Technology in Society最新文献

{"title":"Harnessing AI-metaverse synergies for smart sustainability: A knowledge management perspective on immersion, ethics, and decentralization","authors":"Ebtesam Abdullah Alzeiby ,&nbsp;Vinay Khandelwal ,&nbsp;Jiyang Cheng ,&nbsp;Snigdha Dash ,&nbsp;Valerio Temperini ,&nbsp;Rosa Palladino","doi":"10.1016/j.techsoc.2026.103234","DOIUrl":"10.1016/j.techsoc.2026.103234","url":null,"abstract":"<div><div>Businesses are increasingly using technology to assist in running their organizations. AI and the metaverse together have the potential to reform knowledge management with sustainable opportunities. This study discusses the impact of immersive digital environments and decentralized AI-based architecture on smart knowledge systems and cognitive transformation. This study further examines how these mechanisms foster sustainability-driven business models and resilient knowledge ecosystems. A structural model was tested with data of 290 professionals. The findings reveal that immersive and decentralized technologies advance organizational knowledge systems and induce cognitive transformation in employees, resulting in sustainable business models and resilient ecosystems. Mediation analysis reveals that immersive and decentralized technologies translate into strategic outcomes through knowledge systems and cognitive transformation. However, cognitive transformation fails to mediate the decentralization and resilience nexus. This implies the need for knowledge systems to support transformation, but systematically. Building on the socio-technical systems theory, the study concludes that for digital transformation to occur, the system-level processes and the forces driving cognitive change must also coincide to drive sustainability. The findings present ethical dimensions underlying AI-driven knowledge systems related to transparency, trust, and inclusion.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103234"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037442","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}

{"title":"Decoding AI innovation: How R&D alliances drive technological breakthrough","authors":"Yang Huang ,&nbsp;Fangzhou Song ,&nbsp;Chengkun Liu","doi":"10.1016/j.techsoc.2025.103165","DOIUrl":"10.1016/j.techsoc.2025.103165","url":null,"abstract":"<div><div>Artificial intelligence (AI) innovation is central to technological progress in the digital economy, yet little is known about how different R&amp;D alliance types shape this process. Drawing on resource dependence theory (RDT), we examine how market- and research-oriented alliances affect AI innovation using patent-based measures constructed via a bag-of-words (BoW) model and panel data on Chinese listed firms. Results show that market alliances significantly enhance AI innovation, including generative AI (Gen_AI), whereas research alliances hinder general AI innovation and exhibit no significant relationship with Gen_AI. These results remain consistent across different robustness (replacement variables, exclusion of financial volatility, stricter fixed effects, dual machine learning) and endogeneity tests (GMM and instrumental variables). Moderation analyses reveal that knowledge path dependence weakens the benefits of market alliances and amplifies the drawbacks of research alliances, while dynamic capabilities reverse these effects by enabling knowledge integration and redeployment. Therefore, we extend RDT by revealing how internal inertia and adaptive capacity influence the effectiveness of R&amp;D alliances in driving AI innovation through moderation effects. These findings offer theoretical insights and practical guidance for firms leveraging R&amp;D alliances to sustain AI innovation in fast-changing environments.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103165"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579374","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}

