The concept of the new tourism destinations: an exploration of satisfaction and dissatisfaction factors through visitors’ reviews
Alireza Ranjbaran*, Mohammadjavad Shabankareh**, Nader Seyyedamiri***, Gholamreza Jandaghi****
Faculty of Management, University of Tehran, Tehran, Iran* Faculty of Management, University of Tehran, Tehran, Iran** University of Tehran, Tehran, Iran*** Faculty of Management, Farabi College, University of Tehran, Qom, Iran****
Abstract: In the last decade, one of the fastest growing industries in the world has been the tourism industry which has been developed in the various types. This study aims to define a new concept called "new tourism destination "in the tourism industry, and investigate the factors of satisfaction and dissatisfaction in these destinations. The data of this study consisted of 15561 positive and negative Travelers’ reviews collected from the new tourism destinations page on the TripAdvisor travel platform. Then, the Latent Sentiment Analysis (LSA) method was employed to analyse the data to explore and rank Satisfaction and dissatisfaction determinants in four most popular new destinations including suspended bridges, water parks, shopping malls and towers. Our findings revealed satisfaction and dissatisfaction factors among new tourism destinations are different. Interestingly, results indicate that in adventurous destinations, satisfaction and dissatisfaction factors are related to safety, view and cleanliness, while in non-adventurous destinations, factors are related to staff attributes, diversity and food quality. This study contributes to the existing literature and knowledge on the tourism destinations by providing a new definition in the tourism industry as ‘new tourism destinations’. Also, by analysing tourists' opinions about the new tourism destinations, this study provides a deep insight for the managers of tourism destinations and offers practical suggestions.
Keywords: New Tourism Destinations, Traveler Satisfaction, Traveler dissatisfaction, Online Reviews, Text Mining
