Technological Forecasting and Social Change最新文献_第10页

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 : 2026-03-01 Epub Date: 2025-12-09 DOI: 10.1016/j.techfore.2025.124463

Jaskirat Singh , Gurdip Singh Batra , Sarvjeet Kaur Chatrath

引用次数: 0

Adapting to technological change: How innovation ecosystems shape startup inter-organizational integration decisions 适应技术变革：创新生态系统如何塑造创业公司的组织间整合决策

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-03-01 Epub Date: 2025-12-05 DOI: 10.1016/j.techfore.2025.124454

Moacir Godinho Filho , Renata de Oliveira Mota , Cauê Ribeiro S. Frungilo , Gilberto Miller Devós Ganga , Jonhatan Magno Silva , Serena Strazzullo , Antonello Cammarano

In the context of technological turbulence, startups must navigate a dynamic environment characterized by rapid and unpredictable changes. This study, anchored in the Contingency Theory, investigates how technological turbulence and innovation ecosystems influence startups' strategic decisions regarding inter-organizational integration with customers, suppliers, and other institutions. Based on survey data from 183 startup managers, founders, CEOs, and team leaders, our study elucidates the adaptive strategies crucial for startups' survival and growth in technology-driven marketplaces. The findings reveal that startups embedded in innovation ecosystems exhibit a heightened propensity for inter-organizational integration, leveraging external capabilities to better adapt to technological changes. This integration fosters synergistic relationships, enhances information flow, and drives continuous innovation and operational efficiency. Conversely, startups outside these ecosystems face barriers in accessing resources and establishing trust-based relationships, highlighting the critical role of ecosystem participation in facilitating external collaborations. The study contributes to Contingency Theory by underscoring how environmental contingencies shape startup strategies and provides practical guidance for startup leaders on the importance of innovation ecosystem embeddedness and strategic partnerships.

在技术动荡的背景下，创业公司必须在一个以快速和不可预测的变化为特征的动态环境中航行。本研究以权变理论为基础，探讨了技术动荡和创新生态系统如何影响创业公司与客户、供应商和其他机构进行组织间整合的战略决策。基于183位初创公司经理、创始人、首席执行官和团队领导者的调查数据，我们的研究阐明了在技术驱动的市场中，初创公司生存和发展的关键适应性策略。研究结果表明，嵌入创新生态系统的初创企业表现出更高的组织间整合倾向，利用外部能力更好地适应技术变革。这种整合促进了协同关系，增强了信息流，并推动了持续创新和运营效率。相反，这些生态系统之外的初创企业在获取资源和建立基于信任的关系方面面临障碍，这凸显了生态系统参与在促进外部合作方面的关键作用。该研究通过强调环境偶然性如何影响创业战略，为权变理论做出了贡献，并为创业领导者提供了关于创新生态系统嵌入和战略合作伙伴关系重要性的实践指导。

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引用次数: 0

Corrigendum to “Corporate governance for digital transformation: The role of ownership and the board of directors” [Technological forecasting & social change in-print] “数字化转型中的公司治理：所有权和董事会的角色”的勘误表[技术预测与社会变革]

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-03-01 Epub Date: 2025-12-16 DOI: 10.1016/j.techfore.2025.124494

Nurit Nahum , Ulf Larsson Olaison , Timur Uman , Leona Achtenhagen

引用次数: 0

Assessment of 5G spectrum values and investment strategies considering demands forecasts and regulations: A Korean 5G case 考虑到需求预测和法规的5G频谱价值评估和投资策略——以韩国5G为例

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-03-01 Epub Date: 2026-01-05 DOI: 10.1016/j.techfore.2026.124525

Donghyun An, Deok-Joo Lee

In South Korea, the 28 GHz 5G licenses issued in 2018 were revoked after operators failed to meet the network building requirement, highlighting the need for rigorous assessment of regulatory obligations. This study develops an analytical framework that evaluates license value and the economic effects of regulatory conditions by integrating multi-generation demand forecasting, optimal base-station allocation, and a constrained real-options model. By representing regulatory rules as explicit constraints and quantifying their economic impact through shadow prices, the framework clarifies how policy choices influence deployment decisions. A case study on mmWave 5G identifies regional disparities in reserve prices and obligation burdens, and a sensitivity analysis shows how regulatory, financial, and usage parameters affect license feasibility. The results illustrate how regulators can calibrate obligations to regional conditions and how operators can assess deployment feasibility under alternative regulatory or demand scenarios, providing guidance for designing regulations that are economically evaluable.

