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Impact of government policies on the electric vehicle industry, environment, and society: A systematic review 政府政策对电动汽车产业、环境和社会的影响:系统回顾
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-05 DOI: 10.1016/j.techsoc.2026.103226
Chi Yang, Lixian Qian, Miaomiao Liu
Countries worldwide are implementing government policies to promote the development of the electric vehicle industry, and this is attracting increasing research attention. However, a systematic and holistic discussion on the effectiveness of these policies is still lacking, which makes it difficult to understand comprehensively how government interventions influence the electric vehicle industry, environment, and society. To address this research gap, we conduct a systematic literature review of 76 selected empirical studies on electric vehicle policy effectiveness that used observational data. Grounding it in three core theoretical perspectives (i.e., signaling, information, and policy mix), we develop an integrated and multidimensional framework to theorize about the impact of four types of electric vehicle policies (i.e., demonstration, financial, regulatory, and soft instruments) on five outcomes (i.e., research and development performance, financial performance, market performance, environmental impact, and social impact). We further examine the (in)consistencies of prior research findings using the Herfindahl–Hirschman Index and provide promising directions for future research. This study advances the conceptual and empirical understanding of electric vehicle policy effectiveness and offers valuable practical implications for researchers, policymakers, and authorities seeking to explore and manage its complexity.
世界各国都在实施促进电动汽车产业发展的政府政策,这引起了越来越多的研究关注。然而,对这些政策的有效性仍缺乏系统和全面的讨论,这使得很难全面了解政府干预如何影响电动汽车产业,环境和社会。为了解决这一研究空白,我们对76项使用观测数据的关于电动汽车政策有效性的实证研究进行了系统的文献综述。在三个核心理论视角(即信号、信息和政策组合)的基础上,我们开发了一个综合的多维框架,以理论化四种类型的电动汽车政策(即示范、金融、监管和软工具)对五种结果(即研发绩效、财务绩效、市场绩效、环境影响和社会影响)的影响。我们使用Herfindahl-Hirschman指数进一步检验了前人研究结果的一致性,并为未来的研究提供了有希望的方向。本研究促进了对电动汽车政策有效性的概念和实证理解,并为寻求探索和管理其复杂性的研究人员、政策制定者和当局提供了有价值的实际意义。
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引用次数: 0
Innovating against the odds? The impact of regulatory challenges on technology commercialization and product innovation performance 克服困难进行创新?监管挑战对技术商业化和产品创新绩效的影响
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-05 DOI: 10.1016/j.techsoc.2026.103214
Samuel Adomako , Mai Dong Tran
This study investigates how regulatory burden influences product innovation performance in emerging markets. Integrating the institutional theory, we propose that regulatory burden undermines firms’ perceived ability to commercialize new technologies, termed technology commercialization potential, which mediates the negative impact on innovation outcomes. We further examine how this relationship is shaped by two contextual factors: intangible resource advantage and environmental hostility. Using a two-wave, multi-informant survey data from 336 Vietnamese SMEs, the results confirm the mediating role of commercialization potential. Moreover, while intangible resource advantage strengthens the commercialization–innovation link, environmental hostility unexpectedly weakens it, indicating that external pressures can overwhelm firms’ commercialization efforts. These findings contribute to regulatory science and innovation research by highlighting commercialization potential as a critical mechanism through which institutions affect innovation. The study offers insights for managers seeking to overcome institutional barriers and for policymakers aiming to create more innovation-friendly regulatory environments.
本研究探讨监管负担如何影响新兴市场的产品创新绩效。结合制度理论,我们提出监管负担削弱了企业将新技术商业化的感知能力,即技术商业化潜力,从而中介了对创新结果的负面影响。我们进一步研究了这一关系是如何由两个背景因素形成的:无形资源优势和环境敌意。通过对336家越南中小企业的两波、多信息来源调查数据,结果证实了商业化潜力的中介作用。此外,虽然无形资源优势加强了商业化与创新的联系,但环境敌意出人意料地削弱了这种联系,这表明外部压力可以压倒企业的商业化努力。这些发现通过强调商业化潜力作为制度影响创新的关键机制,有助于监管科学和创新研究。这项研究为寻求克服制度障碍的管理者和旨在创造更有利于创新的监管环境的政策制定者提供了见解。
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引用次数: 0
Bridging the divide? Realizing urban-rural integrated development in the artificial intelligence era: Evidence from China 弥合分歧?在人工智能时代实现城乡融合发展:来自中国的证据
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-05 DOI: 10.1016/j.techsoc.2026.103227
Shuyi Wang , Hong Yao , Zijun Mao
Urban-rural integrated development (URID) is vital for fostering sustainable economic growth and social stability. Therefore, whether Artificial Intelligence (AI) promotes or hinders this process is of great importance to both academics and policymakers. Using panel data for 277 cities in China from 2012 to 2021, this study examines the impact of AI on URID. The results show that AI significantly promotes URID: a 1-unit increase in the AI level corresponds to a 0.243-unit rise in URID. Grounded in Resource Orchestration Theory, this effect unpacks three primary channels: optimizing digital resource allocation, enhancing green innovation capabilities, and boosting entrepreneurial activity. Furthermore, the effect exhibits a significant positive spatial spillover. This research deepens the theoretical understanding of the relationship between AI and URID. It also provides a scientific basis for policies using smart technologies to promote the two-way flow of resources, empowering sustainable development across urban and rural areas.
