Pub Date : 2025-12-08DOI: 10.1016/j.techsoc.2025.103191
Tangjie Huang , Wei Zhang, Shiqi Ye
The rapid advancement of disruptive technologies has open new pathways for innovation and urban safety enhancement. Drawing on panel data from 30 Chinese provinces between 2011 and 2020, this study constructs a composite index to measure disruptive technologies levels and employs a Spatial Durbin Model to explore their relationships with municipal infrastructure capacity, education investment, and urban safety. The findings show that disruptive technologies significantly improve urban safety, but also introduce a negative spatial spillover effect. Municipal infrastructure capacity serves as a key channel through which these technologies influence safety, while education investment strengthens the relationship between infrastructure capacity and safety outcomes. These findings highlight the dual-edged nature of technological disruption and emphasize the importance of coordinated governance. Policymakers should foster balanced technological diffusion, strengthen infrastructure resilience, and invest in education to ensure that technological progress effectively contributes to sustainable urban development and safety.
{"title":"How disruptive technologies reshape urban safety: Spatial spillovers and governance mechanisms in China","authors":"Tangjie Huang , Wei Zhang, Shiqi Ye","doi":"10.1016/j.techsoc.2025.103191","DOIUrl":"10.1016/j.techsoc.2025.103191","url":null,"abstract":"<div><div>The rapid advancement of disruptive technologies has open new pathways for innovation and urban safety enhancement. Drawing on panel data from 30 Chinese provinces between 2011 and 2020, this study constructs a composite index to measure disruptive technologies levels and employs a Spatial Durbin Model to explore their relationships with municipal infrastructure capacity, education investment, and urban safety. The findings show that disruptive technologies significantly improve urban safety, but also introduce a negative spatial spillover effect. Municipal infrastructure capacity serves as a key channel through which these technologies influence safety, while education investment strengthens the relationship between infrastructure capacity and safety outcomes. These findings highlight the dual-edged nature of technological disruption and emphasize the importance of coordinated governance. Policymakers should foster balanced technological diffusion, strengthen infrastructure resilience, and invest in education to ensure that technological progress effectively contributes to sustainable urban development and safety.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103191"},"PeriodicalIF":12.5,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747112","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}
Generative artificial intelligence (generative AI) plays a vital role in developing productivity, while also reshaping the way workers work and bringing about career shock. This research aims at enriching the understanding of factors influencing workers' attitudes toward generative AI and its underlying mechanism. According to elaboration likelihood model (ELM), usage experience as elaborated information is processed through the central route, shaping attitudes and perceptions. We conducted five studies including experiments and questionnaire surveys. The results demonstrate that: (1) worker's usage experience of generative AI is positively related to their overall evaluations of generative AI; (2) the relationship between usage experience and overall evaluation is mediated by assist-perception rather than substitute-perception; (3) creative self-efficacy can moderate the relationship between usage experience and overall evaluation, as well as the indirect effect path of assist-perception; (4) Employability can moderate the relationship between usage experience and overall evaluation. For workers with low creative self-efficacy and low employability, usage experience does not improve their overall evaluation. Theoretically, this study extends the understanding of antecedents that shape workers' attitudes toward generative AI and identifies the relative independence of perceived assistance and substitution. It practically offers managerial recommendations for addressing the opportunities and challenges posed by generative AI. Future research may build on this work by further exploring how usage experience influences perceptions across different technological and occupational contexts.