{"title":"Empirical analysis of the roles of dynamic sustainable capabilities and artificial intelligence in accelerating circular business model innovation: Insights from Chinese manufacturing firms","authors":"Chen Renfei ,&nbsp;Li Zhongwen","doi":"10.1016/j.techsoc.2025.103176","DOIUrl":"10.1016/j.techsoc.2025.103176","url":null,"abstract":"<div><div>Despite increasing managerial focus on Artificial Intelligence (AI) -enhanced environmental strategies, few studies have examined how dynamic sustainable capabilities (DSC) and AI-enabled circular business model innovation (CBMI) affect sustainability-oriented corporate performance (SOCP). Grounded in dynamic capabilities theory and dynamic managerial capabilities theory, this study develops a unified framework to investigate the mechanisms through which DSC fosters AI capabilities and CBMI, ultimately enhancing SOCP, while examining managerial cognition as a key moderator. This study empirically analyzes data from 289 questionnaires from 120 manufacturing companies through the PLS-SEM method. The findings reveal that DSC has a positive effect on AI capabilities, CBMI, and SOCP. AI capabilities and CBMI partially mediate the DSC-SOCP relationship. Managerial cognition positively contributes to the role of CBMI on SOCP, and AI capabilities have a positive effect on CBMI. This study advances the literature by elucidating the sequential pathways from DSC to AI-driven CBMI, highlighting micro-foundations for circular transitions. Moreover, this study extends managerial cognition to CBMI practices, revealing the synergies between managerial cognition and CBMI and its role in accelerating SOCP, contributing to clarifying the sources of performance differences in circular economy practices. This lays the foundation for future research agendas on AI integration in the circular economy.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103176"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579373","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}

{"title":"Cross-layer diffusion in patent networks: Forecasting innovation through enterprise–technology synergy","authors":"Dejian Yu ,&nbsp;Aoqiu Shen ,&nbsp;Wenjin Zuo","doi":"10.1016/j.techsoc.2025.103193","DOIUrl":"10.1016/j.techsoc.2025.103193","url":null,"abstract":"<div><div>Firms face serious challenges in predicting the direction of innovation and identifying strategic partners in rapidly evolving technological fields, as traditional single-layer network models tend to ignore the synergies between inter-firm relationships and cross-field technology diffusion. To address this limitation, we combine the firm perspective with bi-layer patent networks to analyze synergistic technology diffusion links and predict the direction of innovation frontiers. We use a bi-layer diffusion-based patent network model that dynamically combines firm-level technology similarity networks with technology topic co-occurrence networks. By employing diffusion-based network analysis, the model quantifies the propagation of technological elements across organizational and disciplinary boundaries and identifies emerging technological directions and collaboration opportunities. The model is empirically validated on a dataset in the field of \"Blockchain + Audit\" to effectively predict future research directions and recommend potential technology development fields and partners for firms. This study provides valuable insights into the diffusion process of technology elements in bi-layer networks, and provides strategic insights to guide firms’ innovation decisions in dynamic technological environments.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103193"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796951","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}

{"title":"Impact of government policies on the electric vehicle industry, environment, and society: A systematic review","authors":"Chi Yang,&nbsp;Lixian Qian,&nbsp;Miaomiao Liu","doi":"10.1016/j.techsoc.2026.103226","DOIUrl":"10.1016/j.techsoc.2026.103226","url":null,"abstract":"<div><div>Countries worldwide are implementing government policies to promote the development of the electric vehicle industry, and this is attracting increasing research attention. However, a systematic and holistic discussion on the effectiveness of these policies is still lacking, which makes it difficult to understand comprehensively how government interventions influence the electric vehicle industry, environment, and society. To address this research gap, we conduct a systematic literature review of 76 selected empirical studies on electric vehicle policy effectiveness that used observational data. Grounding it in three core theoretical perspectives (i.e., signaling, information, and policy mix), we develop an integrated and multidimensional framework to theorize about the impact of four types of electric vehicle policies (i.e., demonstration, financial, regulatory, and soft instruments) on five outcomes (i.e., research and development performance, financial performance, market performance, environmental impact, and social impact). We further examine the (in)consistencies of prior research findings using the Herfindahl–Hirschman Index and provide promising directions for future research. This study advances the conceptual and empirical understanding of electric vehicle policy effectiveness and offers valuable practical implications for researchers, policymakers, and authorities seeking to explore and manage its complexity.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103226"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924196","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}

