Technology in Society最新文献

Spatio-temporal shifts, driving mechanisms, and resilience dynamics: Unraveling the evolution of global innovation networks (2003–2023) 时空变迁、驱动机制与弹性动态：全球创新网络的演变（2003-2023）

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-12-11 DOI: 10.1016/j.techsoc.2025.103192

Jinbao Wen , Xiang Yu , Wei Yang

This study examines the spatio-temporal shifts, driving mechanisms, and structural resilience of Global Innovation Networks (GINs) by leveraging transnational patent data from the World Intellectual Property Organization (2003–2023). Through Social Network Analysis (SNA), Temporal Exponential Random Graph Models (TERGM), and Network Resilience Assessment Modeling (NRAM), we deliver a dynamic and multi-level analysis of GINs. Findings indicate that GINs maintain small-world properties and a stable core-periphery architecture, while experiencing a marked eastward shift in influential nodes. The traditional Western-centered core has expanded to incorporate emerging economies such as China, India, and South Korea, signaling a decentralization of global innovation activity. TERGM results reveal multi-level drivers: endogenous structures such as reciprocity and triadic closure guide self-organization; actor attributes exhibit asymmetric effects, where patent protection strength, political stability, and market size attract innovation inflows, whereas economic scale and trade promote outflows; exogenous proximities show cultural similarity fosters connections, while geographic and administrative distances act as barriers. Notably, knowledge distance's constraining role weakens when accounting for structural embeddedness. NRAM assessments show that GIN resilience has strengthened over time, with improved tolerance to both targeted and random disruptions. Yet systemic vulnerability persists through a limited set of core nations (including the US, China, and Germany)—whose failure may trigger broad instability. By incorporating endogenous dynamics, seldom-studied exogenous factors, and resilience into a unified framework, this research advances GIN theory and offers strategic insights for governance and global patent planning amid systemic uncertainties.

本文利用世界知识产权组织2003-2023年跨国专利数据，分析了全球创新网络的时空变迁、驱动机制和结构弹性。通过社会网络分析（SNA），时间指数随机图模型（TERGM）和网络弹性评估模型（NRAM），我们提供了一个动态和多层次的分析网络安全风险。研究结果表明，新兴经济体保持了小世界特征和稳定的核心-外围结构，但在有影响的节点上经历了明显的东移。传统的以西方为中心的核心已经扩展到包括中国、印度和韩国等新兴经济体，这标志着全球创新活动的分散化。TERGM结果揭示了多层次的驱动因素：互惠和三元闭包等内生结构引导自组织；行动者属性表现出不对称效应，专利保护力度、政治稳定性和市场规模吸引创新流入，而经济规模和贸易促进创新流出；外源性接近表明，文化相似性促进了联系，而地理和行政距离则成为障碍。值得注意的是，当考虑结构嵌入性时，知识距离的约束作用减弱。NRAM评估显示，随着时间的推移，GIN的恢复能力有所增强，对目标中断和随机中断的容忍度都有所提高。然而，系统性脆弱性在少数核心国家（包括美国、中国和德国）中依然存在——这些国家的失败可能引发广泛的不稳定。通过将内生动力学、很少被研究的外生因素和弹性纳入一个统一的框架，本研究推进了GIN理论，并为系统不确定性下的治理和全球专利规划提供了战略见解。

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引用次数: 0

How disruptive technologies reshape urban safety: Spatial spillovers and governance mechanisms in China 颠覆性技术如何重塑中国城市安全：空间溢出效应与治理机制

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-12-08 DOI: 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.

颠覆性技术的快速发展为创新和提高城市安全开辟了新的途径。本文利用2011 - 2020年中国30个省份的面板数据，构建了衡量颠覆性技术水平的综合指数，并运用空间德宾模型探讨了颠覆性技术水平与城市基础设施容量、教育投资和城市安全的关系。研究结果表明，颠覆性技术显著提高了城市安全水平，但也引入了负面的空间溢出效应。市政基础设施能力是这些技术影响安全的关键渠道，而教育投资则加强了基础设施能力与安全结果之间的关系。这些发现突出了技术颠覆的双刃剑性质，并强调了协调治理的重要性。政策制定者应促进均衡的技术扩散，加强基础设施抵御能力，并投资于教育，以确保技术进步有效促进可持续城市发展和安全。

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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 : 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

Digital communities of practice and the knowledge transformation cycle: Enabling sustainable food systems through AI and Metaverse technologies 数字实践社区和知识转化周期：通过人工智能和元宇宙技术实现可持续粮食系统

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-12-03 DOI: 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.

