Dissertation/Thesis Abstract

Relationship Between Perceived Usefulness, Ease of Use, and Acceptance of Business Intelligence Systems
by Sandema-Sombe, Christina Ndiwa, D.B.A., Walden University, 2019, 158; 27543035
Abstract (Summary)

In retail, the explosion of data sources and data has provided incentive to invest in information systems (IS), which enable leaders to understand the market and make timely decisions to improve performance. Given that users’ perceptions of IS affects their use of IS, understanding the factors influencing user acceptance is critical to acquiring an effective business intelligence system (BIS) for an organization. Grounded in the technology acceptance model theory, the purpose of this correlational study was to examine the relationship between perceived usefulness (PU), perceived ease of use (PEOU), and user acceptance of business intelligence systems (BIS) in retail organizations. A 9-question survey was used to collect data from end-users of BIS in strategic managerial positions from retail organizations in the eastern United States who reported using BIS within the past 5 years. A total of 106 complete survey responses were collected and analyzed using multiple linear regression and Pearson’s product-moment correlation. The results of the multiple linear regression indicated the model’s ability to predict user acceptance, F(2,103) = 21.903, p < .000, R2 = 0.298. In addition, PU was a statistically significant predictor of user acceptance (t = -3.947, p = .000), which decreased with time as shown by the results from Pearson’s product-moment correlation, r = -.540, n = 106, p < .01. The implications of this study for positive social change include the potential for business leaders to leverage BIS in addressing the underlying causes of social and economic challenges in the communities they serve.

Indexing (document details)
Advisor: Simmons, Brandon
Commitee: Vadell, Jamiel, Klein, Jaime
School: Walden University
Department: Management
School Location: United States -- Minnesota
Source: DAI-A 81/4(E), Dissertation Abstracts International
Subjects: Information Technology, Information science, Management
Keywords: Analytics, BI, Big Data, Competitive Intelligence, TAM, Technology Acceptance Model
Publication Number: 27543035
ISBN: 9781392434093
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