Pub Date : 2025-11-11DOI: 10.1016/j.techsoc.2025.103165
Yang Huang , Fangzhou Song , Chengkun Liu
Artificial intelligence (AI) innovation is central to technological progress in the digital economy, yet little is known about how different R&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&D alliances in driving AI innovation through moderation effects. These findings offer theoretical insights and practical guidance for firms leveraging R&D alliances to sustain AI innovation in fast-changing environments.
{"title":"Decoding AI innovation: How R&D alliances drive technological breakthrough","authors":"Yang Huang , Fangzhou Song , 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&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&D alliances in driving AI innovation through moderation effects. These findings offer theoretical insights and practical guidance for firms leveraging R&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}
Pub Date : 2025-11-10DOI: 10.1016/j.techsoc.2025.103162
Huma Iftikhar , Luo Guang , Atta Ullah
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.
{"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 , Luo Guang , 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}
Pub Date : 2025-11-10DOI: 10.1016/j.techsoc.2025.103158
Carlos Parra-López , Carmen Carmona-Torres
The intensification of agriculture is a primary driver of global biodiversity decline. In response, the European Union (EU) is promoting a transition towards sustainable, biodiversity-friendly agriculture. This article explores how digital/4.0 technologies — such as remote sensing, artificial intelligence, and nanotechnology — can support this transition, based on a scoping thematic literature review of 127 articles published between 2021 and 2025. The analysis identifies three potential pathways: (1) mitigating the negative impacts of intensive farming, (2) enhancing habitat and species monitoring, and (3) strengthening the knowledge base for policy and decision-making. We link these technological opportunities to EU policy objectives, highlighting the critical interplay between innovation and regulation. However, significant technical, socio-economic and environmental challenges, including data interoperability, the digital divide and potential rebound effects, hinder widespread adoption. The primary contribution of this paper is its synthesis of the technology–policy nexus in the agri-biodiversity transition, offering a structured framework for both theoretical understanding and practical application. In conclusion, realising the potential of these technologies requires interdisciplinary collaboration, targeted policy support and proactive risk management, ensuring that technological advancements genuinely contribute to biodiversity conservation. The EU's experience can inform future policies by providing insights for reconciling agricultural production with biodiversity on a global scale.
{"title":"The role of digital/4.0 technologies in the agri-biodiversity transition: Potential pathways and lessons from the European Union","authors":"Carlos Parra-López , Carmen Carmona-Torres","doi":"10.1016/j.techsoc.2025.103158","DOIUrl":"10.1016/j.techsoc.2025.103158","url":null,"abstract":"<div><div>The intensification of agriculture is a primary driver of global biodiversity decline. In response, the European Union (EU) is promoting a transition towards sustainable, biodiversity-friendly agriculture. This article explores how digital/4.0 technologies — such as remote sensing, artificial intelligence, and nanotechnology — can support this transition, based on a scoping thematic literature review of 127 articles published between 2021 and 2025. The analysis identifies three potential pathways: (1) mitigating the negative impacts of intensive farming, (2) enhancing habitat and species monitoring, and (3) strengthening the knowledge base for policy and decision-making. We link these technological opportunities to EU policy objectives, highlighting the critical interplay between innovation and regulation. However, significant technical, socio-economic and environmental challenges, including data interoperability, the digital divide and potential rebound effects, hinder widespread adoption. The primary contribution of this paper is its synthesis of the technology–policy nexus in the agri-biodiversity transition, offering a structured framework for both theoretical understanding and practical application. In conclusion, realising the potential of these technologies requires interdisciplinary collaboration, targeted policy support and proactive risk management, ensuring that technological advancements genuinely contribute to biodiversity conservation. The EU's experience can inform future policies by providing insights for reconciling agricultural production with biodiversity on a global scale.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103158"},"PeriodicalIF":12.5,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527399","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}
Pub Date : 2025-11-10DOI: 10.1016/j.techsoc.2025.103157
Feng Wu , Jin Chen , Yue Tang , Yanwei Zhang
This study extends the concept of open innovation from the firm level to regional innovation ecosystems by integrating social-ecological system insights and operationalizing a 3D index architecture covering basic innovation capacity, open innovation capacity, and innovation adaptability. Using a projection pursuit model optimized by a real-coded accelerating genetic algorithm (RAGA-PPM), kernel density estimation, and spatial correlation analysis, we evaluate the regional innovation capacity of 31 Chinese provinces from 2011 to 2021 and examine their spatiotemporal evolution. Results indicate that innovation adaptability carries the largest and most stable weight among Level 1 dimensions, indicating that coordination, learning, and risk absorption routines increasingly shape how inputs and openness translate into outcomes. Spatially, Beijing–Tianjin–Hebei, the Bohai Rim, the Yangtze River Delta, and the Pearl River Delta all exhibit strong capacity but heterogeneous integration, with tighter coupling in Shanghai–Jiangsu–Zhejiang–Anhui. Globally and locally, positive spatial correlations follow a pattern of initial decline and subsequent increase; local high-high clusters contract overall, with apparent weakening in the north, stronger integration in the east, and improvements around the southwest. Methodologically, RAGA-PPM improves sensitivity to nonlinear, multimodal structures and yields temporally coherent measures compared with entropy-based baselines. Furthermore, policy translation is specified along three tracks: capability formation for adaptability, orchestration of cross-regional collaboration, and demand-side measures to enhance absorption, each with concrete instruments for provincial implementation. The findings of the study advance the integration of open innovation and regional innovation systems as well as provide actionable guidance for differentiated public policies.
