Encouraging the use of self-service business intelligence–an examination of employee-related influencing factors

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OriginalspracheEnglisch
Seiten (von - bis)1-26
Seitenumfang26
FachzeitschriftJournal of Decision Systems
Jahrgang29
Ausgabenummer1
PublikationsstatusVeröffentlicht - 21 März 2020

Abstract

This study examines which factors influence the use of self-service business intelligence (SSBI) applications. To analyse the interdependencies, we develop a structural equation model (SEM) and test it by surveying potential users of SSBI across different sectors. The SEM shows that the intention to use is significantly influenced by the expected contribution of SSBI to information needs, which is significantly influenced by business intelligence (BI) experience, SSBI flexibility, SSBI expected time savings and the importance of data quality. The perceived attention of a company to data quality has a significant negative influence on the intention to use. These results imply that the mere introduction of SSBI is not sufficient for successful use. Training on how to use SSBI and how SSBI can change individual ways of working are important components. A well-designed concept for ensuring data quality also promotes the intention to use. In addition, we found that the utilitarian value is independent of the decision environment.

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Encouraging the use of self-service business intelligence–an examination of employee-related influencing factors. / Passlick, Jens; Guhr, Nadine; Lebek, Benedikt et al.
in: Journal of Decision Systems, Jahrgang 29, Nr. 1, 21.03.2020, S. 1-26.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Passlick J, Guhr N, Lebek B, Breitner MH. Encouraging the use of self-service business intelligence–an examination of employee-related influencing factors. Journal of Decision Systems. 2020 Mär 21;29(1):1-26. doi: 10.1080/12460125.2020.1739884
Passlick, Jens ; Guhr, Nadine ; Lebek, Benedikt et al. / Encouraging the use of self-service business intelligence–an examination of employee-related influencing factors. in: Journal of Decision Systems. 2020 ; Jahrgang 29, Nr. 1. S. 1-26.
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