{"title":"Assist or substitute? The influential mechanism of worker's usage experience on their overall evaluation of generative artificial intelligence","authors":"Boyang Zheng , Chunqu Xiao , Yayu Zhou , Lei Wu , Hongyong Zhou","doi":"10.1016/j.techsoc.2025.103190","DOIUrl":"10.1016/j.techsoc.2025.103190","url":null,"abstract":"<div><div>Generative artificial intelligence (generative AI) plays a vital role in developing productivity, while also reshaping the way workers work and bringing about career shock. This research aims at enriching the understanding of factors influencing workers' attitudes toward generative AI and its underlying mechanism. According to elaboration likelihood model (ELM), usage experience as elaborated information is processed through the central route, shaping attitudes and perceptions. We conducted five studies including experiments and questionnaire surveys. The results demonstrate that: (1) worker's usage experience of generative AI is positively related to their overall evaluations of generative AI; (2) the relationship between usage experience and overall evaluation is mediated by assist-perception rather than substitute-perception; (3) creative self-efficacy can moderate the relationship between usage experience and overall evaluation, as well as the indirect effect path of assist-perception; (4) Employability can moderate the relationship between usage experience and overall evaluation. For workers with low creative self-efficacy and low employability, usage experience does not improve their overall evaluation. Theoretically, this study extends the understanding of antecedents that shape workers' attitudes toward generative AI and identifies the relative independence of perceived assistance and substitution. It practically offers managerial recommendations for addressing the opportunities and challenges posed by generative AI. Future research may build on this work by further exploring how usage experience influences perceptions across different technological and occupational contexts.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103190"},"PeriodicalIF":12.5,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746921","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 : 2025-12-03DOI: 10.1016/j.techsoc.2025.103188
Luca Cacciolatti , Soo Hee Lee , Michael Christofi , Ioannis Christodoulou , Su Ha Van
This study develops a conceptual framework to theorise how digitally augmented Communities of Practice (CoPs), such as the Slow Food Movement, can support sustainable food systems transformation through advanced knowledge management. Although digital innovation is increasingly applied in agri-food systems, much of the literature remains technocentric, focusing on infrastructure and automation, while overlooking how digital tools mediate community-based knowledge flows and adaptive capabilities. Addressing this gap, we integrate Nonaka and Takeuchi's SECI model with Teece's dynamic capabilities framework to examine how Artificial Intelligence (AI) and Metaverse technologies enable CoPs to create, share, and transform knowledge.
The main contribution is the DEKA-CoPs model (Digitally Enabled Knowledge Architecture in Communities of Practice), which explains how digital mediation can enhance epistemic agility, collaborative innovation, and system adaptability. Methodologically, the paper uses a theory-building approach to develop four propositions that can guide future empirical work.
This framework advances knowledge management and sustainability literature by shifting the focus from firm-based innovation to digitally enabled, community-led knowledge infrastructures. It offers practical implications for policymakers, technologists, and sustainability practitioners interested in designing inclusive, adaptive platforms that embed local knowledge in agri-food transitions.
{"title":"Digital communities of practice and the knowledge transformation cycle: Enabling sustainable food systems through AI and Metaverse technologies","authors":"Luca Cacciolatti , Soo Hee Lee , Michael Christofi , Ioannis Christodoulou , Su Ha Van","doi":"10.1016/j.techsoc.2025.103188","DOIUrl":"10.1016/j.techsoc.2025.103188","url":null,"abstract":"<div><div>This study develops a conceptual framework to theorise how digitally augmented Communities of Practice (CoPs), such as the Slow Food Movement, can support sustainable food systems transformation through advanced knowledge management. Although digital innovation is increasingly applied in agri-food systems, much of the literature remains technocentric, focusing on infrastructure and automation, while overlooking how digital tools mediate community-based knowledge flows and adaptive capabilities. Addressing this gap, we integrate Nonaka and Takeuchi's SECI model with Teece's dynamic capabilities framework to examine how Artificial Intelligence (AI) and Metaverse technologies enable CoPs to create, share, and transform knowledge.</div><div>The main contribution is the DEKA-CoPs model (Digitally Enabled Knowledge Architecture in Communities of Practice), which explains how digital mediation can enhance epistemic agility, collaborative innovation, and system adaptability. Methodologically, the paper uses a theory-building approach to develop four propositions that can guide future empirical work.</div><div>This framework advances knowledge management and sustainability literature by shifting the focus from firm-based innovation to digitally enabled, community-led knowledge infrastructures. It offers practical implications for policymakers, technologists, and sustainability practitioners interested in designing inclusive, adaptive platforms that embed local knowledge in agri-food transitions.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103188"},"PeriodicalIF":12.5,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747701","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 : 2025-12-01DOI: 10.1016/j.techsoc.2025.103186
Muhammad Sadiq , Ka Yin Chau , Massoud Moslehpour , Ivan Brezina , Mei Kei Leong
