Technological Forecasting and Social Change最新文献_第3页

Evaluating Delphi survey accuracy in transportation: Evidence from Japanese technology foresight 评价交通运输中的德尔菲调查准确性：来自日本技术预见的证据

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-31 DOI: 10.1016/j.techfore.2025.124496

Sukhayl Niyazov , Olesia Maibakh , Alexei Sukharev , Tatiana Kulakova , Andrey Ufimtsev

This research evaluates the accuracy of Delphi surveys in technology foresight with a focus on the transportation sector by determining the realization status of topics forecasted in the three Science and Technology Forecast Surveys administered by Japan's National Institute of Science and Technology Policy (NISTEP) in 1992, 1997, and 2001. The analysis included 167 topics, representing 647 observations when different Delphi rounds, survey iterations, and respondent pools are taken into account. Through expert verification, an overall forecasting accuracy rate of 25 % was found.

The results highlight a “forecastability pit”: topics in early and late technological stages demonstrate higher accuracy compared to middle stages, when technologies first enter practical use or are improved. Accuracy was lowest for “aviation” (11 %), “railway” (19 %), and “road” (25 %) sectors and highest for “marine” (31 %) and “other new transportation sectors” (36 %). Greater accuracy was not found to be correlated with higher levels of self-rated expertise, second-round Delphi forecasts, a topic's perceived importance and anticipated magnitude of effects.

The low accuracy rate may stem from the regulatory and technological complexities inherent to the sector. Overall, the study underscores the need for methodological refinements and a reassessment of the role of expert judgment processes in S&T Delphi.

本研究通过确定由日本国家科学技术政策研究所（NISTEP）于1992年、1997年和2001年进行的三次科学技术预测调查中预测的主题的实现状况，评估了德尔菲调查在技术预测方面的准确性，重点是交通部门。分析包括167个主题，在考虑不同德尔菲回合、调查迭代和受访者池时，代表647个观察结果。经专家验证，总体预测准确率为25%。结果突出了一个“可预测性坑”：与技术首次进入实际使用或得到改进的中期阶段相比，早期和晚期技术阶段的主题显示出更高的准确性。准确度最低的是“航空”（11%）、“铁路”（19%）和“公路”（25%）行业，最高的是“海洋”（31%）和“其他新运输行业”（36%）。更高的准确性与更高水平的自评专业知识、第二轮德尔菲预测、主题的感知重要性和预期影响程度无关。低准确率可能源于该行业固有的监管和技术复杂性。总体而言，该研究强调需要改进方法，并重新评估专家判断过程在标准普尔Delphi中的作用。

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引用次数: 0

From information to operations: Exploring the impact of integrated AI-HI on information diffusion and users' willingness in humanitarian aid 从信息到行动：探索综合AI-HI对人道主义援助中信息传播和用户意愿的影响

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-30 DOI: 10.1016/j.techfore.2025.124501

Shizhen Bai , Jiamin Zhou , Chunjia Han , Mu Yang , Chen Wang , Brij B. Gupta

The advancement in AI usage and technological capabilities has provided greater convenience in the diffusion of information within humanitarian aid operations, offering aid workers expanded operational possibilities and improving the efficiency of response. Consequently, experts in the field suggest that integrating AI and HI represents the next major development in humanitarian aid. Unfortunately, there is currently a lack of research exploring the integration of AI within communication platforms as an information hub, leaving a gap for both aid workers and scholars. To address this gap, this study, based on the concept of perceived affordances and combined with affordance theory, investigates the interaction and overlay of AI and communication platforms. We conducted three studies in an online environment using real disaster relief videos and simulated communication platforms. Our findings indicate that the integration of AI (vs. Without AI) in communication platforms functioning as information hubs enhances perceived affordances. Specifically, AI improves perceived visibility and perceived editability, which in turn increases aid workers' willingness to exchange information and use the platform. Moreover, the facilitating effect of AI integration is less constrained by the actual level of affordances. Additionally, time pressure moderates these effects. Our study contributes to the field of humanitarian aid.

人工智能的使用和技术能力的进步为人道主义援助行动中的信息传播提供了更大的便利，为援助人员提供了更多的行动可能性，提高了反应效率。因此，该领域的专家建议，将人工智能和医疗保健相结合是人道主义援助的下一个重大发展。不幸的是，目前缺乏将人工智能作为信息中心整合到通信平台中的研究，这给援助工作者和学者留下了空白。为了解决这一差距，本研究基于感知可视性的概念，结合可视性理论，研究人工智能与通信平台的交互和叠加。我们利用真实的救灾视频和模拟的交流平台，在网络环境下进行了三项研究。我们的研究结果表明，在作为信息中心的通信平台中集成人工智能（与没有人工智能相比）可以增强感知能力。具体来说，人工智能提高了感知可见性和感知可编辑性，这反过来又增加了援助工作者交流信息和使用平台的意愿。此外，人工智能集成的促进作用较少受到实际能力水平的约束。此外，时间压力会缓和这些影响。我们的研究有助于人道主义援助领域。

