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

Corrigendum to “Enhancing supplier innovation capabilities through digital technology integration: A relational perspective” [Technol. Forecast. Soc. Change 223 (February 2026) 124426] “通过数字技术集成提高供应商创新能力：关系视角”的勘误表[技术]。预测。Soc。更改223（2026年2月）124426]

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-11 DOI: 10.1016/j.techfore.2025.124473

Umair Tanveer , Thinh Gia Hoang , Shamaila Ishaq , Muhammad Mustafa Kamal , Rekha Attri

引用次数: 0

The dual environmental impact of AI technologies: Analyzing direct effects vs. economic growth dynamics 人工智能技术对环境的双重影响：分析直接影响与经济增长动态

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-11 DOI: 10.1016/j.techfore.2025.124480

Zahoor Ahmed

Unlike past studies, this research makes a novel contribution by analyzing the dual environmental impact of artificial intelligence (AI), including both its direct effects and its indirect effects through economic growth, on the load capacity factor (LCF), a comprehensive proxy for environmental sustainability, controlling the influence of political globalization (POG), renewable energy (REN), and political corruption (PCR). Analyzing panel data from 1996 to 2021 for the 10 largest economies, the Method of Moments Quantile Regression (MM-QR) is employed to uncover heterogeneous impacts across the distribution. Furthermore, the Feasible Generalized Least Squares (FGLS), the Driscoll-Kraay (DK) standard errors, and the Panel Corrected Standard Errors (PCSEs) are employed for robustness. The empirical analysis reveals that AI directly reduces LCF across all quantiles, indicating that AI adoption hampers environmental sustainability. However, the moderating effects of AI on LCF through economic growth are positive, implying that AI, indirectly through economic growth, can contribute to environmental sustainability. Both PCR and POG contribute to environmental degradation, while the use of green energy augments the LCF with an increasing impact. Economic growth poses varying effects on the LCF at different percentiles. These findings provide critical insights for policymakers, offering a significant contribution to the sustainable development literature.

与以往的研究不同，本研究通过分析人工智能（AI）对环境的双重影响，包括其直接影响和通过经济增长对负载能力因子（LCF）的间接影响，对环境可持续性的综合代表，控制政治全球化（POG），可再生能源（REN）和政治腐败（PCR）的影响做出了新颖的贡献。本文分析了1996年至2021年10个最大经济体的面板数据，采用矩量分位数回归（MM-QR）方法揭示了分布中的异质性影响。此外，采用可行广义最小二乘（FGLS）、Driscoll-Kraay （DK）标准误差和面板校正标准误差（PCSEs）进行鲁棒性分析。实证分析表明，人工智能直接降低了所有分位数的LCF，表明人工智能的采用阻碍了环境的可持续性。然而，人工智能通过经济增长对LCF的调节作用是正向的，这意味着人工智能通过经济增长间接地促进了环境的可持续性。PCR和POG都对环境退化有影响，而绿色能源的使用增加了LCF，影响越来越大。经济增长对不同百分位数的LCF有不同的影响。这些发现为政策制定者提供了重要的见解，为可持续发展文献做出了重大贡献。

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引用次数: 0

A promise-attentive triple embeddedness framework, applied to cellular foods 一个承诺-关注三重嵌入框架，应用于细胞食品

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-10 DOI: 10.1016/j.techfore.2025.124466

Mads Dahl Gjefsen

By conceptualizing embeddedness as integral to how incumbent firms evaluate technology promises, we might gain a clearer understanding of the roles these actors could play in sustainability transitions. Geels' Triple Embeddedness Framework (TEF) is traditionally applied to long-term historical analysis of firms-in-industries in the context of grand challenges; here, the framework is extended to enable analyses of technology promise dynamics, as conceptualized in cultural political economy terms. The promise-attentive TEF demarcates a global universal realm of promises from a contextual realm wherein pressures are experienced and strategies employed. The framework is applied to a study of Norwegian food system actors' views on cellular food (CF), which encompasses cultured, in-vitro meat and precision fermentation. The analysis shows how globally articulated promises become interpreted in relation to national-level factors, which not only filter pressures but also give direction to hypothetical response strategies. Empirically, the article documents skepticism among incumbents regarding CF's global uptake potential and food system transformation promises. Conceptually, the article elaborates on how the promise-attentive TEF might inform future research into technology promises as a distinct phenomenon across transition domains (e.g. health, energy, digitalization), via attention to characteristic processes in incumbents' promise evaluation, including boundary-drawing, scalar attachments, and digging deep.

