International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
line decor
  
line decor

 Volume 11, Issue 5 (May 2024), Pages: 55-61

----------------------------------------------

 Original Research Paper

Strategies for success: A theoretical model for implementing business intelligence systems to enhance organizational performance

 Author(s): 

 Tamara Adel Al-Maaitah 1, *, Al Smadi Khalid 1, Ala'a Mohammed Fadel Al-Junaidi 1, Tariq Khairo Issa Al Daabseh 1, Ahmed Alnawafleh 2, Nour Abdulwahab Qatawneh 3, Dirar Abdelaziz Al-Maaitah 4

 Affiliation(s):

 1Business Intelligence Department, Business School, Jadara University, Irbid, Jordan
 2Business Administration Department, Business School, Jadara University, Irbid, Jordan
 3Management Information System, Business School, Mutah University, Karak, Jordan
 4Business and Accounting Department, Alburaimi University, Al Buraimi, Oman

 Full text

  Full Text - PDF

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0003-1787-8373

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2024.05.006

 Abstract

The use of Business Intelligence Systems (BIS) has seen a significant rise worldwide in recent years, aiming to support organizations in navigating the competitive business environment. Despite this, many organizations struggle to fully benefit from BIS due to challenges in its implementation. A key reason identified for these challenges is the lack of effective measurement strategies. This paper seeks to provide a clear overview of business intelligence and the key factors that influence its successful implementation in organizations. Through a review of existing literature, the study identifies the most critical components necessary for the effective use of a business intelligence system. It proposes a theoretical model for evaluating BIS performance at the organizational level inspired by the Information System Performance Model. This model suggests that system quality, information quality, service quality, relationship quality, and process quality all play a vital role in enhancing perceived usefulness and user satisfaction, thereby leading to organizational benefits. By integrating insights from relevant literature, this paper offers a detailed understanding of how to assess the success of BIS within an organization. The findings highlight the positive impact of business intelligence systems on organizational performance and decision-making processes, aiding organizations in making informed decisions. This research is unique in that it presents a theoretical model for evaluating the success of BIS in organizations based on an extensive review of the literature. Additionally, it extends the application of the Information System Success Model to the domain of BIS for analyzing performance at the management level.

 © 2024 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Business intelligence systems, Implementation success, Organizational performance, Measurement strategies, Theoretical model

 Article history

 Received 18 December 2023, Received in revised form 3 April 2024, Accepted 25 April 2024

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Al-Maaitah TA, Khalid AS, Al-Junaidi AMF, Al Daabseh TKI, Alnawafleh A, Qatawneh NA, and Al-Maaitah DA (2024). Strategies for success: A theoretical model for implementing business intelligence systems to enhance organizational performance. International Journal of Advanced and Applied Sciences, 11(5): 55-61

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2

 Tables

 No Table

----------------------------------------------   

 References (39)

