Technological Forecasting and Social Change最新文献_第7页

Artificial intelligence and urban social risk in China: A spatial analysis 人工智能与中国城市社会风险的空间分析

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-08 DOI: 10.1016/j.techfore.2025.124230

Zhiyuan Gao , Ying Zhao , Lianqing Li , Yu Hao

{"title":"Artificial intelligence and urban social risk in China: A spatial analysis","authors":"Zhiyuan Gao , Ying Zhao , Lianqing Li , Yu Hao","doi":"10.1016/j.techfore.2025.124230","DOIUrl":"10.1016/j.techfore.2025.124230","url":null,"abstract":"<div><div>In recent years, China's youth unemployment rate has remained high (e.g., 18.8 % in September 2024), raising concerns about social stability. Meanwhile, the application of artificial intelligence (AI) in China has deepened. AI not only influences the development of the technology sector but also poses technological challenges—such as algorithmic black boxes and privacy breaches—and social issues, including unemployment risks and social injustice. These challenges span politics, economics, society, and ethics, contributing to social risks such as public security issues, labor disputes, and sudden collective incidents. Exploring the relationship between AI and social risks is of great practical significance for China, which is undergoing a transformative period marked by the end of its demographic dividend, slowing economic growth, and intensifying societal contradictions. Given the spatial characteristics of social risks, this study analyzes data from 285 cities between 2010 and 2019 by constructing a Spatial Durbin Model (SDM) and a spatial mediation effect model to investigate the impact of AI on social risks and its spatial diffusion effects. The findings indicate that AI exacerbates social risks both locally and in neighboring regions, with the income gap serving as a significant mediating factor in this relationship. The study also reveals heterogeneity in the effects of AI on urban social risks across cities of different sizes and regional contexts, highlighting the notable spatial diffusion effects of AI. To foster positive interactions between technology and society, it is crucial to recognize the influence of AI on social risks, reduce income disparities, and place particular emphasis on small and medium-sized cities.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"219 ","pages":"Article 124230"},"PeriodicalIF":12.9,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144240700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proactive social learning and green product consumption: Evidence from new energy vehicle sales in China 主动社会学习与绿色产品消费：来自中国新能源汽车销售的证据

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-06 DOI: 10.1016/j.techfore.2025.124232

Zhe Jiang , Ning Liu , Xiaobing Zhang , Yanlai Chu , Lin Zhang

{"title":"Proactive social learning and green product consumption: Evidence from new energy vehicle sales in China","authors":"Zhe Jiang , Ning Liu , Xiaobing Zhang , Yanlai Chu , Lin Zhang","doi":"10.1016/j.techfore.2025.124232","DOIUrl":"10.1016/j.techfore.2025.124232","url":null,"abstract":"<div><div>Growing literature on social norms points to the effectiveness of leveraging social interactions to spur prosocial purchase behaviors. This article studies the effects of proactive social learning, a dynamic social norm formation process measured by the public's online normative information acquisition regarding climate change, on new energy vehicle (NEV) sales in China. Drawing on model–month sales data, we provide robust evidence that citizens' broad searches for information about climate change or global warming boost local NEV sales. By distinguishing between search topics, we find that impact-based learning has a greater influence on NEV sales than reason-based learning. City-level analysis further reveals that local social norms formed through economic openness, public literacy, and strategic government interventions enhance proactive social learning-driven NEV sales. Our findings highlight the importance of understanding proactive social learning embedded in localized social norms in promoting prosocial consumer decisions.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"219 ","pages":"Article 124232"},"PeriodicalIF":12.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

User practices in shaping complementarities for creating diverse systems of use: Insights from users in situations of hearing loss 形成互补性以创建多样化使用系统的用户实践：来自听力损失情况下用户的见解

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-05 DOI: 10.1016/j.techfore.2025.124228

Neva Bojovic , Annabelle Gawer , Vincent Mangematin

引用次数: 0

State of art and future research directions for marketing technologies in healthcare 医疗保健市场营销技术的现状及未来研究方向

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-04 DOI: 10.1016/j.techfore.2025.124226

