Technology in Society最新文献_第10页

Can artificial intelligence drive enterprise green management innovation? A new perspective on harnessing intelligence 人工智能能否推动企业绿色管理创新？利用智力的新视角

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2025-11-08 DOI: 10.1016/j.techsoc.2025.103156

Shuai Che , Chen Liu , Jie Wang , Jun Wang

Amid the dual pressures of environmental pollution and resource constraints, enterprises are compelled to pursue green innovation to confront novel management challenges, and artificial intelligence emerges as a critical enabler by endowing enterprise green management innovation with advanced technological capabilities. Using data from Chinese enterprises spanning 2008–2023, this study comprehensively assesses artificial intelligence's catalytic role, revealing that artificial intelligence significantly enhances green management innovation efficiency. Local state-owned enterprises, firms with strong brand and content innovation capabilities, and industries such as water conservancy, public facilities management, wholesale, and retail gain disproportionate benefits. Artificial intelligence's green influence intensifies over time with a notable poverty alleviation effect at the 40th percentile and enhances productivity, resolving the productivity paradox. Theoretically, this study advances understanding by identifying digital, financing, operational, and R&D empowerment as key transmission mechanisms through which artificial intelligence drives green management innovation, collectively helping enterprises overcome high-pollution dilemmas. This research provides a basis for global enterprises to accelerate green management transformation and unleash the power of intelligent technologies in the digital age.

在环境污染和资源约束的双重压力下，企业不得不追求绿色创新，以应对新的管理挑战，而人工智能作为关键的使能器，赋予了企业绿色管理创新先进的技术能力。利用2008-2023年中国企业数据，综合评估了人工智能的催化作用，发现人工智能显著提高了绿色管理创新效率。地方国有企业、具有较强品牌和内容创新能力的企业以及水利、公共设施管理、批发、零售等行业获得了不成比例的收益。人工智能的绿色影响随着时间的推移而增强，在第40百分位的扶贫效果显著，并提高了生产率，解决了生产率悖论。从理论上讲，本研究通过确定数字、融资、运营和研发授权是人工智能推动绿色管理创新的关键传导机制，从而促进了人们的理解，共同帮助企业克服高污染困境。本研究为全球企业在数字化时代加快绿色管理转型，释放智能技术的力量提供了依据。

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引用次数: 0

Out of gratification or fears? A dual model to explore drivers of generative artificial intelligence adoption 出于满足还是恐惧？探索生成式人工智能采用驱动因素的双重模型

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2025-11-20 DOI: 10.1016/j.techsoc.2025.103177

Chien-Hsiang Liao , Yu-Hui Fang , Chia-Ying Li

Generative artificial intelligence (GenAI) has emerged as a transformative force reshaping how individuals work, live, and interact with their environments. Despite its rapid diffusion, research has yet to clarify the psychological mechanisms driving individual-level GenAI adoption and resistance. This study addresses this critical gap by proposing a dual-path model grounded in Uses and Gratifications Theory (UGT) and an extended Protection Motivation Theory (PMT) framework. UGT explains the positive, need-fulfilling motivations for GenAI use, incorporating novel gratification constructs such as serendipity, perceived diagnosticity, tangibility, curiosity fulfillment, and enjoyment. In contrast, the enhanced PMT framework captures both traditional and extended pathways of perceived threats. By including fear of losing power (FLP) and fear of missing out (FoMO) as internal psychological mechanisms, this study offers a more comprehensive account of GenAI adoption and resistance. Trait competitiveness and AI self-efficacy are introduced as moderators, delineating how individual differences shape protective responses. Using data from a two-wave longitudinal survey of 1271 ChatGPT users, the findings reveal that UGT-related factors primarily drive adoption, while traditional and extended PMT factors explain resistance behaviors. Notably, FoMO functions as a dual-pathway factor, facilitating adoption and mitigating resistance. Trait competitiveness and AI self-efficacy demonstrate partial moderating effects, underscoring the role of personal dispositions in shaping user behavior. This study contributes theoretically by integrating positive gratification and protective aversion into a unified model of GenAI use. Practically, it provides actionable insights for designing adaptive, user-centered AI systems that enhance engagement while reducing resistance.

