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SERVQUAL-Based Performance Analysis of Agricultural Financing in E-Banking Industry: An Evaluation by IT2 Fuzzy Decision-Making Model

SERVQUAL-Based Performance Analysis of Agricultural Financing in E-Banking Industry: An Evaluation by IT2 Fuzzy Decision-Making Model

Serhat Yüksel, Hasan Dinçer
Copyright: © 2020 |Pages: 21
ISBN13: 9781799800354|ISBN10: 1799800350|ISBN13 Softcover: 9781799800361|EISBN13: 9781799800378
DOI: 10.4018/978-1-7998-0035-4.ch002
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MLA

Yüksel, Serhat, and Hasan Dinçer. "SERVQUAL-Based Performance Analysis of Agricultural Financing in E-Banking Industry: An Evaluation by IT2 Fuzzy Decision-Making Model." Tools and Techniques for Implementing International E-Trading Tactics for Competitive Advantage, edited by Yurdagül Meral, IGI Global, 2020, pp. 21-41. https://doi.org/10.4018/978-1-7998-0035-4.ch002

APA

Yüksel, S. & Dinçer, H. (2020). SERVQUAL-Based Performance Analysis of Agricultural Financing in E-Banking Industry: An Evaluation by IT2 Fuzzy Decision-Making Model. In Y. Meral (Ed.), Tools and Techniques for Implementing International E-Trading Tactics for Competitive Advantage (pp. 21-41). IGI Global. https://doi.org/10.4018/978-1-7998-0035-4.ch002

Chicago

Yüksel, Serhat, and Hasan Dinçer. "SERVQUAL-Based Performance Analysis of Agricultural Financing in E-Banking Industry: An Evaluation by IT2 Fuzzy Decision-Making Model." In Tools and Techniques for Implementing International E-Trading Tactics for Competitive Advantage, edited by Yurdagül Meral, 21-41. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-0035-4.ch002

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Abstract

The aim of the study is to measure the effectiveness of commercial banks in the agricultural financing in Turkey. For this purpose, 10 different criteria are identified based on five different SERVQUAL perspectives. Moreover, 10 different Turkish deposit banks traded on BIST are taken into consideration in the analysis process. Interval type-2 fuzzy DEMATEL (IT2 FDEMATEL) method is used to weight the dimensions and criteria. Also, deposit banks are ranked with interval type-2 fuzzy TOPSIS (IT2 FTOPSIS). The findings show that flexibility of needs, branch availability, and qualified personnel are the most important criteria for agricultural financing. Hence, it is recommended that banks design a system in which customers can access the banks in flexible times related to the agricultural financing. Another important recommendation is that banks open new branches near the agricultural regions so that farmers can reach the banking services easily. Furthermore, banks should also improve their personnel for agricultural issues with necessary trainings.

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