Technology in Society最新文献

{"title":"A hybrid Bayesian BWM-machine learning framework for university digital transformation assessment: Integrating expert clustering and predictive validation","authors":"Huai-Wei Lo ,&nbsp;Sheng-Wei Lin","doi":"10.1016/j.techsoc.2025.103170","DOIUrl":"10.1016/j.techsoc.2025.103170","url":null,"abstract":"<div><div>The rapid advancement of artificial intelligence–driven technologies has underscored the need for universities to undergo a comprehensive digital transformation. This study introduces a novel hybrid framework that combines the Bayesian best–worst method (BBWM) with machine learning techniques to identify and assess key success factors for university digital transformation. This study integrates expert clustering analysis and predictive modeling validation to provide enhanced decision support capabilities. Through systematic evaluation of 27 experts across 5 key dimensions—digital infrastructure, teaching and learning, research, administration and governance, and stakeholder engagement—the analysis revealed critical insights into transformation priorities. Clustering analysis identified seven distinct stakeholder assessment patterns, demonstrating significant heterogeneity in evaluation approaches across professional backgrounds and experience levels. Digital skills and literacy development emerged as the most influential factor, followed by the availability of online learning resources and the adequacy of network infrastructure. Methodological validation demonstrated exceptional convergence between the BBWM and traditional BWM (correlation coefficient: 0.9961), whereas machine learning validation confirmed the robustness of dimensional priority hierarchies through feature importance analysis. The hybrid framework achieved a ranking confidence of 70.23 % and provides stakeholder-specific insights for developing differentiated implementation strategies. This study contributes to the digital transformation literature by presenting the first integration of Bayesian inference and machine learning for university assessment, providing evidence-based frameworks to support strategic technology planning and resource allocation in an increasingly digital educational landscape.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103170"},"PeriodicalIF":12.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145623536","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":"Employment in the digital economy: Role of artificial intelligence and technological innovation","authors":"Myne Uddin ,&nbsp;Ayub Ali ,&nbsp;Abu Bakkar Siddik","doi":"10.1016/j.techsoc.2025.103171","DOIUrl":"10.1016/j.techsoc.2025.103171","url":null,"abstract":"<div><div>In the age of the digital economy, technological advancements are reshaping labor markets, creating both new opportunities and challenges. However, the impact of digitalization, particularly the roles of artificial intelligence (AI) and technological innovation (TI), on employment remains insufficiently examined. This study examines the effect of the digital economy on employment in 36 OECD countries from 2005 to 2022, focusing on the moderating roles of AI and TI, using the Driscoll-Kraay Standard Errors (DKSE) model and various robustness tests. The findings show that: (1) the digital economy enhances employment, with a stronger effect at lower employment quantiles; (2) AI and TI strengthen the digital economy's impact, although AI's direct effect is negative, while innovation's effect is positive; (3) the digital economy increases employment through political, economic, and social globalization; (4) sectoral analysis reveals that the digital economy reduces jobs in agriculture while boosting those in the service sector, and has a positively insignificant effect on the industrial sector; and (5) heterogeneity analysis indicates that the digital economy's benefits are more pronounced in highly developed, industrialized, and less urbanized countries. The study emphasizes the need for tailored policies to maximize the benefits of digitalization, address the challenges posed by AI, and ensure sustainable and equitable labor market growth.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103171"},"PeriodicalIF":12.5,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579369","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":"Hybrid global governance for responsible and inclusive Artificial Intelligence: Proposing a new Sustainable Development Goal 18","authors":"Esmat Zaidan ,&nbsp;Jon Truby ,&nbsp;Imad Antoine Ibrahim ,&nbsp;Thomas Hoppe","doi":"10.1016/j.techsoc.2025.103159","DOIUrl":"10.1016/j.techsoc.2025.103159","url":null,"abstract":"<div><div>Artificial Intelligence (AI) is increasingly recognised as a transformative force in advancing and potentially undermining, the United Nations Sustainable Development Goals (SDGs). While AI can drive innovation to benefit SDG's , it also amplifies risks such as bias, surveillance abuse, and environmental impacts. Existing governance approaches remain fragmented, with principles-based, rights-based, risk-based, and ethics-based frameworks operating in silos. This paper proposes integrating them into a hybrid governance framework by introducing a new SDG 18 on Responsible and Inclusive AI for Sustainable Development. The proposed SDG 18 can offer a politically feasible, soft-law mechanism to align AI innovation with SDGs of societal well-being, global equity and sustainability. Designed as a pervasive Goal across the SDGs, the proposal would be beneficial by embedding human-centric values, environmental stewardship, and collaborative governance into AI oversight, and seek to advance the achievement of the remaining SDGs with AI tools. The framework contributes to debates on international technology governance by providing policymakers with an adaptable tool for managing AI's cross-border impacts, promoting trust and ensuring that technological progress serves public interest.