Technological Forecasting and Social Change最新文献

A structural-evolutionary rationale for public support of private technological innovation 公共支持私人技术创新的结构演化理论

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-17 DOI: 10.1016/j.techfore.2026.124539

Kenneth I. Carlaw , Gregory Bridgett

Dynamic competition in technological innovation drives long run economic growth. We find a rationale for public support of private technological innovation in features of this process which are central to our appreciative structural-evolutionary growth theory presented here. Agents face uncertainty and allocate resources to innovative endeavors based on subjective perceptions of potential opportunities that are generated by and limited to the evolving structural context in which they operate. Efforts cannot be evaluated on optimality criteria of equilibrium models because much of the value that may come to be associated with originating innovations is yet to be determined over the uncertain futures of their development trajectories. The system's history determines its present and future states. Influencing agent behaviours with respect to technological innovation alters the evolutionary path of economic growth. Policy that is historically conditioned, selectively focused and embedded in the structure of technology and the economy induces beneficial technological innovation trajectories. This role is absent from the equilibrium approach to economic growth theory in which fully-informed agents allocate resources based on calculations of optimal returns, producing growth on a stationary balanced growth path. In this approach, policy's sole purpose is the correction of divergence between social and private returns.

技术创新的动态竞争驱动着经济的长期增长。我们在这一过程的特征中发现了公共支持私人技术创新的基本原理，这是我们在这里提出的欣赏结构进化增长理论的核心。代理人面对不确定性，并根据对潜在机会的主观感知，将资源分配给创新努力，这些机会是由他们所处的不断变化的结构环境产生的，并受其限制。不能根据均衡模型的最优性标准来评估努力，因为可能与原始创新相关的许多价值尚未在其发展轨迹的不确定未来中确定。系统的历史决定了它现在和未来的状态。技术创新对主体行为的影响改变了经济增长的演化路径。受历史制约、有选择地集中和嵌入技术和经济结构的政策，会产生有益的技术创新轨迹。这种作用在经济增长理论的均衡方法中是不存在的，在均衡方法中，充分知情的主体根据最优回报的计算来分配资源，在平稳的平衡增长路径上产生增长。在这种方法中，政策的唯一目的是纠正社会和私人回报之间的差异。

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引用次数: 0

A data-driven framework for new product development: Integrating QFD and FCM based on online customer reviews 新产品开发的数据驱动框架：基于在线客户评论集成QFD和FCM

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-17 DOI: 10.1016/j.techfore.2025.124523

Romina Raafat , Jalil Heidary Dahooie , Edwin Garces , Tugrul Daim

Today, companies increasingly utilize customer-driven approaches like Quality Function Deployment (QFD) in new product development (NPD) to differentiate their products from competitors and satisfy customer needs and demands. Despite QFD's many capabilities in product design based on customer opinions, its practical implementation faces numerous challenges, such as heavy reliance on personal opinions for identifying and assessing the importance of customer requirements (CRs) and engineering characteristics (ECs), as well as the difficulty of understanding interactions between them. This problem worsens when there are connections and correlations between the identified requirements and characteristics. Given the benefits of extracting CRs from product reviews over traditional methods such as questionnaires and interviews, this study proposes a data-driven framework that combines data mining techniques and multi-attribute decision-making to tackle these issues. In this framework, online customer reviews (OCRs) are considered at all stages of NPD to maximize customer involvement, and association rule mining (ARM) is employed to discover causal relationships and weights among CRs, ECs, and their interactions. Additionally, by applying the Fuzzy Cognitive Map (FCM) method and integrating it with QFD, the relationships between CRs and ECs are analyzed, and CRs are prioritized accordingly. To demonstrate the practical application of this data-driven development framework, it is applied to the development of a mobile phone product using OCRs from Amazon.