{"title":"Generative AI and responsible supply chains: When sustainability gains undermine social legitimacy","authors":"Min Jae Park","doi":"10.1016/j.techsoc.2026.103240","DOIUrl":"10.1016/j.techsoc.2026.103240","url":null,"abstract":"<div><div>Generative artificial intelligence (GenAI) is increasingly adopted in supply chains to advance sustainability goals; however, empirical evidence on its environmental and social consequences remains limited and fragmented. This study examines how GenAI adoption affects responsible supply chain outcomes by integrating Difference-in-Differences (DiD) and fuzzy-set Qualitative Comparative Analysis (fsQCA). Using firm–quarter panel data from 320 South Korean firms covering the period from 2023Q1 to 2025Q2, we estimate the short-run causal effects of GenAI adoption on environmental, operational, and social performance, while also identifying the organizational configurations under which these effects emerge. The DiD results provide causal evidence that GenAI adoption significantly reduces CO₂ intensity and strengthens circular supply chain practices in the short term. Mediation analyses further show that these environmental benefits are realized primarily through enhanced circular practices rather than through direct improvements in operational efficiency. In contrast, the average effects on operational efficiency and social responsibility outcomes are statistically insignificant, indicating substantial heterogeneity across firms. The fsQCA analysis uncovers multiple sufficient pathways to sustainability. GenAI adoption combined with high absorptive capacity consistently produces environmental gains, whereas the combination of GenAI, responsible AI governance, and strong managerial commitment is the only configuration that generates joint environmental and social outcomes. Conversely, GenAI adoption in the absence of governance safeguards leads to environmental improvements while undermining social legitimacy, underscoring the conditional and double-edged nature of GenAI in supply chains. By integrating causal inference with configurational analysis, this study advances understanding of when and how GenAI contributes to responsible supply chains. The findings demonstrate that while GenAI can serve as a powerful enabler of circular and low-carbon supply chains, its broader social legitimacy critically depends on complementary organizational capabilities and governance arrangements.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103240"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037445","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}

{"title":"Contextualizing job design for individual work performance: The role of organizational strategy and structure","authors":"Tomislav Hernaus ,&nbsp;Matej Černe ,&nbsp;Aleša Saša Sitar ,&nbsp;Matija Marić ,&nbsp;Sara Melkić","doi":"10.1016/j.techsoc.2025.103147","DOIUrl":"10.1016/j.techsoc.2025.103147","url":null,"abstract":"<div><div>This two-study, top-down multilevel research examines how to create high-performance jobs within well-designed organizations. By integrating a broad strategic human resource management perspective with the traditional strategy–structure–performance framework and influential job demands–resources theory, we explored whether and how the alignment of cognitive job demands and task-related resources mediates the cross-level relationship between strategy–structure fit and employees' task performance. Multilevel mediation analyses were performed using nested, time-lagged data (Study 1: 874 employees across 49 organizations; Study 2: 479 employees and 171 managers across 40 organizations). Results consistently show that strategy–structure fit, as a macrolevel context, is too distal to directly influence individual work performance. Instead, the alignment of strategic ambidexterity and cross-functional integration enhances microlevel job demands–resources fit, which then improves employees’ task performance. These replicated findings, further supported by latent profile analysis, highlight the importance of contextualizing job design within organizational systems and introduce a multilevel, multi-fit framework with practical insights for human resource and organizational design professionals.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103147"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527400","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}

{"title":"AI-driven financial operational Efficiency: A dynamic capabilities perspective on knowledge-oriented leadership and financial flexibility","authors":"Zitao Yang ,&nbsp;Zixiao Zhang ,&nbsp;Huaxia Hu","doi":"10.1016/j.techsoc.2026.103235","DOIUrl":"10.1016/j.techsoc.2026.103235","url":null,"abstract":"<div><div>While artificial intelligence (AI) offers transformative potential for corporate finance, the specific combination of organizational capabilities needed to achieve high operational efficiency remains ambiguous, particularly in knowledge-intensive firms. This study addresses this gap by moving beyond linear-causal models to uncover the synergistic pathways to success. Using a hybrid partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methodology on survey data from the survey and design industry, we analyze how knowledge-oriented leadership, financial flexibility, trust in AI, and AI utilization combine to drive efficiency. Our findings reveal that no single capability is sufficient. Instead, high financial efficiency is achieved through multiple configurational pathways, all of which require a core foundation of knowledge-oriented leadership and financial flexibility. Critically, we find that trust in AI and the utilization of AI can function as substitutes for one another, demonstrating strategic equifinality. This study's primary contribution is to the Dynamic Capabilities Theory, revealing the complex, configurational, and substitutive nature of the capabilities required for AI-driven transformation and offering a nuanced strategic roadmap for managers.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103235"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975891","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}