通过将嵌入性概念化为现有企业如何评估技术承诺的组成部分，我们可能更清楚地了解这些参与者在可持续性转型中可能发挥的作用。Geels的三重嵌入性框架（TEF）传统上应用于大挑战背景下的行业企业的长期历史分析；在这里，该框架被扩展为能够分析技术承诺动态，如文化政治经济学术语的概念。关注承诺的TEF将承诺的全球普遍领域与经历压力和采用策略的上下文领域区分开来。该框架适用于挪威食品系统演员对细胞食品（CF）的看法的研究，其中包括培养，体外肉和精密发酵。分析显示了全球明确的承诺如何与国家层面的因素相关联，这些因素不仅过滤了压力，而且为假设的应对策略提供了方向。从经验上看，本文记录了现任者对CF全球吸收潜力和粮食系统转型承诺的怀疑态度。从概念上讲，本文详细阐述了关注承诺的TEF如何通过关注在位者承诺评估中的特征过程（包括边界绘制、标量附加和深入挖掘），为未来的技术承诺研究提供信息，将其作为一种跨过渡领域（如健康、能源、数字化）的独特现象。

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引用次数: 0

Exploring the impact of AI investments on waste management and mitigation from the Lens of sustainable circular economy 从可持续循环经济的角度探讨人工智能投资对废物管理和缓解的影响

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-10 DOI: 10.1016/j.techfore.2025.124468

Shanshan Li , Ummara Razi , Hawazen Almugren , Leilei Zhang , Aradhana Galgotia

Although artificial intelligence (AI) is boosting environmental and socio-economic progress in developed countries, its role in waste reduction, management, and recycling remains limited. Hence, this study explores the role of AI investments in waste management (WGN) and waste mitigation efforts in G7 economies through quarterly data from 2012Q1 to 2022Q4. In doing so, several econometric techniques were applied, which range from diagnostic tests for unit root and multicollinearity issues, while the primary method used was quantile regression due to the nonlinearity of the data. The outcomes show that AI's impact increases from lower to higher quantiles, from Q_15th − 0.001 towards Q_75th 0.030. In other words, AI is efficient in areas where WGN is low. However, WGN might increase due to AI, where the waste is already high due to the acceleration of industrial sectors and consumption. Furthermore, industrial productivity has a positive but insignificant impact, while urbanization has a negative and significant impact on WGN across quantiles. Air pollution has asymmetrical effects on WGN in both models. Novel policies that adopt AI technologies and applications and reduce air pollution should acknowledge the rising significance of waste management and circular economic models.

尽管人工智能（AI）正在推动发达国家的环境和社会经济进步，但它在减少废物、管理和回收方面的作用仍然有限。因此，本研究通过2012Q1至2022Q4的季度数据，探讨了人工智能投资在G7经济体废物管理（WGN）和废物减排工作中的作用。在此过程中，应用了几种计量经济学技术，其中包括对单位根和多重共线性问题的诊断测试，而由于数据的非线性，使用的主要方法是分位数回归。结果表明，人工智能的影响从低到高的分位数增加，从q15 - 0.001到q75 - 0.030。换句话说，人工智能在WGN低的区域是有效的。然而，由于人工智能，WGN可能会增加，由于工业部门和消费的加速，浪费已经很高。此外，工业生产率对WGN的影响为正但不显著，而城市化对WGN的影响为负但显著。在两个模型中，空气污染对WGN的影响是不对称的。采用人工智能技术和应用并减少空气污染的新政策应承认废物管理和循环经济模式日益重要。

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引用次数: 0

Balancing fun and function: How gamification designs and family communication shape continuous usage in online learning platforms 平衡乐趣和功能：游戏化设计和家庭交流如何塑造在线学习平台的持续使用

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-10 DOI: 10.1016/j.techfore.2025.124464