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引用次数: 0

Divergent Paths: Unpacking the role of skill-biased and routine-biased technological change on urban income inequality in China 发散路径：揭示技能偏向和常规偏向的技术变革在中国城市收入不平等中的作用

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-29 DOI: 10.1016/j.techfore.2025.124518

Zuge Xing , Canfei He , Yuxin Pan

Biased technological changes have reshaped urban labor markets, significantly affecting income distribution. Despite the recognition of skill-biased technological change (SBTC) and routine-biased technological change (RBTC) frameworks as key to explaining income inequality, it remains unclear whether all types of biased technological changes widen urban income inequality (UII). This paper uses machine learning methods on Chinese census data from 2000 to 2015 to build a large sample urban labor income dataset and analyzes the effects of SBTC, non-routine cognitive RBTC, and non-routine manual RBTC on UII. The results reveal that SBTC and non-routine cognitive RBTC exacerbate UII in China, while non-routine manual RBTC can reduce it and weaken the adverse distributional effects of SBTC. The influence of these technological changes varies markedly across cities with different human capital, foreign direct investment, and economic complexity. The findings of this study contribute to a deeper understanding of the interplay between technological progress and labor market income distribution and offer insights for policymakers in developing countries to formulate targeted labor skill training and employment diversification strategies.

有偏见的技术变革重塑了城市劳动力市场，显著影响了收入分配。尽管认识到技能偏倚技术变革（SBTC）和常规偏倚技术变革（RBTC）框架是解释收入不平等的关键，但是否所有类型的偏倚技术变革都会扩大城市收入不平等（UII）仍不清楚。本文采用机器学习方法对2000 - 2015年中国人口普查数据构建了大样本城镇劳动收入数据集，分析了非常规性认知RBTC、非常规性手动RBTC对用户满意度的影响。结果表明，在中国，非常规性认知RBTC和非常规性认知RBTC加剧了ii，而非常规性手动RBTC可以减轻ii，并削弱其不利的分布效应。这些技术变革的影响在人力资本、外国直接投资和经济复杂程度不同的城市之间存在显著差异。研究结果有助于深入了解技术进步与劳动力市场收入分配之间的相互作用，并为发展中国家的政策制定者制定有针对性的劳动技能培训和就业多元化战略提供参考。

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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 : 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 : 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

Responsible AI and employee service innovation behavior: A sequential mediation model of AI self-efficacy and AI crafting 负责任的人工智能与员工服务创新行为：人工智能自我效能感与人工智能制作的顺序中介模型

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-26 DOI: 10.1016/j.techfore.2025.124470

Yong Xu , Peijun Xie , Rana Muhammad Naeem , Intesar Almugren , Zahid Hameed , Shivani Agarwal

While the use of artificial intelligence (AI) has become an effective tool for transforming individuals and organizations, adopting a responsible approach to AI systems is imperative. Drawing on conservation of resources theory and social learning theory, this study examines how responsible AI enhances employees' service innovation behavior via employee AI self-efficacy and employee AI crafting, with a particular focus on the moderating role of leader AI crafting. We tested the proposed relationships using structural equation modeling with data collected from 335 U.S. employees working in various service organizations. The findings demonstrate that the indirect effect of responsible AI on employee service innovation behavior is mediated serially by employee AI self-efficacy and employee AI crafting. Furthermore, leader AI crafting strengthens the positive relationship between responsible AI and employee AI self-efficacy. This study contributes to the AI and management literature by highlighting the importance of responsible AI systems in promoting service innovation behavior among employees. This study addresses both theoretical and practical dimensions, as well as proposing directions for future research.

虽然人工智能（AI）的使用已成为改变个人和组织的有效工具，但对人工智能系统采取负责任的方法势在必行。利用资源守恒理论和社会学习理论，本研究考察了负责任的人工智能如何通过员工人工智能自我效能感和员工人工智能制作来增强员工的服务创新行为，并特别关注了领导者人工智能制作的调节作用。我们使用结构方程模型测试了所提出的关系，该模型收集了来自不同服务组织的335名美国员工的数据。研究结果表明，负责任的人工智能对员工服务创新行为的间接影响是由员工人工智能自我效能感和员工人工智能制作感依次中介的。此外，领导者人工智能锻造强化了负责任的人工智能与员工人工智能自我效能之间的正相关关系。本研究通过强调负责任的人工智能系统在促进员工服务创新行为方面的重要性，为人工智能和管理文献做出了贡献。本研究从理论和实践两个方面进行了探讨，并提出了未来研究的方向。