{"title":"When trust becomes a liability: Relational vulnerability and technology misappropriation in asymmetric innovation ecosystems","authors":"Min Jae Park","doi":"10.1016/j.techsoc.2026.103260","DOIUrl":"10.1016/j.techsoc.2026.103260","url":null,"abstract":"<div><div>Technology misappropriation in asymmetric business-to-business (B2B) innovation partnerships occupies an ethical gray zone in which formally legal practices coexist with relational exploitation. This study examines how structural asymmetries embedded in innovation ecosystems condition such misappropriation by shaping power relations, trust dynamics, and institutional accountability. We conceptualize relational vulnerability as the mechanism through which power asymmetry (unequal control over resources and decision-making) and trust asymmetry (imbalanced relational exposure) jointly undermine ethical stability when institutional safeguards are weak. Drawing on five in-depth case studies of South Korean innovation partnerships and a computational analysis of 5280 social media posts and 154 news articles, the study employs a mixed-method design integrating qualitative coding with large-scale discourse analytics. The findings show that while trust facilitates collaborative engagement within innovation partnerships, it can also amplify vulnerability when partnerships are embedded in asymmetric innovation ecosystems characterized by institutional voids and limited enforcement capacity. In such contexts, formal avenues for redress are constrained, prompting affected actors to seek informal accountability through public discourse, where digital publics function as emergent moral adjudicators. By demonstrating that ethical breakdowns arise not from isolated opportunism but from systemic misalignments between relational expectations and ecosystem-level governance capacities, this study contributes to research on corporate social irresponsibility, interorganizational governance, and innovation ecosystem theory. The findings highlight ethical fragility and relational vulnerability as critical yet underexplored dimensions of innovation ecosystems and point to the need for policy frameworks and intermediary mechanisms that align trust with accountability in contexts of structural asymmetry.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"86 ","pages":"Article 103260"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190348","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}

{"title":"Development and validation of a scale to assess algorithmic literacy in the context of recommender systems (ALRS)","authors":"José Manuel Sotero,&nbsp;Paulo Nuno Vicente,&nbsp;António Granado","doi":"10.1016/j.techsoc.2026.103237","DOIUrl":"10.1016/j.techsoc.2026.103237","url":null,"abstract":"<div><div>Algorithmic systems, particularly recommender systems, are central to online platforms yet remain largely opaque to users. Algorithmic literacy has therefore emerged as a critical competence to foster informed and autonomous engagement, especially among younger audiences. This study developed and validated a multidimensional scale—Algorithmic Literacy in the Context of Recommender Systems (ALRS)— focused on online audiovisual entertainment platforms. An initial pool of 51 items, derived from the literature, was refined through expert content validation, cognitive interviews, and lexical review, resulting in 38 items. The instrument was tested with 1564 Portuguese students aged 15–25. Reliability analyses showed strong internal consistency (α = 0.955; ω = 0.955; Spearman-Brown = 0.881). Exploratory factor analysis identified five dimensions, and confirmatory factor analysis on an independent sample supported a second-order structure with excellent fit indices (χ²/df = 1.55; CFI = 0.991; RMSEA = 0.040). Composite reliability and average variance extracted were also satisfactory. The final 29-item ALRS scale demonstrates robust psychometric properties across five dimensions—awareness, knowledge, assessment, reflection, and practical use—offering a valid and reliable instrument to assess algorithmic literacy in the context of recommender systems, with applications in education, research, and policy.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103237"},"PeriodicalIF":12.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037444","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}