IDEAS home Printed from https://ideas.repec.org/a/ids/ijmore/v11y2017i3p369-395.html
   My bibliography  Save this article

Using of FAHP and fuzzy TOPSIS techniques for prioritising of Iranian banks to customer relationship management factors

Author

Listed:
  • Mohammad Mahmoudi Maymand
  • Elham Keshavarz

Abstract

The purpose of this research is to realise how organisations have been sustaining their growth through applying customer relationship management. Considering that Mellat, Melli and Central Saderat banks in Semnan have been brought for this research as statistic population, the number of experts participating in the study is 30 persons who were interested in improving discussion. The main tools used for gathering the data in this study were bank records and questionnaire. In this study, banks including private bank, state-owned bank, semi-private bank were ranked regarding to sub-scales related to different levels of customer relationship management factors and strategy, organisational performance, customer, process, infrastructure, technology sub-criteria of banking industry by using fuzzy analytic hierarchy process (FAHP) and fuzzy TOPSIS. The results obtained from both methods indicate that private bank is more important than semi-private bank and owned state bank in the banking industry. According to the customer relationship management factors, it is concluded that strategy is superior to other factors and then customer, organisational performance, process, infrastructure and technology are at the next rank, respectively. According to the strategy scale, it is concluded that strategic alliance is more important than other factors.

Suggested Citation

  • Mohammad Mahmoudi Maymand & Elham Keshavarz, 2017. "Using of FAHP and fuzzy TOPSIS techniques for prioritising of Iranian banks to customer relationship management factors," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 11(3), pages 369-395.
  • Handle: RePEc:ids:ijmore:v:11:y:2017:i:3:p:369-395
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=87213
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tsung-Yu Chou & Yen-Ting Chen, 2020. "Applying Fuzzy AHP and TOPSIS Method to Identify Key Organizational Capabilities," Mathematics, MDPI, vol. 8(5), pages 1-16, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijmore:v:11:y:2017:i:3:p:369-395. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=320 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.