生成式人工智能（GenAI）已经成为一股变革力量，重塑了个人的工作、生活以及与环境的互动方式。尽管基因ai传播迅速，但研究尚未阐明驱动个体水平基因ai采用和抵制的心理机制。本研究通过提出基于使用和满足理论（UGT）和扩展保护动机理论（PMT）框架的双路径模型来解决这一关键差距。UGT解释了GenAI使用的积极的、满足需求的动机，结合了新奇的满足结构，如意外发现、感知诊断、有形、好奇心满足和享受。相比之下，增强的PMT框架捕获了感知威胁的传统途径和扩展途径。通过将失去权力的恐惧（FLP）和错过的恐惧（FoMO）作为内部心理机制，本研究提供了一个更全面的基因采用和抵抗的解释。引入特质竞争力和人工智能自我效能作为调节因子，描述个体差异如何塑造保护反应。利用对1271名ChatGPT用户的两波纵向调查数据，研究结果表明，与ugt相关的因素主要推动了采用，而传统和扩展的PMT因素解释了抵制行为。值得注意的是，FoMO起到了促进采用和减轻抵制的双重作用。特质竞争力和人工智能自我效能表现出部分调节效应，强调了个人性格在塑造用户行为中的作用。本研究通过将积极满足和保护性厌恶整合到GenAI使用的统一模型中，在理论上做出了贡献。实际上，它为设计自适应的、以用户为中心的人工智能系统提供了可行的见解，这些系统可以增强用户粘性，同时减少阻力。

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引用次数: 0

Assist or substitute? The influential mechanism of worker's usage experience on their overall evaluation of generative artificial intelligence 协助还是替代？员工使用经验对生成式人工智能整体评价的影响机制

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2025-12-08 DOI: 10.1016/j.techsoc.2025.103190

Boyang Zheng , Chunqu Xiao , Yayu Zhou , Lei Wu , Hongyong Zhou

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.

生成式人工智能在提高生产力方面发挥着至关重要的作用，同时也重塑了工人的工作方式，带来了职业冲击。本研究旨在丰富对影响员工对生成式人工智能态度的因素及其潜在机制的理解。根据细化似然模型（ELM），使用经验作为细化信息通过中心路径进行加工，形成态度和感知。我们进行了包括实验和问卷调查在内的五项研究。结果表明：(1)员工对生成式人工智能的使用体验与其对生成式人工智能的总体评价呈正相关；(2)使用体验与综合评价之间的中介作用是辅助知觉而非替代知觉；(3)创造性自我效能感可以调节使用体验与整体评价的关系，以及辅助感知的间接效应路径；(4)就业能力可以调节使用体验与综合评价之间的关系。对于低创造自我效能和低就业能力的工作者，使用体验并不能提高他们的整体评价。从理论上讲，本研究扩展了对影响工人对生成式人工智能态度的前因的理解，并确定了感知援助和替代的相对独立性。它实际上为应对生成式人工智能带来的机遇和挑战提供了管理建议。未来的研究可能会建立在这项工作的基础上，进一步探索使用经验如何影响不同技术和职业背景下的认知。

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引用次数: 0

Spatiotemporal evolution and configuration pathways of digital-intelligent regional innovation ecosystem sustainability: Evidence from China based on symbiosis theory 数字智能区域创新生态系统可持续性的时空演化与配置路径——基于共生理论的中国证据

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2025-11-04 DOI: 10.1016/j.techsoc.2025.103144

Qinwen Deng

Amid the global wave of digital and intelligent transformation, Digital-Intelligent Regional Innovation Ecosystem Sustainability (DIRGIES) has become vital for promoting innovation, enhancing resilience, and overcoming growth bottlenecks. Grounded in symbiosis theory, this study develops a five-dimensional evaluation framework, which includes units, matrix, community, network, and environment. By integrating the CRITIC-TOPSIS method, spatial econometrics, and dynamic QCA, it systematically examines the spatiotemporal evolution and configuration pathways of DIRGIES across Chinese provinces from 2011 to 2023. The findings reveal that DIRGIES in China exhibit a spatial divergence pattern characterized by strong performance in the eastern region and weaker performance in the west; however, with the widespread adoption of digital technologies and deepening policy coordination, spatial dependence has weakened and network-based collaboration has intensified. Dynamic QCA identifies four configurations associated with high DIRGIES and four associated with low DIRGIES, highlighting the complex, nonlinear, and synergistic causal mechanisms among multiple factors. Digital-intelligent technologies significantly enhance system resilience by reconfiguring resource allocation, optimizing network structures, and strengthening environmental adaptability. Based on these insights, this study proposes a stratified, differentiated, and dynamically adaptive policy framework that provides a theoretical foundation and practical guidance for differentiated regional governance.