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引用次数: 0

Generative AI and ESG opportunism in supply chains: A utilitarian perspective on unintended consequences for sustainability 供应链中的生成式人工智能和ESG机会主义：对可持续性意外后果的功利主义视角

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-26 DOI: 10.1016/j.techfore.2025.124498

Zhe Sun , Lei Liu , Liang Zhao , Hind Alofaysan , Bhumika Gupta

Existing research has overwhelmingly emphasized the positive effects of generative artificial intelligence (AI) on corporate environmental, social, and governance (ESG) performance, while largely neglecting the risk of dimensional imbalance in ESG resource allocation and its potential contagion across supply chains. Drawing on utilitarian theory, this study introduces the novel concept of ESG opportunism and empirically examines the impact of generative AI adoption on its emergence and intensity. Results show that generative AI significantly heightens firms' opportunistic ESG behavior by increasing agency costs and weakening internal controls. This relationship is further amplified by stringent government environmental regulations and strong green investor preferences yet attenuated by greater analyst attention and higher-quality information disclosure. Moreover, a clear supply chain spillover effect is identified: generative AI adoption by focal firms transmits and intensifies ESG opportunism among both upstream suppliers and downstream customers. By challenging the dominant optimistic narrative surrounding generative AI's ESG implications, this study offers timely and critical insights for establishing responsible generative AI governance throughout global supply chains.

现有研究绝大多数强调了生成式人工智能（AI）对企业环境、社会和治理（ESG）绩效的积极影响，而在很大程度上忽视了ESG资源配置维度失衡的风险及其在整个供应链中的潜在传染。利用功利主义理论，本研究引入了ESG机会主义的新概念，并实证考察了采用生成式人工智能对其出现和强度的影响。结果表明，生成式人工智能通过增加代理成本和弱化内部控制，显著提高了企业的机会主义ESG行为。严格的政府环境法规和强烈的绿色投资者偏好进一步放大了这种关系，而更多的分析师关注和更高质量的信息披露则减弱了这种关系。此外，我们还发现了一个明显的供应链溢出效应：焦点企业采用生成式人工智能传播并加剧了上游供应商和下游客户之间的ESG机会主义。通过挑战围绕生成式人工智能的ESG影响的主流乐观叙事，本研究为在全球供应链中建立负责任的生成式人工智能治理提供了及时和关键的见解。

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引用次数: 0

Advertising strategies for innovation capability sharing: A two-sided market analysis 创新能力共享的广告策略：一个双边市场分析

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-26 DOI: 10.1016/j.techfore.2025.124462

Longfei He , Xiao Zhang , Francisco Saldanha-da-Gama , Xiaohang Yue

In addition to pricing strategies, user-targeted advertising represents a key approach for innovation capability sharing platforms to enhance profitability. Incorporating cross-network externalities, this paper examines platform advertising investment and pricing decisions under both monopoly and competitive scenarios. Our findings indicate that platforms always charge users on the side with stronger cross-network externalities, while the decision regarding whether to charge or subsidize users on the side with weaker externalities depends on advertising sensitivity and platform differentiation. Social welfare is positively affected by cross-network externalities but negatively influenced by advertising costs. In scenarios with multi-homing suppliers and single-homing purchasers, we characterize the equilibrium advertising strategies for competing platforms, which are determined by the advertising cost coefficients for both platform sides. These strategies may lead to a prisoner's dilemma; we therefore propose a penalty mechanism to resolve it. Conversely, under single-homing suppliers and multi-homing purchasers, multiple Nash equilibria exist for advertising strategies, though Pareto optimality determines the equilibrium outcome. Finally, we find that platforms are more likely to encourage exclusive supplier contracts when competition is less intense, but these contracts reduce profits as competition intensifies.

除了定价策略，用户定向广告是创新能力共享平台提高盈利能力的关键途径。考虑到跨网络的外部性，本文研究了垄断和竞争两种情况下的平台广告投资和定价决策。我们的研究结果表明，平台总是对跨网络外部性较强的一侧用户收费，而对外部性较弱的一侧用户收费或补贴的决定取决于广告敏感性和平台差异化。社会福利受跨网络外部性的正向影响，而受广告成本的负向影响。在多家供应商和单家购买者的情况下，我们描述了竞争平台的均衡广告策略，这是由平台双方的广告成本系数决定的。这些策略可能导致囚徒困境；因此，我们建议建立一种惩罚机制来解决这一问题。相反，在单住房供应商和多住房购买者的情况下，广告策略存在多个纳什均衡，尽管帕累托最优决定了均衡结果。最后，我们发现，当竞争不那么激烈时，平台更有可能鼓励独家供应商合同，但随着竞争加剧，这些合同会减少利润。

