at Google ScholarTitle data
Duda, Sebastian ; Stoetzer, Jens-Christian ; Guggenberger, Tobias ; Urbach, Nils:
Understanding the Machine Economy : Combining Findings From Science and Practice.
In: International Journal of Innovation and Technology Management.
Vol. 21
(2024)
Issue 4
.
- 2450034.
ISSN 0219-8770
DOI: https://doi.org/10.1142/S0219877024500342
Project information
| Project title: |
Project's official title Project's id Projektgruppe WI BLockchain-Labor No information Projektgruppe WI IoT No information Projektgruppe WI Künstliche Intelligenz No information Projektgruppe WI Strategisches IT-Management No information |
|---|
Abstract in another language
The machine economy is an emergent phenomenon that combines multiple emerging digital technologies, such as IoT, AI, or blockchain, enabling economically autonomous acting machines. We investigate this phenomenon by combining a literature review and a qualitative interview study across different industries to derive propositions about the machine economy. Finally, we develop a five-layer model of the machine economy from our propositions that helps academia and practice to further explore this emerging phenomenon. Our results indicate that the machine economy builds on several emerging digital technologies and becomes increasingly relevant for practice and academia.
Further data
| Item Type: | Article in a journal |
|---|---|
| Refereed: | Yes |
| Keywords: | Machine Economy; Machine-to-Machine (M2M) Communication; Economy of Things; Propositions; Layer Model |
| Institutions of the University: | Faculties > Faculty of Law, Business and Economics > Department of Business Administration Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT Research Institutions > Affiliated Institutes > FIM Research Center for Information Management Faculties Faculties > Faculty of Law, Business and Economics |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics |
| Date Deposited: | 10 Apr 2024 11:14 |
| Last Modified: | 27 Jun 2024 11:30 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/89284 |