Johana Hajdini , Stefano Za , Lea Iaia

{"title":"State of art and future research directions for marketing technologies in healthcare","authors":"Johana Hajdini , Stefano Za , Lea Iaia","doi":"10.1016/j.techfore.2025.124226","DOIUrl":"10.1016/j.techfore.2025.124226","url":null,"abstract":"<div><div>This study synthesizes the body of knowledge on marketing technologies for healthcare with the aim to explore the different perspectives of extant research into a comprehensive multidisciplinary approach. We arranged the bibliometric analysis of 334 articles in two steps, the descriptive and conceptual structure analysis respectively. The former includes the analysis of the publications trend, most relevant journals, most productive countries and authors, and citations. The conceptual structure analysis on the other hand focuses on the most used keywords, developing a keyword co-occurrence analysis and a conceptual structure map to craft the main topic discussed in the dataset. Marketing technology in healthcare is a worldwide researched topic that has gained increased attention in recent years. The findings provide insights about marketing technologies for healthcare, identifying three main research directions, specifically 1) virtual health interactions, 2) healthcare digital transformation investigating a broad set of technologies, and 3) digital patient experience. Exploring the traits of the debate on marketing technologies in healthcare and proposing potential avenues for future research, this paper adds to the literature on the intersection of marketing and healthcare, thus unveiling opportunities for the health sector.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"218 ","pages":"Article 124226"},"PeriodicalIF":12.9,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biases in expert judgements in large-scale S&T Delphi Surveys: How to cope with them? 大型科技德尔菲调查中专家判断偏差：如何应对？

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-04 DOI: 10.1016/j.techfore.2025.124223

Alexander Sokolov , Anna Grebenyuk , Kuniko Urashima

{"title":"Biases in expert judgements in large-scale S&T Delphi Surveys: How to cope with them?","authors":"Alexander Sokolov , Anna Grebenyuk , Kuniko Urashima","doi":"10.1016/j.techfore.2025.124223","DOIUrl":"10.1016/j.techfore.2025.124223","url":null,"abstract":"<div><div>When preparing to a new large-scale science and technology (S&T) Foresight study we decided to analyse available previous Delphi surveys in order to assess the results they achieve. The most important issue for us was how to avoid biases in expert judgements, in particular related to reaching convergence in the second round of the survey compared to the first round. This article presents the results, which turned out to be unexpected for us.</div><div>The paper is devoted to analyzing the key characteristics of the Delphi method used in large-scale S&T Foresight studies. It provides insight into the major features of the method, its strong and weak points. A closer analysis is paid to potential constraints of using the Delphi method related to expert judgement biases and approaches to cope with them. There were identified three major groups of typical biases in expert judgements in Delphi studies; for each of them a number of approaches proposed to minimize the biases.</div><div>Based on analysis of five large-scale national S&T Delphi surveys (conducted in Japan, Germany, UK, and Russia), it was shown that there is a systemic bias in judgements given by experts in their assessment of importance of topics in the second round compared to the first round. It is also shown that in most cases the variance of expert's judgements in the second round of the survey is higher than in the first round, which means that the second round both gives a systemic bias of judgements and in general does not lead to convergence of expert opinions. It leads to a discussion on the approaches and practical instruments, which can increase the quality of Delphi outputs and make them more useful for policy-making.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"218 ","pages":"Article 124223"},"PeriodicalIF":12.9,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart farming technologies and changes to farm work: New insights into on-farm experiences 智能农业技术和农业工作的变化：对农场体验的新见解

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-04 DOI: 10.1016/j.techfore.2025.124227

