IDEAS home Printed from https://ideas.repec.org/a/taf/rcitxx/v25y2022i13p2042-2047.html
   My bibliography  Save this article

People's perception on dark tourism: a quantitative exploration

Author

Listed:
  • Anirban Sarkar
  • Prabal Chakraborty
  • Marco Valeri

Abstract

The aim of this paper is to find out the perceptions of Indian Citizens about dark tourism in Indian context. Dark tourism is slowly getting attention among tourists in India. Here, cluster sampling method was applied and the total sample size was 396 respondents. We took help from the primary and secondary data here. The analysis is being undertaken with the help of Logistic Regression Technique applying SPSS Software. Logistic Regression technique can only be applied if the dependent variable is categorical in nature and independent variables can be either continuous or categorical. Hence, we applied binomial logistic regression technique to analyse the data. The findings could be useful for the marketers to develop service-related strategy formulations for the tourists.

Suggested Citation

  • Anirban Sarkar & Prabal Chakraborty & Marco Valeri, 2022. "People's perception on dark tourism: a quantitative exploration," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(13), pages 2042-2047, July.
  • Handle: RePEc:taf:rcitxx:v:25:y:2022:i:13:p:2042-2047
    DOI: 10.1080/13683500.2021.1889483
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13683500.2021.1889483
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13683500.2021.1889483?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    More about this item

    Statistics

    Access and download statistics

    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:taf:rcitxx:v:25:y:2022:i:13:p:2042-2047. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rcit .

    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.