Technovation最新文献

Digital orientation and performance in innovative SMEs: exploring the (curvi)linear effects 创新型中小企业的数字化取向与绩效：探索（曲线）线性效应

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2026-01-17 DOI: 10.1016/j.technovation.2026.103478

Ludovica Antenozio , Pilar Marques , Andrea Bikfalvi

Digital orientation plays a key role in the competitiveness of firms, enhancing business processes and improving performance. In this paper, we examine how digital orientation affects innovative SMEs in terms of innovation and financial performance. Our analysis is based on an original panel data set of 250 innovative Italian SMEs over a period of 10 years, constructed using novel methods. We applied the Generalised Method of Moments, considering the curvilinear (inverted U-shaped) effect between businesses’ digital orientation and innovation and financial performance. The study finds support for the positive influence of digital orientation on financial performance, confirming the inverted U-shape, while results for innovation are contrary to the hypothesis raised. Our research provides insightful evidence of the complex relationship between digital orientation and different types of performance, contributing to the discussion on the IT paradox and highlighting a key managerial implication whereby innovative SMEs, rather than steadily increasing digital investment, should focus on optimising their digital assets to sustain both innovation and financial performance.

数字化导向在企业的竞争力、增强业务流程和提高绩效方面发挥着关键作用。在本文中，我们研究了数字化取向如何影响创新型中小企业的创新和财务绩效。我们的分析基于250家创新型意大利中小企业在10年期间的原始面板数据集，使用新颖的方法构建。我们应用了广义矩量法，考虑了企业数字化取向与创新和财务绩效之间的曲线（倒u形）效应。研究结果支持数字化取向对财务绩效的积极影响，证实了倒u型，而创新的结果与提出的假设相反。我们的研究为数字导向与不同类型绩效之间的复杂关系提供了深刻的证据，有助于讨论IT悖论，并强调了一个关键的管理含义，即创新型中小企业不应稳步增加数字投资，而应专注于优化其数字资产，以维持创新和财务绩效。

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引用次数: 0

Initial opportunity selection for deep technologies: Deep Technology Opportunity Navigator (DTON) 深度技术的初始机会选择：深度技术机会导航器（DTON）

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2026-01-08 DOI: 10.1016/j.technovation.2025.103464

Alexander Myers , Ekaterina Albats , Mariia Kozlova , Julian Yeomans

Deep technology ventures (DTVs) are new firms that aim to commercialize fundamental scientific or engineering breakthroughs and are usually located in the high-cost economies that fund such research. Deep technologies can potentially provide value to many industries or sectors but doing so requires making significant investments amid uncertainty. That situation complicates DTVs’ choice of the opportunity to focus on. We employed an iterative design science approach to develop a practical tool that can help DTVs navigate that complex decision. In doing so, we first reviewed the innovation management literature to identify the important factors in opportunity selection by a DTV. We subsequently interviewed a panel of deep technology entrepreneurship experts to supplement that information. These factors were translated into tool requirements. We analyzed existing opportunity selection tools against these requirements, finding only partial support for the DTV context. The same requirements were used to build an add-on to the widely used market opportunity navigator (MON) tool specifically to inform decision-making in DTVs. We label that advancement the deep technology opportunity navigator (DTON). The DTON was deployed as part of a facilitated workshop with two DTVs to collect feedback and iterate the design of the workshop and tool. The results of those workshops are supplemented by a thought experiment to imagine how it could help DTVs, providing illustrative examples of the potential impact of the new tool. The resulting DTON design is a practical tool that DTVs and other stakeholders can use to guide strategic decision-making, and its validation contributes to the literature on science-based entrepreneurship and opportunity selection.

深度技术企业（dtv）是旨在将基础科学或工程突破商业化的新公司，通常位于资助此类研究的高成本经济体。深度技术可以为许多行业或部门提供潜在价值，但这样做需要在不确定的情况下进行大量投资。这种情况使数字电视选择关注的机会变得复杂。我们采用了一种迭代设计科学方法来开发一种实用的工具，可以帮助dtv进行复杂的决策。为此，我们首先回顾了创新管理文献，以确定数字电视选择机会的重要因素。随后，我们采访了一组深度技术创业专家，以补充这些信息。这些因素被转化为工具需求。我们根据这些要求分析了现有的机会选择工具，发现只有部分支持数字电视环境。同样的需求也用于为广泛使用的市场机会导航（MON）工具构建一个附加组件，专门用于为dtv的决策提供信息。我们将这一进步称为深度技术机遇导航仪（DTON）。DTON是作为一个便利的讲习班的一部分部署的，有两个dtv收集反馈并迭代讲习班和工具的设计。这些研讨会的结果还补充了一个思想实验，以想象它如何帮助数字电视，提供了新工具潜在影响的说明性示例。由此产生的DTON设计是DTVs和其他利益相关者可以用来指导战略决策的实用工具，其验证有助于科学创业和机会选择的文献。

