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A Data-Driven Business Model Framework for Value Capture in Industry 4.0
| Content Provider | Semantic Scholar |
|---|---|
| Author | Schaefer, Dirk Walker, Joel Flynn, Joseph |
| Copyright Year | 2017 |
| Abstract | Manufacturing is undergoing a period of intense change as a result of advanced smart technologies, such as real-time sensors and the Industrial Internet of Things (IIoT). This has paved the way for a new era of digitized manufacturing known as Industry 4.0. It is anticipated that Industry 4.0 will be disruptive enough to present both new opportunities and threats to firms within a new competitive landscape. Manufacturers will be forced to adopt new business models to effectively capture value from the emerging smart technologies. A literature review revealed that few studies have addressed business models for Industry 4.0. Hence, this research addresses: What fundamental principles should companies in the manufacturing industry consider when adopting a data-driven business model? An analysis of four case studies on data-driven business models revealed significant common attributes. Through a SWOT analysis, twelve model principles for implementing a data-driven value capture framework could be identified. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://purehost.bath.ac.uk/ws/portalfiles/portal/158401847/ICMR17_Paper_77_final.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
