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آیین نامه اجرایی قانون پیگیری و مقابله با تقلب در تهیه آثار علمی

Identifying factors affecting event tourism: bibliometric approach and artificial neural networks (ANN)

Document Type : Research Paper

Authors

1 Associated Professor, Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.

2 Ph.D Student, Marketing Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.

Abstract

This research is a part of qualitative and quantitative research in terms of practical purpose and terms of method. The analyses of the bibliometric section are related to the qualitative section and the neural network analyses are related to the quantitative section. The method of systematic bibliometric review was carried out with VOSviewer software and R programming language. Three main clusters were identified in the vocabulary co-occurrence analysis section, which include: (1) innovation in event tourism attractions (2) mental engagement towards event tourism destination attachment (3) event tourism experiences in social media. In the quantitative section, following the results of the TCM-ADO framework, neural network analyses were performed on the clusters to predict event tourism revisit intention. The results indicate that the variables of social media, experience, and tourist attractions, satisfaction, loyalty, attitudes, mental involvement and dependence on the place effect revisiting.

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References
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Tourism Management Studies
Volume 19, Issue 67
September 2024
Pages 117-160
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