Tianyi Ma , Bowen Zheng , Wei Wang , Hefu Liu

Online learning platforms are increasingly integral to K-12 education, but face persistent challenges with high dropout rates. While gamification is widely employed to boost engagement, there is limited research on the underlying mechanisms through which different gamification designs influence students' continuous usage intentions (CUI). This study addresses these gaps by investigating how achievement, social, and immersion gamification designs impact perceived hedonic (PHV) and utilitarian values (PUV), which in turn influence CUI. It also explores the moderating role of conversation-oriented family communication pattern (CFCP), a critical but understudied factor in K-12 education. Using a mixed-method approach that combines moderated mediation analysis and fuzzy set qualitative comparative analysis (fsQCA), this study surveys 212 users of online learning platforms in central China. Results show that achievement and immersion designs are positively related to CUI through PHV, while achievement and social designs are positively related to CUI via PUV. Moreover, high CFCP strengthens the positive relationship between achievement and immersion designs on CUI via PHV, but weakens the relationship between achievement and social designs on CUI via PUV. These findings provide valuable insights for online learning platform designers and educators, offering guidance on how to tailor gamification strategies to improve student engagement and retention.

在线学习平台日益成为K-12教育不可或缺的一部分，但面临着高辍学率的持续挑战。虽然游戏化被广泛用于提高参与度，但关于不同游戏化设计如何影响学生持续使用意图（CUI）的潜在机制的研究有限。本研究通过调查成就、社交和沉浸式游戏化设计如何影响感知享乐（PHV）和实用价值（PUV）来解决这些差距，而感知享乐（PHV）和实用价值反过来又影响CUI。本文还探讨了以对话为导向的家庭沟通模式（CFCP）的调节作用，这是K-12教育中一个关键但尚未得到充分研究的因素。本研究采用有调节中介分析和模糊集定性比较分析（fsQCA）相结合的混合方法，对中部地区212名在线学习平台用户进行了调查。结果表明，成就设计和沉浸设计通过PHV与CUI正相关，而成就设计和社交设计通过PUV与CUI正相关。此外，高CFCP通过PHV强化了成就与沉浸设计之间的正相关关系，而通过PUV削弱了成就与社交设计之间的正相关关系。这些发现为在线学习平台设计师和教育工作者提供了有价值的见解，为如何定制游戏化策略以提高学生参与度和保留率提供了指导。

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引用次数: 0

How generative AI adoption affects supply chain resilience: An operations and supply chain management perspective 生成式人工智能的采用如何影响供应链弹性：从运营和供应链管理的角度

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-09 DOI: 10.1016/j.techfore.2025.124446

Jiguang Guo , Fu Jia , Lujie Chen

Generative AI drives profound societal transformations, and there is an urgent need to explore its potential in enhancing business resilience and sustainability. However, its influence on supply chain resilience remains empirically underexplored. Drawing on the operations and supply chain management (OSCM) perspective, this research aims to examine how generative AI improves or impedes supply chain resilience, while exploring the moderating effects of operational capability and supply chain concentration. Using panel data from Chinese A-share listed companies from 2017 to 2022, we employ fixed-effects models and a series of robustness checks to test the predictions. We discover that firms' generative AI enhances their supply chain resilience, and this effect is more pronounced among high-tech companies. Drawing on dynamic capability theory, this research sheds new light on the positive effect of operational capability (i.e., operational efficiency and operational slack), and the negative effect of supply chain concentration (i.e., customer concentration and supplier concentration) in shaping the impact of generative AI adoption on supply chain resilience. This study provides novel empirical evidence for the association between generative AI adoption and supply chain resilience and identifies key OSCM-related contingency factors in this relationship.

生成式人工智能推动了深刻的社会变革，迫切需要探索其在增强商业弹性和可持续性方面的潜力。然而，其对供应链弹性的影响仍未得到实证研究。从运营和供应链管理（OSCM）的角度出发，本研究旨在研究生成式人工智能如何提高或阻碍供应链弹性，同时探索运营能力和供应链集中度的调节作用。本文利用2017 - 2022年中国a股上市公司的面板数据，采用固定效应模型和一系列稳健性检验对预测结果进行检验。我们发现，企业的生成式人工智能增强了其供应链弹性，这种效应在高科技公司中更为明显。借助动态能力理论，本研究揭示了运营能力（即运营效率和运营松弛）和供应链集中度（即客户集中度和供应商集中度）在形成生成式人工智能采用对供应链弹性的影响方面的积极影响。本研究为生成式人工智能采用与供应链弹性之间的关系提供了新的经验证据，并确定了这种关系中与oscm相关的关键偶然性因素。

