Bridging the ‘Concept–Product’ gap in new product development: Emerging insights from the application of artificial intelligence in FinTech SMEs

IF 11.1 1区 管理学 Q1 ENGINEERING, INDUSTRIAL Technovation Pub Date : 2024-05-29 DOI:10.1016/j.technovation.2024.103017
Marija Cubric , Feng Li
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Abstract

Building on the literature on the concept-product gap in new product development, we examine how FinTech SMEs are developing Artificial Intelligence (AI)-based innovations and which organisational or project factors best contribute to the acceleration of AI innovation. The empirical evidence collected from interviews with key stakeholders, practitioners’ forums, and public company documents yields two distinct approaches that differ in their potential for accelerating innovation and reducing the concept-product gap. From a contingency perspective, these two approaches are expanded into four distinct development process configurations, contingent on the business development stage, reliance on 3rd party platforms, availability of high volumes of data, investment level, organisational agility, and level of novelty. The resulting process typology could be used as a diagnostic tool for FinTech SMEs interested in effectively leveraging AI innovation. Using contingency theory, we further develop these insights into a new theoretical framework to explain how AI innovation development unfolds in FinTech SMEs and the rationale for different implementations. Our new process typology and theoretical model can help researchers investigate the mechanisms underlying technological innovation processes. We further identify the specific reasons why the potential of AI for creating new services and disrupting incumbents via digital startups has not been fully realised even in contexts with significant investment and support from public and private business development programmes. This field is still rapidly evolving, and thus, new areas for future research are also highlighted.

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弥合新产品开发中的 "概念-产品 "鸿沟:金融科技中小企业应用人工智能的新启示
在有关新产品开发中概念与产品差距的文献基础上,我们研究了金融科技中小企业如何开发基于人工智能(AI)的创新,以及哪些组织或项目因素最有助于加速人工智能创新。从与主要利益相关者的访谈、从业者论坛和上市公司文件中收集的实证证据得出了两种截然不同的方法,它们在加速创新和缩小概念-产品差距方面的潜力各不相同。从应急的角度来看,这两种方法被扩展为四种不同的开发流程配置,取决于业务发展阶段、对第三方平台的依赖、大量数据的可用性、投资水平、组织灵活性和新颖程度。由此产生的流程类型学可作为诊断工具,供有意有效利用人工智能创新的金融科技中小型企业使用。利用权变理论,我们进一步将这些见解发展成一个新的理论框架,以解释金融科技中小企业如何开展人工智能创新发展以及不同实施方式的理由。我们的新流程类型学和理论模型有助于研究人员探究技术创新流程的内在机制。我们进一步确定了人工智能通过数字初创企业创造新服务和颠覆现有企业的潜力尚未得到充分发挥的具体原因,即使在公共和私营企业发展计划提供大量投资和支持的情况下也是如此。这一领域仍在快速发展,因此也强调了未来研究的新领域。
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来源期刊
Technovation
Technovation 管理科学-工程:工业
CiteScore
15.10
自引率
11.20%
发文量
208
审稿时长
91 days
期刊介绍: The interdisciplinary journal Technovation covers various aspects of technological innovation, exploring processes, products, and social impacts. It examines innovation in both process and product realms, including social innovations like regulatory frameworks and non-economic benefits. Topics range from emerging trends and capital for development to managing technology-intensive ventures and innovation in organizations of different sizes. It also discusses organizational structures, investment strategies for science and technology enterprises, and the roles of technological innovators. Additionally, it addresses technology transfer between developing countries and innovation across enterprise, political, and economic systems.
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