Forecasting the success of a new tourism service by a neuro-fuzzy technique

George S. Atsalakis, Ioanna G. Atsalaki and Constantin Zopounidis

European Journal of Operational Research, 2018, vol. 268, issue 2, 716-727

Abstract: This paper presents a novel approach to forecasting the success of a newly launched service in tourism by using a hybrid intelligence system called the Adaptive Neuro Fuzzy Inference System (ANFIS). Recent studies have addressed the problem of modeling the success of a newly launched service by using different methods including artificial intelligence and model-based approaches. The ANFIS combines both the learning capabilities of a neural network and the reasoning capabilities of fuzzy logic to give enhanced forecasting capabilities, as compared to using a single methodology alone. Data collected through a questionnaire that concerns the variables of developing a new service in tourism have been used as inputs to the model. A new technique that is achieved by using a method that cycles through all the inputs and builds ANFIS models has been used for input reduction and input selection. The final model has been trained by leaving out a part of the data. The model was then evaluated by the data that were left out. The forecasting accuracy of the ANFIS model is evaluated by calculating well-known performance measures. The results have shown that ANFIS provides a prudent way to capture uncertainty in relationships among input variables and output variables to forecast the successful launch of a new tourism service. A comparative analysis with other methodologies confirms the superiority of the proposed approach.

Keywords: Fuzzy sets; Artificial intelligence; Neuro-fuzzy systems; Tourism service forecasting; ANFIS (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:268:y:2018:i:2:p:716-727

DOI: 10.1016/j.ejor.2018.01.044

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