本研究开发了一个概念性框架，以理论化数字增强的实践社区（cop），如慢食运动，如何通过先进的知识管理支持可持续的粮食系统转型。尽管数字创新越来越多地应用于农业食品系统，但许多文献仍然以技术为中心，关注基础设施和自动化，而忽略了数字工具如何调节基于社区的知识流动和适应能力。为了解决这一差距，我们将Nonaka和Takeuchi的SECI模型与Teece的动态能力框架结合起来，研究人工智能（AI）和元宇宙技术如何使cop能够创造、共享和转化知识。主要贡献是DEKA-CoPs模型（实践社区中的数字化知识架构），该模型解释了数字中介如何增强认知敏捷性、协作创新和系统适应性。在方法上，本文采用理论构建方法提出了四个可以指导未来实证工作的命题。该框架通过将重点从基于企业的创新转向数字化、社区主导的知识基础设施，推动了知识管理和可持续性文献的发展。它为决策者、技术专家和对设计包容性、适应性平台感兴趣的可持续发展从业者提供了实际意义，这些平台将当地知识融入农业食品转型中。

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引用次数: 0

Digital platforms, innovation networks, and institutional support in circular economy adoption: A moderated mediation analysis in Emerging Economies 采用循环经济的数字平台、创新网络和制度支持：新兴经济体的有调节中介分析

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-12-01 DOI: 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.

该研究探讨了数字平台整合、创新网络实力和可持续性的制度支持如何通过创新生态系统动力（IED）影响循环经济的采用（CEA），其中柬埔寨和越南的数字转型准备程度（DTR）起到了调节作用。采用横断面定量方法从900名受访者（每个国家450名）中收集信息。研究发现，数字平台、创新网络和制度支持对企业创新能力有显著影响，进而促进企业创新能力的提升。DTR直接或间接地加强了这些关系，这表明了它在循环转换中的重要性。各国之间的比较表明，与循环经济转型相关的背景存在差异。在越南，所有途径对CEA的影响更加一致，因此，数字平台和IED的影响更强。越南创新网络和制度支持对IED的中介作用更大，因为DTR具有调节作用。柬埔寨的关系和调节效应明显较低，但不可忽略，这表明在结构和数字准备方面存在差异。这些背景差异表明，数字和制度成熟度如何塑造资源协调的可持续性。该研究通过将数字化转型、创新生态系统和制度支持整合到一个新的、有调节的中介框架中来推进理论。在越南，决策者和管理者应该利用更先进的数字平台和稳定的政策来加速CEA。在柬埔寨，对数字基础设施和制度支持的投资对于克服结构性障碍和促进CEA至关重要。作为在东南亚跨国使用有调节的中介模型的首批实证研究之一，本研究展示了数字准备如何影响循环过渡。

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引用次数: 0

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? 揭示人工智能、生态创新效率和严格的环境政策在环境可持续性中的作用：七国集团经济体的负荷能力曲线假说是否成立？

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-12-01 DOI: 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.

近年来，全球环境影响加剧了全球变暖和气候变化的迫在眉睫的威胁。因此，即使对发达国家，如七国集团，实施创新的方法和可持续的生态保护实践仍然是一个相当大的挑战。因此，确定推动环境可持续性进展的关键因素是不可避免的。在此背景下，本研究首次尝试在负荷能力曲线（LCC）框架下，探讨人工智能（AI）、生态创新效率（EIE）、环境政策严格性（EPS）和绿色增长（GG）对负荷能力因子（LCF）的影响，以实现G7国家的环境可持续性。在这方面，采用创新的Driscoll-Kraay标准误差（DKSE）和面板校正标准误差（PCSE）方法，使用1990 - 2020年的数据来研究长期关系。研究发现：(1)生态创新效率主要通过提高承载能力因子促进环境可持续性，这对G7国家有利；(2)人工智能、环境政策严密性和绿色增长通过降低承载能力因子影响环境可持续性，对G7国家不利；（iii） LCC假设在G7国家无效，说明收入与LCC之间存在倒“u”型关系。这意味着，经济增长最初提高了环境的可持续性，但在达到一定阈值后，随后使环境恶化。这些研究结果强调，决策者应该通过优先考虑人工智能技术、加强严格的环境政策、实施清洁能源倡议、将经济增长和资源消耗脱钩以及进一步加强生态高效技术来重组七国集团（G7）国家的能源和环境政策。

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引用次数: 0

A societal readiness tool for responsible product innovation 负责任的产品创新的社会准备工具

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-11-29 DOI: 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.

