• Journal of Global Scholars of Marketing Science
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• v.15 no.3
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• pp.149-168
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• 2005

The purpose of this paper is to study the impact of brand personality on the choice of tour site. For this purpose, Japanese, Chinese and Korean tourists visiting Jeju-Ireland were sampled and asked to evaluate the personality dimensions and attributes of six major tour sites in Asia. Factor analysis is applied to 42 personality scales of Aaker and 5 personality dimensions are extracted. Then, Multinomial Logit model is applied to estimate the relative impact of personality dimensions and attributes on the choice of tour sites. Results suggest useful implications. The personality of tour sites has meaningful influence on choice of tour sites, in some cases more important than tour site attributes. Among 5 dimensions of personality, sincerity and excitement are found to be important dimensions in the choice process of tour site. Sophistication of the site, expressed as glamorous, charming, handsomeness, uniqueness, and smooth, is also found to be important in determining intention to visit in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.