Role of tourist motivation as mediating variable on visitor decisions at Indonesian tourism village

  • Received June 11, 2021;
    Accepted August 3, 2021;
    Published August 20, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.17(3).2021.07
  • Article Info
    Volume 17 2021, Issue #3, pp. 88-98
  • TO CITE АНОТАЦІЯ
  • Cited by
    6 articles
  • 1167 Views
  • 599 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The tourism sector has become a truly global force for promoting economic growth and development. Therefore, the study of tourism has become an interesting topic for researchers lately. On the other hand, local tourism, generally in developing countries, is often neglected by academics and policymakers. For this reason, this study aims to examine and analyze the role of tourist motivation in mediating accessibility, amenities, and attractions on visiting decisions. This study is a survey research with an explanatory method. The population is tourists who visit the tourism village of Bumiaji, Indonesia, in the low and busy seasons. The population is infinite and the number of respondents who were interviewed is 100 respondents; data were collected by distributing questionnaires to domestic tourists who came from outside the tourist village of Bumiaji, then the data were processed and analyzed using Warp Partial Least Squares. The findings indicate that the effect of accessibility on visiting decisions is not mediated by tourist motivation. This shows that the decision of tourists to visit can be directly influenced by the time and means of transportation available. Meanwhile, the influence of amenities and attractions on the decision to visit is mediated by the motivation of tourists. This means that amenities and attractions can influence a tourist’s decision to visit if there is an urge from tourist to relax or make friends or enjoy the culture at tourist attractions, etc.

view full abstract hide full abstract
    • Figure 1. Conceptual framework
    • Table 1. Warp PLS model fit
    • Table 2. R and Q Squares
    • Table 3. First path result
    • Table 4. Second path result
    • Conceptualization
      Martaleni Martaleni
    • Investigation
      Martaleni Martaleni
    • Software
      Martaleni Martaleni
    • Writing – original draft
      Martaleni Martaleni, Yussi Isna Pertiwi
    • Data curation
      Ernani Hadiyati
    • Methodology
      Ernani Hadiyati
    • Supervision
      Ernani Hadiyati
    • Writing – review & editing
      Ernani Hadiyati, Ni Nyoman Kerti Yasa
    • Formal Analysis
      Yussi Isna Pertiwi, Ni Nyoman Kerti Yasa
    • Project administration
      Yussi Isna Pertiwi
    • Validation
      Yussi Isna Pertiwi
    • Resources
      Ni Nyoman Kerti Yasa
    • Visualization
      Ni Nyoman Kerti Yasa