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引用次数: 0

Harnessing artificial intelligence for ambidextrous innovation: Contingent roles of complementary investments 利用人工智能进行双灵巧创新：互补投资的偶然作用

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2026-01-08 DOI: 10.1016/j.technovation.2026.103475

Yang (Eric) Zhou , Jingjun (David) Xu , Zhiying Liu

While a growing body of literature has explored the role of artificial intelligence (AI) in innovation management, current research lacks understanding of how AI adoption affects firms' ambidextrous innovation and what contextual factors may influence this relationship. Drawing on the innovation search perspective and upper echelons theory, this study theorizes the impact of AI adoption on ambidextrous innovation and evaluates the contingent roles of complementary investments. Using panel data from Chinese listed firms between 2011 and 2022, we find strong evidence that AI adoption significantly increases exploratory innovation (ERI) and exploitative innovation (EII). The mechanisms by which AI adoption affect ERI and EII involve broadening and heightening the scope and depth of knowledge search, respectively. Moderating analyses reveal that executives’ features (e.g., educational level and tenure) exert varying contingent effects. Specifically, executive educational level amplifies the positive impact of AI on EII but has no significant role in the AI–ERI relationship. Furthermore, executives with longer tenure tend to diminish the positive effect of AI on ERI and EII. These findings contribute to the existing literature at the intersection of AI and innovation and provide insights into how firms should make complementary investments to fully capture the benefits of AI.

虽然越来越多的文献探讨了人工智能（AI）在创新管理中的作用，但目前的研究缺乏对人工智能的采用如何影响公司的双灵巧创新以及哪些背景因素可能影响这种关系的理解。利用创新搜索视角和上层梯队理论，研究了人工智能应用对双灵巧创新的影响，并评估了互补投资的偶然性作用。利用2011年至2022年中国上市公司的面板数据，我们发现人工智能的采用显著提高了探索性创新（ERI）和剥削性创新（EII）。人工智能的采用影响ERI和EII的机制分别涉及拓宽和提高知识搜索的范围和深度。调节分析表明，高管的特征（如教育水平和任期）会产生不同的偶然效应。具体而言，高管教育水平放大了人工智能对EII的积极影响，但在AI - eri关系中没有显著作用。此外，任期较长的高管往往会削弱人工智能对ERI和EII的积极影响。这些发现为人工智能与创新交叉领域的现有文献做出了贡献，并为企业应如何进行互补投资以充分利用人工智能的好处提供了见解。

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引用次数: 0

How does the financial sector learn in socio-technical transitions? 金融部门如何在社会技术转型中学习？

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2026-01-07 DOI: 10.1016/j.technovation.2026.103467

Cătălina-Alexandra Papari , Friedemann Polzin , Florian Egli , Bjarne Steffen , Tobias S. Schmidt

Socio-technical transitions depend on not only technological innovation and supportive policy but also on the effective allocation of capital to emerging technologies, enabling them to scale beyond the niches in which they initially developed. One key element influencing financing decisions and shifting the financial flow to project realization is how financial actors learn — how they build, share, and use knowledge under uncertainty. This paper lays the groundwork for a theory of financial learning for sustainability transitions by examining how learning processes shape investment decisions in the case of utility-scale wind and solar technologies. Based on 54 expert interviews with stakeholders involved in project finance for renewable energy technologies across eight European countries, we developed a conceptual framework that extends the multi-level perspective by introducing financial learning as a key mechanism in the mainstreaming of niche technologies. We identified 12 distinct types of knowledge and traced how they are shaped and transmitted through specific “learning channels.” The framework highlights where “learn-by-doing” and “learn-by-interacting” channels emerge in financial decision making and offers a basis for identifying leverage points to enhance the adaptiveness of the financial sector. The paper provides a novel theoretical lens for scholars and actionable insights for policymakers aiming to accelerate sustainability transitions. By tracing where financial learning occurs, it also offers practical insights for accelerating capital reallocation and fostering systemic change across regimes beyond energy, such as biodiversity conservation and physical infrastructure.

