IDEAS home Printed from https://ideas.repec.org/a/bum/cactus/cactus-2024-10.html

Are there 'hygiene-motivation' factors in the choice of India as a tourist destination? A structural equation modelling approach

Author

Listed:
  • Vlad Diaconescu

    (Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

This study examines the role of motivational factors in the selection of India as a travel destination, using Herzberg’s two-factor theory of motivation (Hygiene-Motivation model) as a theoretical foundation. By examining how stereotypes about India influence tourists' decision making, this study categorises motivational factors into hygiene and motivation categories and examines their influence on destination choice. A survey conducted at the Romanian Tourism Fair in February 2019 with 729 participants forms the basis for this analysis. Structural equation modelling (SEM) was applied to assess the relationships between these factors. The study reveals two main types of factors that influence tourists: Hygiene factors (e.g. accessibility, comfort, food and overall quality of services) and motivational factors (e.g. cultural richness, scenic beauty and local traditions).The study shows that stereotypes about India play a crucial role in shaping tourists’ priorities — those who have negative stereotypes are more likely to focus on hygiene factors, such as ensuring that basic service expectations are met. In addition, while motivational factors still play an important role, elements such as natural beauty and cultural experiences take center stage in the travel decision.

Suggested Citation

  • Vlad Diaconescu, 2024. "Are there 'hygiene-motivation' factors in the choice of India as a tourist destination? A structural equation modelling approach," Cactus - The tourism journal for research, education, culture and soul, Bucharest University of Economic Studies, vol. 30(1).
  • Handle: RePEc:bum:cactus:cactus-2024-10
    as

    Download full text from publisher

    File URL: https://cactus-journal-of-tourism.ase.ro/wp-content/uploads/pdfs/vol6_no2_2024_art4_II.2-Diaconescu.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • Z30 - Other Special Topics - - Tourism Economics - - - General
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    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:bum:cactus:cactus-2024-10. 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: CACTUS Editorial Team (email available below). General contact details of provider: https://cactus-journal-of-tourism.ase.ro .

    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.