The study explores how digital platform integration, innovation network strength, and institutional support for sustainability affect the circular economy adoption (CEA) through innovation ecosystem dynamism (IED), where digital transformation readiness (DTR) acts as a moderator in Cambodia and Vietnam. A cross-sectional quantitative method was used to gather information from 900 respondents, 450 each from country. Findings denote that digital platform, innovation networks, and institutional support have a significant effect on IED, which consequently enhances CEA. DTR enhances these relations directly and indirectly, which demonstrates its significance in circular transformation. The comparisons across countries demonstrate that there are differences in contexts related to a circular economy transition. The effects on CEA in Vietnam are more consistent across all paths and, as a result, the effect of digital platform and IED is stronger. The mediating role of innovation network and institutional support on IED is greater in Vietnam because of the moderation of DTR. The relationship and moderation effect in Cambodia are significantly lower, but not negligible, which suggests that there are discrepancies in structural and digital readiness. These contextual differences indicate how digital and institutional maturity can shape the resource orchestration towards sustainability. The research advances theory by integrating digital transformation, innovation ecosystems, and institutional support into a new, moderated mediation framework. In Vietnam, policymakers and managers should take advantage of more advanced digital platforms and stable policies to accelerate CEA. In Cambodia, investment in digital infrastructure and institutional support is essential to overcome structural barriers and boost CEA. As one of the first empirical studies using a moderated mediation model in trans-country Southeast Asia, this research demonstrates how digital preparedness shapes circular transitions.
{"title":"Digital platforms, innovation networks, and institutional support in circular economy adoption: A moderated mediation analysis in Emerging Economies","authors":"Muhammad Sadiq , Ka Yin Chau , Massoud Moslehpour , Ivan Brezina , Mei Kei Leong","doi":"10.1016/j.techsoc.2025.103186","DOIUrl":"10.1016/j.techsoc.2025.103186","url":null,"abstract":"<div><div>The study explores how digital platform integration, innovation network strength, and institutional support for sustainability affect the circular economy adoption (CEA) through innovation ecosystem dynamism (IED), where digital transformation readiness (DTR) acts as a moderator in Cambodia and Vietnam. A cross-sectional quantitative method was used to gather information from 900 respondents, 450 each from country. Findings denote that digital platform, innovation networks, and institutional support have a significant effect on IED, which consequently enhances CEA. DTR enhances these relations directly and indirectly, which demonstrates its significance in circular transformation. The comparisons across countries demonstrate that there are differences in contexts related to a circular economy transition. The effects on CEA in Vietnam are more consistent across all paths and, as a result, the effect of digital platform and IED is stronger. The mediating role of innovation network and institutional support on IED is greater in Vietnam because of the moderation of DTR. The relationship and moderation effect in Cambodia are significantly lower, but not negligible, which suggests that there are discrepancies in structural and digital readiness. These contextual differences indicate how digital and institutional maturity can shape the resource orchestration towards sustainability. The research advances theory by integrating digital transformation, innovation ecosystems, and institutional support into a new, moderated mediation framework. In Vietnam, policymakers and managers should take advantage of more advanced digital platforms and stable policies to accelerate CEA. In Cambodia, investment in digital infrastructure and institutional support is essential to overcome structural barriers and boost CEA. As one of the first empirical studies using a moderated mediation model in trans-country Southeast Asia, this research demonstrates how digital preparedness shapes circular transitions.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103186"},"PeriodicalIF":12.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145690542","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 : 2025-12-01DOI: 10.1016/j.techsoc.2025.103187
Salman Hamid , Ke Wang , Xiang Zhang
In recent times, the global environmental repercussions have intensified the imminent threat of global warming and climate change. In response, implementing innovative approaches and sustainable practices for ecological preservation remains a considerable challenge even for developed nations, such as G7. It is therefore inevitable to identify key factors driving the progress of environmental sustainability. Motivated by this, the current research is an earliest attempt which delve the impact of artificial intelligence (AI), eco-innovation efficiency (EIE), environmental policy stringency (EPS), and green growth (GG) on load capacity factor (LCF) under the load capacity curve (LCC) framework to achieve environmental sustainability in G7 countries. In this regard, innovative approaches of Driscoll-Kraay standard errors (DKSE) and panel-corrected standard errors (PCSE) are employed to investigate the long-run relationships, using the data from 1990 to 2020. The findings highlight that: (i) eco-innovation efficiency primarily promotes environmental sustainability by improving load capacity factor, which is advantageous for G7 countries; (ii) artificial intelligence, environmental policy stringency, and green growth inhabits environmental sustainability by decreasing load capacity factor, which are detrimental for G7 countries; (iii) the LCC hypothesis is invalid in G7 countries illustrating an inverted “U-shaped” relationship between income and LCF. This implies that economic growth initially improves environmental sustainability but later deteriorates the environment after reaching a certain threshold. These findings emphasize that decision-makers should restructure energy and environmental policies for G7 countries by prioritizing AI technologies, augmenting stringent environmental policies, implementing clean energy initiatives, and decoupling economic growth and resource consumption along with further strengthening ecologically efficient technologies.
