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

How does corporate greenwashing affect firm resilience –Causal inference utilizing dual machine learning techniques 企业“漂绿”如何影响企业弹性——利用双机器学习技术的因果推理

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-02-03 DOI: 10.1016/j.techfore.2026.124561

Fu Jia , Dingguo Hu , Lujie Chen

In the context of accelerating climate change, corporate greenwashing (CGW), has emerged as a critical governance risk undermining long-term sustainable development. Grounded in dynamic capability theory supplemented by paradox theory, this study unveils systematically the causal mechanisms through which CGW affects firm resilience for the first time as far as we are aware. Drawing on panel data from Chinese listed manufacturing firms between 2017 and 2023, we construct a novel CGW index using text analysis and measure firm resilience via the volatility of total factor productivity. To address endogeneity concerns and accommodate high-dimensional controls, we adopt a double machine learning approach. Our findings show: (1) CGW significantly undermines firm resilience by distorting the dynamic capability cycle of sensing, seizing, and reconfiguring; (2) financing constraints act as a negative mediating mechanism in that CGW exacerbates information asymmetries, thereby raising financing costs, whereas operational slack functions as a positive mediator, as redundant resources provide short-term buffers against external shocks; and (3) environmental regulation intensity and investor attention positively moderate this negative relationship, meaning private enterprises exhibit greater vulnerability due to limited access to policy-based resources. This research contributes to the theoretical advancement of firm resilience by introducing CGW as a “dark side” capability and identifies mechanisms of internal mediation and external moderation. The findings provide practical insights for firms aiming to mitigate CGW, optimize resource allocation, and enhance risk management.

在气候变化加速的背景下，企业洗绿（CGW）已成为破坏长期可持续发展的关键治理风险。本研究以动态能力理论为基础，以悖论理论为补充，首次系统地揭示了集体绩效影响企业弹性的因果机制。本文利用2017 - 2023年中国制造业上市公司的面板数据，利用文本分析构建了一个新的CGW指数，并通过全要素生产率的波动来衡量企业的弹性。为了解决内生性问题并适应高维控制，我们采用了双重机器学习方法。研究结果表明：(1)CGW通过扭曲感知、捕获和重构的动态能力周期，显著破坏了企业弹性；(2)融资约束为负向中介机制，即CGW加剧了信息不对称，从而提高了融资成本；而业务松弛为正向中介机制，即冗余资源为应对外部冲击提供了短期缓冲；(3)环境监管强度和投资者关注度正向调节这一负相关关系，即民营企业由于获得政策性资源的机会有限而表现出更大的脆弱性。本研究将CGW作为一种“黑暗面”能力引入企业弹性理论，并确定了内部中介和外部调节机制。研究结果可为企业减轻CGW、优化资源配置和加强风险管理提供实践见解。

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引用次数: 0

Sustainable last-mile delivery: Understanding perceived benefits and risks of AI-automated delivery drones in France 可持续的最后一英里交付：了解法国人工智能自动交付无人机的预期收益和风险

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-02-03 DOI: 10.1016/j.techfore.2026.124576

Lars Meyer-Waarden , Julien Cloarec , Stéphane Salgado , Vincent Favarin

This study investigates the adoption of delivery drones in last-mile logistics by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with constructs related to well-being, perceived technology risk, privacy concerns, and environmental concerns. Drawing on a 2x2x2 experimental design involving 3212 French participants, we examine how physical accidents, cyberattacks, product criticality, and environmental values shape consumers' performance expectancy, social influence, risk perception, and behavioral intentions. The findings show that environmental concerns enhance the positive impact of performance expectancy and social influence on well-being, while unexpectedly reducing the negative effect of privacy concerns. Product criticality significantly weakens the relationship between well-being and adoption intention. This paper contributes theoretically by integrating sustainability and perceived risk theory into UTAUT2, thereby advancing understanding of how consumers evaluate novel autonomous technologies under conditions of uncertainty and ecological awareness.