Ruth Nettle , Julie Ingram

{"title":"Smart farming technologies and changes to farm work: New insights into on-farm experiences","authors":"Ruth Nettle , Julie Ingram","doi":"10.1016/j.techfore.2025.124227","DOIUrl":"10.1016/j.techfore.2025.124227","url":null,"abstract":"<div><div>The intersect between technologies and the future of work is a key topic for both practitioner and scholarly communities. In this paper, we explore this intersect within agriculture by examining the changes to work for farmers implementing smart farming technologies (SFTs) in the United Kingdom (UK) and Australia. We interviewed 17 farmers across the UK and Australia from horticulture, dairy and mixed farming (arable and livestock) enterprises who were implementing diverse SFTs. Interview questions explored farmers' experiences in implementing SFTs with respect to any changes to work for themselves and their employees. Based on an interdisciplinary conceptual framework we developed from the literature for analysing farm work, we applied qualitative data analysis methods to examine the changes to work. We found the benefits from reduced work-duration were commonly counteracted by time spent in computer set-up and data work, with subsequent negative effects for the cognitive and affective dimensions of workload. The organisation of farm work influenced the type of skills and knowledge required to implement SFTs, with larger and corporate farms outsourcing these requirements to advisers, while smaller-medium sized farms used SFTs to augment their existing knowledge and skills, enabling employers to do more with their own time and enhancing employee engagement in work. We found more similarities than differences in work changes between countries. The interrelationships and feedback loops we have identified between the different aspects of work bring a novel perspective to technological transitions in agriculture and represent an important orientation point for researchers and technology developers to better anticipate work effects from different types of SFTs.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"218 ","pages":"Article 124227"},"PeriodicalIF":12.9,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unlocking blockchain's potential for supply chain transformation: A robust system analysis for enhanced strategic performance 解锁区块链的供应链转型潜力：增强战略绩效的稳健系统分析

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-02 DOI: 10.1016/j.techfore.2025.124216

Samuel Yousefi, Babak Mohamadpour Tosarkani

{"title":"Unlocking blockchain's potential for supply chain transformation: A robust system analysis for enhanced strategic performance","authors":"Samuel Yousefi, Babak Mohamadpour Tosarkani","doi":"10.1016/j.techfore.2025.124216","DOIUrl":"10.1016/j.techfore.2025.124216","url":null,"abstract":"<div><div>Supply chains (SCs) are becoming more complex due to globalization, the increased risk of disruptions, and regulatory requirements, which mandate greater coordination among stakeholders. The integration of a blockchain-based information-sharing mechanism can improve compliance and streamline operations across SC networks. However, blockchain adoption in SCs remains relatively unexplored, leading to managers' unfamiliarity with its potential outcomes and increasing conservatism. Therefore, this study incorporates a strategic perspective into analyzing blockchain adoption enablers. We propose a robust system analysis-based framework to investigate the interplay between enablers and supply chain performance (SCP) improvement. First, the critical success factor theory and the balanced scorecard are employed to identify and categorize the enablers in establishing a blockchain-based sustainable SC network. The systems theory-enabled fuzzy cognitive map is developed to create a causal-based model of the identified 23 enablers, and then a hybrid learning algorithm is adopted to quantify the impact of these factors on the four strategic SCP metrics, including cost-effectiveness, improved quality, lead time minimization, and increased customer satisfaction. Afterward, the blockchain adoption enablers analysis problem is formulated using the fixed-input robust data envelopment analysis to identify the most effective factors on SCP across diverse scenarios. The findings imply that each enabler affects SCP metrics either directly through causal relationships or indirectly via other enablers. Considering the overall impact, smart contracts, traceability, and streamlined communication can be regarded as key drivers that shape mediators and consequently enhance SCP. The results further indicate that the proposed framework supports greater flexibility in designing adoption strategies.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"218 ","pages":"Article 124216"},"PeriodicalIF":12.9,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bridging AI minds and corporate sustainability - Exploring the role of business model innovation and organizational sensemaking 连接人工智能思想和企业可持续发展-探索商业模式创新和组织意义的作用

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-06-02 DOI: 10.1016/j.techfore.2025.124229