城乡一体化发展对促进经济可持续增长和社会稳定至关重要。因此,人工智能(AI)是促进还是阻碍这一进程,对学术界和政策制定者都非常重要。本研究利用2012年至2021年中国277个城市的面板数据,考察了人工智能对城市id的影响。结果表明,人工智能显著促进了URID,人工智能水平每增加1个单位,URID就会增加0.243个单位。基于资源编排理论,该效应揭示了三个主要渠道:优化数字资源配置、增强绿色创新能力和促进创业活动。此外,该效应还表现出显著的正空间溢出效应。本研究加深了对AI与uri关系的理论认识。它还为利用智能技术促进资源双向流动、促进城乡可持续发展的政策提供了科学依据。
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引用次数: 0
Digital transformation, open innovation and circular business model transition: The role of effectual logic 数字化转型、开放式创新与循环商业模式转型:有效逻辑的作用
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-05 DOI: 10.1016/j.techsoc.2026.103223
Safiya Mukhtar Alshibani , Sanjay Chaudhary , Snigdha Dash , Raj V. Mahto
Despite the theorized role of open innovation in shaping circular business models, there remains ambiguity about how open innovation can accelerate the transition toward circularity. Transition towards a circular business model typically presents obstacles for entrepreneurial organizations because they lack access to resources. Ambiguity remains on how organizations transitioning to a circular business model deploy open innovation strategies and what decision-making mechanisms underpin the value co-creation processes. We address the research question: How do organizations deploy open innovation in circular business models? We explore how open innovation is integrated with circular business models. Based on a qualitative analysis of forty-three open-ended online interviews and Gioia’s methodology, the findings reveal that effectual logic supports organizations in effectively deploying open innovation while pursuing a circular business model. The transition towards circularity raises dilemmas about leveraging collaborations, and effectuctual logic assists in integrating an open innovation strategy into the circular business model. By minimizing resource commitment, collaborating with diverse stakeholders, and continuously refining processes, managers pursuing circularity can effectively address the challenges encountered during the transition to circularity.
尽管开放式创新在形成循环商业模式中的理论作用,但关于开放式创新如何加速向循环的过渡,仍然存在模糊性。向循环商业模式的过渡通常会给企业家组织带来障碍,因为他们缺乏获取资源的途径。在向循环商业模式过渡的组织如何部署开放式创新战略以及支持价值共同创造过程的决策机制方面,仍然存在模糊性。我们解决了研究问题:组织如何在循环商业模式中部署开放式创新?我们探索开放式创新如何与循环商业模式相结合。基于对43个开放式在线访谈和Gioia方法的定性分析,研究结果表明,有效逻辑支持组织在追求循环商业模式的同时有效地部署开放式创新。向循环的转变带来了利用协作的困境,而有效的逻辑有助于将开放式创新战略整合到循环商业模式中。通过最小化资源承诺,与不同的涉众合作,以及不断地改进过程,追求循环的管理人员可以有效地处理在向循环过渡期间遇到的挑战。
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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 Pub 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
Workers' subjective well-being in human-robot interaction: Evidence from China labor-force dynamics survey 人机交互中工人的主观幸福感:来自中国劳动力动态调查的证据
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-03 DOI: 10.1016/j.techsoc.2026.103212
Chen Shen , Hao Zeng , Ruizhe Fan
As the new wave of the technological revolution accelerates, the widespread industrial robot adoption is profoundly reshaping the labor market. While existing research has predominantly focused on objective socioeconomic indicators such as employment, income, and workplace safety, the systematic impact on workers' subjective well-being (WSWB) remains largely underexplored. By integrating global robotics data from the International Federation of Robotics (IFR), micro-level firm data from China's Second National Economic Census, and micro-individual data from the China Labor-force Dynamics Survey (CLDS), this paper explores the impact and mechanisms of industrial robot adoption on WSWB in the industrial sectors of cities at or above the prefecture level in China. The research results indicate that industrial robot adoption has a significant positive effect on improving WSWB. The mechanism analysis reveals heterogeneous effects across skill levels. For high-skilled workers, robots deliver multi-dimensional benefits, including higher wages and welfare income, reduced physical labor intensity, enhanced skill development, and an improved work-life balance. For low-skilled workers, while robot-driven productivity improvements facilitate wage growth, particularly for lower-income groups, their improvements in welfare benefits, skill diversification, and health-related outcomes remain relatively limited. Moreover, heterogeneity analysis reveals that the impact of industrial robot adoption on WSWB exhibits substantial significant differences across individual, sectoral, and regional dimensions. The findings provide empirically grounded support and actionable pathways to optimize labor market structures, narrow inter-group well-being gaps, and boost national well-being as industrial robots proliferate.