本研究通过扩展“技术接受与使用统一理论2”（UTAUT2），用与福祉、感知技术风险、隐私问题和环境问题相关的概念来调查无人机在最后一英里物流中的应用。利用涉及3212名法国参与者的2x2x2实验设计，我们研究了物理事故、网络攻击、产品临界性和环境价值如何影响消费者的绩效预期、社会影响、风险感知和行为意图。研究结果表明，环境关注增强了绩效预期和社会影响对幸福感的积极影响，同时出人意料地降低了隐私关注的负面影响。产品临界性显著削弱幸福感与采用意愿之间的关系。本文通过将可持续性和感知风险理论整合到UTAUT2中，从而促进了对消费者如何在不确定性和生态意识条件下评估新型自主技术的理解。

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引用次数: 0

Designing a global resilient vaccine supply chain: Forecasting with hybrid neural network 全球弹性疫苗供应链设计：混合神经网络预测

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-02-02 DOI: 10.1016/j.techfore.2026.124524

Ehsan Torshizi , Fatemeh Sabouhi , Ali Bozorgi-Amiri

In the present research, a hybrid decision-making and data-driven optimization approach is developed based on economic management theory to design a global COVID-19 vaccine supply chain. Economic management theory includes three complementary theories of information processing, transaction cost economics, and the resource-based view/dynamic capabilities to examine the logic of the proposed approach. The first phase involves assessing the efficiency of foreign suppliers and manufacturers through non-radial data envelopment analysis. In this phase, the foreign exchange rate parameter is forecasted using the hybrid neural network. Then, the second phase introduces a multi-objective optimization model for designing a vaccine supply chain under uncertain conditions. Flow complexity, node complexity, and node criticality are considered in the model to increase the overall resilience of the network. To deal with the uncertainty of the problem, a stochastic robust optimization model is employed. The objective functions aim to maximize supply chain efficiency and minimize the non-resilience of the network and the total cost. The approach implemented in this research is validated by an actual-world case study in Iran. The findings highlight that resilience indicators can improve economic costs by up to 13% and network efficiency by up to 18% under the worst-case pandemic scenario. Also, the implemented forecasting algorithm performs better than other methods based on R2, RMSE, MSE, and MAE metrics. Lastly, a comprehensive analysis is performed on the computational results obtained, which derives some practical managerial insights.

本文基于经济管理理论，提出了一种基于决策和数据驱动的混合优化方法来设计全球COVID-19疫苗供应链。经济管理理论包括三个互补的理论：信息处理、交易成本经济学和基于资源的观点/动态能力，以检验所提出方法的逻辑。第一阶段涉及通过非径向数据包络分析评估外国供应商和制造商的效率。在这一阶段，使用混合神经网络对外汇汇率参数进行预测。第二阶段引入了不确定条件下疫苗供应链设计的多目标优化模型。模型中考虑了流复杂性、节点复杂性和节点临界性，以提高网络的整体弹性。为了处理问题的不确定性，采用了随机鲁棒优化模型。目标函数旨在使供应链效率最大化，使网络的非弹性和总成本最小化。本研究中采用的方法通过伊朗的实际案例研究得到了验证。研究结果强调，在最坏的大流行情景下，弹性指标可以将经济成本提高13%，将网络效率提高18%。此外，实现的预测算法比基于R2、RMSE、MSE和MAE指标的其他方法表现更好。最后，对计算结果进行了综合分析，得出了一些实用的管理见解。

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引用次数: 0

Generative AI-driven transition to circular and responsible supply chains: Unpacking the dynamics of eco-centric design intelligence and ethical responsiveness 生成式人工智能驱动的向循环和负责任供应链的过渡：揭示以生态为中心的设计智能和道德响应的动态

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-29 DOI: 10.1016/j.techfore.2025.124522