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引用次数: 0

Corrigendum to “Forecasting inclusive futures: Fintech, capability expansion, and livelihood pathways in urban Indian slums – A mixed-methods analysis” [Published in Technological Forecasting & Social Change, volume- 221, December (2025)] “预测包容性未来：金融科技、能力扩张和印度城市贫民窟的生计途径——混合方法分析”的勘误表[发表于《技术预测与社会变革》，第221卷，2025年12月]

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-09 DOI: 10.1016/j.techfore.2025.124463

Jaskirat Singh , Gurdip Singh Batra , Sarvjeet Kaur Chatrath

引用次数: 0

Perceptions matter. Exploring dynamics of circular economy innovation processes 观念问题。探索循环经济创新过程的动态

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-08 DOI: 10.1016/j.techfore.2025.124465

Eli Fyhn Ullern , Luitzen de Boer , Julia Schmitt , Sigurd Sagen Vildåsen

Transitioning to a circular economy (CE) entails a fundamental shift in how resources are produced, consumed, and valued in society. This presents challenges and opportunities for innovation across industries. Using absorptive capacity (ACAP) as a lens, we conceptualize the dynamics shaping firms' perceptions of drivers and barriers in CE innovation processes. We aim to better understand the reasons for the limited adoption of CE and how innovation processes emerge within and between firms. Through a longitudinal process study, we tracked how a collective of firms addressed the challenge of post-consumer plastic (PCP) waste in the Norwegian aquaculture industry. Our findings suggest that perceptions change over time as firms explore, assimilate, and exploit new knowledge from interactions between firm-level and the collective level. Moving from a static identification to a dynamic understanding, we captured how changing perceptions can cause shifting framings of drivers and barriers. We develop a framework that depicts how tensions are mitigated over time, in parallel with increasing adoption of CE, underscoring the need for a processual perspective. These insights are illustrated using the example of the world's first net pen walkways made of recycled PCP. Furthermore, we outline recommendations for policymakers and industry, particularly regarding the role of ‘Learning alliances’ and implications for the use of post-consumer materials across industries. Our study adds to the literature on circular economy innovation (CEI) by elucidating how drivers and barriers unfold and by highlighting the roles of collective ACAP and interaction in overcoming barriers to CE.

向循环经济转型需要从根本上改变资源的生产、消费和社会价值。这为各行各业的创新带来了挑战和机遇。以吸收能力（ACAP）为视角，我们概念化了企业对电子产品创新过程中驱动因素和障碍的认知的动态。我们的目标是更好地理解有限采用CE的原因，以及创新过程如何在公司内部和公司之间出现。通过纵向过程研究，我们跟踪了一批公司如何应对挪威水产养殖业消费后塑料（PCP）废物的挑战。我们的研究结果表明，随着企业从企业层面和集体层面的互动中探索、吸收和利用新知识，观念会随着时间的推移而改变。从静态识别到动态理解，我们捕捉到不断变化的感知如何导致驱动因素和障碍的变化框架。我们开发了一个框架，描述了随着时间的推移如何缓解紧张局势，同时越来越多地采用CE，强调了过程视角的必要性。这些见解是用世界上第一个由回收PCP制成的净笔式人行道的例子来说明的。此外，我们概述了对政策制定者和行业的建议，特别是关于“学习联盟”的作用和跨行业使用后消费材料的影响。我们的研究补充了关于循环经济创新（CEI）的文献，阐明了驱动因素和障碍是如何展开的，并强调了集体ACAP和相互作用在克服循环经济创新障碍中的作用。

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引用次数: 0

Trajectories and turning points: Objects of intermediation for generalisation 轨迹和转折点：泛化的中介对象

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-05 DOI: 10.1016/j.techfore.2025.124469