社会技术转型不仅取决于技术创新和支持性政策，还取决于对新兴技术的有效资本配置，使其能够超越最初发展的利基。影响融资决策和将资金流转向项目实现的一个关键因素是金融行为者如何学习——他们如何在不确定的情况下构建、共享和使用知识。本文通过研究学习过程如何影响公用事业规模的风能和太阳能技术的投资决策，为可持续转型的财务学习理论奠定了基础。基于对8个欧洲国家可再生能源技术项目融资相关利益相关者的54位专家访谈，我们开发了一个概念框架，通过将金融学习作为利基技术主流化的关键机制，扩展了多层次视角。我们确定了12种不同类型的知识，并追踪了它们是如何通过特定的“学习渠道”形成和传播的。该框架强调了“在实践中学习”和“在互动中学习”渠道在金融决策中出现的地方，并为确定杠杆点以增强金融部门的适应性提供了基础。本文为学者提供了一个新的理论视角，为旨在加速可持续转型的政策制定者提供了可行的见解。通过追踪金融学习发生的地方，它还为加速资本重新配置和促进能源以外的制度的系统性变革（如生物多样性保护和物理基础设施）提供了实际见解。

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引用次数: 0

Digital service innovation for smarter production: Servitized-AI progress towards smart products 面向智能生产的数字化服务创新：服务化ai向智能产品迈进

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2026-01-06 DOI: 10.1016/j.technovation.2026.103466

Esteban Lafuente , Yancy Vaillant , Ajax Persaud

This paper investigates if the simultaneous integration of servitization and AI-intensive strategies lead manufacturers to develop products with more advanced analytically ‘smart’ capabilities. The proliferation of smart products, equipped with sensors and connectivity, has significantly enhanced value creation through remote monitoring, control, optimization, and autonomy. While the potential of digital technologies from these products is well-recognized, true smart capabilities require more than mere data collection; they necessitate AI-augmented Digital Service Innovation (DSI). This study posits that integrating AI with digital servitization enables manufacturers to develop advanced smart products. Utilizing a unique dataset from 576 Spanish manufacturing firms for 2023, the study employs an ordered probit model with sample selection to assess the impact of servitization and AI-intensive strategies on smart product development. Findings reveal that while both servitization and AI-intensive strategies contribute to the development of analytically smarter products, only the combined implementation significantly advances a product's smart capabilities. This research underscores the critical role of DSI in the progression of smart products through monitoring, control, optimization, and autonomy stages.

本文研究了服务化和人工智能密集型战略的同时整合是否会导致制造商开发具有更先进分析“智能”功能的产品。配备传感器和连接的智能产品的激增，通过远程监控、控制、优化和自主，显著提高了价值创造。虽然这些产品的数字技术的潜力是公认的，但真正的智能功能需要的不仅仅是数据收集；它们需要人工智能增强的数字服务创新（DSI）。本研究认为，将人工智能与数字化服务化相结合，使制造商能够开发先进的智能产品。该研究利用来自2023年576家西班牙制造公司的独特数据集，采用有序概率模型和样本选择来评估服务化和人工智能密集型战略对智能产品开发的影响。研究结果显示，虽然服务化和人工智能密集型战略都有助于开发分析上更智能的产品，但只有结合实施才能显著提高产品的智能能力。这项研究强调了DSI在智能产品通过监测、控制、优化和自治阶段的发展中的关键作用。

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引用次数: 0

Automation — Augmentation of Artificial Intelligence and Human Intelligence 自动化——人工智能和人类智能的增强

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2026-01-02 DOI: 10.1016/j.technovation.2025.103462

Rishav Raj , Amit Kumar Srivastava , Ratikanta Behera

We studied how Artificial Intelligence (AI) and Human Intelligence (HI) can substitute (automate) and complement (augment) each other over time. Through the adaptation of the Lotka–Volterra predator–prey model, we provide a mathematical framework to depict the cyclical interaction. These models are supported by real-world examples that highlight how AI and HI co-evolve, continuously optimizing task efficiency. The findings challenge the “either-or” view of automation and augmentation, presenting a nuanced perspective on how AI–HI mutually enhance each other over time.

我们研究了人工智能（AI）和人类智能（HI）如何随着时间的推移相互替代（自动化）和补充（增强）。通过对Lotka-Volterra捕食者-猎物模型的改进，我们提供了一个描述周期性相互作用的数学框架。这些模型由现实世界的例子支持，这些例子突出了AI和HI如何共同进化，不断优化任务效率。研究结果挑战了自动化和人工智能“非此即彼”的观点，对人工智能和人工智能如何随着时间的推移相互增强提出了微妙的观点。

引用次数: 0

Editorial on emerging technologies, crowdfunding, and entrepreneurship in emerging markets 关于新兴技术、众筹和新兴市场创业的社论

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2025-12-31 DOI: 10.1016/j.technovation.2025.103461