在韩国，由于运营商未能满足网络建设要求，2018年颁发的28 GHz 5G许可证被撤销，这突显了严格评估监管义务的必要性。本研究开发了一个分析框架，通过整合多代需求预测、最优基站分配和受限实际期权模型，评估许可价值和监管条件的经济影响。通过将监管规则表示为明确的约束，并通过影子价格量化其经济影响，该框架阐明了政策选择如何影响部署决策。毫米波5G的案例研究确定了保留价格和义务负担的地区差异，敏感性分析显示了监管、财务和使用参数如何影响许可可行性。研究结果说明了监管机构如何根据地区条件调整义务，以及运营商如何在替代监管或需求情景下评估部署可行性，为设计经济上可评估的监管规定提供指导。

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引用次数: 0

The relationship between organizational focus on AI, financial growth and sustainable development: Evidence from Europe 组织对人工智能的关注、财务增长和可持续发展之间的关系：来自欧洲的证据

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-03-01 Epub Date: 2025-12-27 DOI: 10.1016/j.techfore.2025.124499

Daniele Giordino , Elisa Ballesio , Nourah Alshaghdali , Dhruv Galgotia

This study examines the link between organizations' focus on AI and their environmental, social, and governance (ESG) score. Furthermore, this study examines the relationship between organizations' AI focus and financial performance, measured by return on assets (ROA) and Tobin's Q. This manuscript relies on observations from a balanced panel of data comprising 432 publicly listed companies headquartered in Europe. The sample excludes banks and insurance companies, given their distinct accounting, governance, and capital structure standards. The sample consists of observations spanning from 2015 to 2023. Observations are gathered from LSEG Data & Analytics. We conduct baseline regression models. To ensure rigor, we also applied Hausman tests, variance inflation factors (VIF), and several robustness checks. The present manuscript is grounded in the economic theory framework. The empirical findings indicate: I) a positive and significant association between organizations' AI focus and their environmental (b = 0.127***; p = 0.001) and social pillar scores (b = 0.072**; p = 0.023); II) a positive and significant link with financial performance (ROA: b = 0.094**; p = 0.012; TobinQ: 0.103*; p = 0.051) and; III) a positive but statistically insignificant relationship with governance pillar scores (b = 0.030; p = 0.166). The obtained results yield significant contributions to both theory and practice. Specifically, the obtained results clarify and reconcile previously heterogeneous findings in the literature. Furthermore, it emphasizes that an organizational focus on AI may contribute to advancing the United Nations Sustainable Development Goals, while simultaneously enhancing financial performance.

本研究探讨了组织对人工智能的关注与其环境、社会和治理（ESG）评分之间的联系。此外，本研究考察了组织的人工智能焦点与财务绩效之间的关系，通过资产回报率（ROA）和托宾q来衡量。本文依赖于由总部位于欧洲的432家上市公司组成的平衡数据面板的观察结果。该样本不包括银行和保险公司，因为它们的会计、治理和资本结构标准不同。样本包括2015年至2023年的观测数据。观察结果收集自LSEG数据分析。我们进行基线回归模型。为了确保严谨性，我们还应用了Hausman检验，方差膨胀因子（VIF）和几个稳健性检查。本文以经济理论框架为基础。实证结果表明：1)组织对人工智能的关注与环境（b = 0.127**, p = 0.001）和社会支柱得分（b = 0.072**, p = 0.023）呈显著正相关；II)与财务绩效呈正相关且显著（ROA: b = 0.094**; p = 0.012; TobinQ: 0.103*; p = 0.051）；III)与治理支柱得分呈正相关，但统计学上不显著（b = 0.030; p = 0.166）。所得结果具有重要的理论和实践意义。具体地说，获得的结果澄清和调和先前文献中异质的发现。此外，报告强调，组织对人工智能的关注可能有助于推进联合国可持续发展目标，同时提高财务绩效。

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引用次数: 0

Leveraging blockchain technology and process innovation for green supply chain performance in environmentally sensitive industries 利用区块链技术和流程创新提高环境敏感行业的绿色供应链绩效

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-03-01 Epub Date: 2025-12-27 DOI: 10.1016/j.techfore.2025.124505