随着新一轮技术革命浪潮的加速,工业机器人的广泛采用正在深刻地重塑劳动力市场。虽然现有的研究主要集中在就业、收入和工作场所安全等客观社会经济指标上,但对工人主观幸福感(wsb)的系统性影响仍未得到充分探讨。本文通过整合国际机器人联合会(IFR)的全球机器人数据、中国第二次全国经济普查的微观企业数据和中国劳动力动态调查(CLDS)的微观个体数据,探讨了中国地级以上城市工业部门采用工业机器人对wsb的影响及其机制。研究结果表明,工业机器人的采用对改善WSWB有显著的积极作用。机制分析揭示了不同技能水平的异质性效应。对于高技能工人来说,机器人带来了多方面的好处,包括更高的工资和福利收入,降低体力劳动强度,促进技能发展,改善工作与生活的平衡。对于低技能工人来说,虽然机器人驱动的生产率提高促进了工资增长,特别是对低收入群体而言,但它们在福利、技能多样化和健康相关结果方面的改善仍然相对有限。此外,异质性分析表明,工业机器人的采用对wsb的影响在个人、部门和地区层面上都存在显著差异。随着工业机器人的激增,研究结果为优化劳动力市场结构、缩小群体间福祉差距、提高国民福祉提供了实证支持和可行途径。
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引用次数: 0
How automotive firms enable value creation within mature innovation ecosystems: The case of Polestar 汽车企业如何在成熟的创新生态系统中实现价值创造:以北极星为例
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-03 DOI: 10.1016/j.techsoc.2026.103218
Maya Hoveskog , Magnus Holmén , Anya Ernest , Magnus Bergquist
Complementors and their role in inducing and supporting the value co-creation of other complementors have rarely been in focus in innovation ecosystems studies. Specifically, the literature does not explain how a complementor can transition from a peripheral role to becoming a focal complementor. This paper explains how a peripheral complementor characterized by scarce resources and poorly aligned capabilities can overcome these obstacles through co-creation with other complementors and the focal actor of an innovation ecosystem. Through a qualitative case study approach, we show how a product-centric company, the automotive firm Polestar, entered a mature innovation ecosystem centered on the digital platform Android Automotive OS, thereby enhancing Polestar's onboard app development during the period 2018–2022. Using a thematic analysis, the paper shows how a complementor can transition to a focal position by creating and enabling a sub-ecosystem within a mature innovation ecosystem. The focal complementor is capable of aligning complementors to co-create value while simultaneously exploiting the focal actor's resources. The paper explains how the three mechanisms of strategic focus, agile practices, and capability building allow the focal complementor to maintain internal and external legitimacy and mobilize resources.
