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Testing a model of destination image formation: Application of Bayesian relational modelling and fsQCA

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  • Glückstad, Fumiko Kano
  • Schmidt, Mikkel N.
  • Mørup, Morten

Abstract

Individuals’ destination images are constantly updated through their exposure to various stimuli sent from diverse information sources11Information Sources: ISs. widely accessible in the modern society. Such dynamics of destination image formation22Dynamics of Destination Image Formation: DDIF. is better explained with the iterative process of a concept learning framework integrated into the destination image models. DDIF implies that individuals having been exposed to similar stimuli in the iterative image formation process have a higher likelihood of developing a similar mental representation33Mental Representation: MR.. Accordingly, this study employs an innovative methodological framework to extract patterns of MR of destinations held by groups of individuals (segments) and to compare segment-specific patterns of MR with their relations to willingness to visit44Willingness to Visit: W2V. and to ISs. The results demonstrate that what segments associate with a destination relates to their W2V, and segments having rich and positive associations with a destination accessed a wider range of ISs to learn about the destination.

Suggested Citation

  • Glückstad, Fumiko Kano & Schmidt, Mikkel N. & Mørup, Morten, 2020. "Testing a model of destination image formation: Application of Bayesian relational modelling and fsQCA," Journal of Business Research, Elsevier, vol. 120(C), pages 351-363.
    • Handle: RePEc:eee:jbrese:v:120:y:2020:i:c:p:351-363
    DOI: 10.1016/j.jbusres.2019.10.014
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