{"title":"Unraveling the role of artificial intelligence, eco-innovation efficiency, and stringent environmental policies in environmental sustainability: Is the load capacity curve hypothesis true in G7 economies?","authors":"Salman Hamid , Ke Wang , Xiang Zhang","doi":"10.1016/j.techsoc.2025.103187","DOIUrl":"10.1016/j.techsoc.2025.103187","url":null,"abstract":"<div><div>In recent times, the global environmental repercussions have intensified the imminent threat of global warming and climate change. In response, implementing innovative approaches and sustainable practices for ecological preservation remains a considerable challenge even for developed nations, such as G7. It is therefore inevitable to identify key factors driving the progress of environmental sustainability. Motivated by this, the current research is an earliest attempt which delve the impact of artificial intelligence (AI), eco-innovation efficiency (EIE), environmental policy stringency (EPS), and green growth (GG) on load capacity factor (LCF) under the load capacity curve (LCC) framework to achieve environmental sustainability in G7 countries. In this regard, innovative approaches of Driscoll-Kraay standard errors (DKSE) and panel-corrected standard errors (PCSE) are employed to investigate the long-run relationships, using the data from 1990 to 2020. The findings highlight that: (i) eco-innovation efficiency primarily promotes environmental sustainability by improving load capacity factor, which is advantageous for G7 countries; (ii) artificial intelligence, environmental policy stringency, and green growth inhabits environmental sustainability by decreasing load capacity factor, which are detrimental for G7 countries; (iii) the LCC hypothesis is invalid in G7 countries illustrating an inverted “U-shaped” relationship between income and LCF. This implies that economic growth initially improves environmental sustainability but later deteriorates the environment after reaching a certain threshold. These findings emphasize that decision-makers should restructure energy and environmental policies for G7 countries by prioritizing AI technologies, augmenting stringent environmental policies, implementing clean energy initiatives, and decoupling economic growth and resource consumption along with further strengthening ecologically efficient technologies.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103187"},"PeriodicalIF":12.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145690543","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 : 2025-11-29DOI: 10.1016/j.techsoc.2025.103183
Bennet Francis , Tynke Schepers , Andrea Porcari , Philip Brey
This paper introduces the Societal Readiness Tool (SRT), an approach that supports actors in product design and innovation in aligning product development with societal needs and expectations. The tool serves two functions. First, it provides guidance for developers, enabling them to navigate the product development process in a manner that builds in ethical, legal and social impact considerations from the very earliest stages. Second, the tool enables developers and other stakeholders to conduct qualitative self-assessments of the societal readiness level of a product. The substantive claim embodied by the tool is that technical and commercial readiness of new products should be supplemented by societal readiness, which is accomplished by embedding concern for ethical, legal and social impacts in product development.
