Pub Date : 2025-02-12DOI: 10.1016/j.techsoc.2025.102839
Guanghui He, Shicheng Zhou
Since 2023, bank failures in America and Europe have reignited concerns about trust in credit transactions. During financial turbulence, heightened attention tends to be directed towards inter-enterprise trust management. However, existing studies have mainly focused on individual enterprise credit credibility, leaving a gap in analysing trust ecology within entire enterprise clusters. This study proposes an enterprise trust ecology assessment based on percolation theory. First, we established cluster-based enterprise trust networks (C-ETNs) and employed an entropy method to calculate the trust values of enterprise nodes. Subsequently, based on percolation theory, we mapped the trust ecology evolution to point percolation model to quantify trust ecology. Through simulations and data analysis of Chinese A-shares from 2007 to 2021, we uncovered a phase-transition phenomenon in trust ecology improvement. Trust in A-shares moderately improved, with business and comprehensive industry sectors as well as midland and west areas showing prominent improvement. However, overall trust ecology remained in early-phase transition, and almost all sectors and regions experienced upward bottlenecks. This study provides a new technical method for improving credit management in inter-enterprise transactions, thus enhancing market credit construction. Its extensive application is also valuable for economic and societal trust concerns.
{"title":"Assessing the ecology of cluster-based enterprise trust networks through percolation theory: Is your business environment trustworthy?","authors":"Guanghui He, Shicheng Zhou","doi":"10.1016/j.techsoc.2025.102839","DOIUrl":"10.1016/j.techsoc.2025.102839","url":null,"abstract":"<div><div>Since 2023, bank failures in America and Europe have reignited concerns about trust in credit transactions. During financial turbulence, heightened attention tends to be directed towards inter-enterprise trust management. However, existing studies have mainly focused on individual enterprise credit credibility, leaving a gap in analysing trust ecology within entire enterprise clusters. This study proposes an enterprise trust ecology assessment based on percolation theory. First, we established cluster-based enterprise trust networks (C-ETNs) and employed an entropy method to calculate the trust values of enterprise nodes. Subsequently, based on percolation theory, we mapped the trust ecology evolution to point percolation model to quantify trust ecology. Through simulations and data analysis of Chinese A-shares from 2007 to 2021, we uncovered a phase-transition phenomenon in trust ecology improvement. Trust in A-shares moderately improved, with business and comprehensive industry sectors as well as midland and west areas showing prominent improvement. However, overall trust ecology remained in early-phase transition, and almost all sectors and regions experienced upward bottlenecks. This study provides a new technical method for improving credit management in inter-enterprise transactions, thus enhancing market credit construction. Its extensive application is also valuable for economic and societal trust concerns.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102839"},"PeriodicalIF":10.1,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429237","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 : 2025-02-11DOI: 10.1016/j.techsoc.2025.102836
June Jeon , Lanu Kim , Jaehyuk Park
Despite growing attention to the ethics of Generative AI, there has been little discussion about how research ethics should be updated for social science research practice. This paper fills this gap at the intersection of AI ethics and social science research ethics. Based on 17 semi-structured interviews, we present three narratives about generative AI and research ethics: 1) the equalizer narrative, 2) the meritocracy narrative, and 3) the community narrative. We argue that the ethics of AI-assisted social-scientific research cannot be reduced to universal checklists, and institutionally grounded research ethics principles are necessary. In all of the narratives, the technical functions of Generative AI were merely necessary conditions of unethical practices, while ethical dilemmas started to arise when such functions were situated in the institutional arrangements of academia. Our findings suggest that the ethics of AI-assisted research should encompass not only specific ethical rules concerning AI functionalities but also incorporate community engagement, educational imperatives, institutional governance, and the societal impact of such technologies to organize “ethics-in-practice.” This will require democratic deliberations to address the complex, emergent interactions between AI systems and societal structures.