Eszter Lukács , Sabrine Mallek , Jiyang Cheng

The study focuses on understanding how the use of generative Artificial Intelligence (AI) can beneficially result in circular supply chain transformation while embedding design intelligence, ethical intelligence, and predictive intelligence within socio-technical systems. This study proposes and validates a model that integrates generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness, which collectively affect circular supply chain resilience and socio-environmental value realization, mediated by Sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To test the hypothesis, data were collected from 264 professionals in supply chain and technology-related industries in the USA. As the findings suggest, generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness significantly enhance sustainable process reconfiguration capability, which drives AI-enabled stakeholder co-creation. A serial mediation model indicates that Generative AI capabilities affect circular supply chain resilience and socio-environmental value realization via sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To our surprise, the regenerative policy ambidexterity negatively moderates the relationship between AI-enabled stakeholder co-creation and the realization of socio-environmental value. The results provide actionable advice for managers implementing generative AI in sustainable supply chains. Instead of focusing solely on algorithmic efficiency, if an organization can develop reconfiguration capability and engage stakeholders, it would generate systemic sustainability benefits.

该研究的重点是了解生成式人工智能（AI）的使用如何在社会技术系统中嵌入设计智能、伦理智能和预测智能的同时，有利于循环供应链的转型。本研究提出并验证了一个集成了生成生态设计智能、预测性循环供应链规划和伦理生成人工智能意识的模型，这些模型共同影响循环供应链弹性和社会环境价值实现，由可持续流程重构能力和人工智能支持的利益相关者共同创造介导。为了验证这一假设，我们从美国供应链和技术相关行业的264名专业人士中收集了数据。研究结果表明，生成式生态设计智能、预测性循环供应链规划和伦理生成式人工智能意识显著增强了可持续流程重构能力，从而推动了人工智能驱动的利益相关者共同创造。序列中介模型表明，生成式人工智能能力通过可持续流程重构能力和人工智能支持的利益相关者共同创造，影响循环供应链弹性和社会环境价值实现。令我们惊讶的是，再生政策的双重性负向调节了人工智能驱动的利益相关者共同创造与社会环境价值实现之间的关系。研究结果为管理人员在可持续供应链中实施生成式人工智能提供了可行的建议。如果一个组织能够发展重构能力并吸引利益相关者，它将产生系统性的可持续性效益，而不是仅仅关注算法效率。

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引用次数: 0

Guest editorial: Technological transformation and change 嘉宾评论：技术转型与变革

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-29 DOI: 10.1016/j.techfore.2026.124560

Daniel Palacios-Marqués , Yogesh K. Dwivedi

Technological transformation and change have become key features of modern economies and societies. Digital technologies, artificial intelligence (AI), data analytics, and platform-based business models now form widespread socio-technical infrastructures that reshape value creation, organizational design, and stakeholder relationships. At the same time, global shocks and growing sustainability challenges reveal tensions between the promises and unintended effects of these technologies. This special issue includes 27 articles that explore technological transformation and change across different levels of analysis, sectors, and regions. Using various theoretical perspectives and methods, the contributions show how digital transformation connects to green innovation and sustainability, organizational capabilities and learning, AI- and data-driven decision-making, as well as changing patterns of consumer behavior, marketing, and platform governance. In this guest editorial, we first set the context and explain the main motivation for the special issue. Then, we provide an overview of the included papers, organized into thematic groups. We end by reflecting on the common insights from the collection, highlighting implications for managers and policymakers, and suggesting promising areas for future research on technological transformation and change.

