{"title":"在工业元宇宙时代释放工业物联网 (IIOT) 的潜力:商业模式与挑战","authors":"Herbert Endres , Marta Indulska , Arunava Ghosh","doi":"10.1016/j.indmarman.2024.03.006","DOIUrl":null,"url":null,"abstract":"<div><p>While the Industrial Internet of Things (IIoT) holds much promise, there is a mismatch between its potential and companies capturing value from investments in IIoT. Indeed, even when companies recognize the value of IIoT, they do not necessarily know how to grasp related opportunities and are challenged in developing a suitable business model. Accordingly, to alleviate roadblocks to capturing value from IIoT, in this paper we address the challenge of identifying suitable business models in the age of the industrial metaverse. We do so through an extensive review and classification of main IIoT business model archetypes that are successful in practice. In particular, we conduct a content analysis of IIoT projects based on over 2000 articles in industry trade magazines and newspapers. Our analysis identifies four distinct business model archetypes in the context of IIoT, <em>viz</em>. IIoT digical, IIoT service-centered, IIoT data-driven, and IIoT platform, and further explores the challenges that need to be addressed to ensure that companies can capture value from their IIoT initiatives. We explore appropriate contexts for these business model archetypes, and, in doing so, we provide actionable guidance for industrial (marketing) managers seeking to position their IIoT offerings and maximize their value.</p></div>","PeriodicalId":51345,"journal":{"name":"Industrial Marketing Management","volume":"119 ","pages":"Pages 90-107"},"PeriodicalIF":7.8000,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0019850124000440/pdfft?md5=460f26507e6b5c770ab29433f3c69a74&pid=1-s2.0-S0019850124000440-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Unlocking the potential of Industrial Internet of Things (IIOT) in the age of the industrial metaverse: Business models and challenges\",\"authors\":\"Herbert Endres , Marta Indulska , Arunava Ghosh\",\"doi\":\"10.1016/j.indmarman.2024.03.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>While the Industrial Internet of Things (IIoT) holds much promise, there is a mismatch between its potential and companies capturing value from investments in IIoT. Indeed, even when companies recognize the value of IIoT, they do not necessarily know how to grasp related opportunities and are challenged in developing a suitable business model. Accordingly, to alleviate roadblocks to capturing value from IIoT, in this paper we address the challenge of identifying suitable business models in the age of the industrial metaverse. We do so through an extensive review and classification of main IIoT business model archetypes that are successful in practice. In particular, we conduct a content analysis of IIoT projects based on over 2000 articles in industry trade magazines and newspapers. Our analysis identifies four distinct business model archetypes in the context of IIoT, <em>viz</em>. IIoT digical, IIoT service-centered, IIoT data-driven, and IIoT platform, and further explores the challenges that need to be addressed to ensure that companies can capture value from their IIoT initiatives. We explore appropriate contexts for these business model archetypes, and, in doing so, we provide actionable guidance for industrial (marketing) managers seeking to position their IIoT offerings and maximize their value.</p></div>\",\"PeriodicalId\":51345,\"journal\":{\"name\":\"Industrial Marketing Management\",\"volume\":\"119 \",\"pages\":\"Pages 90-107\"},\"PeriodicalIF\":7.8000,\"publicationDate\":\"2024-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0019850124000440/pdfft?md5=460f26507e6b5c770ab29433f3c69a74&pid=1-s2.0-S0019850124000440-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Industrial Marketing Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0019850124000440\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Marketing Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0019850124000440","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
Unlocking the potential of Industrial Internet of Things (IIOT) in the age of the industrial metaverse: Business models and challenges
While the Industrial Internet of Things (IIoT) holds much promise, there is a mismatch between its potential and companies capturing value from investments in IIoT. Indeed, even when companies recognize the value of IIoT, they do not necessarily know how to grasp related opportunities and are challenged in developing a suitable business model. Accordingly, to alleviate roadblocks to capturing value from IIoT, in this paper we address the challenge of identifying suitable business models in the age of the industrial metaverse. We do so through an extensive review and classification of main IIoT business model archetypes that are successful in practice. In particular, we conduct a content analysis of IIoT projects based on over 2000 articles in industry trade magazines and newspapers. Our analysis identifies four distinct business model archetypes in the context of IIoT, viz. IIoT digical, IIoT service-centered, IIoT data-driven, and IIoT platform, and further explores the challenges that need to be addressed to ensure that companies can capture value from their IIoT initiatives. We explore appropriate contexts for these business model archetypes, and, in doing so, we provide actionable guidance for industrial (marketing) managers seeking to position their IIoT offerings and maximize their value.
期刊介绍:
Industrial Marketing Management delivers theoretical, empirical, and case-based research tailored to the requirements of marketing scholars and practitioners engaged in industrial and business-to-business markets. With an editorial review board comprising prominent international scholars and practitioners, the journal ensures a harmonious blend of theory and practical applications in all articles. Scholars from North America, Europe, Australia/New Zealand, Asia, and various global regions contribute the latest findings to enhance the effectiveness and efficiency of industrial markets. This holistic approach keeps readers informed with the most timely data and contemporary insights essential for informed marketing decisions and strategies in global industrial and business-to-business markets.