Assessing Information System Performance in Banks Based on Multi-Criteria Decision Making Techniques


  • Ansar Daghouri
  • Khalifa Mansouri
  • Mohammed Qbadou





banks, criteria, decision making techniques, evaluation models, information system.


The objective of this paper is to introduce a new technique to evaluate and analyze the performance of information system based on the DeLone and McLean information systems success model. The technique presented is derived from the research done on measuring information system success and multi criteria decision making techniques. In this work, a framework has been developed to select the most performing information system via a combined approach of two most popular methods: AHP and TOPSIS. The work methodology consists of three main steps. In first step, the main criteria are chosen from the Delone and McLean model (2003). In the second step, the weights of the main criteria and sub-criteria are calculated using the AHP method. In the final step, alternatives are ranked by using TOPSIS. A demonstration of this methodology on five Moroccan banks is presented.




[1] K Pilarczyk, "Importance of Management Information System in Banking Sector," Annales Universitatis Mariae Curie-Sklodowska Lublin-Polonia, no. 2, 2016.

[2] F A Lootsma, "Multi-Criteria decision analysis via ratio and difference judgment," Kluwer Academic Publishers, 1999.

[3] H R Weistroffer, C H Smith, and S C Narula, "Multiple criteria decision support software," Multiple Criteria Decision Analysis: State of the Art Surveys Series, Springer: New York, 2005.

[4] P McGinley, "Decision analysis software survey," 2012.

[5] N H Zardari, K Ahmed, S M Shirazi, and Z B Yusop, "Weighting Methods and their Effects on Multi-Croteria Decision Making Model Outcomes in Water Ressources Management," , 2015.

[6] F A Lootsma, "Multi-criteria decision analysis via ratio and difference judgement," Kluwer Academic Publishers, 1999.

[7] J Fulop, "Introduction to Decision Making Methods," in BDEI-Workshop, 2005, pp. 1-15.

[8] V Podvezko, "The Comparative Analysis of MCDA Methods SAW and COPRAS," Inzinerine Ekonomika-Engineering Economics, vol. 22, no. 2, pp. 134-146, 2011.

[9] T L Saaty, The analytic hierarchy process.: New York: McGraw-Hill, 1980.

[10] T L Saaty and K Penivati, Group decision making: Drawing out and reconciling Differences.: RWS Publications, Pittsburgh, PA, USA, 2008.

[11] T L Saaty, "Rank from Comparisons and From Ratings in the Analytic Hierarchy/Network Process," European Journal of Operational Research, vol. 168, no. 2, pp. 557-570, 2009.

[12] T L Saaty, "Decision making with the analytic hierarchy process," Int. J. Services Sciences, pp. 83-98, 2008.

[13] A.H I Lee, W-C Chen, and C-J Chang, "A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan," in Expert Systems with Applications, 2008, pp. 96-107.

[14] M Dagdeviren, S Yavuz, and N Kilinc, "Weapon selection using the AHP and TOPSIS methods under fuzzy environment," in Expert Systems with Applications, 2009, pp. 8143-8151.

[15] C L Hwang and K Yoon, "Manufacturing plant location analysis by multiple attribute decision making: Part II. Multi-plant strategy and plant relocation," International Journal of Production Research, vol. 23, no. 2, pp. 361-370, 1985.

[16] C L Hwang and K Yoon, "Multiple attributes decision making methods and applications," in Berlin: Springer, 1981.

[17] W H DeLone and E R McLean, "The DeLone and McLean model of information system success: a ten-year update," Journal of management information systems, vol. 19, no. 4, pp. 9-30, 2003.

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How to Cite

Daghouri, A., Mansouri, K., & Qbadou, M. (2018). Assessing Information System Performance in Banks Based on Multi-Criteria Decision Making Techniques. International Journal of Engineering & Technology, 7(4.32), 101–104.
Received 2019-01-04
Accepted 2019-01-04
Published 2018-12-06