在全球数字化和智能化转型浪潮中，数字智能区域创新生态系统可持续性（diggies）对于促进创新、增强韧性和克服增长瓶颈至关重要。本研究以共生理论为基础，构建了包括单位、矩阵、社区、网络和环境在内的五维评价框架。运用critical - topsis方法、空间计量经济学和动态QCA方法，系统分析了2011 - 2023年中国省区乡镇乡镇生态系统的时空演化与配置路径。研究结果表明：中国省级以上产业发展呈现出东强西弱的空间差异格局；然而，随着数字技术的广泛采用和政策协调的深化，空间依赖性减弱，基于网络的协作得到加强。动态QCA确定了与高DIRGIES相关的四种配置和与低DIRGIES相关的四种配置，突出了多因素之间复杂、非线性和协同的因果机制。数字智能技术通过重新配置资源配置、优化网络结构和增强环境适应性，显著增强了系统的弹性。在此基础上，本研究提出了一个分层、差别化、动态适应的政策框架，为差别化区域治理提供理论基础和实践指导。

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引用次数: 0

AI companions and subjective well-being: Moderation by social connectedness and loneliness 人工智能同伴和主观幸福感：社会联系和孤独感的调节

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2026-01-07 DOI: 10.1016/j.techsoc.2026.103229

Atsushi Nakagomi , Yasuko Akutsu , Mika Yasuoka , Noriyuki Abe , Shiichi Ihara , Taisuke Teroh , Takahiro Tabuchi

Conversational AI companions—such as Replika and Character.AI—are increasingly adopted to provide emotional support, yet their psychological effects remain underexplored. This study investigates whether the use of AI companions is associated with enhanced well-being, and whether these associations are moderated by social network/support and loneliness. We analysed cross-sectional data from 14,721 Japanese adults participating in nationwide internet panel surveys conducted in December 2024 and January 2025. Well-being was assessed across three domains: evaluative (life satisfaction), hedonic (happiness), and eudaimonic (purpose and meaning in life). AI use was categorized as either companion or non-companion. Moderators included social network/support (measured via the Lubben Social Network Scale, LSNS-6) and loneliness (UCLA Loneliness Scale). Multivariable linear regression and restricted cubic spline models were used to assess associations and effect modification. Use of AI companions was significantly associated with higher scores across all well-being domains. In contrast, non-companion AI use showed weaker or inconsistent associations. A U-shaped moderation pattern emerged for friend-based social network/support: the benefits of AI companions were most pronounced among those with moderate levels of social connection and attenuated among those with either very high or very low levels. The strongest positive associations were observed among individuals reporting high loneliness. These findings suggest that AI companions may offer emotional and psychological benefits, particularly for individuals with unmet social and emotional needs or moderate social embeddedness. Future research should explore causal mechanisms and develop design strategies that promote well-being without impairing real-world social engagement.

会话AI伙伴，如Replika和Character。人工智能越来越多地被用于提供情感支持，但其心理影响仍未得到充分研究。本研究调查了人工智能伴侣的使用是否与增强幸福感有关，以及这些联系是否受到社交网络/支持和孤独感的调节。我们分析了14,721名日本成年人的横断面数据，这些成年人参加了在2024年12月和2025年1月进行的全国性互联网小组调查。幸福感的评估分为三个领域：评估型（生活满意度）、享乐型（幸福）和udaimonic（生活的目的和意义）。人工智能的使用分为陪伴和非陪伴。调节因子包括社会网络/支持（通过Lubben社会网络量表，LSNS-6测量）和孤独感（UCLA孤独量表）。多变量线性回归和限制三次样条模型用于评估关联和效果修正。人工智能伴侣的使用与所有幸福领域的高分显著相关。相比之下，非伴侣人工智能的使用显示出较弱或不一致的关联。基于朋友的社交网络/支持出现了u型调节模式：人工智能同伴的好处在社交联系水平中等的人群中最为明显，而在社交联系水平非常高或非常低的人群中则有所减弱。在报告高度孤独感的个体中观察到最强的正相关。这些发现表明，人工智能伴侣可能会带来情感和心理上的好处，特别是对那些社会和情感需求未得到满足或社会嵌入程度不高的人来说。未来的研究应该探索因果机制，并制定设计策略，在不损害现实世界社会参与的情况下促进幸福。

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引用次数: 0

Driving sustainability: ESG and business strategy in global autonomous driving industry 推动可持续发展：全球自动驾驶行业的ESG与商业战略