  1. Ahmad AA, Nuseir MT, Alzoubi HM, Al Kurdi B, Alshurideh MT, and Al-Hamad A (2024). Impact of the internet of things (IoT) on the e-supply chain with the mediating role of information technology capabilities: An empirical evidence from the UAE automotive manufacturing industry. In: Alzoubi HM, Alshurideh MT, and Ghazal TM (Eds.), Cyber security impact on digitalization and business intelligence: Big cyber security for information management: 409-429. Springer International Publishing, Cham, Switzerland. https://doi.org/10.1007/978-3-031-31801-6_25   [Google Scholar]
  2. Al-Ajlouni MM, Al-Maaitah DA, and Al-Maaitah TA (2024). Managing supply chains using business intelligence. Kurdish Studies, 12(2): 5328-5337.   [Google Scholar]
  3. Al-Hamad AQM, Hamadneh S, Nuseir MT, Alzoubi HM, Al Kurdi B, and Alshurideh MT (2024). A critical review of cloud computing architecture empowered with blockchain technology. In: Alzoubi HM, Alshurideh MT, and Ghazal TM (Eds.), Cyber security impact on digitalization and business intelligence: Big cyber security for information management: 495-506. Springer International Publishing, Cham, Switzerland. https://doi.org/10.1007/978-3-031-31801-6_29   [Google Scholar]
  4. Alkhwaldi AF (2024). Understanding the acceptance of business intelligence from healthcare professionals’ perspective: An empirical study of healthcare organizations. International Journal of Organizational Analysis. https://doi.org/10.1108/IJOA-10-2023-4063   [Google Scholar]
  5. Al-Maaitah TA, Tha’er Majali MA, and Almaaitah DA (2021). The impact of COVID-19 on the electronic commerce users behavior. Journal of Contemporary Issues in Business and Government, 27(1): 784-793.   [Google Scholar]
  6. Alshurideh MT, Al Kurdi B, Alquqa EK, Alzoubi HM, Hamadneh S, and AlHamad A (2024). Investigating the online buying behavior in the UAE online retail industry: The role of emotional intelligence and customer perception. In: Alzoubi HM, Alshurideh MT, and Ghazal TM (Eds.), Cyber security impact on digitalization and business intelligence: Big cyber security for information management: 371-386. Springer International Publishing, Cham, Switzerland. https://doi.org/10.1007/978-3-031-31801-6_23   [Google Scholar]
  7. Alyan MAA (2022). The impact of business intelligence on employee empowerment, the mediating role of information and communication technology (ICT), a field study on Jordanian Universities-Zarqa governorate. Ph.D. Dissertation, Zarqa University, Zarqa, Jordan.   [Google Scholar]
  8. Alzahrani MA (2024). The user analysis of amazon using artificial intelligence at customer churn. Journal of Data Analysis and Information Processing, 12(1): 40-48. https://doi.org/10.4236/jdaip.2024.121003   [Google Scholar]
  9. Alzghoul A, Khaddam AA, Abousweilem F, Irtaimeh HJ, and Alshaar Q (2022). How business intelligence capability impacts decision-making speed, comprehensiveness, and firm performance. Information Development, 40(2): 220-233. https://doi.org/10.1177/02666669221108438   [Google Scholar]
  10. Arefin MS, Hoque MR, and Rasul T (2021). Organizational learning culture and business intelligence systems of health-care organizations in an emerging economy. Journal of Knowledge Management, 25(3): 573-594. https://doi.org/10.1108/JKM-09-2019-0517   [Google Scholar]
  11. Chen Y and Lin Z (2021). Business intelligence capabilities and firm performance: A study in China. International Journal of Information Management, 57: 102232. https://doi.org/10.1016/j.ijinfomgt.2020.102232   [Google Scholar]
  12. Costa HCS, de Lima Carneiro FL, Pereira JRLA, Pereira MA, Neto ATP, and da Silva Júnior HB (2024). Optimizing industrial data analysis: The convergence of business intelligence and dynamic simulations in chemical process management. Revista De Gestão Social E Ambiental, 18(3): e04475. https://doi.org/10.24857/rgsa.v18n3-025   [Google Scholar]
  13. Daradkeh M (2022). Innovation in business intelligence systems: The relationship between innovation crowdsourcing mechanisms and innovation performance. International Journal of Information Systems in the Service Sector, 14(1): 1-25. https://doi.org/10.4018/IJISSS.302885   [Google Scholar]
  14. DeLone WH and McLean ER (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4): 9-30. https://doi.org/10.1080/07421222.2003.11045748   [Google Scholar]
  15. Huang ZX, Savita KS, and Zhong-Jie J (2022). The business intelligence impact on the financial performance of start-ups. Information Processing and Management, 59(1): 102761. https://doi.org/10.1016/j.ipm.2021.102761   [Google Scholar]
  16. Ismail Al-Alawi A, Almulla D, Abbas M, and Alkooheji L (2024). Process and impact evaluation of artificial intelligence in managerial accounting: A systematic literature review. International Journal of Computing and Digital Systems, 15(1): 1-26. https://doi.org/10.12785/ijcds/1501104   [Google Scholar]
  17. Jadhav B, Khang A, Kulkarni A, Kulkarni P, and Kulkarni S (2024). Artificial intelligence-based model and applications in business decision-making. In: Khang A, Abdullayev V, Jadhav B, Gupta S, and Morris G (Eds.), AI-centric modeling and analytics: 1-12. CRC Press, Boca Raton, USA. https://doi.org/10.1201/9781003400110-1   [Google Scholar] PMCid:PMC10186283
  18. Jaradat Z, Al-Dmour A, Alshurafat H, Al-Hazaima H, and Al Shbail MO (2022). Factors influencing business intelligence adoption: Evidence from Jordan. Journal of Decision Systems, 33(2): 242–262. https://doi.org/10.1080/12460125.2022.2094531   [Google Scholar]
