商业模式
原型
背景(考古学)
价值(数学)
计算机科学
新业务开发
工业互联网
业务
知识管理
数据科学
营销
万维网
物联网
艺术
古生物学
文学类
机器学习
生物
作者
Herbert Endres,Marta Indulska,Arunava Ghosh
标识
DOI:10.1016/j.indmarman.2024.03.006
摘要
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.
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