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Evaluation of Islamic Banking Efficiency in Iran

East Asian Journal of Business Economics / East Asian Journal of Business Economics, (E)2288-2766
2014, v.2 no.2, pp.37-47
https://doi.org/10.13106/eajbe.2014.vol2.no2.pp.37-47
Jalil Khaksar (Islamic Azad University)
Mahdi Salehi (Ferdowsi University of Mashhad)
Elahe Torabi (Islamic Azad University)

Abstract

Purpose – In this study, it is attempted to examine the Islamic banking practice in Iran based on new scientific methods. Design/methodology/approach- It is used the financial ratios demonstrating healthy or non-healthy of banks to assess the financial health of listed banks in Tehran Stock Exchange. The assessment of these ratios with use of decision tree as a non-parametric method for modeling is recommended for presenting this model. Information about the financial health of banks could be effective on the decisions of different groups of banks’ financial reports users, including shareholders, auditors, stock exchange, central bank and etc. Findings – the results of the study show that Decision Tree is strong approach in order to classifying Islamic banks in Iran. Originality/value- So far, several studies have been conducted in various countries on the topic of this study. Considering the importance Islamic banking, it is almost the first study in Iran and the outcomes of the study may helpful to Iranian economy.

keywords
Islamic Banking, efficiency, Shariah, Iran

Reference

1.

Andrews, J.D. and Morgan, J.M., (1986). Application of the digraph method of fault tree construction to process plant. Reliability Engineering, Vol. 14, No. 2, pp. 85-106.

2.

Chen, C., Kang, C., Sarrafzadeh, M, (2002). Activity-Sensitive Clock Tree Construction for Low Power, proceedings of the international symposium on Low power electronics and design.

3.

Gehrka, J., Ganti, V., Ramakrishnan, R., Loh, W, Y, (1999). BOAT-Optimistic Decision Tree Construction, Vol. 28, No. 2, pp.1-12.

4.

Gherka, J., Ramakrisnan, R., Ganti, V, (2000). Rainforest- A Frame Work Fast Decision Tree Construction of Large Datasets, Data mining and Knowledge Discovery, Vol. 4, pp.127-162.

5.

Jin, R., Agrawal, G (2003). Efficient Decision Tree Construction on Streaming data, Proceedings of the ninth ACM SIGKDD international conference on knowledge discovery and data mining.

6.

Lawrence, R, L., Wright, A, (2001). Rule-Based Classification Systems Using Classification and Regression Tree (CART) Analysis, Photogrammetric Engineering & Remote Sensing Vol. 67, No. 10, pp.1137-1142.

7.

Lin, C, W., Chen, S, Y., Li, S, F., Chang, Y, W., Yang, C, L, (2007). Efficient Obstacle-Avoiding Rectilinear Steiner Tree Construction, Proceedings of the international symposium on Physical design.

8.

Zhou, Ken., Hou, Q., Wang, R., Guo, B (2008). Real-Time KD- Tree Construction on Graphics Hardware. ACM Transactions on Graphics Journal (TOG), Vol. 27, No. 5, pp. 1-12.

East Asian Journal of Business Economics