{"title":"A societal readiness tool for responsible product innovation","authors":"Bennet Francis , Tynke Schepers , Andrea Porcari , Philip Brey","doi":"10.1016/j.techsoc.2025.103183","DOIUrl":"10.1016/j.techsoc.2025.103183","url":null,"abstract":"<div><div>This paper introduces the Societal Readiness Tool (SRT), an approach that supports actors in product design and innovation in aligning product development with societal needs and expectations. The tool serves two functions. First, it provides guidance for developers, enabling them to navigate the product development process in a manner that builds in ethical, legal and social impact considerations from the very earliest stages. Second, the tool enables developers and other stakeholders to conduct qualitative self-assessments of the societal readiness level of a product. The substantive claim embodied by the tool is that technical and commercial readiness of new products should be supplemented by societal readiness, which is accomplished by embedding concern for ethical, legal and social impacts in product development.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103183"},"PeriodicalIF":12.5,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746920","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 : 2025-11-29DOI: 10.1016/j.techsoc.2025.103185
Huwei Wen , Chunyun Qiao , Xuan-Hoa Nghiem
The intensification of climate vulnerability severely constrains the long-term viability of human societies, and the digital economy is a key pathway for mitigating its negative impacts. This study examines the impact of climate vulnerability on inclusive green growth (IGG) using cross-national panel data from 2013 to 2023 and tests the moderating effect of the digital economy. The results indicate that heightened climate vulnerability significantly inhibits IGG, and this conclusion remains robust after adjusting the model settings and sample scope and addressing endogeneity issues. Mechanistic analysis reveals that climate vulnerability primarily hinders IGG by suppressing energy structure transition and weakening social equity. Moderation effect analysis reveals that the digital economy can mitigate the adverse impacts of climate shocks on IGG. However, the panel threshold model results indicate that the moderation strength does not significantly differ on either side of the digital economy threshold value. The limited mixed regression models can effectively capture the moderating effects of the digital economy and indicate that its mitigating role continues to strengthen as the digital economy develops. This study offers policymakers critical empirical support and actionable policy insights to address climate challenges and advance IGG.
{"title":"Does the digital economy moderate the climate vulnerability-inclusive green growth nexus? International evidence","authors":"Huwei Wen , Chunyun Qiao , Xuan-Hoa Nghiem","doi":"10.1016/j.techsoc.2025.103185","DOIUrl":"10.1016/j.techsoc.2025.103185","url":null,"abstract":"<div><div>The intensification of climate vulnerability severely constrains the long-term viability of human societies, and the digital economy is a key pathway for mitigating its negative impacts. This study examines the impact of climate vulnerability on inclusive green growth (IGG) using cross-national panel data from 2013 to 2023 and tests the moderating effect of the digital economy. The results indicate that heightened climate vulnerability significantly inhibits IGG, and this conclusion remains robust after adjusting the model settings and sample scope and addressing endogeneity issues. Mechanistic analysis reveals that climate vulnerability primarily hinders IGG by suppressing energy structure transition and weakening social equity. Moderation effect analysis reveals that the digital economy can mitigate the adverse impacts of climate shocks on IGG. However, the panel threshold model results indicate that the moderation strength does not significantly differ on either side of the digital economy threshold value. The limited mixed regression models can effectively capture the moderating effects of the digital economy and indicate that its mitigating role continues to strengthen as the digital economy develops. This study offers policymakers critical empirical support and actionable policy insights to address climate challenges and advance IGG.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103185"},"PeriodicalIF":12.5,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145690545","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 : 2025-11-29DOI: 10.1016/j.techsoc.2025.103181
Shouxiang Qiu , Bingjie Li , Zhao Duan
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.
{"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":"2025-11-29","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}
Pub Date : 2025-11-28DOI: 10.1016/j.techsoc.2025.103184
Jun-Hong Du , Meng-Nan Tian , Zhi-Liang Yang
The harmonious coexistence of robots and the workforce in the era of artificial intelligence is crucial for China's high-quality economic development and the promotion of Chinese-style modernization. This study constructs an estimation method for the elasticity of substitution based on a nested CES production function model with three factors. By utilizing manufacturing data from 2006 to 2019 in China and robot data from the International Federation of Robotics (IFR), we estimate the elasticity of substitution between robots and labor. The research findings indicate that there is a complementary relationship between robots and labor in China's manufacturing sector, and that the combination of robots and labor is also complementary with nested capital. However, across manufacturing sub-sectors, the elasticity of substitution between robots and labor exceeds unity in some industries (classified as substitution industries) and falls below unity in others (complementary industries). Moreover, robot adoption exerts a significant crowding-out effect on labor in substitution industries, whereas its impact remains statistically insignificant in complementary industries. By estimating substitution elasticities, this study provides compelling evidence of a strong symbiotic relationship between robot deployment and employment. These findings offer policymakers in the AI era valuable insights to promote high-quality, inclusive employment in the manufacturing sector.