本文介绍了社会准备工具（SRT），一种支持产品设计和创新的方法，使产品开发与社会需求和期望保持一致。该工具有两个功能。首先，它为开发人员提供指导，使他们能够以一种从最早期阶段就考虑道德、法律和社会影响的方式来导航产品开发过程。其次，该工具使开发人员和其他涉众能够对产品的社会准备水平进行定性的自我评估。该工具所体现的实质性主张是，新产品的技术和商业准备应辅以社会准备，这是通过在产品开发中嵌入对道德、法律和社会影响的关注来实现的。

引用次数: 0

Does the digital economy moderate the climate vulnerability-inclusive green growth nexus? International evidence 数字经济能否缓和气候脆弱性与包容性绿色增长之间的关系？国际证据

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-11-29 DOI: 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.

气候脆弱性的加剧严重制约了人类社会的长期生存能力，数字经济是缓解其负面影响的关键途径。本研究利用2013 - 2023年的跨国面板数据，考察了气候脆弱性对包容性绿色增长（IGG）的影响，并检验了数字经济的调节作用。结果表明，气候脆弱性的增加显著抑制了IGG，并且在调整模型设置和样本范围并解决内生性问题后，这一结论仍然是稳健的。机制分析表明，气候脆弱性主要通过抑制能源结构转型和削弱社会公平来阻碍IGG。调节效应分析表明，数字经济可以缓解气候冲击对IGG的不利影响。然而，面板阈值模型结果表明，在数字经济阈值的两侧，调节强度并没有显著差异。有限混合回归模型能够有效捕捉数字经济的调节效应，并表明其调节作用随着数字经济的发展而不断增强。该研究为政策制定者提供了关键的经验支持和可操作的政策见解，以应对气候挑战并推进政府间免疫组。

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引用次数: 0

How AI shapes entrepreneurial processes in social enterprises: A model of augmented and centric pathways 人工智能如何塑造社会企业的创业过程：增强和中心路径的模型

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-11-29 DOI: 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.

为了应对复杂的社会挑战，社会企业家越来越多地利用人工智能（AI）。然而，现有文献往往将人工智能视为一种静态的技术投入，对其融入社会企业的动态、展开过程的探索严重不足。此外，这种观点将技术视为整体，忽视了具体的数字表示和集成深度如何重新配置创业过程。为了解决这一差距，本研究开发了人工智能融入社会创业的过程模型。采用纵向、多案例研究方法，我们研究了人工智能集成如何塑造社会创业的三个过程：机会识别、机会开发和机会利用。我们的研究结果确定了两种战略路径：人工智能增强型社会创业，即人工智能被用于增强现有的社会商业模式；以及以人工智能为中心的社会创业，即一种新的人工智能能力从根本上创造了社会价值主张。我们的主要贡献是一个流程框架，阐明了创业活动、战略重点和发展动态在人工智能增强和以人工智能为中心的路径上是如何分化的。该模型推进了对社会创业中技术整合的理论认识，并为利用人工智能创造和扩大社会价值提供了实践指导。

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引用次数: 0

How can robots coexist with labor employment?—Empirical evidence based on matching data of Chinese industrial robots 机器人如何与劳动就业共存？——基于中国工业机器人匹配数据的经验证据

IF 12.5 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2025-11-28 DOI: 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.

在人工智能时代，机器人与劳动力的和谐共存对于中国经济的高质量发展和中国式现代化的推进至关重要。本文基于嵌套的三因素CES生产函数模型，构建了替代弹性的估计方法。利用2006 - 2019年中国制造业数据和国际机器人联合会（IFR）的机器人数据，我们估计了机器人与劳动力之间的替代弹性。研究结果表明，中国制造业中机器人与劳动力之间存在互补关系，机器人与劳动力的结合与嵌套资本之间也存在互补关系。然而，在制造业子行业中，机器人与劳动力之间的替代弹性在一些行业（被归类为替代行业）超过了统一，在另一些行业（互补行业）低于统一。此外，机器人的采用对替代产业的劳动力有显著的挤出效应，而对互补产业的影响在统计上不显著。通过估算替代弹性，本研究提供了令人信服的证据，证明机器人部署与就业之间存在强大的共生关系。这些发现为人工智能时代的政策制定者提供了宝贵的见解，以促进制造业的高质量、包容性就业。

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引用次数: 0