Nadia Zahoor , Albert Danso , Jie Wu , Samuel Adomako , Zaheer Khan

This special issue explores how emerging technologies are transforming entrepreneurial finance through crowdfunding in emerging markets. While entrepreneurs in these contexts face institutional voids and limited access to traditional finance, digital technologies such as mobile payments, platform algorithms, and machine learning are enabling new forms of resource mobilization. This editorial highlights three key insights: 1) digital technologies such as mobile payments and platform algorithms are transforming resource mobilization and legitimacy-building for entrepreneurs facing institutional voids; 2) crowdfunding serves not only as an alternative financing mechanism but also as a catalyst for inclusion, resilience, and innovation; and 3) platform governance and algorithmic mediation raise pressing questions of fairness and trust. We outline future research opportunities in digital affordances, informal–formal financing interactions, and policy frameworks for financial inclusion and sustainable development. The discussion advances theoretical perspectives on digitally mediated finance while offering practical guidance for entrepreneurs, policymakers, and development institutions seeking to leverage crowdfunding for venture growth in underrepresented economies.

本期特刊探讨了新兴技术如何通过新兴市场的众筹改变创业融资。虽然这些情况下的企业家面临制度空白和传统金融渠道有限，但移动支付、平台算法和机器学习等数字技术正在实现新形式的资源调动。这篇社论强调了三个关键观点：1)移动支付和平台算法等数字技术正在改变面临制度空白的企业家的资源动员和合法性建设；2)众筹不仅可以作为另一种融资机制，还可以作为包容性、弹性和创新的催化剂；3)平台治理和算法调解提出了公平和信任的紧迫问题。我们概述了未来在数字支持、非正式-正式融资互动以及普惠金融和可持续发展政策框架方面的研究机会。讨论提出了数字中介金融的理论观点，同时为寻求在代表性不足的经济体中利用众筹促进风险增长的企业家、政策制定者和发展机构提供了实践指导。

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引用次数: 0

Literature, the arts, and the societal impact of research 文学、艺术和研究的社会影响

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2025-12-30 DOI: 10.1016/j.technovation.2025.103463

Joaquín M. Azagra-Caro , David A. Kirby , Alessandro Muscio

The societal impact of research increasingly extends beyond commercialisation and policy uptake, engaging broader publics through cultural and creative practices. This special issue explores how literature and the arts open alternative pathways for knowledge transfer, public engagement, and societal relevance. We introduce the LASIR model, which conceptualises two complementary mechanisms: direct collaborations between researchers and creative practitioners, and the cultural representation of science and technology in literary and artistic narratives. The contributions examine cases ranging from science-theatre and art–science policy programmes to speculative fiction shaping public imaginaries of artificial intelligence. Together, these contributions advance understanding of how creative practices intersect with research impact, demonstrating how literature and the arts serve as sites where research is co-produced, societal meaning is negotiated, and the cultural legitimacy and practical relevance of science are constructed. The issue calls for expanded innovation policy and research evaluation frameworks that fully recognise creative practices as integral to knowledge valorisation and research impact, and for the development of dedicated funding instruments and evaluation approaches to support them.

研究的社会影响日益超越商业化和政策吸收，通过文化和创造性实践吸引更广泛的公众。本期特刊探讨了文学和艺术如何为知识转移、公众参与和社会关联开辟另一种途径。我们介绍了LASIR模型，它概念化了两个互补的机制：研究人员和创造性从业者之间的直接合作，以及文学和艺术叙事中科学技术的文化表现。这些贡献研究了从科学戏剧和艺术科学政策计划到塑造公众对人工智能想象的投机小说的案例。总之，这些贡献促进了对创造性实践如何与研究影响交叉的理解，展示了文学和艺术如何作为研究共同产生、社会意义协商以及科学的文化合法性和实践相关性构建的场所。这个问题要求扩大创新政策和研究评估框架，充分认识到创造性实践是知识增值和研究影响的组成部分，并要求开发专门的资助工具和评估方法来支持它们。

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引用次数: 0

Leveraging AI and generative AI in urban design and planning: Unveiling advantages and challenges through problem structuring methods 在城市设计和规划中利用人工智能和生成式人工智能：通过问题结构化方法揭示优势和挑战

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2025-12-27 DOI: 10.1016/j.technovation.2025.103465

Amali Çipi , Neuza C.M.Q.F. Ferreira , Fernando A.F. Ferreira , João J.M. Ferreira , Florentin Smarandache