{"title":"Spatiotemporal evolution of regional innovation capacity from an open innovation perspective","authors":"Feng Wu , Jin Chen , Yue Tang , Yanwei Zhang","doi":"10.1016/j.techsoc.2025.103157","DOIUrl":"10.1016/j.techsoc.2025.103157","url":null,"abstract":"<div><div>This study extends the concept of open innovation from the firm level to regional innovation ecosystems by integrating social-ecological system insights and operationalizing a 3D index architecture covering basic innovation capacity, open innovation capacity, and innovation adaptability. Using a projection pursuit model optimized by a real-coded accelerating genetic algorithm (RAGA-PPM), kernel density estimation, and spatial correlation analysis, we evaluate the regional innovation capacity of 31 Chinese provinces from 2011 to 2021 and examine their spatiotemporal evolution. Results indicate that innovation adaptability carries the largest and most stable weight among Level 1 dimensions, indicating that coordination, learning, and risk absorption routines increasingly shape how inputs and openness translate into outcomes. Spatially, Beijing–Tianjin–Hebei, the Bohai Rim, the Yangtze River Delta, and the Pearl River Delta all exhibit strong capacity but heterogeneous integration, with tighter coupling in Shanghai–Jiangsu–Zhejiang–Anhui. Globally and locally, positive spatial correlations follow a pattern of initial decline and subsequent increase; local high-high clusters contract overall, with apparent weakening in the north, stronger integration in the east, and improvements around the southwest. Methodologically, RAGA-PPM improves sensitivity to nonlinear, multimodal structures and yields temporally coherent measures compared with entropy-based baselines. Furthermore, policy translation is specified along three tracks: capability formation for adaptability, orchestration of cross-regional collaboration, and demand-side measures to enhance absorption, each with concrete instruments for provincial implementation. The findings of the study advance the integration of open innovation and regional innovation systems as well as provide actionable guidance for differentiated public policies.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103157"},"PeriodicalIF":12.5,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527329","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}
Pub Date : 2025-11-08DOI: 10.1016/j.techsoc.2025.103156
Shuai Che , Chen Liu , Jie Wang , Jun Wang
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.
{"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":"2025-11-08","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}
Pub Date : 2025-11-07DOI: 10.1016/j.techsoc.2025.103155
Bingbing Liu
While digitalization is increasingly recognized as a critical driver of competitive advantage, existing literature has predominantly examined its impact on supply chain resilience and efficiency, with limited attention to its spillover effects across supply chains. This study addresses this gap by introducing the supply chain spillover perspective to investigate how digital transformation (DT) in focal firms influences their customers' technological innovation. We also analyze the direct and indirect mechanisms through which this effect occurs. Using panel data from Chinese listed companies (2018–2023), we employ a two-way fixed effects model and a Probit model to assess the impact of focal firms' DT on customers' innovation input and output probabilities. Our results indicate that focal firms’ DT significantly enhances their customers' innovation input and output. Grounded in signaling theory, open innovation, and market competition theories, we find that alleviating financing constraints, fostering cooperative innovation, and intensifying industry competition are main indirect impact mechanisms. Heterogeneity analyses reveal that the effect is more pronounced in industries with higher levels of digitalization, among state-owned enterprises in terms of innovation input and private firms in terms of output, as well as among market-leading firms and within supply chains characterized by stronger inter-firm linkages. Our findings suggest that managers should formulate DT strategies from an industrial chain perspective, enhancing their technological innovation capabilities by establishing deep collaborative relationships with supply chain partners and actively participating in digital innovation platforms.