{"title":"The ethics of generative AI in social science research: A qualitative approach for institutionally grounded AI research ethics","authors":"June Jeon , Lanu Kim , Jaehyuk Park","doi":"10.1016/j.techsoc.2025.102836","DOIUrl":"10.1016/j.techsoc.2025.102836","url":null,"abstract":"<div><div>Despite growing attention to the ethics of Generative AI, there has been little discussion about how research ethics should be updated for social science research practice. This paper fills this gap at the intersection of AI ethics and social science research ethics. Based on 17 semi-structured interviews, we present three narratives about generative AI and research ethics: 1) the equalizer narrative, 2) the meritocracy narrative, and 3) the community narrative. We argue that the ethics of AI-assisted social-scientific research cannot be reduced to universal checklists, and institutionally grounded research ethics principles are necessary. In all of the narratives, the technical functions of Generative AI were merely necessary conditions of unethical practices, while ethical dilemmas started to arise when such functions were situated in the institutional arrangements of academia. Our findings suggest that the ethics of AI-assisted research should encompass not only specific ethical rules concerning AI functionalities but also incorporate community engagement, educational imperatives, institutional governance, and the societal impact of such technologies to organize “ethics-in-practice.” This will require democratic deliberations to address the complex, emergent interactions between AI systems and societal structures.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102836"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429154","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 : 2025-02-11DOI: 10.1016/j.techsoc.2025.102837
Wucheng Han , Weijie Zhu , Zhaoli Song , Ruoyu Lu
In the era of rapid artificial intelligence (AI) technology advancement, enterprises increasingly consider AI as a strategic imperative. However, the determinants of AI adoption and strategy formulation in enterprises remain elusive. Drawing on an integrated Resource-Based View (RBV) and Strategic Choice Theory (SCT) framework, this study presents a theoretical model that scrutinizes the factors and boundary conditions influencing enterprises in crafting AI strategies. Empirical assessments of theoretical hypotheses were conducted utilizing survey data gathered from 717 executives across global firms. We found strong evidence that internal innovation resources (IIR) and collaborative innovation networks (CIN) have a positive impact on firm's AI orientation. The study revealed that environmental uncertainty (EU) can negatively moderate the relationship between internal innovation resources, collaborative innovation networks, and AI orientation. A positive moderating effect was observed between corporate digital culture (DC) and the relationship between internal innovation resources, collaborative innovation networks, and AI orientation. Meanwhile, we found a positive moderating effect of Executives' Not-Invented-Here Syndrome (NIHS) on the relationship between internal innovation resources and AI orientation. This research contributes to the ongoing discourse on AI strategy in management and offers valuable guidance for organizations seeking to harness the potential of AI in a rapidly changing business environment.
{"title":"Innovative resources driven artificial intelligence orientation: The moderating role of environmental and executives’ characteristics","authors":"Wucheng Han , Weijie Zhu , Zhaoli Song , Ruoyu Lu","doi":"10.1016/j.techsoc.2025.102837","DOIUrl":"10.1016/j.techsoc.2025.102837","url":null,"abstract":"<div><div>In the era of rapid artificial intelligence (AI) technology advancement, enterprises increasingly consider AI as a strategic imperative. However, the determinants of AI adoption and strategy formulation in enterprises remain elusive. Drawing on an integrated Resource-Based View (RBV) and Strategic Choice Theory (SCT) framework, this study presents a theoretical model that scrutinizes the factors and boundary conditions influencing enterprises in crafting AI strategies. Empirical assessments of theoretical hypotheses were conducted utilizing survey data gathered from 717 executives across global firms. We found strong evidence that internal innovation resources (IIR) and collaborative innovation networks (CIN) have a positive impact on firm's AI orientation. The study revealed that environmental uncertainty (EU) can negatively moderate the relationship between internal innovation resources, collaborative innovation networks, and AI orientation. A positive moderating effect was observed between corporate digital culture (DC) and the relationship between internal innovation resources, collaborative innovation networks, and AI orientation. Meanwhile, we found a positive moderating effect of Executives' Not-Invented-Here Syndrome (NIHS) on the relationship between internal innovation resources and AI orientation. This research contributes to the ongoing discourse on AI strategy in management and offers valuable guidance for organizations seeking to harness the potential of AI in a rapidly changing business environment.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102837"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422628","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 : 2025-02-11DOI: 10.1016/j.techsoc.2025.102833
Guillaume Zumofen
By definition, the mapping of technological development occurs in the context of uncertainty and with a risk of failure. Decisions taken at the onset of the development phase are significant because the technology has not reached the market yet. The technology loses its malleability during the development phase because of entrenchment. Thus, the objective of a constructive technological assessment is to embed social aspects – additional perspectives – in the context of technological developments. In line with extant literature, a pivotal perspective is the (future) end-user of the technology. Hence, market acceptance remains a constraining factor in technological development, notably for renewable energy technology. However, existing studies have not included (future) end-users in development phases. They have always taken place after the technology has reached the market.