{"title":"How can robots coexist with labor employment?—Empirical evidence based on matching data of Chinese industrial robots","authors":"Jun-Hong Du , Meng-Nan Tian , Zhi-Liang Yang","doi":"10.1016/j.techsoc.2025.103184","DOIUrl":"10.1016/j.techsoc.2025.103184","url":null,"abstract":"<div><div>The harmonious coexistence of robots and the workforce in the era of artificial intelligence is crucial for China's high-quality economic development and the promotion of Chinese-style modernization. This study constructs an estimation method for the elasticity of substitution based on a nested CES production function model with three factors. By utilizing manufacturing data from 2006 to 2019 in China and robot data from the International Federation of Robotics (IFR), we estimate the elasticity of substitution between robots and labor. The research findings indicate that there is a complementary relationship between robots and labor in China's manufacturing sector, and that the combination of robots and labor is also complementary with nested capital. However, across manufacturing sub-sectors, the elasticity of substitution between robots and labor exceeds unity in some industries (classified as substitution industries) and falls below unity in others (complementary industries). Moreover, robot adoption exerts a significant crowding-out effect on labor in substitution industries, whereas its impact remains statistically insignificant in complementary industries. By estimating substitution elasticities, this study provides compelling evidence of a strong symbiotic relationship between robot deployment and employment. These findings offer policymakers in the AI era valuable insights to promote high-quality, inclusive employment in the manufacturing sector.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103184"},"PeriodicalIF":12.5,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746919","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 : 2025-11-27DOI: 10.1016/j.techsoc.2025.103182
Adriaan Lombard , Stephen Flowerday , John Hale
The growing adoption of emotionally adaptive Artificial Intelligence (AI) companionship applications raises critical concerns about privacy, emotional dependency, and behavioural susceptibility. These systems provide affective gratification while relying on continuous data tracking, generating tension between intimacy and surveillance. This study investigates how users’ understanding of tracking mechanisms, perceived risks, and perceived benefits jointly shape susceptibility, which is behavioural susceptibility to AI influence. Integrating cognitive dissonance theory, cognitive adaptation theory, and the privacy paradox, the research develops and validates an affective-override privacy calculus that explains how emotional rationalisation mediates privacy decision-making. The study compares users and non-users of AI companionship apps using cross-sectional survey data (n = 698) and partial least squares structural equation modelling with multi-group analysis. Results show that tracking awareness is a cognitive safeguard for non-users but an emotional rationalisation tool for users, amplifying perceived benefits and engagement despite recognised risks. The model demonstrates that emotional attachment can invert conventional risk–behaviour relationships, reframing awareness as context-dependent. Findings inform the ethical design of emotional AI, highlighting the need for emotional transparency, privacy literacy, and regulatory attention to affective coercion.
{"title":"Understanding user susceptibility to risks in AI companionship applications","authors":"Adriaan Lombard , Stephen Flowerday , John Hale","doi":"10.1016/j.techsoc.2025.103182","DOIUrl":"10.1016/j.techsoc.2025.103182","url":null,"abstract":"<div><div>The growing adoption of emotionally adaptive Artificial Intelligence (AI) companionship applications raises critical concerns about privacy, emotional dependency, and behavioural susceptibility. These systems provide affective gratification while relying on continuous data tracking, generating tension between intimacy and surveillance. This study investigates how users’ understanding of tracking mechanisms, perceived risks, and perceived benefits jointly shape susceptibility, which is behavioural susceptibility to AI influence. Integrating cognitive dissonance theory, cognitive adaptation theory, and the privacy paradox, the research develops and validates an affective-override privacy calculus that explains how emotional rationalisation mediates privacy decision-making. The study compares users and non-users of AI companionship apps using cross-sectional survey data (n = 698) and partial least squares structural equation modelling with multi-group analysis. Results show that tracking awareness is a cognitive safeguard for non-users but an emotional rationalisation tool for users, amplifying perceived benefits and engagement despite recognised risks. The model demonstrates that emotional attachment can invert conventional risk–behaviour relationships, reframing awareness as context-dependent. Findings inform the ethical design of emotional AI, highlighting the need for emotional transparency, privacy literacy, and regulatory attention to affective coercion.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"85 ","pages":"Article 103182"},"PeriodicalIF":12.5,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145623541","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号