互补体及其在诱导和支持其他互补体共同创造价值中的作用在创新生态系统研究中很少受到关注。具体来说,文献没有解释互补如何从外围角色转变为焦点互补。本文解释了以资源稀缺和能力不一致为特征的外围互补企业如何通过与其他互补企业和创新生态系统的核心参与者共同创造来克服这些障碍。通过定性案例研究方法,我们展示了以产品为中心的汽车公司Polestar如何进入一个以数字平台Android automotive OS为中心的成熟创新生态系统,从而在2018-2022年期间增强了Polestar的车载应用程序开发。通过专题分析,本文展示了如何通过在成熟的创新生态系统中创建和启用子生态系统来实现互补过渡到焦点位置。焦点互补者能够协调互补者共同创造价值,同时利用焦点行动者的资源。本文解释了战略焦点、敏捷实践和能力建设这三种机制如何使焦点互补保持内部和外部合法性并调动资源。
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引用次数: 0
The impact of artificial intelligence on startup business model innovation: exploring conditional effects of different strategic goals 人工智能对创业公司商业模式创新的影响:探索不同战略目标的条件效应
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-03 DOI: 10.1016/j.techsoc.2026.103215
Nicole Cecchele Lago , Daniel de Abreu Pereira Uhr , Jose Luis Duarte Ribeiro , Yasmin Olteanu , Klaus Fichter
The adoption of Artificial Intelligence (AI) is reshaping how startups create, deliver, and capture value. Despite widespread practical use, empirical evidence on AI's impact on startup business model innovation (BMI) remains limited. This study examines the causal effect of AI on BMI and investigates how this effect is conditioned by strategic goals—rapid growth, profitability, market share, and social/environmental impact. Using data from 1104 German startups and nonparametric tree-based Double Machine Learning models, we find that startups with intense use of AI exhibit significantly higher BMI than startups with little or no AI use. This effect is especially pronounced in startups prioritizing rapid growth and profitability, and it is strongest when startups pursue multiple strategic goals simultaneously, highlighting the amplifying role of strategic alignment. By providing quantitative effect estimates, this research advances understanding of AI as a technological enabler of BMI and offers actionable guidance for entrepreneurs and policymakers on how BMI can be enhanced through the alignment of AI with distinct strategic goals.
人工智能(AI)的采用正在重塑初创公司创造、传递和获取价值的方式。尽管人工智能在实际应用中得到了广泛应用,但关于人工智能对初创企业商业模式创新(BMI)影响的实证证据仍然有限。本研究考察了人工智能对BMI的因果关系,并调查了这种影响如何受到战略目标的制约——快速增长、盈利能力、市场份额和社会/环境影响。使用来自1104家德国初创公司和非参数树型双机器学习模型的数据,我们发现大量使用人工智能的初创公司的BMI明显高于很少或没有使用人工智能的初创公司。这种效应在优先考虑快速增长和盈利能力的初创公司中尤为明显,当初创公司同时追求多个战略目标时,这种效应最为明显,这凸显了战略一致性的放大作用。通过提供定量效果估计,本研究促进了对人工智能作为BMI的技术推动者的理解,并为企业家和政策制定者提供了可操作的指导,说明如何通过人工智能与不同的战略目标相结合来提高BMI。
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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 Pub 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
Technology assessment through a hybrid scenario-based decision Making: Case of wind energy 基于混合场景决策的技术评估:风能案例
IF 12.5 1区 社会学 Q1 SOCIAL ISSUES Pub Date : 2026-01-02 DOI: 10.1016/j.techsoc.2025.103205
Chih-Hung Hsieh , Dana Bakry , Tugrul Daim
This study combines the CRITIC and DEMATEL methods and introduces a new hybrid scenario analysis approach that identifies cross-scenario strategies. We use Taiwan's wind energy industry as a case study to validate the process. Although scenario analysis has been applied across various fields and organization types—including strategic planning, education, training, and recent environmental issues—scholars have highlighted problems such as the subjectivity of qualitative analysis and the lack of quantitative evidence. To address this, this study integrates scenario analysis with quantitative multi-criteria decision analysis to support decision makers in conducting scenario evaluations. We achieve this by applying a multi-criteria approach to analyze the weights of uncertainty axes and causal relationships, leading to management prioritization that yields near-optimal decision analysis and enhances decision quality. Our methodology is validated with a case study in Taiwan's wind energy sector. In the best-case scenario, Taiwan's green energy substitution rate surpasses 20 %, simultaneously fostering new industrial chains in green manufacturing, energy storage, and carbon management. Conversely, under a pessimistic scenario, challenges such as land acquisition issues, tense international relations, grid delays, or regulatory uncertainties could limit renewable energy penetration to below 20 %.
该研究结合了CRITIC和DEMATEL方法,并引入了一种新的混合场景分析方法,用于识别跨场景策略。我们以台湾的风能产业为案例来验证这一过程。尽管情景分析已经应用于各个领域和组织类型,包括战略规划、教育、培训和最近的环境问题,但学者们强调了定性分析的主观性和缺乏定量证据等问题。为了解决这一问题,本研究将情景分析与定量多准则决策分析相结合,以支持决策者进行情景评估。我们通过应用多标准方法来分析不确定性轴和因果关系的权重,从而实现管理优先级,从而产生接近最优的决策分析并提高决策质量。我们的方法通过台湾风能行业的案例研究得到了验证。在最好的情况下,台湾的绿色能源替代率超过20%,同时培育绿色制造、能源储存和碳管理等新产业链。相反,在悲观的情况下,诸如土地征用问题、紧张的国际关系、电网延迟或监管不确定性等挑战可能会将可再生能源的渗透率限制在20%以下。
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引用次数: 0
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