Modeling and Forecasting the Tourism Demand for Iran Using ARIMA and Fuzzy Neural Networks Methods

Undoubtedly, any successful marketing strategy has roots in the correct market segmentation, and the tourism industry is not an exception. Although the ecotourism has become one of the major forms of the tourism industry; however, many properties of this important market has remained unknown in Iran. Given the gap between the current ecotourism market and the country’s potential,employment of correct strategies to develop ecotourism highly depends upon more understanding of the market segments. In this study, it was tried to understand the motivations of eco-tourists besides the segments in the issues of ecotourism to be identified. In this regard, adopting a two stage approach, the internal ecotourism market was segmented based on motivation, and the market properties were identified; then applicable proposals in the field of marketing, separated in clusters, were presented. Statistical population of the research comprises the internal eco-tourists visiting theAlamout region. Convenience sampling was used for choosing our respondents and a total of 246 valid questionnaires were analyzed. In the first stage, followed by cluster analysis based on motivation, three clusters were extracted: clusters of real eco-tourists, professionals and vacationers. Next, discriminant analysis was used to examine the inclination of individuals in the clusters towards eco-centric and anthropocentric dimensions. Overall, results of the discriminant analysis, with 95% of confidence, show that the membership of individuals in the cluster neither affects their inclinations towards the eco-centric nor anthropocentric dimensions. All the above statistical analyzes were performed using LISREL 8/72 and SPSS 19.