Testing a model of destination image formation: Application of Bayesian relational modelling and fsQCA
•Dynamics of destination image formation are explained as an iterative process of concept learning.•A Bayesian generative method simultaneously segmented people and destination attributes.•fsQCA found segment-specific relations between sets of attributes and behavioural intention.•How people learn a...
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Veröffentlicht in: | Journal of business research 2020-11, Vol.120, p.351-363 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Dynamics of destination image formation are explained as an iterative process of concept learning.•A Bayesian generative method simultaneously segmented people and destination attributes.•fsQCA found segment-specific relations between sets of attributes and behavioural intention.•How people learn about, and what they associate with, a destination relates to their willingness.•The iterative process was explained by patterns of association and types of information source.
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. |
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ISSN: | 0148-2963 1873-7978 |
DOI: | 10.1016/j.jbusres.2019.10.014 |