Delgosha, M.S., Hajiheydari, N. and Talafidaryani, M. (2022) Discovering IoT implications in business and management: A computational thematic analysis. Technovation, 118. 102236. ISSN 0166-4972
Abstract
IoT as a disruptive technology is contributing toward ground-breaking experiences in contemporary enterprises and in our daily life. Rapidly changing business environment and phenomenally evolving technology enhancement necessitate a robust understanding of IoT implications from business and management perspective. The current study benefits from an explanatory sequential mixed-method approach to represent and interpret the inductive topical framework of IoT literature in business and management with emphasis on business model. Bayesian statistical topic model called latent Dirichlet allocation is employed to conduct a comprehensive analysis of 347 related scholarly articles to reveal the topical composition of related research. Further, we followed a thematic analysis for interpreting the extracted topics and gaining in-depth qualitative insights. Theoretical implications with emphasizing on research agenda for future study avenues and managerial implications based on influential themes are provided.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2021 Elsevier Ltd. This is an author produced version of a paper subsequently published in Technovation. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Internet of things; Topic modelling; Business model; Thematic analysis; Business and management; Future research |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 01 Mar 2021 10:54 |
Last Modified: | 19 Jun 2024 14:29 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.technovation.2021.102236 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:171632 |