Global Events to Enhance Tourism: New Era for Marketing Through Location Analytics

Global Events to Enhance Tourism: New Era for Marketing Through Location Analytics

ISBN13: 9781668465912|ISBN10: 1668465914|ISBN13 Softcover: 9781668465929|EISBN13: 9781668465936
DOI: 10.4018/978-1-6684-6591-2.ch005
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MLA

Lakshmi Shree K., and Ashok Kumar R. "Global Events to Enhance Tourism: New Era for Marketing Through Location Analytics." Global Perspectives on the Strategic Role of Marketing Information Systems, edited by Jose Melchor Medina-Quintero, et al., IGI Global, 2023, pp. 66-86. https://doi.org/10.4018/978-1-6684-6591-2.ch005

APA

Lakshmi Shree K. & Ashok Kumar R. (2023). Global Events to Enhance Tourism: New Era for Marketing Through Location Analytics. In J. Medina-Quintero, M. Sahagun, J. Alfaro, & F. Ortiz-Rodriguez (Eds.), Global Perspectives on the Strategic Role of Marketing Information Systems (pp. 66-86). IGI Global. https://doi.org/10.4018/978-1-6684-6591-2.ch005

Chicago

Lakshmi Shree K., and Ashok Kumar R. "Global Events to Enhance Tourism: New Era for Marketing Through Location Analytics." In Global Perspectives on the Strategic Role of Marketing Information Systems, edited by Jose Melchor Medina-Quintero, et al., 66-86. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-6591-2.ch005

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Abstract

Targeting tourist behavior at global events could be one of the interesting topics for business houses. Location Based Analytical - Business Intelligent (LBA-BIntelligent) frameworks predict targeted tourist behavior at global events. The organizing countries create new businesses and gain a competitive advantage from tourists. This framework streamlines marketing to the right people at the right time. This study focuses on implementing bagging and boosting ensemble approaches. These classifiers have been evaluated on various parameters such as accuracy, precision, recall, F-score, Kappa score, and ROC-AUC score. The classification results show that the bagging approach gives better results through all the evaluation metrics.

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