Title: Business intelligence systems success model based on information system theory

Authors: Mohammad Almuiet; Mohammad Bany Baker; Zaid Jaradat; Ala'a Bani Bakr; Qotadeh Saber Aljawazneh; Ghaith Jaradat

Addresses: Department of Data Science and Artificial Intelligence, Irbid National University, Irbid 21110, P.O. Box 2600, Jordan ' Faculty of Computing and Information Technology, Sohar University, Sohar, Sultanate of Oman ' Department of Accounting, School of Business, Al al-Bayt University, Mafraq 25113, P.O. Box 130040, Jordan ' Department of Cyber Security, Faculty of Information Technology, Zarqa University, Zarqa, 13110, Jordan ' Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa 13110, P.O. Box 2000, Jordan ' Faculty of Computer Science and Informatics, Amman Arab University, Amman 11953, Jordan

Abstract: In the literature, research often places more emphasis on decision-making systems than on the variables influencing BI adoption, and business intelligence (BI) is seen as a new decision-making domain. Along with other BI-relevant criteria, the article used the technology acceptance model (TAM), De Lone and McLean's model, and TAM. Survey information was collected from managers, accounting department heads, and IT department employees at Jordanian hospitals in order to experimentally test the suggested model. Based on the PLS-SEM results, it is clear that perceived usefulness, perceived usability, system quality, service quality, and information quality all had a favourable impact on BI adoption intentions, which in turn had a favourable impact on BI use. From a practical standpoint, stakeholders such as technology-based BI vendors, legislators, and healthcare providers can greatly benefit from the guidance provided by these findings.

Keywords: business intelligence; BI; technology acceptance model; TAM model; IS model; healthcare sector; Jordan.

DOI: 10.1504/IJSOM.2026.153857

International Journal of Services and Operations Management, 2026 Vol.54 No.1, pp.38 - 57

Received: 10 Sep 2023
Accepted: 18 Jan 2024
Published online: 29 May 2026 *

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