Business Intelligence Deployment and Firm Performance: Literature Review of Empirical Evidences
- November 24, 2020
- Posted by: RSIS Team
- Categories: IJRSI, Management
International Journal of Research and Scientific Innovation (IJRSI) | Volume VII, Issue XI, November 2020 | ISSN 2321–2705
Business Intelligence Deployment and Firm Performance: Literature Review of Empirical Evidences
Yonney Atsu Ahlijah
Senior Lecturer, Faculty of Computer Science & Engineering Kings University College, Accra, Ghana
ABSTRACT
The main objective of this research is to empirically review recent studies on business intelligence deployment and its impact on firm performance based on two cardinal perspectives: (i) passage of time and themes, and (ii) research methodology adopted. The literature review took global dimension as it covered all geographical parts of the world. Twenty (20) empirically related studies were reviewed from 2004 – 2020 (17 years’ period). In geographical bread, four (4) of the empirically reviewed researches (representing 20%) originated from African countries; six (6) of the empirically reviewed researches (representing 30%) originated from Asian countries; another six (6) of the empirically reviewed researches (representing 30%) originated from European countries; two (2) of the empirically reviewed researches (representing 10%) originated from North American country (USA); one (1) of the empirically reviewed researches (representing 5%) originated from South American country (Brazil); and another one (1) of the empirically reviewed researches (representing 5%) originated from Australia. The major findings of the study include the following: (i) there is dearth of research on secondary data collection instrumentation; (ii) there is dearth of theoretical backed business intelligence related studies; (iii) the number of quantitative and mixed researches in business intelligence as a whole is very small; and (iv) there is absence of comparative business intelligence studies incorporating technological, organizational, and environmental variables. It is the recommendation of the study that these observed gaps in literature be empirically bridged.
Keywords: Business Intelligence, Deployment, Empirical Evidences, Firm Performance, Literature Review
1.0 INTRODUCTION
Business Intelligence (BI) has multiplicity of definitions or meanings depending from the view point being looked at: technological, organizational, managerial, process, or product. The development and democratization of business intelligence software makes it possible for people that lack high level of technical competence to be able to analyze and have good understanding of data; and such persons only need little assistance from information technology units to have access to organizational reports that would aid them in data-driven decision making process (Lebied, 2017).The fundamental underpin of this empirical review is anchored on the premise that business intelligence (BI) technology brings about different processes of value creation in an organisation via the instrumentality of data-driven business decision-making (Fink, Yogev& Even, 2017). Business intelligence appears to be among the most promising technologies in recent years in terms of value creation to organisations that deploy it (Kappelman, McLean, Luftman& Johnson, 2013). Despite the huge investment in business intelligence and the expected value perception originating there from, little empirical research has addressed the value creation processes unique to business intelligence systems (Eckerson, 2008; Wixom & Watson, 2001). Popovič, Turk and Jaklič (2015) stated that one major aim of information technology managers is how to quantify the added value through investment in new technologies (business intelligence inclusive); and Grover, Teng, Segars and Fiedler (1998) added that this has become a problematic issue to information technology researchers and managers as a result of different varieties of computing value added, presence of multiple intervening variables, productivity measurement challenges, and the treatment of business intelligence infrastructure investments as a lump sum. It is equally very worrisome that there seems to be very insignificant discussions on the benefits of business intelligence investments to business and non-business organisations (Davenport & Short, 2003; Dewett& Jones, 2001; Li & Ye, 1999; Williams & Williams, 2007).