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2026-01-05 DOI: 10.1016/j.techsoc.2026.103225

Feng-Ping Lee , Irene Wei Kiong Ting , Wen-Min Lu

This research investigates the influence of environmental, social and governance (ESG) factors on the sustainable performance of global autonomous driving firms, specifically examining the moderating effect of business strategy. Drawing on data from 2017 to 2024 for 34 global enterprises—collectively representing approximately 85 % of total market capitalisation—this study assesses operational and market efficiency via a data envelopment analysis framework. These assessments are further refined through nonparametric tests and truncated regression analyses. Findings demonstrate that social initiatives enhance operational efficiency, whereas environmental and governance initiatives primarily strengthen market performance. Furthermore, business strategy moderates these relationships; strategic misalignment, such as rigid governance structures within prospector firms, diminishes ESG effectiveness. Regional analysis reveals distinct patterns: North American firms excel in social and environmental metrics; European firms lead in governance and operational efficiency; and Asian firms, whilst driven by technology and production, exhibit lower marketability and social responsibility scores. Beyond firm-specific metrics, these results underscore the broader societal importance of autonomous driving technologies. Integrating ESG frameworks remains essential to guiding innovation that is ethical, environmentally sustainable and socially responsible. Ultimately, this study offers actionable insights for policymakers, industry leaders and investors, highlighting the importance of aligning ESG practices with strategic priorities to foster sustainable technological development and ensure that autonomous driving yields public and economic benefits.

本研究考察了环境、社会和治理（ESG）因素对全球自动驾驶公司可持续绩效的影响，特别是考察了商业战略的调节作用。利用2017年至2024年34家全球企业的数据，本研究通过数据包络分析框架评估了运营和市场效率。这些企业的总市值约占总市值的85%。这些评估通过非参数测试和截断回归分析进一步完善。研究结果表明，社会举措提高了运营效率，而环境和治理举措主要提高了市场绩效。此外，企业战略调节了这些关系；战略错位，如勘探公司内部僵化的治理结构，降低了ESG的有效性。区域分析揭示了不同的模式：北美公司在社会和环境指标方面表现出色；欧洲公司在治理和运营效率方面处于领先地位；亚洲企业虽然受到技术和生产的推动，但在市场竞争力和社会责任方面得分较低。除了公司特定的指标，这些结果强调了自动驾驶技术在更广泛的社会重要性。整合ESG框架对于指导道德、环境可持续和社会负责的创新仍然至关重要。最终，本研究为政策制定者、行业领导者和投资者提供了可操作的见解，强调了将ESG实践与战略重点相结合的重要性，以促进可持续技术发展，并确保自动驾驶产生公共和经济效益。

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引用次数: 0

From promise to concern: Public perceptions of AI in ESG frameworks over time 从承诺到关注：公众对ESG框架中人工智能的看法

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2026-01-03 DOI: 10.1016/j.techsoc.2026.103219

Francesco Laviola, Nicola Cucari

This study investigates how public sentiment toward Artificial Intelligence (AI) has evolved at the intersection of Environmental, Social, and Governance (ESG) frameworks and the rising field of Corporate Digital Responsibility (CDR) over the past 25 years. Drawing on a dataset of 33,628 news articles published between 2000 and 2025, we conduct a large-scale longitudinal sentiment analysis to identify discursive patterns in the perception of AI's role across the ESG dimensions. Our findings reveal substantial variation across the three pillars. While sentiment toward AI in governance contexts shows a consistently positive trend, associated with increased expectations for transparency, monitoring, and compliance, environmental sentiment exhibits a sharp downturn after 2022, reflecting concerns over the carbon footprint of generative AI technologies. The social dimension displays fluctuating sentiment, influenced by debates on automation, fairness, and ethical accountability. These differentiated trajectories suggest that AI legitimacy is a domain-specific and socially negotiated construct, rather than a uniform outcome of technological advancement. Public discourse, as captured in news media, functions as an anticipatory indicator of emerging regulatory tensions and reputational risks, offering valuable foresight for corporate and institutional decision-makers. This study contributes to the literature on technology and society by highlighting the role of sentiment dynamics in shaping AI governance and sustainability strategies. It provides both theoretical insights into the social construction of technological legitimacy and practical implications for the design of responsive, context-sensitive ESG policies in the age of digital transformation.