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103159"},"PeriodicalIF":12.5,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746918","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":"The relationship between worry about technological progress and job engagement - Differences by type of job characteristics","authors":"Sojin Yoon,&nbsp;Na Yeon Lee,&nbsp;Yerim Lim,&nbsp;Sehee Hong","doi":"10.1016/j.techsoc.2025.103163","DOIUrl":"10.1016/j.techsoc.2025.103163","url":null,"abstract":"<div><div>Unlike earlier waves of technological development, Industry 4.0 technologies now challenge the assumption that complex and analytical roles are less susceptible to automation. This study examines the relationship of concerns about technological progress with workers' job engagement, particularly how these vary across different job characteristics. Using data from 17,087 Korean employees, we categorized job characteristics into four types: <em>High Autonomy-Simple</em> (23.4 %), <em>Low Autonomy-Simple</em> (33.8 %), <em>High Autonomy-Complex</em> (28.8 %), and <em>Low Autonomy-Complex</em> (14.0 %). The results indicate that worry about technological progress and automation negatively relates to job engagement, with the extent of these results differing across job characteristic groups. These findings highlight the need to consider job characteristics when assessing the relationship between technological concerns and workers' job engagement. Additionally, the importance of enhancing employees' perceived usefulness and ease of use of emerging technologies to foster resilience in an evolving labor market was emphasized.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103163"},"PeriodicalIF":12.5,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579368","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":"Digital industrial agglomeration and breakthrough technological innovation: Evidence from business registration data","authors":"Hong Zhao ,&nbsp;Xiaoxi Cao ,&nbsp;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":"2025-11-13","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}

{"title":"A comparative investigation of the impact of digitalisation and work-from-home policy on firm performance: MNEs vs international SMEs","authors":"Seyed Hossein Razavi Hajiagha ,&nbsp;Hannan Amoozad Mahdiraji ,&nbsp;Maryam Behnam ,&nbsp;Jose Arturo Garza-Reyes","doi":"10.1016/j.techsoc.2025.103169","DOIUrl":"10.1016/j.techsoc.2025.103169","url":null,"abstract":"<div><div>The COVID-19 pandemic accelerated the adoption of work-from-home (WFH) practices, raising important questions about their long-term implications for organisational performance. This issue is particularly salient for multinational enterprises (MNEs) and international small and medium-sized enterprises (SMEs), where digitalisation has significantly reshaped work arrangements. This study evaluates the advantages and disadvantages of WFH and their differential impacts on MNEs and international SMEs. A comparative analysis was conducted using expert pairwise judgements, assessed through linguistic terms with weakened hedges (LTWHs) within the Best–Worst Method (BWM) framework. The LTWHs approach enables experts to articulate nuanced and flexible preferences, extending traditional linguistic scales by softening the strength of evaluations. This makes it particularly suited for capturing subjective assessments of WFH impacts under conditions of uncertainty. The findings indicate substantial variation in WFH adoption, with private sector organisations demonstrating approximately 50 % greater willingness to adopt WFH compared to public authorities. The analysis further highlights the distinct advantages and disadvantages that shape the performance outcomes of MNEs and international SMEs. By introducing a novel hesitant fuzzy linguistic preference approach, this study develops a comprehensive framework for assessing the organisational consequences of WFH. The results offer valuable insights for managers and policymakers seeking to strike a balance between flexibility, productivity, and resilience in the design of post-pandemic work strategies.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103169"},"PeriodicalIF":12.5,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579366","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":"Fintech, BigTech credit and sustainable development: International evidence","authors":"Shahzad Hussain ,&nbsp;Ajid Ur Rehman ,&nbsp;Hina Affandi ,&nbsp;Mamdouh Abdulaziz Saleh Al-Faryan ,&nbsp;Nader Naifar","doi":"10.1016/j.techsoc.2025.103160","DOIUrl":"10.1016/j.techsoc.2025.103160","url":null,"abstract":"<div><div>This research study explores the connection between financial and technological services, namely BigTech and Fintech credit and sustainable development in 85 nations. The findings show a strong and positive association between tech-enabled credit and sustainable development, although with a more substantial impact observed in developed economies than in developing ones. The study highlights how Fintech credit promotes financial inclusion, reduces the cost of transactions, and encourages investments in green technologies, thus promoting sustainable economic development. Fintech's role in enhancing access to financial services and supporting environmentally friendly investments is highlighted. These results underscore the need for forward-looking policymaking in stimulating Fintech uptake as a way of facilitating both environmental and economic sustainability. This research contributes to the body of knowledge by providing robust empirical evidence of Fintech contribution to sustainable development.