IDEAS home Printed from https://ideas.repec.org/a/ids/ijbexc/v22y2020i1p114-138.html
   My bibliography  Save this article

SSTQUAL model: assessment of ATM service quality in an emerging economy

Author

Listed:
  • Mohd. Adil
  • Mohd. Nasir
  • Mohd. Sadiq
  • Kumkum Bharti

Abstract

This study aims to identify the key dimensions of automated teller machine (ATM) service quality and attempts to analyse the dynamic relationships among service quality, e-satisfaction and e-loyalty in Indian bank industry. Items were drawn from well-known SSTQUAL model, with cultural adjustment and industry specific modifications. A structured questionnaire in English language was used to collect the data from 360 ATM users. Research findings show that security/privacy and enjoyments have emerged as key dimensions that concern ATM users in India. The relative importance of the SSTQUAL dimensions identified in this study provides bank managers with a handbook as to which issues are critical in order of importance. Because of the limited sample size, the research results may lack generalisability. More replicative works are needed to enhance the generalisability.

Suggested Citation

  • Mohd. Adil & Mohd. Nasir & Mohd. Sadiq & Kumkum Bharti, 2020. "SSTQUAL model: assessment of ATM service quality in an emerging economy," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 22(1), pages 114-138.
    • Handle: RePEc:ids:ijbexc:v:22:y:2020:i:1:p:114-138
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=109222
    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. Farrukh Rafiq & Nikhil Dogra & Mohd Adil & Jei-Zheng Wu, 2022. "Examining Consumer’s Intention to Adopt AI-Chatbots in Tourism Using Partial Least Squares Structural Equation Modeling Method," Mathematics, MDPI, vol. 10(13), pages 1-15, June.

    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:ijbexc:v:22:y:2020:i:1:p:114-138. 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=291 .

    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.