今天，公司越来越多地在新产品开发（NPD）中使用客户驱动的方法，如质量功能部署（QFD），以使他们的产品与竞争对手区分开来，并满足客户的需求。尽管QFD在基于客户意见的产品设计中具有许多功能，但其实际实施面临许多挑战，例如在识别和评估客户需求（cr）和工程特征（ec）的重要性时严重依赖个人意见，以及理解两者之间相互作用的困难。当确定的需求和特征之间存在联系和相关性时，这个问题就会恶化。考虑到从产品评论中提取cr比传统方法（如问卷调查和访谈）的好处，本研究提出了一个数据驱动的框架，该框架结合了数据挖掘技术和多属性决策来解决这些问题。在该框架中，在新产品开发的各个阶段都考虑在线客户评论（ocr），以最大限度地提高客户参与度，并使用关联规则挖掘（ARM）来发现客户评论、客户评论及其交互之间的因果关系和权重。此外，应用模糊认知图（FCM）方法，将其与QFD相结合，分析了cr与ec之间的关系，并对cr进行了排序。为了演示这个数据驱动开发框架的实际应用，我们将其应用于使用来自Amazon的ocr的移动电话产品的开发。

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引用次数: 0

Interdisciplinary research and technological change 跨学科研究和技术变革

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-16 DOI: 10.1016/j.techfore.2026.124537

Bing Li , Kun Ding , Vincent Larivière

This study investigates the relationship between interdisciplinary research and technological change, using paper-patent citations. Technological change is defined as the extent to which a technology consolidates or disrupts existing technologies, patents can be categorized into three types: destabilizing, consolidating, and moderating. Drawing on all journal articles published in 2002 and indexed in the Web of Science database and all patents from the USPTO, our study reveals that research papers have a relatively minor impact on destabilizing patents compared to moderating and consolidating patents. Particularly noteworthy is the significant contribution of papers in the field of Biomedical Research to technological advancements. Analyzing distinct dimensions of interdisciplinary research—variety, balance, disparity, and the Rao-Stirling index—we find that destabilizing patent citations decrease with both variety and the Rao-Stirling index increase. The correlation with balance exhibits a U-shaped relationship, but we observe no significant relationship with disparity. Moreover, consolidating patent citations demonstrate an increase with disparity and the Rao-Stirling index, while showing a decrease in relation to balance, but no negligible association is found with variety. Moderate patent citations increase with both variety and balance, and decrease with both disparity and the Rao-Stirling index.

本研究以论文专利引文为工具，探讨跨学科研究与技术变革之间的关系。技术变革被定义为一项技术巩固或破坏现有技术的程度，专利可以分为三种类型：不稳定、巩固和缓和。通过对Web of Science数据库收录的2002年发表的所有期刊文章和美国专利商标局的所有专利进行分析，我们的研究表明，与缓和和巩固专利相比，研究论文对不稳定专利的影响相对较小。特别值得注意的是生物医学研究领域的论文对技术进步的重大贡献。通过对跨学科研究的多样性、平衡性、差异性和Rao-Stirling指数进行分析，我们发现不稳定专利引用随多样性和Rao-Stirling指数的增加而减少。与平衡呈u型相关，与差异无显著相关。合并专利被引率随差异和Rao-Stirling指数的增加而增加，随平衡而降低，但与多样性的关系不容忽视。中等专利被引量随多样性和平衡性而增加，随差异和Rao-Stirling指数而减少。

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引用次数: 0

The role of environmental taxes in promoting sustainable utilization of disaggregated natural resources toward global greening: A novel dynamic ARDL simulation approach 环境税在促进分类自然资源可持续利用、实现全球绿化中的作用：一种新的动态ARDL模拟方法

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-14 DOI: 10.1016/j.techfore.2026.124535

Isaac Ahakwa , Yi Xu , Evelyn Agba Tackie

Environmental degradation remains a critical challenge for resource-rich economies, where different forms of natural resources may exert heterogeneous environmental effects. This study evaluates how disaggregated natural resources, namely forest, oil, minerals, and natural gas, affect environmental degradation in Ghana, while assessing the moderating role of environmental taxes. Using a dynamic ARDL simulation approach, the analysis reveals that forest resources reduce environmental degradation, whereas oil, mineral, and natural gas resources intensify environmental degradation. Environmental taxes are found to mitigate the adverse environmental impacts associated with oil and mineral resource extraction, but are ineffective in offsetting degradation linked to natural gas and forest resources. These findings demonstrate that the environmental effects of resource exploitation and taxation are highly resource-specific, highlighting the heterogeneous dynamics between natural resources and environmental degradation.

