal that UGT-related factors primarily drive adoption, while traditional and extended PMT factors explain resistance behaviors. Notably, FoMO functions as a dual-pathway factor, facilitating adoption and mitigating resistance. Trait competitiveness and AI self-efficacy demonstrate partial moderating effects, underscoring the role of personal dispositions in shaping user behavior. This study contributes theoretically by integrating positive gratification and protective aversion into a unified model of GenAI use. Practically, it provides actionable insights for designing adaptive, user-centered AI systems that enhance engagement while reducing resistance.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103177"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0