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  • All fields: Visiting
(169 results)



Display: 20

    • Page 111

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    • 101 Chapter V Article II: Influencing Destination Image and Visiting Intent Using Communication Mix: A Case Study of Austria Abstract Identifying the factors that influence destination image and visiting intentions helps tourism planners...
    • Page 113

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    • 103 Exploratory research was conducted to identify and measure the relationships between information sources, socio-cultural preferences, and travel motives on destination image and visiting intentions. An adaptation of the study conducted...
    • Page 117

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    • 107 Research Methodology Research design. The research methodology was multi-phased, with the initial phase being a pilot study of the survey instrument, followed by structural equation analysis of the final survey data. The objective of this...
    • Page 123

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    • 113 variables. Standardized parameter estimates are normalized unstandardized parameter estimates that allow parameters throughout the model to be compared and thus are more functional (Hoyle, 1995). When results are interpreted, unstandardized...
    • Page 124

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    • 114 validity constitute construct validity. Construct validity refers to the extent to which an operationalization measures the factor it is supposed to measure (Bagozzi, Yi, & Phillips, 1991). Convergent validity has been defined as the extent to...
    • Page 22

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    • 12 for nor be able to produce (Bolan & Williams, 2008). Movies can showcase a destination‘s natural scenery, historical background, and culture. Austria is not exempt from this phenomenon. Since the release of The Sound of Music in 1965, many...
    • Page 131

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    • 121 Preliminary SEM Data Analysis The Confirmatory Factor Analysis (CFA) model specified one second-order factor: information sources (IS), as well as four first-order factors: destination image (DI); socio-cultural preferences (SCP); travel...
    • Page 132

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    • 122 critical value of 0.7 suggested by Nunnally and Bernstein (1978; 1994). All other constructs exceeded the critical value. Measurement theory suggested that the relationships among items were logically connected to the relationships of items to...
    • Page 133

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    • 123 ----------------------- Insert Table 12 Here ----------------------- SEM Data Analysis Structural equation modeling (SEM) was used to examine the hypothesized relationships among the constructs in the study. The hypothesized models were...
    • Page 134

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    • 124 modification process. Examination of skewness and kurtosis (univariate and multivariate) indicated that maximum likelihood estimation was appropriate for this study. The correlations among the indicators of nine constructs were all...
    • Page 135

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    • 125 ----------------------- Insert Table 13 Here ----------------------- Structural Model Results To examine the goodness-of-fit of the hypothesized model, the measurement model was re-specified by imposing the structure of each model (see Figure...
    • Page 136

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    • 126 model in the appendix assured that the model fit the data well: no evidence of improper solutions was found, all measurement parameters were statistically significant, the confirmatory factor loadings were of relatively large size, and the...
    • Page 137

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    • 127 The analysis results did not support the proposed effect of information sources on destination image (hypothesis 2) and the proposed effect of information sources on visiting intention (hypothesis 3). Although the results of these two...
    • Page 139

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    • 129 Hypothesis 3: Information sources have a positive effect on visiting intention Hypothesis 3 predicted that information sources would positively affect visiting intention, but this result was not supported. With positive influence of...
    • Page 140

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    • 130 Hypothesis 6 predicted that travel motive has a positive effect on visiting intention and was supported with a coefficient of 0.138; supporting results of the previous study conducted by McCartney, Butler and Bennett (2008). A strong...
    • Page 142

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    • 132 tourism authorities may need only to ensure that relevant information reaches the specified target audience. Hypothesis 3 predicted that information sources would positively affect visiting intention and was also not supported by this study....
    • Page 143

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    • 133 Hypothesis 5 predicted that travel motive has a positive effect on destination image and was supported with a coefficient of 0.118. When prospective visitors have high travel motivation, they tend to have strong destination image of Austria....
    • Page 144

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    • 134 Since a primary goal of destination marketers is to attract new visitors, this strong destination image of Austria for socio-cultural tourism can be used to increase the visiting intention of travelers. Cities such as Salzburg and Vienna appeal...
    • Page 145

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    • 135 Perhaps the most important implications of this study are the findings of the structural equation analysis. Results of the structural equation modeling analysis showed that information sources have a positive effect on travel motive....

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