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A Taxonomy of Industrial IoT Platforms' Architectural Features

Title data

Arnold, Laurin ; Jöhnk, Jan ; Vogt, Florian ; Urbach, Nils:
A Taxonomy of Industrial IoT Platforms' Architectural Features.
In: 16th International Conference on Wirtschaftsinformatik (WI) : Proceedings ; 09.03-11.03.2021. - s.l. , 2021

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
Projektgruppe WI IoTNo information
Projektgruppe WI Strategisches IT-ManagementNo information

Abstract in another language

In the industrial Internet of Things (IIoT), the concept of digital platforms has received significant attention. Although IIoT platforms revolve around similar business objectives, they address a variety of use cases and, thus, differ considerably in their architectural setup. While research has already investigated IIoT platforms from a business or governance perspective, little is known about their underlying technology stack and its implications. To unveil different IIoT platform configurations and better understand their architectural design, we systematically develop and validate a taxonomy of IIoT platforms’ architectural features based on related literature, real-world objects, and expert interviews. On this foundation, we identify and discuss four IIoT platform archetypes. Our findings contribute to the descriptive knowledge in this ambiguous research field, while also elucidating the interplay of IIoT platforms’ architectural setup and their purpose. From a managerial viewpoint, our results may guide practitioners in comparing and selecting a suitable IIoT platform.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Industrial Internet of Things; IIoT Platforms; Architecture; Taxonomy; Archetypes
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 > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & 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: 08 Jan 2021 10:45
Last Modified: 15 Jul 2021 07:29
URI: https://eref.uni-bayreuth.de/id/eprint/61481