{"title":"The ripple effect: Does digital transformation spark enterprises' technological innovation in supply chains?","authors":"Bingbing Liu","doi":"10.1016/j.techsoc.2025.103155","DOIUrl":"10.1016/j.techsoc.2025.103155","url":null,"abstract":"<div><div>While digitalization is increasingly recognized as a critical driver of competitive advantage, existing literature has predominantly examined its impact on supply chain resilience and efficiency, with limited attention to its spillover effects across supply chains. This study addresses this gap by introducing the supply chain spillover perspective to investigate how digital transformation (DT) in focal firms influences their customers' technological innovation. We also analyze the direct and indirect mechanisms through which this effect occurs. Using panel data from Chinese listed companies (2018–2023), we employ a two-way fixed effects model and a Probit model to assess the impact of focal firms' DT on customers' innovation input and output probabilities. Our results indicate that focal firms’ DT significantly enhances their customers' innovation input and output. Grounded in signaling theory, open innovation, and market competition theories, we find that alleviating financing constraints, fostering cooperative innovation, and intensifying industry competition are main indirect impact mechanisms. Heterogeneity analyses reveal that the effect is more pronounced in industries with higher levels of digitalization, among state-owned enterprises in terms of innovation input and private firms in terms of output, as well as among market-leading firms and within supply chains characterized by stronger inter-firm linkages. Our findings suggest that managers should formulate DT strategies from an industrial chain perspective, enhancing their technological innovation capabilities by establishing deep collaborative relationships with supply chain partners and actively participating in digital innovation platforms.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103155"},"PeriodicalIF":12.5,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527328","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}
Pub Date : 2025-11-04DOI: 10.1016/j.techsoc.2025.103147
Tomislav Hernaus , Matej Černe , Aleša Saša Sitar , Matija Marić , Sara Melkić
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.
{"title":"Contextualizing job design for individual work performance: The role of organizational strategy and structure","authors":"Tomislav Hernaus , Matej Černe , Aleša Saša Sitar , Matija Marić , 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":"2025-11-04","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}
Pub Date : 2025-11-04DOI: 10.1016/j.techsoc.2025.103145
Hang Zhou , Zihao Liu , Chengjie Huang
Driven by the rapid development of digital economy, corporate digital transformation has become a key strategy for gaining competitive advantages. However, substantive transformation often requires substantial investment. Facing resource constraints, some enterprises engage in digital washing, shaping an advanced image through selective disclosure of digital transformation information with less substantive investment. Based on an integrated framework of signaling theory and resource dependence theory, this study uses Chinese A-share listed companies from 2007 to 2023 as the sample and employs a two-way fixed effects model to examine the relationship between digital washing and corporate innovation. This study finds: (1) digital washing significantly promotes corporate innovation; (2) digital washing primarily enhances corporate innovation through two pathways: attracting R&D personnel and promoting strategic alliance construction; (3) under high market competition environments and when the proportion of directors with R&D background on the board is higher, the promotional effect of digital washing on corporate innovation is more significant. After multiple robustness tests including instrumental variable method and propensity score matching method, the above results remain valid. The research reveals that digital washing is not simply opportunistic behavior, but has intertemporal strategic value. Enterprises acquire external resources through a “say first, do later” strategy and transform them into substantive innovation. This finding provides important insights for enterprise management practices, investor decision-making, and regulatory policy formulation.