技术转型和变革已成为现代经济和社会的主要特征。数字技术、人工智能（AI）、数据分析和基于平台的商业模式现在形成了广泛的社会技术基础设施，重塑了价值创造、组织设计和利益相关者关系。与此同时，全球冲击和日益严峻的可持续性挑战揭示了这些技术的承诺与意想不到的影响之间的紧张关系。这期特刊包括27篇文章，探讨了不同层次的分析、行业和地区的技术转型和变化。利用各种理论视角和方法，这些贡献展示了数字化转型如何与绿色创新和可持续性、组织能力和学习、人工智能和数据驱动的决策，以及不断变化的消费者行为模式、营销和平台治理联系在一起。在这篇客座社论中，我们首先设定了背景，并解释了特刊的主要动机。然后，我们提供了一个概述，包括论文，组织成专题小组。最后，我们反思了收集到的共同见解，强调了对管理者和政策制定者的影响，并提出了未来技术转型和变革研究的有希望的领域。

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引用次数: 0

Enhancing data governance through transparency: An empirical study of the data trust model 通过透明度加强数据治理：数据信任模型的实证研究

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-28 DOI: 10.1016/j.techfore.2026.124551

Yei Jin Kim , Young Soo Park , Sung-Pil Park

As data-driven ecosystems expand, the Data Trust Model (DTM) has gained attention as a governance framework for secure transactions, yet adoption remains uncertain due to high information asymmetry and the dual burden of evaluating asset quality and transactional risk. Prior research has largely emphasized supply-side institutional design, treating transparency as a monolithic construct and overlooking user heterogeneity. To address these limitations, this study develops a context-specific model integrating the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Transparency is bifurcated into Perceived Data Transparency (adverse selection) and Perceived Transaction Transparency (moral hazard) within an Agency Theory framework. The model is tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) based on data from 400 potential users. Results show that transparency operates as a conditional enabler mediated by attitude rather than a direct driver. MGA further reveals systematic heterogeneity: experienced users rely more heavily on institutional signals—reputation, security, and warranty—when forming perceptions. Theoretically, this study integrates Agency and Signaling Theories to explain adoption under uncertainty. Practically, findings highlight the need for differentiated transparency mechanisms tailored to user experience.

随着数据驱动生态系统的扩展，数据信任模型（DTM）作为安全交易的治理框架受到了关注，但由于信息高度不对称以及评估资产质量和交易风险的双重负担，采用仍然不确定。先前的研究主要强调供给侧的制度设计，将透明度视为一个整体结构，忽视了用户的异质性。为了解决这些局限性，本研究开发了一个结合技术接受模型（TAM）和计划行为理论（TPB）的情境特定模型。在代理理论框架下，透明度分为感知数据透明度（逆向选择）和感知交易透明度（道德风险）。基于400名潜在用户的数据，采用偏最小二乘结构方程模型（PLS-SEM）和多组分析（MGA）对模型进行了测试。结果表明，透明度是态度介导的条件促成因素，而不是直接驱动因素。MGA进一步揭示了系统异质性：有经验的用户在形成感知时更依赖于制度信号——声誉、安全性和保修。在理论上，本研究结合代理理论和信号理论来解释不确定性下的采用。实际上，研究结果强调了针对用户体验量身定制的差异化透明度机制的必要性。

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引用次数: 0

Leveraging generative AI and circular innovation for equitable and resilient supply chains: The mediating role of transparency and sustainability-oriented decision empowerment 利用生成式人工智能和循环创新实现公平和有弹性的供应链：透明度和面向可持续性的决策赋权的中介作用

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-28 DOI: 10.1016/j.techfore.2026.124556

Yanfang Xia , Yong Qiu , Zhuoyu Gu , Liang Zhang , Jiayu Yang

Sustainability is now a business necessity as climate pressures, digital transformation, and supply chain shocks push concerns on the table. In response to this agenda, this study proposes and tests an empirically grounded sociotechnical framework in which three generative AI-enabled enablers act in concert to amplify supply chain transparency. Supply chain transparency allows decisions to be made that lead to fair and resilient supply outcomes. The present research shows how AI-enabled decision intelligence and circular innovation practices can enhance organizational transparency and the manager's potential to make inclusion-oriented, sustainable, equitable and resilient decisions through a socio-technical framework. Survey responses were used to empirically test the prepositions using a structural equation modelling framework. The research expands the theory of socio-technical systems. As such, it shows the need for technical (AI-enabled decision intelligence, circular innovation alignment) and cultural (responsible AI communication culture) capabilities. These should co-evolve with transparency and decision architectures for attaining social resilience. The study has practical implications for managers. They will have to invest money in not just generative AI powered analytics but also responsible communication norms. Moreover, aligning with circular innovation can aid in unlocking data visibility and inclusive decision loop.