环境退化仍然是资源丰富的经济体面临的重大挑战，在这些经济体中，不同形式的自然资源可能产生不同的环境影响。本研究评估了分类自然资源（即森林、石油、矿产和天然气）如何影响加纳的环境退化，同时评估了环境税的调节作用。采用动态ARDL模拟方法分析，森林资源减少了环境退化，而石油、矿产和天然气资源加剧了环境退化。环境税可以减轻与石油和矿产资源开采有关的不利环境影响，但无法抵消与天然气和森林资源有关的退化。这些发现表明，资源开发和税收的环境影响是高度资源特异性的，突出了自然资源和环境退化之间的异质性动态。

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引用次数: 0

Evaluating the use of structural equation modeling in online purchase intention research: A comprehensive review (2000−2023) 评价结构方程模型在在线购买意愿研究中的应用：综述（2000 - 2023）

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-12 DOI: 10.1016/j.techfore.2025.124512

René Abreu-Ledón , Darkys E. Luján-García , Pedro Garrido-Vega , Jose A.D. Machuca , Yodaira Borroto-Pentón

Technological advances—and, more recently, the COVID-19 pandemic—have accelerated the growth of online purchasing, prompting a surge in empirical research on online consumer behavior. A substantial share of these studies rely on structural equation modeling (SEM) for data analysis. However, inadequate or improper application of SEM can produce unreliable results and misleading conclusions, undermining scientific progress and managerial decision-making. To address this critical concern, the present study provides, to the best of our knowledge, the first comprehensive assessment of SEM applications—encompassing both covariance-based structural equation modeling (CB-SEM) and partial least squares structural equation modeling (PLS-SEM)— in online purchase intention (OPI) research. Our review covers 120 empirical articles published between 2000 and 2023 and reveals that methodological requirements of SEM are often overlooked, which risks invalidating both theoretical contributions and managerial implications. In response, we offer practical recommendations and a results-based guide to assist researchers and reviewers in enhancing the rigor, reliability, and decision-oriented value of SEM studies in this field.

技术进步，以及最近的COVID-19大流行，加速了在线购物的增长，促使对在线消费者行为的实证研究激增。这些研究的很大一部分依赖于结构方程模型（SEM）进行数据分析。然而，扫描电镜应用不充分或不当会产生不可靠的结果和误导性的结论，从而影响科学进步和管理决策。为了解决这一关键问题，据我们所知，本研究首次全面评估了在线购买意向（OPI）研究中基于协方差的结构方程建模（CB-SEM）和偏最小二乘结构方程建模（PLS-SEM）的SEM应用。我们回顾了2000年至2023年间发表的120篇实证文章，发现SEM的方法要求经常被忽视，这可能会使理论贡献和管理意义失效。作为回应，我们提供了实用的建议和基于结果的指南，以帮助研究人员和审稿人提高该领域扫描电镜研究的严谨性、可靠性和决策导向价值。

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引用次数: 0

The digital-environmental tension: Managerial attention to digital transformation and energy consumption in healthcare organizations 数字环境的紧张关系：管理对医疗机构数字化转型和能源消耗的关注

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-10 DOI: 10.1016/j.techfore.2025.124519

Dingli Xi , Minhao Zhang , Gianluca Veronesi

Digital transformation is broadly recognized as a promising approach to solving complex and longstanding organizational challenges. However, its environmental implications, particularly within the public sector, remain underexplored. Drawing on the attention-based view, this study addresses this gap by investigating how managerial attention to digital transformation impacts organizational environmental performance. We utilize a fixed-effects model approach to conduct the analysis based on a sample of 118 NHS Foundation Trusts in England between 2016 and 2021. The results show that managerial attention to digital transformation is positively related to energy consumption intensity. Building on core assumptions from the behavioral theory of the firm, we further investigate the moderating role of R&D income intensity discrepancy on the link between digital transformation attention and energy consumption intensity. Our findings indicate that positive R&D income intensity discrepancy weakens the positive relationship between digital transformation attention and energy consumption, whereas negative discrepancy does not have any impact. This study contributes to the extant literature by advancing the understanding of the intersection between digital transformation and sustainability, while extending the theoretical applications of the attention-based view and behavioral theory of the firm within the public sector. The findings also offer insights for policymakers and practitioners seeking to mitigate unintended environmental consequences and promote more sustainable initiatives to digital transformation.