A. Loconto , K.M. Weber , R. van Dis , E. Lhoste , L. Bundgaard , M. Matt

We introduce generalisation as an intermediated trajectory to explain how system innovations, like alternative food systems, diffuse. While existing literature on diffusion and scaling focuses on human agency and steady progression, we propose a relational, object-oriented approach that highlights the role of situated intermediation punctuating/disrupting trajectories of generalisation. We identify four key objects of intermediation—knowledge, value(s), infrastructures, and rules—and demonstrate their role in reconfiguring actor networks and redirecting transformative trajectories. Through three empirical cases (natural wine, sustainable apiculture, and participatory research in France), we demonstrate how intermediation around these objects resolves challenges (interdependencies, uncertainties, complexities, controversies) and creates turning points that redirect transformative pathways. Our framework integrates the trajectory-turning point model to identify four conditions for transformative change: stability, resistance, identity transformation, and role commitment. Findings reveal that generalisation is dynamic and intermediated, whereby objects and actors collaboratively reconfigure networks, institutional contexts, and innovation objectives. The original contribution of this meso-level perspective lies in theorising generalisation as an intermediated trajectory, emphasising the material and relational work of objects alongside human agency. This reframing advances transition studies and innovation policy research by shifting focus from diffusion mechanisms to the situated, iterative processes that enable systems transformation.

我们引入泛化作为中介轨迹来解释系统创新，如替代食品系统，是如何扩散的。虽然现有的关于扩散和尺度的文献关注的是人类的代理和稳定的进展，但我们提出了一种关系的、面向对象的方法，强调了位置中介打断/破坏泛化轨迹的作用。我们确定了中介的四个关键对象——知识、价值、基础设施和规则——并展示了它们在重新配置行动者网络和重新定向变革轨迹中的作用。通过三个经验案例（法国的天然葡萄酒、可持续养蜂业和参与性研究），我们展示了围绕这些对象的中介如何解决挑战（相互依赖性、不确定性、复杂性、争议），并创造了重定向变革路径的转折点。我们的框架整合了轨迹-转折点模型，以确定转型变革的四个条件：稳定性、阻力、身份转换和角色承诺。研究结果表明，泛化是动态的和中介的，客体和行动者协同重新配置网络、制度背景和创新目标。这种中观视角的原始贡献在于将概括作为一种中介轨迹理论化，强调对象与人类代理的物质和关系工作。这种重构通过将焦点从扩散机制转移到使系统转型成为可能的情境、迭代过程，推进了转型研究和创新政策研究。

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引用次数: 0

Understanding barriers to agricultural technology adoption: Evidence from U.S. agribusiness firms 理解农业技术采用的障碍：来自美国农业综合企业的证据

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-05 DOI: 10.1016/j.techfore.2025.124448

Zubeyde Senturk Ulucak , Pathmanathan Sivashankar , Samir Huseynov , Recep Ulucak

This study investigates how economic, environmental, technical, political, and socio-cultural barriers shape innovation outcomes of openness, effort and success among US agribusiness firms. Drawing from perception-based survey data from agribusiness employees, the analysis employs a sequential modeling strategy combining ordered probit and triple hurdle probit estimation, complemented by tests of heterogeneity based on firm size and industry. The results reveal that environmental barriers are the most significant obstacle to innovation across all innovation stages, indicating regulatory and sustainability pressures can stimulate adaptive innovation. Economic barriers exhibit dual effect, reducing openness and effort but positively influencing innovation success once firms commit to adoption. Technical barriers hinder progress in specific contexts, especially for smaller firms and food related enterprises. Findings reveal heterogeneity across subsectors and firm sizes, highlighting that innovation in agribusiness often emerges as a strategic adaptation to constraints. From a policy perspective, interventions such as innovation subsidies, tax incentives for green technology, and inclusive financing mechanisms are essential to enable equitable and sustainable innovation adoption among firms with characteristics similar to those represented in this sample.

本研究探讨了经济、环境、技术、政治和社会文化障碍如何影响美国农业综合企业的开放、努力和成功的创新成果。从农业综合企业员工的基于感知的调查数据中，分析采用顺序建模策略，结合有序概率和三重障碍概率估计，并辅以基于公司规模和行业的异质性测试。结果表明，环境障碍是各阶段创新的最大障碍，表明监管压力和可持续性压力能够刺激适应性创新。经济壁垒表现出双重效应，一方面降低开放程度和努力程度，另一方面一旦企业承诺采用，又对创新成功产生积极影响。技术壁垒在特定情况下阻碍进步，特别是对较小的公司和与食品有关的企业。研究结果揭示了子行业和公司规模之间的异质性，突出表明农业综合企业的创新往往是对约束的战略适应。从政策角度来看，创新补贴、绿色技术税收激励和包容性融资机制等干预措施对于使具有与本样本相似特征的企业公平和可持续地采用创新至关重要。

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引用次数: 0