{"title":"Artificial intelligence enabled product–service innovation: past achievements and future directions","authors":"Rimsha Naeem, Marko Kohtamäki, Vinit Parida","doi":"10.1007/s11846-024-00757-x","DOIUrl":null,"url":null,"abstract":"<p>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. </p>","PeriodicalId":20992,"journal":{"name":"Review of Managerial Science","volume":"34 1","pages":""},"PeriodicalIF":7.8000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Managerial Science","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s11846-024-00757-x","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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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