The Impact of the Adoption Business Intelligence among Iranian Banks
الموضوعات :
1 - collage of Management and Economics science and research islamic azad university
الکلمات المفتاحية: Information Technology, improved marketing, data, Business intelligent,
ملخص المقالة :
Business intelligent (BI) technologies have been adopted by different types of organizations. The banking sector is among the service industry that has been largely influenced by technology currently. This has been manifested in the way the operations of banking have evolved from the pure exchange of cheques, cash, as well as other negotiable platforms to the application of IT (information Technology) to transact business in this service industry. The study conducted on impacts of business technologies adoption among Iranian Banks revealed that the adoption has made banking industry in Iran to be competitive and have improved operational efficiencies. However, in terms of Risk reduction, BI technologies if not used appropriately it can lead to the downfall of these banks. BI solutions allow banking industry in Iran to use the available data to exploit the competitive advantage as well as have an improved understanding of the demands and needs of customers by facilitating effective communication.
1. Caia, F., and Nastase, P. (2015). Modeling a Business Intelligence System for Investment Projects. Economic Computation & Economic Cybernetics Studies & Research, 49(2), 1-24.
2. Chen, H., Chiang, R. H., and Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), 1165-1188.
3. Chung-kuang, H. (2014). User acceptance of business intelligence systems in Taiwan’s electronics industry. Social Behavior & Personality: An International Journal, 42(4), 583-596. doi:10.2224/sbp.2014.42.4.583
4. Cristescu, M. P. (2016). Traditional Enterprise Business Intelligence Software Compared to Software as a Service Business Intelligence. Informatica Economica, 20(1), 39-47. doi:10.12948/issn14531305/20.1.2016.04
5. Elbashir, M. Z., Collier, P. A., and Davern, M. J. (2014). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9(3), 135-153.
6. Elbashir, M. Z., Collier, P. A., Sutton, S. G., Davern, M. J., and Leech, S. A. (2013). Enhancing the Business Value of Business Intelligence: The Role of Shared Knowledge and Assimilation. Journal Of Information Systems, 27(2), 87-105. doi:10.2308/isys-50563
7. Fotache, M. (2016). Data Processing Languages for Business Intelligence. SQL vs. R. Informatica Economica, 20(1), 48-61. doi:10.12948/issn14531305/20.1.2016.05.
8. Fourati-Jamoussi, F., and Niamba, C. N. (2016). An evaluation of business intelligence tools: a cluster analysis of users' perceptions. Journal Of Intelligence Studies In Business, 6(1), 37-47.
9. Gross, A., and Solymossy, E. (2016). Generations of Business Information, 1937-2012: Moving from Data Bits to Intelligence. Information & Culture, 51(2), 226-248. doi:10.7560/IC51204
10. Han, Y., Shen, C., and Farn, C. (2016). Determinants of continued usage of pervasive business intelligence systems. Information Development, 32(3), 424-439. doi:10.1177/0266666914554811
11. Kao, H. h., Yu, M. y., Masud, M. m., Wu, W. w., Chen, L. l., and Wu, Y. w. (2016). Design and evaluation of hospital-based business intelligence system (HBIS): A foundation for design science research methodology. Computers In Human Behavior, 62495-505.
12. Kowalczyk, M., and Buxmann, P. (2015). An ambidextrous perspective on business intelligence and analytics support in decision processes: Insights from a multiple case study. Decision Support Systems, 801-13. doi:10.1016/j.dss.2015.08.010
13. Norris, G., Qureshi, F., and Howitt, D. (2014). Introduction to Statistics with SPSS for Social Science. Florence: Taylor and Francis.
14. Peters, M. D., Wieder, B., Sutton, S. G., and Wakefield, J. (2016). Business intelligence systems use in performance measurement capabilities: Implications for enhanced competitive advantage. International Journal Of Accounting Information Systems, 211-17. doi:10.1016/j.accinf.2016.03.001
15. Ravid, R. (2014). Practical statistics for educators. Lanham, Md: Rowman and Littlefield.
16. Rojewski, J. r., In Heok Lee1, i., and Gemici, S. S. (2012). Use of t-test and ANOVA in Career-Technical Education Research. Career & Technical Education Research, 37(3), 263-275.
17. Rouhani, S., Ashrafi, A., Zare Ravasan, A., and Afshari, S. (2016). The impact model of business intelligence on decision support and organizational benefits. Journal Of Enterprise Information Management, 29(1), 19-50. doi:10.1108/JEIM-12-2014-0126
18. Rud, O. P. (2009). Business intelligence success factors: tools for aligning your business in the global economy (Vol. 18). John Wiley & Sons.
19.Scholz, P., Schieder, C., Kurze, C., Gluchowski, P., and Böhringer, M. (2013. Benefits and Challenges of Business Intelligence Adoption in Small and Medium-Sized Enterprises. In ECIS.
20. Schulz, M., Winter, P., and Choi, S. T. (2015). On the relevance of reports—Integrating an automated archiving component into a business intelligence system. International Journal Of Information Management, 35(6), 662-671. doi:10.1016/j.ijinfomgt.2015.07.005.
21. Sharifi-Renani, H., Moshref-Javadi, M. H., and Hajipoor, M. (2014). The Role of Information Technology in Reduction of Administrative Corruption through Increasing of Information transparency, Improvement of Accountability and Promotion of Integrity; A Case Study of Saderat Bank Branches in Isfahan. Journal Of Information Processing & Management, 28(3), 659-679.
22. Shollo, A., and Galliers, R. D. (2016). Towards an understanding of the role of business intelligence systems in organisational knowing. Information Systems Journal, 26(4), 339-367. doi:10.1111/isj.12071
23. Taghavifard, M. T., Adib, M. Z., and Torabi, M. (2012). Effective Factors on the Use of Internet Banking Services by Customers (Case: Mellat Bank). Journal Of Information Processing & Management, 27(3), 539-559.
24. Tavallaei, R., Shokohyar, S., Moosavi, S. M., and Sarfi, Z. (2015). Assessing the Evaluation Models of Business Intelligence Maturity and Presenting an Optimized Model. International Journal Of Management, Accounting & Economics, 2(9), 1005-1019.
25. Tvrdíková, M. (2016). Increasing the business potential of companies by ensuring continuity of the development of their information systems by current information technologies. Journal Of Business Economics & Management, 17(3), 475-489. doi:10.3846/16111699.2013.839475
26. Wang, H. (2014). Distinguishing the adoption of business intelligence systems from their implementation: the role of managers’ personality profiles. Behaviour & Information Technology, 33(10), 1082-1092. doi:10.1080/0144929X.2013.869260
27. Williams, S., and Williams, N. (2013). The profit impact of business intelligence. Morgan Kaufmann.
