Understanding User Uncertainty during the Implementation of Self-Service Business Intelligence: A Thematic Analysis

Weiler, Severin; Matt, C; Hess, Thomas (2019). Understanding User Uncertainty during the Implementation of Self-Service Business Intelligence: A Thematic Analysis. In: Proceedings of the 52nd Hawaii International Conference on System Sciences 2019. 10.24251/HICSS.2019.709

Preview

Text Understanding_User_Uncertainty_during_the_Implementation_of_Self-Service_Business_Intelligence_A_Thematic_Analysis.pdf - Published Version Available under License Creative Commons: Attribution-Noncommercial-No Derivative Works (CC-BY-NC-ND). Download (1MB) | Preview

Owing to Self-Service Business Intelligence (SSBI) systems’ transformative power for organizations, substantial user uncertainties often blight their potential. Although these uncertainties pose a significant threat to effective SSBI implementation, their sources and determinants remain unclear. We conducted semi-structured interviews with 15 current users of a recently implemented SSBI system to empirically explore the relevant factors of user uncertainty. We undertook a rigorous thematic analysis of the collected data, thereafter developing a thematic map to visualize user uncertainties. This map uncovered three unexplored important factors (work routine change, social dynamics and fear of AI) for future research. Our findings show that users are not only perturbed by “hard” factors (e.g. a lack of technical understanding), but also by “soft” factors (social dynamics, fear of AI and nontransparency). Practitioners can use the thematic map to identify and observe potential uncertainties and to develop adequate procedures.

Interest & Impact

Downloads

269 since deposited on 02 Oct 2018
94 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item