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Individual Enterprise Social Network Adoption : The Influence of Perceived Network Externalities and Perceived Social Capital Advantage

Title data

Kauschinger, Martin ; Letner, Albert ; Schreieck, Maximilian ; Urbach, Nils ; Böhm, Markus ; Krcmar, Helmut:
Individual Enterprise Social Network Adoption : The Influence of Perceived Network Externalities and Perceived Social Capital Advantage.
In: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI). - Nuremberg, Germany , 2022

Official URL: Volltext

Abstract in another language

Empirical evidence indicates that Enterprise Social Networks facilitate intra-organizational knowledge sharing. While organizations continue to invest in Enterprise Social Networks, many implementation projects fail due to insufficient user adoption. Against this background, this paper investigates factors that influence individuals’ adoption of Enterprise Social Networks. We thoroughly reviewed the existing literature and crafted a comprehensive adoption model. Besides commonly known adoption factors, we introduce perceived network externalities and perceived social capital advantage to account for the specific context of Enterprise Social Networks. We tested our model using structural equation modeling and empirical survey data of 155 respondents. Our results show that perceived network externalities are by far the strongest predictor for enterprise social network adoption, followed by perceived enjoyment and perceived social capital advantage. In contrast to other studies, we find perceived usefulness and perceived ease of use to be insignificant.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Enterprise Social Networks; Technology Adoption; Structural Equation Modeling; Network Effects; Collaboration
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
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: 04 Dec 2024 09:00
Last Modified: 04 Dec 2024 09:23
URI: https://eref.uni-bayreuth.de/id/eprint/91318