The recent trend in tourism marketing is focus on customer relationship management. Tourism industry today is one of the highest revenue generating industry and strategic approach for sustainable development of this i...The recent trend in tourism marketing is focus on customer relationship management. Tourism industry today is one of the highest revenue generating industry and strategic approach for sustainable development of this industry hosts benefits not only for the tourism related stakeholders but also the community and economy on the whole. Oman is one of the most preferred destinations for the tourists especially after the declaration of Muscat, Arab tourism Capital for 2012. Thus to materialize this honor and position, the scientific study and analysis of tourist behavior will help to predict the future trend of tourism and will give direction for effort investment. This work presents a novel strategy to identify, analyze and highlights the main tourist behavioral factors that could increase tourists＇ loyalty to a specific destination or agency. The analytical TSS （tourism support system） will also classify customers into two categories--first category will be classified as ＂LT （loyal tourists）＂ and second category as ＂NLT （non-loyal tourists）＂. Dataset is collected from a tourism business organization. Twenty-four attributes and 545 instances were collected and were analyzed by algorithms like logistics, forest of random trees, naive Bayes, J48 and Id3. The explanatory variables were defined, and some transformations were done to identify the response variable. Entropy was used and adapted in order to find the response variable from the explanatory variables. The results obtained from this work confirm that the generated rules can be used for future prediction and tourism business can be improved and efforts can be directed in right place for the right consumer resulting in high return on investment.展开更多
文摘The recent trend in tourism marketing is focus on customer relationship management. Tourism industry today is one of the highest revenue generating industry and strategic approach for sustainable development of this industry hosts benefits not only for the tourism related stakeholders but also the community and economy on the whole. Oman is one of the most preferred destinations for the tourists especially after the declaration of Muscat, Arab tourism Capital for 2012. Thus to materialize this honor and position, the scientific study and analysis of tourist behavior will help to predict the future trend of tourism and will give direction for effort investment. This work presents a novel strategy to identify, analyze and highlights the main tourist behavioral factors that could increase tourists＇ loyalty to a specific destination or agency. The analytical TSS （tourism support system） will also classify customers into two categories--first category will be classified as ＂LT （loyal tourists）＂ and second category as ＂NLT （non-loyal tourists）＂. Dataset is collected from a tourism business organization. Twenty-four attributes and 545 instances were collected and were analyzed by algorithms like logistics, forest of random trees, naive Bayes, J48 and Id3. The explanatory variables were defined, and some transformations were done to identify the response variable. Entropy was used and adapted in order to find the response variable from the explanatory variables. The results obtained from this work confirm that the generated rules can be used for future prediction and tourism business can be improved and efforts can be directed in right place for the right consumer resulting in high return on investment.