随着气候压力、数字化转型和供应链冲击将关注的问题提上日程，可持续发展现在是一项商业必需品。为了响应这一议程，本研究提出并测试了一个基于经验的社会技术框架，其中三个生成式人工智能使能者协同行动，以扩大供应链的透明度。供应链的透明度使决策能够产生公平和有弹性的供应结果。目前的研究表明，人工智能支持的决策智能和循环创新实践如何提高组织透明度，并通过社会技术框架提高管理者做出包容导向、可持续、公平和有弹性决策的潜力。使用结构方程建模框架对调查结果进行实证检验。本研究拓展了社会技术系统理论。因此，它显示了对技术（人工智能支持的决策智能，循环创新对齐）和文化（负责任的人工智能沟通文化）能力的需求。这些应与透明度和决策架构共同发展，以实现社会弹性。该研究对管理者具有实际意义。他们不仅要投资于生成式人工智能分析，还要投资于负责任的沟通规范。此外，与循环创新保持一致有助于解锁数据可见性和包容性决策循环。

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引用次数: 0

Disappointed with Siri: Expectation–experience gaps in human–AI interaction 对Siri的失望：人类与人工智能互动中的预期体验差距

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-28 DOI: 10.1016/j.techfore.2026.124540

You Jin Song , Joohye Park , Sun Kyong Lee

Voice assistants such as Siri increasingly mediate everyday tasks, yet negative experiences with these systems remain understudied. Guided by social representation theory, we use a sequential mixed-methods design—topic modeling of user narratives followed by in-depth interviews—to characterize dissatisfaction with a voice-based AI and to explain how its meanings differ by users' gender. Topic modeling surfaces a broad “inconvenience/disruption” cluster alongside frequent references to speech-recognition errors. Interviews then reveal the interpretive logics beneath these signals: men tend to read failures as breaches of technical performance and task logic, whereas women more often construe the same events as violations of social expectations. These gendered interpretations show that dissatisfaction is not merely an individual usability outcome but a socially anchored perception organized by shared representational frames. The study contributes (1) a theoretically grounded account of how gender structures sense-making around AI malfunctions, (2) a methodological synthesis that links computational signals to qualitative representation mapping, and (3) design implications that anticipate divergent expectations without reinforcing stereotypes. By moving beyond frequency counts to interpretive coherence, the work advances understanding of why the same Siri behavior can produce different forms of dissatisfaction across users.

Siri等语音助手越来越多地调解日常任务，但这些系统的负面体验仍未得到充分研究。在社会表征理论的指导下，我们使用顺序混合方法设计-用户叙述的主题建模，然后进行深度访谈-来表征对基于语音的人工智能的不满，并解释其含义如何因用户性别而异。主题建模显示了广泛的“不便/中断”集群，以及频繁提及的语音识别错误。访谈揭示了这些信号背后的解释逻辑：男性倾向于将失败解读为对技术表现和任务逻辑的破坏，而女性则更多地将同样的事件解读为对社会期望的破坏。这些性别化的解释表明，不满意不仅仅是个人可用性的结果，而是由共享的代表性框架组织的社会锚定感知。该研究贡献了(1)基于理论的关于性别如何围绕人工智能故障构建意义的解释，(2)将计算信号与定性表征映射联系起来的方法综合，以及(3)在不强化刻板印象的情况下预测不同期望的设计含义。通过超越频率计数到解释一致性，这项工作促进了对为什么相同的Siri行为会在用户之间产生不同形式的不满的理解。

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引用次数: 0

A socio-technical perspective on product configuration systems: Insights from Grundfos 产品配置系统的社会技术视角：格兰富的见解