Biaoan Shan , Qasim Ali Nisar , Imran Ali

As environmental concerns escalate globally, there is an urgent need to explore how emerging digital technologies, such as blockchain, can drive improvements in green supply chain performance (GSCP). While blockchain's potential is widely recognised, limited research has unpacked the underlying mechanisms and contextual factors shaping its sustainability impact. Addressing this gap, this study investigates the mediating role of process innovation and the moderating effect of industry environmental sensitivity in the blockchain–GSCP relationship. Drawing on Dynamic Capabilities Theory and the Technology–Organisation–Environment framework, a conceptual model is developed and tested using panel data from 163 firms across environmentally sensitive industries between 2010 and 2023. The findings reveal that blockchain adoption significantly enhances GSCP, primarily by enabling process innovation. This effect is markedly stronger in industries exposed to higher environmental pressures, underscoring the importance of external context. The study contributes to the digital transformation and sustainability literature and provides strategic guidance for firms and policymakers pursuing environmentally responsible supply chain practices through blockchain-enabled innovation.

随着全球对环境问题的关注不断升级，迫切需要探索新兴数字技术（如区块链）如何推动绿色供应链绩效（GSCP）的改善。虽然区块链的潜力得到了广泛认可，但有限的研究揭示了影响其可持续性影响的潜在机制和背景因素。针对这一空白，本研究探讨了流程创新在区块链- gscp关系中的中介作用和行业环境敏感性的调节作用。利用动态能力理论和技术-组织-环境框架，我们开发了一个概念模型，并使用2010年至2023年间环境敏感行业163家公司的面板数据进行了测试。研究结果表明，区块链的采用显著提高了GSCP，主要是通过实现流程创新。在面临较高环境压力的行业，这种影响明显更强，强调了外部环境的重要性。该研究为数字化转型和可持续发展文献做出了贡献，并为企业和政策制定者提供了战略指导，通过区块链支持的创新，追求对环境负责的供应链实践。

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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 : 2026-03-01 Epub 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

Forecasting user perceptions of mHealth apps: AI-driven insights from large-scale user-generated content 预测用户对移动医疗应用的看法：大规模用户生成内容的人工智能驱动见解

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-02-01 Epub Date: 2025-11-27 DOI: 10.1016/j.techfore.2025.124427

Miriam Alzate , Paula Vidaurreta-Apesteguia , Andrea Morales-Garzón , Karel Gutiérrez-Batista

User perceptions of mHealth apps are critical for forecasting adoption trends, optimizing app design, and evaluating their broader societal implications for public health and digital inclusion. Understanding how users engage with these applications is essential for their sustained use. This research incorporates AI-driven methodologies to systematically analyze large-scale user-generated content (UGC), providing predictive insights into consumer behavior and digital health engagement. Through three interconnected stages, this paper contributes to technological forecasting, digital health management, and marketing analytics by applying Natural Language Processing (NLP) and Large Language Models (LLMs) to classify brand associations in mHealth app reviews. At the first stage, 849,918 reviews from the most downloaded mHealth apps in the US were analyzed and categorized into tracking, nutrition, step counters, and rest/meditation apps. Using BERT-based topic modeling (BERTopic) and KMeans clustering, we classify key topics under Keller's brand association dimensions. At a second stage, a predictive classification model was developed using fine-tuned DistilBERT. At a third stage, an ANOVA analysis was used to examine differences in user attitudes based on brand associations and app type. Findings highlight the high number of product-related attributes mentioned in user conversations. However, emotional benefits are those driving higher user satisfaction with mHealth apps.

用户对移动医疗应用程序的看法对于预测应用趋势、优化应用程序设计以及评估其对公共卫生和数字包容的更广泛的社会影响至关重要。了解用户如何使用这些应用程序对于它们的持续使用至关重要。本研究采用人工智能驱动的方法系统分析大规模用户生成内容（UGC），为消费者行为和数字健康参与提供预测性见解。通过三个相互关联的阶段，本文通过应用自然语言处理（NLP）和大语言模型（llm）对移动健康应用程序评论中的品牌关联进行分类，为技术预测、数字健康管理和营销分析做出了贡献。在第一阶段，我们分析了849,918条来自美国下载最多的移动健康应用程序的评论，并将其分为跟踪、营养、计步器和休息/冥想应用程序。利用基于bert的主题建模（BERTopic）和KMeans聚类，我们在Keller的品牌关联维度下对关键主题进行分类。在第二阶段，使用微调的蒸馏酒开发了预测分类模型。在第三阶段，使用方差分析来检查基于品牌联想和应用程序类型的用户态度差异。调查结果突出了用户对话中提到的大量与产品相关的属性。然而，情感上的好处才是推动移动健康应用获得更高用户满意度的因素。