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引用次数: 0

Restoring consumer trust in e-commerce: The role of blockchain technology and its behavioral implications 恢复消费者对电子商务的信任：区块链技术的作用及其行为含义

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-26 DOI: 10.1016/j.techfore.2025.124495

Louisa Uchikoshi , Björn Frank

Blockchain technology has unique technological features that could help e-commerce firms regain consumer trust lost due to widespread online fraud. However, their effectiveness and underlying mechanisms remain unknown. Drawing on trust formation theory, this article examines the effectiveness of these blockchain technology features and its variation across consumer needs. A multi-method approach combines a randomized between-subjects experiment (Study 1: 727 consumers; pretest: 45) and a multi-wave survey of actual experiences of tech-savvy consumers (Study 2: 563 consumers; pretest: 30) in the U.S. Consistent statistically significant results show that the blockchain technology features of privacy ownership, privacy monetization, and metadata transparency increase consumer trust in e-commerce platforms. The openness of a blockchain platform to criminal sellers, which allows consumers to access illicit products, increases trust only for consumers with illicit purchase needs, while decreasing trust for consumers without such needs. Trust mediates the effects of these blockchain technology features on consumers' willingness to pay additional fees and retail use intentions, which in turn mediate the effects on actual future retail use behavior. These findings extend trust formation theory to the context of blockchain technology and inform retail practitioners of a powerful new technology for increasing consumer purchases in their online stores.

区块链技术具有独特的技术特征，可以帮助电子商务公司重新获得因广泛的网络欺诈而失去的消费者信任。然而，它们的有效性和潜在机制尚不清楚。利用信任形成理论，本文考察了这些区块链技术特征的有效性及其在消费者需求中的变化。多方法方法结合了随机受试者间实验（研究1:727名消费者；预试：45名）和对美国精通技术的消费者实际体验的多波调查（研究2:563名消费者；预试：30名）。一致的统计显著结果表明，区块链技术的隐私所有权、隐私货币化和元数据透明度特征增加了消费者对电子商务平台的信任。区块链平台向犯罪卖家开放，允许消费者接触非法产品，只增加了有非法购买需求的消费者的信任，而降低了没有此类需求的消费者的信任。信任在区块链技术特征对消费者额外付费意愿和零售使用意愿的影响中起中介作用，而消费者额外付费意愿和零售使用意愿又在未来实际零售使用行为中起中介作用。这些发现将信任形成理论扩展到区块链技术的背景下，并告知零售从业者一种强大的新技术，可以增加消费者在其在线商店中的购买。

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引用次数: 0

Intelligence by design: Large language model work integration as strategic enablers for supply chain regeneration through digital and cognitive capabilities 设计智能：大型语言模型集成作为通过数字和认知能力实现供应链再生的战略推动者

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2025-12-23 DOI: 10.1016/j.techfore.2025.124497

Weiming Liu , Varun Chotia , Lu Wang , Prashant Sharma , Norah Albishri , Snigdha Dash

This research investigates how working with large language models improves the regenerative capabilities of supply chains by developing digital process transformation capability and cognitive supply chain capability, under varying levels of organisational digital experimentation culture and artificial intelligence (AI) governance maturity. This study develops and tests a multi-stage capability architecture, introducing new perspectives on about cognitive automation, AI capability settings, and algorithmic affordances. The model is validated through analysis of responses from 281 respondents in knowledge-intensive fields. Empirical research supports the proposed serial mediation, depicting that incorporating large language models in supply chains enhance regenerative capacity through digital process transformation and the reconfiguration of cognitive supply chains. Digital experimentation culture strengthens the relationship between the large language model integration into supply chain and digital process capability, whereas AI governance maturity strengthens the link between such integration and regenerative capability. This research adds to modern theories on algorithmic cognition and capability orchestration in AI-enabled systems, adds depth to digital operations and strategic management research, and demonstrates how large language model integration can create regenerative supply chains.

本研究探讨了在不同水平的组织数字实验文化和人工智能（AI）治理成熟度下，大型语言模型如何通过发展数字流程转换能力和认知供应链能力来提高供应链的再生能力。本研究开发并测试了一个多阶段的能力架构，介绍了关于认知自动化、人工智能能力设置和算法支持的新观点。通过对281名知识密集型行业受访者的回答进行分析，验证了模型的有效性。实证研究表明，在供应链中加入大型语言模型可以通过数字化流程转换和认知供应链的重构增强再生能力。数字实验文化加强了大语言模型集成到供应链与数字流程能力之间的关系，而人工智能治理成熟度则加强了这种集成与再生能力之间的联系。这项研究增加了人工智能系统中算法认知和能力编排的现代理论，增加了数字运营和战略管理研究的深度，并展示了大型语言模型集成如何创建再生供应链。

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引用次数: 0