To bring technological development and market acceptance closer, this study develops an innovative method that combines a conjoint experiment with a supervised machine learning model to predict the behavioural intention of end-users to accept a new (energy) technology. This study illustrates the proposed methodology through a conjoint experiment on seasonal thermal energy storage. The ML model uses input from a survey with a conjoint experiment to predict end-users’ market acceptance. With N = 12,096 (1008 participants exposed to 6 x 2 conjoint tasks), the ML model predicts behavioural intention with an accuracy of RMSE = 1.55 on a 10-point scale. The model is then used to predict hypothetical acceptance from mock end-users’ profiles and varying technological features. Thus, this study opens new perspectives for constructive technology assessment and conjoint experiment literature, and furthers discussions on social acceptance of energy technologies.
{"title":"Combining a conjoint experiment and machine learning model to include end-users in a constructive technology assessment: The case of seasonal thermal energy storage","authors":"Guillaume Zumofen","doi":"10.1016/j.techsoc.2025.102833","DOIUrl":"10.1016/j.techsoc.2025.102833","url":null,"abstract":"<div><div>By definition, the mapping of technological development occurs in the context of uncertainty and with a risk of failure. Decisions taken at the onset of the development phase are significant because the technology has not reached the market yet. The technology loses its malleability during the development phase because of entrenchment. Thus, the objective of a constructive technological assessment is to embed social aspects – additional perspectives – in the context of technological developments. In line with extant literature, a pivotal perspective is the (future) end-user of the technology. Hence, market acceptance remains a constraining factor in technological development, notably for renewable energy technology. However, existing studies have not included (future) end-users in development phases. They have always taken place after the technology has reached the market.</div><div>To bring technological development and market acceptance closer, this study develops an innovative method that combines a conjoint experiment with a supervised machine learning model to predict the behavioural intention of end-users to accept a new (energy) technology. This study illustrates the proposed methodology through a conjoint experiment on seasonal thermal energy storage. The ML model uses input from a survey with a conjoint experiment to predict end-users’ market acceptance. With N = 12,096 (1008 participants exposed to 6 x 2 conjoint tasks), the ML model predicts behavioural intention with an accuracy of RMSE = 1.55 on a 10-point scale. The model is then used to predict hypothetical acceptance from mock end-users’ profiles and varying technological features. Thus, this study opens new perspectives for constructive technology assessment and conjoint experiment literature, and furthers discussions on social acceptance of energy technologies.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102833"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-11DOI: 10.1016/j.techsoc.2025.102840
Ha Eun (Grace) Park
The freemium business model has gained increasing attention in digital game design. Drawing on affordance theory, this research examines how the affordances of freemium game design can be leveraged to foster engagement. Data was collected over two years of netnographic study, culminating in 10,927 posts and nine relevant forum topics. The findings identify different game mechanics - farming, loot boxing, raiding, and rewarding - and different types of affordances actualized by free-to-play and pay-to-win players. This research discusses how two levels of technology affordances at individual and team levels foster engagement in a progressive manner. This study provides insights for scholars and game designers to better understand the dynamics of designing freemium digital games in facilitating long-standing engagement.
{"title":"Designing engagement: Exploring affordances in freemium digital games","authors":"Ha Eun (Grace) Park","doi":"10.1016/j.techsoc.2025.102840","DOIUrl":"10.1016/j.techsoc.2025.102840","url":null,"abstract":"<div><div>The freemium business model has gained increasing attention in digital game design. Drawing on affordance theory, this research examines how the affordances of freemium game design can be leveraged to foster engagement. Data was collected over two years of netnographic study, culminating in 10,927 posts and nine relevant forum topics. The findings identify different game mechanics - farming, loot boxing, raiding, and rewarding - and different types of affordances actualized by free-to-play and pay-to-win players. This research discusses how two levels of technology affordances at individual and team levels foster engagement in a progressive manner. This study provides insights for scholars and game designers to better understand the dynamics of designing freemium digital games in facilitating long-standing engagement.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102840"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422626","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 : 2025-02-06DOI: 10.1016/j.techsoc.2025.102835
Elias G. Carayannis , Roman Dumitrescu , Tommy Falkowski , George Papamichail , Nikos - Rigert Zota
This article explores the integration of artificial intelligence (AI) and strategic foresight as a comprehensive framework for enhancing resilience in small and medium-sized enterprises (SMEs). It examines AI applications such as predictive analytics, scenario planning, and risk identification to improve operational efficiency and decision-making. By combining AI tools with foresight methodologies, the proposed framework helps SMEs anticipate market disruptions, adapt to evolving business environments, and build sustainable growth strategies. Addressing challenges like financial constraints and regulatory issues, this article provides practical insights for industry professionals and academics, highlighting effective strategies for leveraging AI to strengthen SME resilience and competitiveness.