本研究调查了在过去25年里，在环境、社会和治理（ESG）框架和企业数字责任（CDR）兴起的交叉点上，公众对人工智能（AI）的看法是如何演变的。利用2000年至2025年间发表的33,628篇新闻文章的数据集，我们进行了大规模的纵向情感分析，以确定人工智能在ESG维度上的角色感知中的话语模式。我们的发现揭示了这三大支柱之间的巨大差异。虽然在治理背景下，对人工智能的看法呈现出持续的积极趋势，与对透明度、监控和合规性的期望增加有关，但在2022年之后，环境情绪出现急剧下滑，反映了对生成式人工智能技术碳足迹的担忧。社会维度表现出波动的情绪，受到自动化、公平和道德责任辩论的影响。这些不同的轨迹表明，人工智能的合法性是一个特定领域和社会协商的结构，而不是技术进步的统一结果。新闻媒体捕捉到的公共话语，可以作为监管紧张局势和声誉风险的预期指标，为企业和机构决策者提供宝贵的预见。这项研究通过强调情感动态在塑造人工智能治理和可持续发展战略中的作用，为技术和社会方面的文献做出了贡献。它为技术合法性的社会建构提供了理论见解，并为数字化转型时代响应性、情境敏感型ESG政策的设计提供了实践意义。

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引用次数: 0

AI-metaverse at work: Trading value for risk in organizational knowledge systems 工作中的人工智能元世界：组织知识系统中的风险交易价值

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2025-12-17 DOI: 10.1016/j.techsoc.2025.103202

Yuheng Ren , Safiya Mukhtar Alshibani , Varun Chotia , Bhumika Gupta , Amedeo Maizza

Artificial Intelligence (AI) and metaverse technologies are transforming organisational knowledge ecosystems by facilitating immersive, intelligent, and interactive digital work environments. Utilising the theory of consumption value and perceived risk theory, this research formulates and experimentally evaluates two structural models to investigate the impact of AI–metaverse features on knowledge engagement as well as on knowledge application performance. SmartPLS4 was used to look at survey data from 279 professionals who worked in IT, manufacturing, finance, healthcare, education, and retail. The findings indicate that AI–metaverse learning value, cognitive immersion, and enjoyment substantially improve knowledge engagement and subsequent application performance. Conversely, techno-overload surprisingly has a positive effect, implying adaptive behaviour in digitally saturated contexts. On the other hand, information overload, data-surveillance fear, and perceived security vulnerability act as positional non-inhibitors of knowledge engagement. These results enhance theory of consumption value and perceived risk theory by illustrating that cognitive–affective appraisal mechanisms collaboratively influence user engagement in organisational metaverse systems. The paper makes a unique contribution by being one of the first to show how value-driven and risk-based AI-metaverse traits work together to affect organisational knowledge outcomes. This helps us understand both the theory and practice of responsible metaverse-enabled work design.

人工智能（AI）和虚拟世界技术通过促进沉浸式、智能和交互式数字工作环境，正在改变组织的知识生态系统。本研究利用消费价值理论和感知风险理论，构建并实验评估了两个结构模型，以探讨人工智能元环境特征对知识投入和知识应用绩效的影响。SmartPLS4用于查看279名在IT、制造业、金融、医疗保健、教育和零售业工作的专业人士的调查数据。研究结果表明，人工智能的元学习价值、认知沉浸和享受显著提高了知识参与和随后的应用性能。相反，令人惊讶的是，科技超载有积极的影响，意味着在数字饱和的环境中适应性行为。另一方面，信息超载、数据监视恐惧和感知到的安全漏洞是知识参与的位置非抑制剂。这些结果通过说明认知-情感评估机制协同影响组织元生态系统中的用户参与，增强了消费价值理论和感知风险理论。这篇论文做出了独特的贡献，它是第一批展示价值驱动和基于风险的人工智能元特征如何共同影响组织知识成果的论文之一。这有助于我们理解负责任的元环境工作设计的理论和实践。

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引用次数: 0

Technological imprints of TMTs, configuration of technological resources and Chinese enterprise digital transformation tmt的技术印记、技术资源配置与中国企业数字化转型

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2025-12-29 DOI: 10.1016/j.techsoc.2025.103210

Meiting Ma , Xiaojie Wu , Xiuqiong Wang

The technological imprint of the top management team (TMT) plays a critical role in firms' digital transformation. However, research on why and how educational and positional technological imprints affect digital transformation differently is lacking. Taking 2303 Chinese listed A-share enterprises from 2011 to 2022 as a sample and combining imprint theory with upper echelons theory, we investigate the mediating effect of the size and quality of the technological resource configuration on the relationship between TMTs' technological imprints and firms’ digital transformation. The results show that when executives have a technological imprint, they prefer a high level of digital transformation. Executives with educational technological imprints tend to enhance the quality of the technological resource configuration to pursue advanced digital transformation, whereas those with positional technological imprints focus on expanding the size of such a configuration. This finding has important theoretical and practical significance for traditional enterprises attending to the role of TMTs in digital transformation.

