Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks

Tomasz Korol () and Anestis Fotiadis ()
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Tomasz Korol: Faculty of Management and Economics, Gdansk University of Technology, Gdansk, Poland
Anestis Fotiadis: Entertainment Management Department, International College, I-Shou University, Kaohsiung, Taiwan

International Journal of Information Technology & Decision Making (IJITDM), 2016, vol. 15, issue 06, 1451-1468

Abstract: This study analyzes two forecasting models based on the application of fuzzy logic and evaluates their effectiveness in predicting visitor expenditure and length of stay at a popular theme park. The forecasting models are based on a set of more than 600 decision rules constructed in the form of a complex series of IF-THEN statements. These algorithms store expert knowledge. A descriptive instrument that records the individual visitor’s time spent and expenditure distribution on activities in the E-Da World in Taiwan was used to gather data. From a process of rigorous verification, the models developed are characterized by a high level of accuracy and efficiency.

Keywords: Fuzzy logic; forecasting; theme park; customer behavior; visitor expenditure; tourism management (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1142/S0219622016500425

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