人工智能支持产品服务创新:过去的成就与未来的方向

IF 7.8 3区 管理学 Q1 MANAGEMENT
Rimsha Naeem, Marko Kohtamäki, Vinit Parida
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引用次数: 0

摘要

本研究旨在仔细研究人工智能(AI)在产品服务创新(PSI)中的作用。自2018年以来,有关人工智能支持的PSI、其他相关创新商业模式、产品服务系统和服务化的文献显著增加;因此,有必要以系统的方式构建文献,并对迄今为止的研究内容进行补充。产品服务创新用来表示在处理包括人工智能在内的创新成果的商业模式中实现创新的相关性。本研究采用书目耦合法分析了计算机科学、工程学、社会科学、决策科学和管理学领域的 159 篇文章。本综述描绘了由五(5)个集群组成的文献结构,即(1)技术采用和转型障碍,描绘了在采用人工智能技术和转型过程中面临的障碍;(2)数据驱动的能力和创新,强调了通过人工智能和创新支持的基于数据的能力;(3) 数字驱动的商业模式创新,阐释了人工智能驱动的商业模式创新是如何发生的;(4) 智能设计变更和可持续性,揭示了人工智能在产品服务环境中的作用,以及基于可持续性的不同设计变更和转型;以及 (5) 行业应用,重点介绍行业实例。每个集群都根据其内容进行了全面分析,包括中心主题、模型、理论和方法,这有助于找出差距并为未来研究方向提供支持建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Artificial intelligence enabled product–service innovation: past achievements and future directions

Artificial intelligence enabled product–service innovation: past achievements and future directions

This study intends to scrutinize the role of Artificial Intelligence (AI) in Product-Service Innovation (PSI). The literature on AI enabled PSI, other related innovation business models, product-service systems, and servitization has grown significantly since 2018; therefore, there is a need to structure the literature in a systematic manner and add to what has been studied thus far. Product-service innovation is used to represent the relevance of achieving innovation in business models dealing with innovation outcomes including artificial intelligence. This study used bibliographic coupling to analyze 159 articles emerging from the fields of computer sciences, engineering, social sciences, decision sciences, and management. This review depicts structures of the literature comprising five (5) clusters, namely, (1) technology adoption and transformational barriers, which depicts the barriers faced during the adoption of AI-enabled technologies and following transformation; (2) data-driven capabilities and innovation, which highlights the data-based capabilities supported through AI and innovation; (3) digitally enabled business model innovation, which explained how AI-enabled business model innovation occurs; (4) smart design changes and sustainability, which reveals the working of AI in product service environments with different design changes and transformations based on sustainability; and (5) sectorial application, which highlights industry examples. Each cluster is comprehensively analyzed based on its contents, including central themes, models, theories, and methodologies, which help to identify the gaps and support suggestions for future research directions.

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来源期刊
CiteScore
11.30
自引率
14.50%
发文量
86
期刊介绍: Review of Managerial Science (RMS) provides a forum for innovative research from all scientific areas of business administration. The journal publishes original research of high quality and is open to various methodological approaches (analytical modeling, empirical research, experimental work, methodological reasoning etc.). The scope of RMS encompasses – but is not limited to – accounting, auditing, banking, business strategy, corporate governance, entrepreneurship, financial structure and capital markets, health economics, human resources management, information systems, innovation management, insurance, marketing, organization, production and logistics, risk management and taxation. RMS also encourages the submission of papers combining ideas and/or approaches from different areas in an innovative way. Review papers presenting the state of the art of a research area and pointing out new directions for further research are also welcome. The scientific standards of RMS are guaranteed by a rigorous, double-blind peer review process with ad hoc referees and the journal´s internationally composed editorial board.
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