高层管理团队（TMT）的技术印记在企业数字化转型中起着至关重要的作用。然而，关于教育和位置技术印记对数字化转型的影响为何以及如何不同的研究却很缺乏。本文以2011 - 2022年2303家中国a股上市企业为样本，结合印记理论和上层梯队理论，探讨技术资源配置规模和质量在技术管理者技术印记与企业数字化转型关系中的中介作用。结果表明，当高管有技术烙印时，他们更倾向于高水平的数字化转型。具有教育技术印记的高管倾向于提高技术资源配置的质量以追求先进的数字化转型，而具有定位技术印记的高管则倾向于扩大这种配置的规模。这一发现对于传统企业关注TMTs在数字化转型中的作用具有重要的理论和现实意义。

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引用次数: 0

Spatiotemporal evolution of regional innovation capacity from an open innovation perspective 开放创新视角下的区域创新能力时空演化

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2026-06-01 Epub Date: 2025-11-10 DOI: 10.1016/j.techsoc.2025.103157

Feng Wu , Jin Chen , Yue Tang , Yanwei Zhang

This study extends the concept of open innovation from the firm level to regional innovation ecosystems by integrating social-ecological system insights and operationalizing a 3D index architecture covering basic innovation capacity, open innovation capacity, and innovation adaptability. Using a projection pursuit model optimized by a real-coded accelerating genetic algorithm (RAGA-PPM), kernel density estimation, and spatial correlation analysis, we evaluate the regional innovation capacity of 31 Chinese provinces from 2011 to 2021 and examine their spatiotemporal evolution. Results indicate that innovation adaptability carries the largest and most stable weight among Level 1 dimensions, indicating that coordination, learning, and risk absorption routines increasingly shape how inputs and openness translate into outcomes. Spatially, Beijing–Tianjin–Hebei, the Bohai Rim, the Yangtze River Delta, and the Pearl River Delta all exhibit strong capacity but heterogeneous integration, with tighter coupling in Shanghai–Jiangsu–Zhejiang–Anhui. Globally and locally, positive spatial correlations follow a pattern of initial decline and subsequent increase; local high-high clusters contract overall, with apparent weakening in the north, stronger integration in the east, and improvements around the southwest. Methodologically, RAGA-PPM improves sensitivity to nonlinear, multimodal structures and yields temporally coherent measures compared with entropy-based baselines. Furthermore, policy translation is specified along three tracks: capability formation for adaptability, orchestration of cross-regional collaboration, and demand-side measures to enhance absorption, each with concrete instruments for provincial implementation. The findings of the study advance the integration of open innovation and regional innovation systems as well as provide actionable guidance for differentiated public policies.

本研究通过整合社会生态系统视角，构建了涵盖基础创新能力、开放式创新能力和创新适应性的三维指标体系，将开放式创新的概念从企业层面扩展到区域创新生态系统。利用实数编码加速遗传算法优化的投影寻踪模型、核密度估计和空间相关分析，对2011 - 2021年中国31个省区的区域创新能力进行了时空演化分析。结果表明，创新适应性在第一级维度中权重最大且最稳定，表明协调、学习和风险吸收习惯对投入和开放转化为结果的影响越来越大。从空间上看，京津冀、环渤海、长三角、珠三角均表现出较强的容量整合但异质性整合，其中沪、苏、浙、皖耦合更为紧密。在全球和局部，正空间相关性遵循最初下降后增加的模式；局地高-高集群整体收缩，北部明显减弱，东部一体化增强，西南周边有所改善。在方法上，与基于熵的基线相比，RAGA-PPM提高了对非线性、多模态结构的灵敏度，并产生了时间上一致的测量。此外，政策翻译沿着三条轨道进行：适应能力的形成，跨区域合作的协调，以及增强吸收的需求侧措施，每一条都有各省实施的具体工具。研究结果促进了开放式创新与区域创新系统的整合，并为差别化的公共政策提供了可操作的指导。

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引用次数: 0