{"title":"Fake it till you make it: Digital washing and corporate innovation","authors":"Hang Zhou , Zihao Liu , Chengjie Huang","doi":"10.1016/j.techsoc.2025.103145","DOIUrl":"10.1016/j.techsoc.2025.103145","url":null,"abstract":"<div><div>Driven by the rapid development of digital economy, corporate digital transformation has become a key strategy for gaining competitive advantages. However, substantive transformation often requires substantial investment. Facing resource constraints, some enterprises engage in digital washing, shaping an advanced image through selective disclosure of digital transformation information with less substantive investment. Based on an integrated framework of signaling theory and resource dependence theory, this study uses Chinese A-share listed companies from 2007 to 2023 as the sample and employs a two-way fixed effects model to examine the relationship between digital washing and corporate innovation. This study finds: (1) digital washing significantly promotes corporate innovation; (2) digital washing primarily enhances corporate innovation through two pathways: attracting R&D personnel and promoting strategic alliance construction; (3) under high market competition environments and when the proportion of directors with R&D background on the board is higher, the promotional effect of digital washing on corporate innovation is more significant. After multiple robustness tests including instrumental variable method and propensity score matching method, the above results remain valid. The research reveals that digital washing is not simply opportunistic behavior, but has intertemporal strategic value. Enterprises acquire external resources through a “say first, do later” strategy and transform them into substantive innovation. This finding provides important insights for enterprise management practices, investor decision-making, and regulatory policy formulation.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103145"},"PeriodicalIF":12.5,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468965","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}
Pub Date : 2025-11-04DOI: 10.1016/j.techsoc.2025.103146
Zhen Han , Erga Luo , Xuezhen Xiong , Jinkai Li
Government innovation subsidies have become a key policy instrument for fostering enterprise innovation and accelerating digital transformation. However, their effectiveness in promoting digital transformation remains insufficiently understood, particularly in emerging economies. Using panel data from Chinese A-share listed enterprises from 2010 to 2021, this study examines how government innovation subsidies influence digital transformation. The results show that such subsidies significantly enhance enterprise digital transformation. Mechanism analysis reveals that subsidies operate through both resource and signaling effects—strengthening R&D investment, expanding technical staff, and accumulating digital assets, while increasing managerial digital attention and market recognition. Furthermore, heterogeneity analysis indicates that the effect is more pronounced for state-owned and small enterprises, as well as those in earlier life-cycle stages. These findings provide evidence that targeted innovation subsidies can serve as effective policy tools for promoting digital transformation, offering practical insights for designing adaptive and differentiated innovation policies in both emerging and advanced economies.
{"title":"Government innovation subsidies and enterprise digital transformation: Evidence from Chinese listed companies","authors":"Zhen Han , Erga Luo , Xuezhen Xiong , Jinkai Li","doi":"10.1016/j.techsoc.2025.103146","DOIUrl":"10.1016/j.techsoc.2025.103146","url":null,"abstract":"<div><div>Government innovation subsidies have become a key policy instrument for fostering enterprise innovation and accelerating digital transformation. However, their effectiveness in promoting digital transformation remains insufficiently understood, particularly in emerging economies. Using panel data from Chinese A-share listed enterprises from 2010 to 2021, this study examines how government innovation subsidies influence digital transformation. The results show that such subsidies significantly enhance enterprise digital transformation. Mechanism analysis reveals that subsidies operate through both resource and signaling effects—strengthening R&D investment, expanding technical staff, and accumulating digital assets, while increasing managerial digital attention and market recognition. Furthermore, heterogeneity analysis indicates that the effect is more pronounced for state-owned and small enterprises, as well as those in earlier life-cycle stages. These findings provide evidence that targeted innovation subsidies can serve as effective policy tools for promoting digital transformation, offering practical insights for designing adaptive and differentiated innovation policies in both emerging and advanced economies.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"84 ","pages":"Article 103146"},"PeriodicalIF":12.5,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466481","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}
Pub Date : 2025-11-04DOI: 10.1016/j.techsoc.2025.103144
Qinwen Deng
Amid the global wave of digital and intelligent transformation, Digital-Intelligent Regional Innovation Ecosystem Sustainability (DIRGIES) has become vital for promoting innovation, enhancing resilience, and overcoming growth bottlenecks. Grounded in symbiosis theory, this study develops a five-dimensional evaluation framework, which includes units, matrix, community, network, and environment. By integrating the CRITIC-TOPSIS method, spatial econometrics, and dynamic QCA, it systematically examines the spatiotemporal evolution and configuration pathways of DIRGIES across Chinese provinces from 2011 to 2023. The findings reveal that DIRGIES in China exhibit a spatial divergence pattern characterized by strong performance in the eastern region and weaker performance in the west; however, with the widespread adoption of digital technologies and deepening policy coordination, spatial dependence has weakened and network-based collaboration has intensified. Dynamic QCA identifies four configurations associated with high DIRGIES and four associated with low DIRGIES, highlighting the complex, nonlinear, and synergistic causal mechanisms among multiple factors. Digital-intelligent technologies significantly enhance system resilience by reconfiguring resource allocation, optimizing network structures, and strengthening environmental adaptability. Based on these insights, this study proposes a stratified, differentiated, and dynamically adaptive policy framework that provides a theoretical foundation and practical guidance for differentiated regional governance.
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