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103160"},"PeriodicalIF":12.5,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579370","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":"Driving out risk: A taxonomy of factors influencing perceived safety in automated vehicles and the role of knowledge-based variation","authors":"Xinyi Wu ,&nbsp;Luca Mora ,&nbsp;Clare McTigue","doi":"10.1016/j.techsoc.2025.103164","DOIUrl":"10.1016/j.techsoc.2025.103164","url":null,"abstract":"<div><div>Despite ongoing technological advancements, public acceptance of automated vehicles (AVs) remains limited, with perceived safety (PSAV) emerging as a pivotal determinant of trust and adoption. While prior research has identified factors such as cybersecurity, legal accountability, and functional performance as influential, these elements are often examined in isolation and without a unifying framework. Furthermore, the role of individuals' Knowledge Levels of AVs (KLAV) in shaping the salience of safety concerns remains underexplored. This study addresses these gaps through a qualitative investigation involving 66 interviews with members of the public and AV experts in the United Kingdom. We develop an empirically grounded taxonomy of PSAV comprising thirteen factors, organized into three overarching categories: Technological Safety, Psychological Safety, and Social Safety. Our findings suggest that perceptions of safety are not uniform but vary with participants’ KLAV, which is associated with differences in how safety concerns are interpreted and prioritized. The study advances theoretical understanding by reconceptualizing PSAV as a multidimensional and knowledge-sensitive construct. Practically, the taxonomy and KLAV-based insights offer actionable guidance for AV research, public engagement, and anticipatory governance, supporting more inclusive and socially responsive pathways for AV deployment.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103164"},"PeriodicalIF":12.5,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527327","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":"2025-11-11","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":"A multi-dimensional FinTech composite integrating infrastructure, access, usage, knowledge transfer, and governance-by-technology: The role of digital silk road policy in BRI economies","authors":"Huma Iftikhar ,&nbsp;Luo Guang ,&nbsp;Atta Ullah","doi":"10.1016/j.techsoc.2025.103162","DOIUrl":"10.1016/j.techsoc.2025.103162","url":null,"abstract":"<div><div>This research pioneers the assessment of the progress, demand, and future potential of financial technology (FinTech) in 148 Belt and Road Initiative (BRI) countries from 2004 to 2023. For this purpose, FinTech index is constructed using Principal Component Analysis (PCA) from 19 indicators, based on five dimensions: (1) digital and technological infrastructure, (2) access to tech-enabled financial services, (3) usage of tech-enabled financial services, (4) knowledge transfer, and (5) digital governance and enabling environment. The methodological credibility and robustness of the FinTech composite were ensured by using a two-step system GMM, parallel trend analysis, difference-in-differences (DiD), and propensity score matching-difference-in-differences (PSM-DiD). In empirical analysis, “Digital Silk Road” is incorporated as a policy variable, whereas research and development, regulatory governance, tax revenue of GDP, inflation, and government spending serve as covariates. An increasing trend was observed from 2015 to 2023, implying that accelerating FinTech adoption was observed after the “Digital Silk Road” initiative of 2015, driven by demand-side pull (smartphone/e-commerce diffusion) and supply-side push (digital infrastructure and pro-FinTech regulation). Further, sub-group income- and region-wise heatmaps in Origin 2025 visually uncovered income and regional disparities in FinTech development. East Asian and European countries emerged as regional FinTech leaders, while African, particularly sub-Saharan economies, reflected weak regulatory frameworks, limited digital financial literacy, and infrastructure deficiencies. This research also serves as an analytical tool for country-wise decomposition, identifying strengths and weaknesses in FinTech adoption and highlighting areas for policy intervention. From 2015 to 2023, Korea ranked highest in BRI-FTI, followed by China and Seychelles, implying the best FinTech ecosystem, whereas Somalia, Ethiopia, and Eritrea have weak FinTech ecosystems. The research introduces new perspectives and serves as a valuable guide for governments, legislators, industries, and financial institutions for tailored policy strategies based on a country's specific development context by integrating a demand–supply lens that attributes outcomes to both consumer uptake and infrastructure/regulatory supply. The findings highlight the urgency of cross-border knowledge exchange, regulatory harmonization, and digital upskilling to bridge the divide between BRI countries. Across Belt and Road corridors, the BRI—especially the Digital Silk Road—expanded the supply of digital rails and enabled regulation while deeper trade, tourism, and platform spillovers amplified demand for cross-border payments, credit, and e-commerce.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103162"},"PeriodicalIF":12.5,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527398","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}