{"title":"Enhancing SME resilience through artificial intelligence and strategic foresight: A framework for sustainable competitiveness","authors":"Elias G. Carayannis , Roman Dumitrescu , Tommy Falkowski , George Papamichail , Nikos - Rigert Zota","doi":"10.1016/j.techsoc.2025.102835","DOIUrl":"10.1016/j.techsoc.2025.102835","url":null,"abstract":"<div><div>This article explores the integration of artificial intelligence (AI) and strategic foresight as a comprehensive framework for enhancing resilience in small and medium-sized enterprises (SMEs). It examines AI applications such as predictive analytics, scenario planning, and risk identification to improve operational efficiency and decision-making. By combining AI tools with foresight methodologies, the proposed framework helps SMEs anticipate market disruptions, adapt to evolving business environments, and build sustainable growth strategies. Addressing challenges like financial constraints and regulatory issues, this article provides practical insights for industry professionals and academics, highlighting effective strategies for leveraging AI to strengthen SME resilience and competitiveness.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102835"},"PeriodicalIF":10.1,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143436987","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 : 2025-02-04DOI: 10.1016/j.techsoc.2025.102834
Lemuel Kenneth David , Jianling Wang , William Brooks , Vanessa Angel
While digital technologies have the potential to significantly boost socio-economic development, their impact varies across emerging economies. This study investigates the influence of internet and mobile penetration on economic growth and human development indices in 30 emerging economies from 2008 to 2023. Using advanced econometric models, structural equation modeling (SEM), and data envelopment analysis (DEA), the research offers a detailed analysis of digital transformation's role in these regions. Case studies from Ghana, Indonesia, and Venezuela provide contextual insights, highlighting the importance of robust digital governance. The results indicate a strong correlation between digital penetration and GDP growth, contingent on effective governance structures. The study concludes with key policy recommendations to enhance digital infrastructure and governance for sustainable development.
{"title":"Digital transformation and socio-economic development in emerging economies: A multinational analysis","authors":"Lemuel Kenneth David , Jianling Wang , William Brooks , Vanessa Angel","doi":"10.1016/j.techsoc.2025.102834","DOIUrl":"10.1016/j.techsoc.2025.102834","url":null,"abstract":"<div><div>While digital technologies have the potential to significantly boost socio-economic development, their impact varies across emerging economies. This study investigates the influence of internet and mobile penetration on economic growth and human development indices in 30 emerging economies from 2008 to 2023. Using advanced econometric models, structural equation modeling (SEM), and data envelopment analysis (DEA), the research offers a detailed analysis of digital transformation's role in these regions. Case studies from Ghana, Indonesia, and Venezuela provide contextual insights, highlighting the importance of robust digital governance. The results indicate a strong correlation between digital penetration and GDP growth, contingent on effective governance structures. The study concludes with key policy recommendations to enhance digital infrastructure and governance for sustainable development.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102834"},"PeriodicalIF":10.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429238","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 : 2025-01-31DOI: 10.1016/j.techsoc.2025.102832
Rachel Chua, Min Wu, Kum Fai Yuen
‘Crowdshipping’ (CS), a burgeoning trend propelled by the upsurge in e-commerce after the COVID-19 pandemic, combines crowdsourcing and shipping, giving rise to a novel logistical paradigm. While shipping entails the physical transportation of goods, crowdsourcing involves task delegation to a network of individuals through an open call. This departure from conventional courier services for last-mile delivery leverages the collective potential of the online public. Using the health belief model and task–technology fit (TTF) theory, this study introduces a theoretical model that delves into the fundamental factors influencing consumer acceptance of CS as a last-mile delivery service within urban landscapes, encompassing its technological alignment. A comprehensive analysis of 450 survey responses, using structural equation modelling, revealed that expected outcome, self-efficacy, perceived threat (security and privacy) and cues to action directly influence consumers acceptance. Contrarily, task and technology characteristics can indirectly influence consumer acceptance through TTF. Analysis of the total effects revealed that cues to action have the strongest impact on consumer acceptance. The study aimed to illuminate consumer perspectives regarding the integration of CS as a last-mile delivery alternative and to enrich urban green logistical planning and regulatory frameworks for policymakers accordingly.