数字化转型被广泛认为是解决复杂和长期组织挑战的一种有前途的方法。但是，其环境影响，特别是在公共部门内的影响，仍未得到充分探讨。借鉴基于注意力的观点，本研究通过调查管理层对数字化转型的关注如何影响组织环境绩效来解决这一差距。我们利用固定效应模型方法对2016年至2021年间英国118家NHS基金会信托基金的样本进行了分析。结果表明，管理者对数字化转型的关注程度与能源消耗强度呈正相关。基于企业行为理论的核心假设，进一步探讨研发收入强度差异对数字化转型关注与能源消耗强度之间关系的调节作用。研究发现，研发收入强度的正差异削弱了数字化转型注意力与能源消耗之间的正相关关系，而负差异则不产生影响。本研究促进了对数字化转型与可持续发展之间交叉关系的理解，同时扩展了公共部门企业关注基础观点和行为理论的理论应用，为现有文献做出了贡献。研究结果还为寻求减轻意外环境后果和促进更可持续的数字化转型举措的政策制定者和从业者提供了见解。

{"title":"The digital-environmental tension: Managerial attention to digital transformation and energy consumption in healthcare organizations","authors":"Dingli Xi , Minhao Zhang , Gianluca Veronesi","doi":"10.1016/j.techfore.2025.124519","DOIUrl":"10.1016/j.techfore.2025.124519","url":null,"abstract":"<div><div>Digital transformation is broadly recognized as a promising approach to solving complex and longstanding organizational challenges. However, its environmental implications, particularly within the public sector, remain underexplored. Drawing on the attention-based view, this study addresses this gap by investigating how managerial attention to digital transformation impacts organizational environmental performance. We utilize a fixed-effects model approach to conduct the analysis based on a sample of 118 NHS Foundation Trusts in England between 2016 and 2021. The results show that managerial attention to digital transformation is positively related to energy consumption intensity. Building on core assumptions from the behavioral theory of the firm, we further investigate the moderating role of R&D income intensity discrepancy on the link between digital transformation attention and energy consumption intensity. Our findings indicate that positive R&D income intensity discrepancy weakens the positive relationship between digital transformation attention and energy consumption, whereas negative discrepancy does not have any impact. This study contributes to the extant literature by advancing the understanding of the intersection between digital transformation and sustainability, while extending the theoretical applications of the attention-based view and behavioral theory of the firm within the public sector. The findings also offer insights for policymakers and practitioners seeking to mitigate unintended environmental consequences and promote more sustainable initiatives to digital transformation.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"225 ","pages":"Article 124519"},"PeriodicalIF":13.3,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The impact of creativity in social AR filters on brand awareness, image, and behavioral intentions: The role of intrusiveness and Ad recognition 社交AR过滤器的创意对品牌意识、形象和行为意图的影响：侵入性和广告识别的作用

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-10 DOI: 10.1016/j.techfore.2025.124521

Carlos Orús , Sergio Ibáñez-Sánchez , Carlos Flavián

Brands use Augmented Reality (AR) technologies in their marketing strategies. Among the AR applications, social AR filters enable brands to build new connections with customers on an intimate level, creating valuable experiences on social media and fostering consumers' storytelling. This research examines the effects of creativity of branded social AR filters, a key feature for the success of entertainment products, on users' responses toward brands. The results from an online questionnaire indicate that perceived originality and enjoyment elicit positive cognitive (awareness) and affective (image) reactions toward brands, which subsequently influence behavioral intentions. Additionally, we analyze the moderating role of brand intrusiveness and ad recognition, which can lessen and reinforce the positive effects of creativity on brand responses. Our findings contribute to the theoretical development of user experiences with branded social AR filters and provide recommendations for brand managers to design creative AR filter experiences that foster effective customer-brand connections.

