{"title":"Enhancing innovation via the digital twin","authors":"Nobuyuki Fukawa, Aric Rindfleisch","doi":"10.1111/jpim.12655","DOIUrl":null,"url":null,"abstract":"<p>A growing number of firms are seeking to leverage emerging technologies, such as artificial intelligence (AI) and 3D printing, to enhance their innovation efforts. These seemingly distinct technologies are currently coalescing into an encompassing new technology called the digital twin. This technology allows innovative firms to create a digital replica of a physical entity that evolves over its life cycle. This article explores the implications of the digital twin for innovation theory and practice. First, we examine the connection between the digital twin and three related technologies (i.e., 3D printing, big data, and AI). Second, we create a typology of four categories of digital twins (i.e., monitoring, making, enhancing, and replicating) and illustrate their relevance for innovation management. Third, we offer a set of four case studies that exemplify this typology and illustrate how digital twins have been put into practice. Fourth, we craft a set of digital twin-related future research directions that encompasses a broad range of innovation-related topics, including service innovation, co-creation, and product design. We hope that our examination of the digital twin serves as a catalyst to help advance innovation thought and practice in this intriguing new domain.</p>","PeriodicalId":16900,"journal":{"name":"Journal of Product Innovation Management","volume":null,"pages":null},"PeriodicalIF":10.1000,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Product Innovation Management","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jpim.12655","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 5
Abstract
A growing number of firms are seeking to leverage emerging technologies, such as artificial intelligence (AI) and 3D printing, to enhance their innovation efforts. These seemingly distinct technologies are currently coalescing into an encompassing new technology called the digital twin. This technology allows innovative firms to create a digital replica of a physical entity that evolves over its life cycle. This article explores the implications of the digital twin for innovation theory and practice. First, we examine the connection between the digital twin and three related technologies (i.e., 3D printing, big data, and AI). Second, we create a typology of four categories of digital twins (i.e., monitoring, making, enhancing, and replicating) and illustrate their relevance for innovation management. Third, we offer a set of four case studies that exemplify this typology and illustrate how digital twins have been put into practice. Fourth, we craft a set of digital twin-related future research directions that encompasses a broad range of innovation-related topics, including service innovation, co-creation, and product design. We hope that our examination of the digital twin serves as a catalyst to help advance innovation thought and practice in this intriguing new domain.
期刊介绍:
The Journal of Product Innovation Management is a leading academic journal focused on research, theory, and practice in innovation and new product development. It covers a broad scope of issues crucial to successful innovation in both external and internal organizational environments. The journal aims to inform, provoke thought, and contribute to the knowledge and practice of new product development and innovation management. It welcomes original articles from organizations of all sizes and domains, including start-ups, small to medium-sized enterprises, and large corporations, as well as from consumer, business-to-business, and policy domains. The journal accepts various quantitative and qualitative methodologies, and authors from diverse disciplines and functional perspectives are encouraged to submit their work.