{"title":"Sustainable crowdshipping: Navigating technological fit and security risks","authors":"Rachel Chua, Min Wu, Kum Fai Yuen","doi":"10.1016/j.techsoc.2025.102832","DOIUrl":"10.1016/j.techsoc.2025.102832","url":null,"abstract":"<div><div>‘Crowdshipping’ (CS), a burgeoning trend propelled by the upsurge in e-commerce after the COVID-19 pandemic, combines crowdsourcing and shipping, giving rise to a novel logistical paradigm. While shipping entails the physical transportation of goods, crowdsourcing involves task delegation to a network of individuals through an open call. This departure from conventional courier services for last-mile delivery leverages the collective potential of the online public. Using the health belief model and task–technology fit (TTF) theory, this study introduces a theoretical model that delves into the fundamental factors influencing consumer acceptance of CS as a last-mile delivery service within urban landscapes, encompassing its technological alignment. A comprehensive analysis of 450 survey responses, using structural equation modelling, revealed that expected outcome, self-efficacy, perceived threat (security and privacy) and cues to action directly influence consumers acceptance. Contrarily, task and technology characteristics can indirectly influence consumer acceptance through TTF. Analysis of the total effects revealed that cues to action have the strongest impact on consumer acceptance. The study aimed to illuminate consumer perspectives regarding the integration of CS as a last-mile delivery alternative and to enrich urban green logistical planning and regulatory frameworks for policymakers accordingly.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102832"},"PeriodicalIF":10.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103619","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 : 2025-01-30DOI: 10.1016/j.techsoc.2025.102825
Liping Wang , Longjun Chen , Shucen Jin , Chuang Li
Enterprises' green behaviour level (EGBL) is an important reflection of a country's green development progress. Gaining foresight into the future trends of EGBL can provide a roadmap for achieving national carbon peak and carbon neutrality ('dual carbon') goals. However, existing research has primarily focused on the factors influencing corporate green behaviour and their potential impacts, whereas predictive studies on EGBL remain underexplored. To address this research gap, this study first combines the characteristics of sustainable development of enterprises and develops a more comprehensive Chinese EGBL evaluation system from 26 evaluation indicators including five positive dimensions and one negative dimension. And then it calculates EGBL based on panel data from 828 industrial enterprises between 2010 and 2020. Subsequently, the study develops the Autoregressive Integrated Moving Average model (ARIMA) and scenario analysis models to conduct a comprehensive, multilevel forecast of the EGBL. The prediction results of EGBL based on the ARIMA model show that: Whether in 2030 or 2060, the EGBL in the middle reaches of the Yangtze River is the highest, and the EGBL in the northeast region is the lowest. The EGBL of state-owned enterprises was higher than that of non-state-owned enterprises. In terms of industry, EGBL ranks highest to lowest in the high-tech, manufacturing, energy, and resource industries. The results of the prediction of EGBL based on the scenario analysis method showed that regardless of the scenario, the overall trend of EGBL continued to increase. In similar scenarios, the evolution of environmental regulations and technological progress from slow to medium growth has a limited effect on EGBL. Only if environmental regulations and technological progress develop rapidly can a significant increase in EGBL be achieved. A cross-scenario analysis shows that for certain environmental regulations and technological progress, the gap in the EGBL caused by changes in economic growth, industrial structure and the degree of urbanisation is relatively small. Therefore, environmental regulations and technological progress are important factors contributing to differences in EGBL. Finally, based on the above prospective analysis, this study identified possible future development paths to improve EGBL in different regions of China.
