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Challenges of Organizations' Adoption of Industrial Iot Platforms : Results of a Delphi Study

Title data

Arnold, Laurin ; Karnebogen, Philip ; Urbach, Nils:
Challenges of Organizations' Adoption of Industrial Iot Platforms : Results of a Delphi Study.
In: International Journal of Innovation and Technology Management. Vol. 20 (2023) Issue 6 . - 2350041.
ISSN 0219-8770
DOI: https://doi.org/10.1142/S0219877023500414

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
Projektgruppe WI IoT
No information

Abstract in another language

Companies are still reticent about adopting IIoT platforms, and research has not yet explained the
underlying challenges that impede such adoption. Uncovering these obstacles can open avenues for
research and practice to realize the intended potential. We take a holistic perspective on technological,
organizational, and environmental challenges that impede organizations’ adoption of IIoT platforms,
which we identify in a Delphi study with 22 international experts from academia and practice. Besides
identifying 29 challenges, our research reveals the comparative relevance of individual challenges,
uncovering differences in perceptions between academics and practitioners. The study contributes to
the diffusion of IIoT platforms in research and practice.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Industrial IoT; IIoT Platform; Adoption; Challenge; Delphi Study
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: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 13 Jun 2023 07:52
Last Modified: 07 Dec 2023 13:31
URI: https://eref.uni-bayreuth.de/id/eprint/81320