The integration of Artificial Intelligence (AI) in general—and its subfield Generative AI (GenAI) in particular—into urban design and planning is revolutionizing traditional methodologies, providing innovative solutions to complex challenges in city development. Despite their transformative potential, existing research underscores a critical need to better understand the multifaceted advantages and challenges associated with these technologies. This study addresses this gap by investigating the causal relationships between the advantages and challenges of AI and GenAI integration in urban design and planning. Leveraging a novel combination of cognitive mapping and neutrosophic DEcision-MAking Trial and Evaluation Laboratory (DEMATEL), the research identifies and evaluates key factors shaping this integration. The findings reveal that dynamic digital city simulations and scenario modeling emerge as the most significant advantages, underscoring their capacity to drive data-informed innovation in urban development. Conversely, ethical concerns surface as the most critical challenge, exhibiting strong interdependencies with other issues, including the “black box” nature of AI systems and the biases embedded in training data. This study provides a comprehensive framework for understanding the interplay between these factors, offering actionable insights to guide both academic research and practical implementation. By addressing a pressing need in the field, the research paves the way for more responsible and effective applications of AI and GenAI in creating smarter, more sustainable urban environments.

将人工智能（AI）——尤其是其子领域生成人工智能（GenAI）——整合到城市设计和规划中，正在彻底改变传统的方法，为城市发展中的复杂挑战提供创新的解决方案。尽管它们具有变革潜力，但现有研究强调，迫切需要更好地了解与这些技术相关的多方面优势和挑战。本研究通过调查人工智能和GenAI集成在城市设计和规划中的优势和挑战之间的因果关系来解决这一差距。利用认知映射和中性决策试验与评估实验室（DEMATEL）的新组合，该研究确定并评估了形成这种整合的关键因素。研究结果显示，动态数字城市模拟和场景建模是最显著的优势，强调了它们在推动城市发展中基于数据的创新方面的能力。相反，道德问题是最关键的挑战，与其他问题表现出强烈的相互依赖性，包括人工智能系统的“黑匣子”性质和训练数据中嵌入的偏见。本研究为理解这些因素之间的相互作用提供了一个全面的框架，为指导学术研究和实际实施提供了可操作的见解。通过解决该领域的迫切需求，该研究为更负责任和更有效地应用人工智能和GenAI铺平了道路，以创造更智能、更可持续的城市环境。

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引用次数: 0

Unraveling the double-edged sword: When and how R&D team-experienced crises foster or hinder team creativity 揭开双刃剑：研发团队经历的危机何时以及如何培养或阻碍团队创造力

IF 10.9 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation

Pub Date : 2025-12-18 DOI: 10.1016/j.technovation.2025.103436

Zhengwei Li , Wenxin Li , Weize Huang , Jingjiang Liu

Despite the growing significance of team creativity in fostering corporate innovation, its underlying generative mechanisms remain insufficiently explored. This gap limits our understanding of when and how crises experienced by R&D teams either stimulate or inhibit their creativity. Drawing on team adaptation theory, this study seeks to clarify the contradictory effects of R&D team-experienced crises on creativity by identifying two distinct team-level mediating processes: team silence and team reflection. Furthermore, by integrating regulatory focus theory, we uncover critical boundary conditions. Specifically, we argue that R&D team-experienced crises reduce creativity through increased team silence when leaders adopt a predominant trait prevention focus. In contrast, they enhance creativity through increased team reflection when leaders adopt a predominant trait promotion focus. Our research hypotheses are empirically supported by multi-source data derived from 544 questionnaires, including responses from 136 leaders and 408 members of R&D teams. A supplementary experiment was conducted to validate further the causal relationship underlying our hypotheses. These findings provide nuanced insights into the paradoxical effects of crises on R&D team creativity, offering a deeper understanding of the conditions under which crises can either stifle or foster innovation.

尽管团队创造力在促进企业创新方面的重要性日益增加，但其潜在的生成机制仍未得到充分的探索。这一差距限制了我们对研发团队所经历的危机何时以及如何激发或抑制他们的创造力的理解。本研究以团队适应理论为基础，通过识别团队沉默和团队反思两种不同的团队层面中介过程，试图阐明研发团队经历的危机对创造力的矛盾影响。此外，通过整合监管焦点理论，我们揭示了关键的边界条件。具体来说，我们认为研发团队经历过的危机会通过增加团队沉默来降低创造力，当领导者采用主要的预防特征时。相比之下，当领导者采用以晋升为主要特质时，他们会通过增加团队反思来提高创造力。我们的研究假设得到了544份调查问卷的实证支持，其中包括136名领导者和408名研发团队成员的回答。为了进一步验证我们假设背后的因果关系，进行了一项补充实验。这些发现为危机对研发团队创造力的矛盾影响提供了细致的见解，为危机抑制或促进创新的条件提供了更深入的理解。

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引用次数: 0