Capturing unobserved heterogeneity in destination attribute evaluation and tourist satisfaction: A response-based segmentation using FIMIX-PLS

Author Bios (50 Words for each Author)

Hongbo Liu (hongbo.liu@temple.edu), is a Ph.D. candidate of Department of Tourism and Hospitality Management and Fox School of Business at Temple University. Her research interests include cross-cultural tourist behavior, destination marketing and social media marketing.

Abstract (150 Words)

Using recent Chinese outbound visitors to the U.S. as a case, this study applies the response-based segmentation method of FIMIX-PLS to capture unobserved heterogeneity among tourists based on the relationship between destination attribute evaluations, overall tourist satisfaction, and tourists’ revisit intention. The results of the initial overall PLS-PM model show that food and beverage, commercial guided tours, telecommunication service, and tourist attractions had a significant positive impact on tourists’ overall satisfaction. The subsequent FIMIX-PLS analysis supports the classification of respondents into three separate segments, which exhibit distinctive path estimates. This study contributes to the tourism literature by uncovering unobserved heterogeneity in PLS-PM, as well as generating useful insights for destination marketers in market segmentation.

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Capturing unobserved heterogeneity in destination attribute evaluation and tourist satisfaction: A response-based segmentation using FIMIX-PLS

Using recent Chinese outbound visitors to the U.S. as a case, this study applies the response-based segmentation method of FIMIX-PLS to capture unobserved heterogeneity among tourists based on the relationship between destination attribute evaluations, overall tourist satisfaction, and tourists’ revisit intention. The results of the initial overall PLS-PM model show that food and beverage, commercial guided tours, telecommunication service, and tourist attractions had a significant positive impact on tourists’ overall satisfaction. The subsequent FIMIX-PLS analysis supports the classification of respondents into three separate segments, which exhibit distinctive path estimates. This study contributes to the tourism literature by uncovering unobserved heterogeneity in PLS-PM, as well as generating useful insights for destination marketers in market segmentation.