品牌在营销策略中使用增强现实（AR）技术。在AR应用中，社交AR过滤器使品牌能够与客户建立亲密的新联系，在社交媒体上创造有价值的体验，并促进消费者的故事讲述。本研究考察了品牌社交AR滤镜的创造力对用户对品牌的反应的影响，这是娱乐产品成功的一个关键特征。一份在线调查问卷的结果表明，感知到的独创性和享受会引发对品牌的积极认知（意识）和情感（形象）反应，进而影响行为意向。此外，我们还分析了品牌侵入性和广告认知度的调节作用，它们可以减弱和增强创意对品牌反应的积极影响。我们的研究结果有助于品牌社交AR过滤器用户体验的理论发展，并为品牌经理设计创造性的AR过滤器体验提供建议，以促进有效的客户与品牌之间的联系。

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引用次数: 0

Integrating human support with algorithmic control: Psychological reactance in platform work 整合人类支持与算法控制：平台工作中的心理抗拒

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-08 DOI: 10.1016/j.techfore.2025.124520

Peng Hu , Xuru Wang , Jinqiang Wang

Algorithmic control has become a central feature of platform work, yet existing research primarily treats platform governance as an impersonal form of technological control. Drawing on self-determination theory, this study advances a co-managed human–algorithm governance perspective that conceptualizes workers' reactions as jointly shaped by algorithmic control and human support. We decompose workers' psychological reactance into cognitive and emotional forms and specify their distinct motivational antecedents. Our findings from platform-based delivery workers reveal that algorithmic control disrupts workers' sense of relatedness, giving rise to emotional reactance, while competence-related mechanisms play a limited role in this setting. Importantly, supervisor support attenuates the link between diminished relatedness and emotional reactance, underscoring the compensatory function of human intervention within algorithm-mediated work. By integrating algorithmic and human elements of control and differentiating the motivational structure of reactance, this study enriches theoretical understanding of the social and technological underpinnings of worker agency in platform labor.

算法控制已经成为平台工作的核心特征，然而现有的研究主要将平台治理视为一种非个人形式的技术控制。利用自我决定理论，本研究提出了一个共同管理的人类-算法治理视角，将工人的反应概念化为算法控制和人类支持共同塑造的。我们将工人的心理抗拒分解为认知和情感两种形式，并明确其不同的动机前因。我们对基于平台的送货员的研究结果表明，算法控制破坏了工人的归属感，引起了情绪上的抗拒，而与能力相关的机制在这种情况下发挥的作用有限。重要的是，主管的支持减弱了关系减少和情绪抗拒之间的联系，强调了在算法介导的工作中人为干预的补偿功能。通过整合控制的算法和人的因素，以及区分抗拒的动机结构，本研究丰富了对平台劳动中工人代理的社会和技术基础的理论认识。

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引用次数: 0

Machine learning approaches to predicting energy price correlation: From a responsible AI perspective 预测能源价格相关性的机器学习方法：从负责任的人工智能角度

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-08 DOI: 10.1016/j.techfore.2025.124515

Yu Su , Xuan Feng

This study is positioned within Responsible AI practice in energy markets, which exhibit inherent volatility and complexity. We integrate classical and modern machine learning techniques for enhanced energy price correlation forecasting. Principal Component Analysis (PCA) is employed for dimensionality reduction to identify underlying factors driving energy price correlations, leveraging its interpretability as a key analytical advantage. Long Short-Term Memory (LSTM) networks are then introduced for time-series modeling of energy prices and their inter-correlations.