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引用次数: 0

Green supply chain management and ESG rating divergence: A quasi-natural experiment in China 绿色供应链管理与ESG评级分化：中国的准自然实验

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-02-01 Epub Date: 2025-12-01 DOI: 10.1016/j.techfore.2025.124457

Chun Guo, Jingbo Luo

Using China's six batches of green supply chain management demonstration enterprises (GSCMs) selection from 2017 to 2022 as exogenous shocks and drawing on the new institutional, signaling and information asymmetry theories, we investigate the information effect of green supply chain management (GSCM) on GSCMs' ESG rating divergence by constructing a staggered difference-in-difference model. We find a significant and negative effect of GSCM on GSCMs' ESG rating divergence. This negative effect is more pronounced for GSCMs in highly polluting industries, with green investor, occupying heightened climate change risk perception, and undergoing greater public environmental attention. The mechanism test demonstrates that GSCM mitigates GSCMs' ESG rating divergence via enhancing internal information disclosure and attracting external stakeholder attention. Further analyses indicate that the capital market values GSCMs, as evidenced by the fact that GSCM improves ESG rating divergent GSCMs' stock liquidity and reduces their equity financing costs. Taken together, we underscore the pivotal information effect of green supply chain management practices and regulations on mitigating ESG rating divergence.

以2017 - 2022年中国6批绿色供应链管理示范企业入选为外生冲击，运用新的制度理论、信号理论和信息不对称理论，构建交错差中差模型，研究绿色供应链管理对绿色供应链企业ESG评级差异的信息效应。我们发现GSCM对GSCM企业的ESG评级差异有显著的负向影响。这种负面影响在高污染行业的gscm中更为明显，绿色投资者占据了更高的气候变化风险认知，并受到更大的公众环境关注。机制检验表明，GSCM通过加强内部信息披露和吸引外部利益相关者的关注来缓解GSCM企业的ESG评级分化。进一步分析表明，资本市场对中小企业进行了估值，GSCM提高了ESG评级，分散了中小企业的股票流动性，降低了中小企业的股权融资成本。综上所述，我们强调了绿色供应链管理实践和法规在缓解ESG评级差异方面的关键信息效应。

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引用次数: 0

Structural oppression and AI: A systematic review of data policy frameworks in India 结构性压迫与人工智能：印度数据政策框架的系统回顾

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-02-01 Epub Date: 2025-11-12 DOI: 10.1016/j.techfore.2025.124415

P.R. Biju , O. Gayathri

This paper argues that emerging AI governance frameworks in India must make sense of the structural inequalities in Indian society, as the prevailing standards set by globally recognized models are inadequate to address discrimination reinvented by algorithm systems deployed in various social situations. AI systems are mathematically grounded in universally applicable principles such as linear algebra, calculus, and probability theory. At the same time, their context-specific ethical, institutional, and cultural forces also influence their design and inventions. When algorithmic systems are integrated into public service delivery, exclusionary consequences encountered by marginalized groups cannot be attributed solely to algorithmic bias. Adopting a systematic review of popular global AI policy frameworks and a comparative assessment of Indian use-cases, particularly in welfare and governance domains, this study proposes that structural failures across various levels from data entry, and verification, to infrastructure design, and implementation, compound the risks attributed to automation. Findings of the paper call for a re-conceptualization of AI not as an isolated technical entity but as part of a dynamic network of interacting systems. The study advances the demand for policy interventions that recognize these interdependencies and promote fairness, transparency, and justice in the design and governance of AI in India.

本文认为，印度新兴的人工智能治理框架必须理解印度社会的结构性不平等，因为全球公认的模型设定的现行标准不足以解决在各种社会情况下部署的算法系统重新创造的歧视。人工智能系统的数学基础是普遍适用的原理，如线性代数、微积分和概率论。与此同时，特定环境下的伦理、制度和文化力量也影响着他们的设计和发明。当算法系统被纳入公共服务提供时，边缘化群体所遇到的排斥性后果不能仅仅归因于算法偏见。通过对流行的全球人工智能政策框架的系统审查和对印度用例的比较评估，特别是在福利和治理领域，本研究提出，从数据输入、验证到基础设施设计和实施等各个层面的结构性失败，加剧了自动化带来的风险。本文的研究结果呼吁将人工智能重新概念化，而不是作为一个孤立的技术实体，而是作为相互作用系统的动态网络的一部分。该研究提出了对政策干预的需求，这些干预应认识到这些相互依赖性，并促进印度人工智能设计和治理中的公平、透明和正义。

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引用次数: 0