IDEAS home Printed from https://ideas.repec.org/a/ids/ijicbm/v6y2013i3p314-329.html
   My bibliography  Save this article

Factors affecting tourists' intention to purchase: a study of Indian domestic tourists

Author

Listed:
  • Neeraj Pandey
  • Vibhava Srivastava

Abstract

In the tourism domain, marketing is getting a lot of attention. The analytical marketing helps in unravelling the phenomenon of tourist shopping behaviour based on the data, which may differ from the routine consumer shopping behaviour. The literature suggests various probable factors for tourists' intention to purchase. The study endeavours to find the conclusive factors that impact Indian domestic tourist's intention to purchase. The present research highlights the importance of store experience such as ambience of the store and interaction with sales person at the store besides specific demographic variables, for enhancing the Indian domestic tourists intention to purchase. Such insights about patterns and predictor factors of Indian domestic tourist's purchase intention would lead to improved planning and management of sales and marketing in the tourism industry.

Suggested Citation

  • Neeraj Pandey & Vibhava Srivastava, 2013. "Factors affecting tourists' intention to purchase: a study of Indian domestic tourists," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 6(3), pages 314-329.
    • Handle: RePEc:ids:ijicbm:v:6:y:2013:i:3:p:314-329
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=53105
    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. Ram, Pappu Kalyan & Pandey, Neeraj & Persis, Jinil, 2024. "Modeling social coupon redemption decisions of consumers in food industry: A machine learning perspective," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    2. Gaurav Khatwani & Gopal Das, 2016. "Evaluating combination of individual pre-purchase internet information channels using hybrid fuzzy MCDM technique: demographics as moderators," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 12(1), pages 28-49.
    3. Mittal, Sheetal & Chawla, Deepak & Sondhi, Neena, 2016. "Segmentation of impulse buyers in an emerging market – An exploratory study," Journal of Retailing and Consumer Services, Elsevier, vol. 33(C), pages 53-61.

    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:ijicbm:v:6:y:2013:i:3:p:314-329. 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=235 .

    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.