{"title":"Forecasting the green behaviour level of Chinese enterprises: A conjoined application of the autoregressive integrated moving average (ARIMA) model and multi-scenario simulation","authors":"Liping Wang , Longjun Chen , Shucen Jin , Chuang Li","doi":"10.1016/j.techsoc.2025.102825","DOIUrl":"10.1016/j.techsoc.2025.102825","url":null,"abstract":"<div><div>Enterprises' green behaviour level (EGBL) is an important reflection of a country's green development progress. Gaining foresight into the future trends of EGBL can provide a roadmap for achieving national carbon peak and carbon neutrality ('dual carbon') goals. However, existing research has primarily focused on the factors influencing corporate green behaviour and their potential impacts, whereas predictive studies on EGBL remain underexplored. To address this research gap, this study first combines the characteristics of sustainable development of enterprises and develops a more comprehensive Chinese EGBL evaluation system from 26 evaluation indicators including five positive dimensions and one negative dimension. And then it calculates EGBL based on panel data from 828 industrial enterprises between 2010 and 2020. Subsequently, the study develops the Autoregressive Integrated Moving Average model (ARIMA) and scenario analysis models to conduct a comprehensive, multilevel forecast of the EGBL. The prediction results of EGBL based on the ARIMA model show that: Whether in 2030 or 2060, the EGBL in the middle reaches of the Yangtze River is the highest, and the EGBL in the northeast region is the lowest. The EGBL of state-owned enterprises was higher than that of non-state-owned enterprises. In terms of industry, EGBL ranks highest to lowest in the high-tech, manufacturing, energy, and resource industries. The results of the prediction of EGBL based on the scenario analysis method showed that regardless of the scenario, the overall trend of EGBL continued to increase. In similar scenarios, the evolution of environmental regulations and technological progress from slow to medium growth has a limited effect on EGBL. Only if environmental regulations and technological progress develop rapidly can a significant increase in EGBL be achieved. A cross-scenario analysis shows that for certain environmental regulations and technological progress, the gap in the EGBL caused by changes in economic growth, industrial structure and the degree of urbanisation is relatively small. Therefore, environmental regulations and technological progress are important factors contributing to differences in EGBL. Finally, based on the above prospective analysis, this study identified possible future development paths to improve EGBL in different regions of China.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102825"},"PeriodicalIF":10.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372910","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 : 2025-01-28DOI: 10.1016/j.techsoc.2025.102831
Liang Yang , Manyang Zhang , Lin Jia , Zhijun Yan , Qiuju Yin
The integration of digital technologies into disease self-management by patients has empowered healthcare delivery. Digital therapeutics (DTx) holds immense promise in improving patient outcomes through personalized and evidence-based interventions. However, existing research predominantly focuses on DTx applications in specific diseases or limited aspects and, thus, neglects a thorough exploration of fundamental concepts, underlying principles, and frameworks. To address this gap, we systematically reviewed the literature and analyzed 292 relevant articles between 2015 and 2023 from 7 main databases. Our study proposed a comprehensive conceptual framework for analyzing existing DTx literature, including (1) development, (2) system design, (3) evaluation, and (4) privacy concerns. Furthermore, we identified potential research opportunities for each theme. This study contributes to a systematic understanding of DTx research and its potential to advance medical outcomes in intervention practices. By bridging the existing knowledge gaps, our research paves the way for a more comprehensive and evidence-based approach to implementing DTx in patient disease self-management.
{"title":"Understanding digital therapeutics in disease self-management: A systematic literature review","authors":"Liang Yang , Manyang Zhang , Lin Jia , Zhijun Yan , Qiuju Yin","doi":"10.1016/j.techsoc.2025.102831","DOIUrl":"10.1016/j.techsoc.2025.102831","url":null,"abstract":"<div><div>The integration of digital technologies into disease self-management by patients has empowered healthcare delivery. Digital therapeutics (DTx) holds immense promise in improving patient outcomes through personalized and evidence-based interventions. However, existing research predominantly focuses on DTx applications in specific diseases or limited aspects and, thus, neglects a thorough exploration of fundamental concepts, underlying principles, and frameworks. To address this gap, we systematically reviewed the literature and analyzed 292 relevant articles between 2015 and 2023 from 7 main databases. Our study proposed a comprehensive conceptual framework for analyzing existing DTx literature, including (1) development, (2) system design, (3) evaluation, and (4) privacy concerns. Furthermore, we identified potential research opportunities for each theme. This study contributes to a systematic understanding of DTx research and its potential to advance medical outcomes in intervention practices. By bridging the existing knowledge gaps, our research paves the way for a more comprehensive and evidence-based approach to implementing DTx in patient disease self-management.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102831"},"PeriodicalIF":10.1,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170437","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}
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