  19. Khan S, Qader MR, Thirunavukkarasu K, and Abimannan S (2020). Analysis of business intelligence impact on organizational performance. In the International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, IEEE, Sakheer, Bahrain: 1-4. https://doi.org/10.1109/ICDABI51230.2020.9325610   [Google Scholar]
  20. Kimball R and Ross M (2024). Relentlessly practical tools for data warehousing and business intelligence. Wiley, Hoboken, USA.   [Google Scholar]
  21. Maaitah T (2023a). The role of business intelligence tools in the decision making process and performance. Journal of Intelligence Studies in Business, 13(1): 43-52. https://doi.org/10.37380/jisib.v13i1.990   [Google Scholar]
  22. Maaitah T (2023b). The role of entrepreneurship on the economic growth and development. Entrepreneurship and Organization Management, 12: 2.   [Google Scholar]
  23. Masa’Deh RE, Obeidat Z, Maqableh M, and Shah M (2021). The impact of business intelligence systems on an organization’s effectiveness: The role of metadata quality from a developing country’s view. International Journal of Hospitality and Tourism Administration, 22(1): 64-84. https://doi.org/10.1080/15256480.2018.1547239   [Google Scholar]
  24. Mudau TN, Cohen J, and Papageorgiou E (2024). Determinants and consequences of routine and advanced use of business intelligence (BI) systems by management accountants. Information and Management, 61(1): 103888. https://doi.org/10.1016/j.im.2023.103888   [Google Scholar]
  25. Nithya N and Kiruthika R (2021). Impact of business intelligence adoption on performance of banks: A conceptual framework. Journal of Ambient Intelligence and Humanized Computing, 12(2): 3139-3150. https://doi.org/10.1007/s12652-020-02473-2   [Google Scholar]
  26. Nuseir MT, Aljumah A, and Alshurideh MT (2021). How the business intelligence in the new startup performance in UAE during COVID-19: The mediating role of innovativeness. In: Alshurideh MT, Hassanien AE, Masa'deh R (Eds.), The effect of coronavirus disease (COVID-19) on business intelligence: 63-79. Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-030-67151-8_4   [Google Scholar]
  27. Olszak C, Zurada J, Kozanoglu D, and Weichbroth P (2024). Introduction to the Minitrack on business intelligence and big data for innovative, collaborative and sustainable development of organizations in digital era. In the Proceedings of the 57th Hawaii International Conference on System Sciences, Honolulu, USA. https://doi.org/10.24251/HICSS.2023.031   [Google Scholar]
  28. Paradza D and Daramola O (2021). Business intelligence and business value in organisations: A systematic literature review. Sustainability, 13(20): 11382. https://doi.org/10.3390/su132011382   [Google Scholar]
  29. Rahardja U and Harahap EP (2019). Implementation of information planning and strategies industrial technology 4.0 to improve business intelligence performance on official site APTISI. In the 1st International Conference on Computer, Science, Engineering and Technology, IOP Publishing, Tasikmalaya, Indonesia, 1179(1): 012111. https://doi.org/10.1088/1742-6596/1179/1/012111   [Google Scholar]
  30. Rahman AAA (2021). Bibliometric approach of Business Intelligence as technical infrastructure to enhance the organizational performance, competitiveness and decision making. Journal of Legal, Ethical and Regulatory Issues, 24: 1-12.   [Google Scholar]
  31. Richards G, Yeoh W, Chong AYL, and Popovič A (2019). Business intelligence effectiveness and corporate performance management: An empirical analysis. Journal of Computer Information Systems, 59(2): 188-196. https://doi.org/10.1080/08874417.2017.1334244   [Google Scholar]
  32. Saleem N and Ilkhanizadeh S (2021). The mediating role of organizational culture in the effect of business intelligence on corporate performance management. International Journal of Research in Humanities and Social Studies, 8: 1-14.   [Google Scholar]
  33. Sorour A and Atkins AS (2024). Big data challenge for monitoring quality in higher education institutions using business intelligence dashboards. Journal of Electronic Science and Technology, 22(1): 100233. https://doi.org/10.1016/j.jnlest.2024.100233   [Google Scholar]
  34. Tripathi A, Bagga T, and Aggarwal RK (2020). Strategic impact of business intelligence: A review of literature. Prabandhan: Indian Journal of Management, 13(3): 35-48. https://doi.org/10.17010/pijom/2020/v13i3/151175   [Google Scholar]
  35. Vugec DS, Vukšić VB, Bach MP, Jaklič J, and Štemberger MI (2020). Business intelligence and organizational performance. Business Process Management Journal, 26(6): 1709-1730. https://doi.org/10.1108/BPMJ-08-2019-0342   [Google Scholar]
  36. Whig P, Velu A, Nadikattu RR, and Alkali YJ (2024). Role of AI and IoT in intelligent transportation. In: Dhanaraj RK, Kamila NK, Pani SK, Balusamy B, and Rajasekar V (Eds.), Artificial intelligence for future intelligent transportation: 199-220. Apple Academic Press, Palm Bay, USA. https://doi.org/10.1201/9781003408468-8   [Google Scholar]
  37. Yaghoubi A, Mirabi V, and Jalali M (2024). Implementation of business intelligence for subsidiaries of Bank Melli Iran. Journal of Management Accounting and Auditing Knowledge, 13(51): 411-432.   [Google Scholar]
  38. Yassine FLYA, Maaitah TA, Maaitah DA, and Al-Gasawneh JA (2023). Impact of COVID-19 on the university education system in Jordan. Journal of Southwest Jiaotong University, 57(1): 1-15. https://doi.org/10.35741/issn.0258-2724.57.1.58   [Google Scholar]
  39. Yiu LD, Yeung AC, and Cheng TE (2021). The impact of business intelligence systems on profitability and risks of firms. International Journal of Production Research, 59(13): 3951-3974. https://doi.org/10.1080/00207543.2020.1756506   [Google Scholar]