Using a controlled simulation experiment, we empirically compare PCA-based and LSTM approaches in predicting energy price co-movements. While PCA provides transparent insights into correlation structure with low computation cost, LSTM achieves higher predictive accuracy (8.7% lower MES, 11.4% lower MAE) by capturing nonlinear temporal dependencies. The analysis highlights a governance-performance trade-off between PCA's interpretability and deep learning's precision, suggesting that model choice should be aligned with institutional capacity, regulatory requirements, and deployment constraints. These findings have significant implications for a technology-driven circular economy transitions, demonstrating how improved predictive modeling can enhance renewable integration and energy efficiency in energy markets.

本研究定位于能源市场中负责任的人工智能实践，其表现出固有的波动性和复杂性。我们整合了经典和现代机器学习技术来增强能源价格相关性预测。主成分分析（PCA）用于降维，以确定驱动能源价格相关性的潜在因素，利用其可解释性作为关键的分析优势。然后，将长短期记忆（LSTM）网络引入能源价格及其相互关系的时间序列建模。通过控制模拟实验，我们对基于pca的方法和LSTM方法在预测能源价格协同运动方面进行了实证比较。PCA以较低的计算成本提供了对相关结构的透明洞察，而LSTM通过捕获非线性时间依赖性实现了更高的预测精度（MES低8.7%，MAE低11.4%）。分析强调了PCA的可解释性和深度学习的精确性之间的治理-性能权衡，建议模型选择应与机构能力、监管要求和部署约束保持一致。这些发现对技术驱动的循环经济转型具有重要意义，证明了改进的预测模型如何提高能源市场的可再生能源整合和能源效率。

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引用次数: 0

Explore or exploit? How explorative and exploitative IT capabilities affect new product development process performance 探索还是利用？探索性和利用性IT能力如何影响新产品开发过程的性能

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change

Pub Date : 2026-01-08 DOI: 10.1016/j.techfore.2025.124517

Sven Heidenreich , Elena D. Denzer , Slawka Jordanow

This study investigates how explorative and exploitative IT capabilities drive performance across concept development, product development, and implementation stages of the new product development (NPD) process, and how environmental dynamism re-weights their effects. Drawing on survey data from 279 German innovation professionals and employing PLS-SEM alongside a polynomial-regression/response-surface analysis, we first show that treating IT exploration and IT exploitation as distinct dimensions uncovers their separate and joint contributions to stage-level outcomes. Both capabilities positively influence each NPD stage, but exploration yields its greatest marginal benefit during implementation, whereas exploitation exerts a steady effect across all stages. Response-surface results reveal that optimal performance is achieved not at a rigid 50:50 balance but at a context-sensitive, slightly exploitative-leaning ratio whose ideal position shifts as projects progress. Finally, environmental dynamism amplifies the value of explorative IT capabilities while attenuating that of exploitative IT capabilities. In turbulent settings firms benefit from heavier IT investment in exploration, whereas stable environments favor exploitation. These findings advance ambidexterity theory by challenging perfect balance assumptions, opening the NPD black box to reveal stage-specific digital mechanisms, and positioning environmental turbulence as a first-order boundary condition for IT strategy.

本研究探讨了探索性和利用性IT能力如何在概念开发、产品开发和新产品开发（NPD）过程的实施阶段推动绩效，以及环境动态如何重新权衡其影响。利用279名德国创新专业人士的调查数据，并采用PLS-SEM以及多项式回归/响应面分析，我们首先表明，将IT探索和IT利用视为不同的维度，揭示了它们对阶段水平结果的单独和共同贡献。这两种能力对每个新产品开发阶段都有积极影响，但勘探在实施过程中产生最大的边际效益，而开发在所有阶段都有稳定的影响。响应面结果显示，最佳性能不是在严格的50:50平衡下实现的，而是在一个上下文敏感的、略具剥削倾向的比例上实现的，其理想位置随着项目的进展而变化。最后，环境动态性放大了探索性IT能力的价值，同时减弱了利用性IT能力的价值。在动荡的环境中，公司从勘探方面的更多信息技术投资中受益，而稳定的环境有利于开采。这些发现通过挑战完美平衡假设，打开NPD黑箱以揭示特定阶段的数字机制，并将环境动荡定位为IT战略的一阶边界条件，从而推进了二元性理论。

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引用次数: 0