Vinit Ghosh , Varun Chotia , Rsha Alghafes , Sarah Basahel , Asif Nazrul

{"title":"Bridging AI minds and corporate sustainability - Exploring the role of business model innovation and organizational sensemaking","authors":"Vinit Ghosh , Varun Chotia , Rsha Alghafes , Sarah Basahel , Asif Nazrul","doi":"10.1016/j.techfore.2025.124229","DOIUrl":"10.1016/j.techfore.2025.124229","url":null,"abstract":"<div><div>The research explores the impact of artificial intelligence understanding on corporate sustainability, as mediated by business model innovation and organizational sensemaking. Data from 260 employees working in manufacturing sector was analyzed. The proposed hypotheses were evaluated using SmartPLS4. The empirical findings supported the hypothesized relationships linking artificial intelligence understanding, business model innovation, organizational sensemaking, and corporate sustainability. The results affirm a positive connection between artificial intelligence understanding and corporate sustainability, mediated by business model innovation and organizational sensemaking. These statistically significant inter-linkages were further validated through qualitative content analysis of structured written responses from twelve experts, revealing the “why” and “how” aspects of these relationships. Artificial intelligence uncovers valuable insights by analyzing economic, social, and environmental factors, helping businesses identify sustainable profit opportunities. The study advocates for organizations to integrate human sensemaking elements when aligning corporate strategies with artificial intelligence. This paradigm calls for a comprehensive approach, wherein technology-driven methodologies and human-centred cognitive strategies collaboratively shape corporate sustainability policies.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"218 ","pages":"Article 124229"},"PeriodicalIF":12.9,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How does large-scale internal migration affect innovation? Evidence from China 大规模内部迁移如何影响创新？来自中国的证据

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-05-30 DOI: 10.1016/j.techfore.2025.124199

Chenghua Guan , Wanting Xu , Peijin Yang , Yao Xiao , Byann Rasul

{"title":"How does large-scale internal migration affect innovation? Evidence from China","authors":"Chenghua Guan , Wanting Xu , Peijin Yang , Yao Xiao , Byann Rasul","doi":"10.1016/j.techfore.2025.124199","DOIUrl":"10.1016/j.techfore.2025.124199","url":null,"abstract":"<div><div>The influx of international and high-skilled migrants has profoundly promoted innovation in developed countries. However, few studies have investigated the effects of large-scale and various types of internal migrants on innovation in developing countries. With a surge in internal migration and innovation progress, China provides an excellent place and unique case to explore this issue. Using the predicted share of migrants as an instrumental variable for migration, this study examines the causal effects and mechanisms of internal migration on innovation in China from 2000 to 2015. Our results indicate that internal migration significantly promotes innovation in China. The promotion effects of migration are more pronounced among high-skilled, ‘urban <em>hukou</em>,’ and urban-urban migrants as well as in coastal areas, larger cities, and cities with higher levels of public services. Migrants can broaden the local human capital stock, enhance cultural diversity, and improve skill complementarity in their destination areas, thereby facilitating innovation. This study highlights the contribution of various types of internal migrants to innovation in China, which differs significantly from previous studies on international migrants in developed countries. These findings provide new insight into migration and innovation and offer references for other developing countries to formulate sustainable migration and innovation policies.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"218 ","pages":"Article 124199"},"PeriodicalIF":12.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Methodological implications of using machine learning to estimate the impact of AI on the workforce 使用机器学习来估计人工智能对劳动力的影响的方法含义

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-05-30 DOI: 10.1016/j.techfore.2025.124197

Andrew J. Evans

{"title":"Methodological implications of using machine learning to estimate the impact of AI on the workforce","authors":"Andrew J. Evans","doi":"10.1016/j.techfore.2025.124197","DOIUrl":"10.1016/j.techfore.2025.124197","url":null,"abstract":"<div><div>Examining the potential effects of artificial intelligence on jobs has been a research topic for many years, carrying significant implications for social and industrial policies. Frey and Osborne's seminal study, which estimated that AI could potentially displace 47 % of jobs, has inspired numerous subsequent studies that have reused many elements of the original research.</div><div>However, the methodological approach and application of machine learning in their study has largely escaped critical examination. Given the study's significant influence in both academic circles and public discourse, this article aims to offer a methodological critique of Frey and Osborne's work and their use of machine learning to assess how these factors may have shaped their findings and conclusions. The analysis finds that their study lacks the necessary methodological robustness to produce reliable results and that the use of machine learning to estimate the impact of AI on the workforce would not be recommended. Additionally, this paper briefly explores the similarities with recent studies on the impact of generative AI on the workforce, highlighting comparable methodological issues. As a result, this paper proposes a future research agenda to help researchers, policymakers, and businesses gain a better understanding of how AI technologies may impact the workforce.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"218 ","pages":"Article 124197"},"PeriodicalIF":12.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0