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-27 DOI: 10.1016/j.techfore.2026.124564

Anders M.S.Ø. Jakobsen, Wim Vanhaverbeke

This study addresses the question of how user roles in Product Configuration Systems (PCS) function as socio-technical agents shaping operational efficiency, digital knowledge integration, and sustainable product customization in manufacturing. Grounded in socio-technical systems theory, the study analyses three years of PCS usage data from Grundfos—a global industrial pump manufacturer—to explore the socio-technical interplay between automated configuration processes and human expertise. Findings reveal that PCS effectiveness varies across Sales, Engineering, and Manufacturing roles: automation accelerates routine configurations, but human expertise remains crucial for complex cases. A regional analysis of global usage patterns indicates that highly automated regions achieve efficiency gains yet require expert oversight, whereas regions reliant on manual processes face digital adoption barriers that limit the system's optimization potential. Moreover, many PCS errors stem from misalignments between system constraints and user adaptations, underscoring the socio-technical nature of these challenges and the need for continuous human–technology alignment. Based on these insights, the study offers three key contributions to theory and practice: (1) a new conceptualization of PCS user roles as socio-technical agents; (2) a theoretical explanation of how user interactions shape PCS outcomes; and (3) a practical framework for embedding sustainability considerations into PCS workflows and decision-making.

本研究解决了产品配置系统（PCS）中的用户角色如何作为社会技术代理人塑造制造中的运营效率、数字知识集成和可持续产品定制的问题。基于社会技术系统理论，该研究分析了全球工业泵制造商格兰富（grundfos）三年的PCS使用数据，以探索自动化配置过程与人类专业知识之间的社会技术相互作用。调查结果显示，PCS的有效性因销售、工程和制造角色而异：自动化加速了常规配置，但对于复杂的情况，人类的专业知识仍然至关重要。对全球使用模式的区域分析表明，高度自动化的地区可以提高效率，但需要专家监督，而依赖人工流程的地区则面临数字采用障碍，限制了系统的优化潜力。此外，许多PCS错误源于系统约束和用户适应之间的不协调，强调了这些挑战的社会技术性质以及持续的人与技术协调的必要性。基于这些见解，本研究提出了三个关键的理论和实践贡献：(1)PCS用户角色作为社会技术代理人的新概念；(2)用户交互如何影响PCS结果的理论解释；(3)将可持续性考虑纳入PCS工作流程和决策的实用框架。

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引用次数: 0

Metaverse beyond the hype: Empirically assessing the future impact of metaverses 超越炒作的虚拟世界：对虚拟世界未来影响的实证评估

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-27 DOI: 10.1016/j.techfore.2026.124534

Savvas Papagiannidis , Ewelina Lacka , Ariana Polyviou , Yann Truong , Ben Marder , Jonas Colliander , Ilias O. Pappas , Giray Gozgor

The metaverse promises to extend our physical world using AR and VR technologies. Virtual environments and immersive spaces have been described as antecedents of the metaverse and offer some insight into the potential socio-economic impact of a fully functional, persistent cross platform metaverse. Considering the renewed interest by big tech companies in metaverses and the investment in relevant technologies, it is important to reflect on the current state of play and assess the socio-economic impact that such transformative technologies could have. The empirical evidence provided by papers responding to the Special Issue call shed light on the impact metaverses have, offering valuable theoretical and practical insights into business and social opportunities and challenges.

虚拟世界承诺使用AR和VR技术扩展我们的物理世界。虚拟环境和沉浸式空间被描述为虚拟世界的前身，并提供了一些关于功能齐全、持久的跨平台虚拟世界潜在的社会经济影响的见解。考虑到大型科技公司对元数据的重新兴趣以及对相关技术的投资，反思当前的游戏状态并评估这种变革性技术可能产生的社会经济影响非常重要。响应特刊呼吁的论文提供的经验证据揭示了元经济的影响，为商业和社会的机遇和挑战提供了宝贵的理论和实践见解。

引用次数: 0