Customer purchase forecasting for online tourism: A data-driven method with multiplex behavior data
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Elservier
Abstract
Online tourism has received increasing attention from scholars and practitioners due to its growing contribution
to the economy. While related issues have been studied, research on forecasting customer purchases and the
influence of forecasting variables, online tourism is still in its infancy. Therefore, this paper aims to develop a
data-driven method to achieve two objectives: (1) provide an accurate purchase forecasting model for online
tourism and (2) analyze the influence of behavior variables as predictors of online tourism purchases. Based on
the real-world multiplex behavior data, the proposed method can predict online tourism purchases accurately by
machine learning algorithms. As for the practical implications, the influence of behavior variables is ranked
according to the predictive marginal value, and how these important variables affect the final purchase is disĀ
cussed with the help of partial dependence plots. This research contributes to the purchase forecasting literature
and has significant practical implications.
Description
Tourism Management 87 (2021) 104357
Keywords
Online tourism purchase forecasting,Behavior data analysis,Machine learning,Result interpretation