Saeed Maleki; Hadi Alizadeh; Mohammad Javad Kamelifar
Abstract
The present study has been performed to assess the urban tourism sustainable drivers in Ahvaz city using the descriptive-analytical methodology. Regarding the main object of the study, two secondary objectives of recognizing the priority of using tourism sustainability drivers and recognizing the impact ...
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The present study has been performed to assess the urban tourism sustainable drivers in Ahvaz city using the descriptive-analytical methodology. Regarding the main object of the study, two secondary objectives of recognizing the priority of using tourism sustainability drivers and recognizing the impact of drivers on the sustainability of urban tourism in Ahvaz have been followed in the research process. For data collection by surveying methods, the opinions of 30 experts related to the field of research have been gathered using a questionnaire. To analyze the priority of drivers, Multilayer Perceptron Neural Network (MPNN) approach, and to analyze the effects of drivers on the sustainability process of urban tourism in Ahvaz, linear regression analysis (R-Linear), logarithmic (R-Logarithmic) and logistics (R-Logistic) has been used. The results show that according to the results of regression models, except for economic and social sustainability drivers, other drivers do not affect the sustainability process of Ahvaz urban tourism. On the other hand, the results of the neural network approach indicate that political sustainability driver, based on the opinion of experts with a significance of 0.235, has a higher priority to improve conditions and create conditions for sustainability in urban tourism in Ahvaz.
shirin mahdavi; Mostafa Emadzadeh; azarnoush ansari
Abstract
The identification of tourism market segments helps to better develop travel packages and more efficient strategies. By identifying the expected values derived from the behavioral patterns and comparing them with the behavioral interests of the travel of elderly people, along with individual characteristics, ...
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The identification of tourism market segments helps to better develop travel packages and more efficient strategies. By identifying the expected values derived from the behavioral patterns and comparing them with the behavioral interests of the travel of elderly people, along with individual characteristics, the market for elderly tourists can be segmented and predicted. In terms of the purposes, this is an applied research and in terms of the data collection method, this is descriptive-survey. The qualitative approach and the Delphi method has been used to identify the expected values and, to predict market groups, a quantitative approach using neural networks has been used. This research has been conducted among 380 Esfahani and Tehrani elderly tourists using non-random and available sampling method. The results show that values are due to individual and personality traits, travel motives, travel experiences, travel style, and travel pleasure. The market for elderly tourists was identified and predicted based on the expected values, with the neural network technique in three conservative, prosperous and younger groups.
