IDEAS home Printed from https://ideas.repec.org/a/aej/apecjn/v20y2013i2p23-36.html
   My bibliography  Save this article

Length of Stay and Frequency of Visits in Chiangkhan (in Thai)

Author

Listed:
  • Arm Nakornthab

    (Faculty of Management Science, Khon Kaen University, Thailand)

  • Surachai Chancharat

    (Faculty of Management Science, Khon Kaen University, Thailand)

Abstract

This paper presents the analysis of tourism demand in Chiangkhan, Loei province. Travel cost method (TCM) with Poisson regression was applied to analyze factors affecting the decision of tourists as to the number of nights they would stay in Chiangkhan. The analysis includes logistic regression to consider the variables that affect the decision to revisit. The respondents were Thai tourists visiting Chiangkhan subdistrict. The data from 856 respondents were collected in January-February and June-July 2011 using a structured interview form. The respondents were impressed and attracted most by the ambience, culture and traditional living style. Young tourists from Bangkok with medium level of income comprised the most number of visitors. Those who had visited Chiangkhan would likely decide to revisit. However, the decision to revisit had an inverse relation to their income level. The tourism strategy should encourage the demand for tourism of the target group and aim to preserve the culture and tradition of Chiangkhan.

Suggested Citation

  • Arm Nakornthab & Surachai Chancharat, 2013. "Length of Stay and Frequency of Visits in Chiangkhan (in Thai)," Applied Economics Journal, Kasetsart University, Faculty of Economics, Center for Applied Economic Research, vol. 20(2), pages 23-36, December.
    • Handle: RePEc:aej:apecjn:v:20:y:2013:i:2:p:23-36
    as

    Download full text from publisher

    File URL: http://www.journal.eco.ku.ac.th/upload/document/thai/20131127095227.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. repec:jtr:journl:v:9:y:2014:i:1:p:94-107 is not listed on IDEAS

    More about this item

    Keywords

    Tourism demand; length of stay; revisiting; Chiangkhan;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

    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:aej:apecjn:v:20:y:2013:i:2:p:23-36. 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: Chatrat Hemmawat (email available below). General contact details of provider: https://edirc.repec.org/data/feckuth.html .

    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.