a data mining approach for evaluating the tourist destination loyalty
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ID: 201585
2016
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Abstract
The aim of this study is to evaluate the tourist loyalty through data mining
approach. The study has exemined 880 domestic tourists who have stayed in
more than one night in four and five star hotels of Isfahan in spring and summer
2014 and 2015. SPSS and Clementine12 was used for data analysis.Also,
Mixture Algorithm PSO-KM was applied for tourism clustering.The results
showed that tourists can be classified in two categories. The first category have
a high average in length of communication with tourism and travel recency and
the cost and frequency of travel are less than average. Therefore, the customers
are loyal and uncertain. The second category has a high average in travel
recency and the length of communication with tourism, cost and frequency of
travel is less than average. Therefore the customers are new and uncertain.
| Reference Key |
2016mulit-ia
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| Authors | ;ali asadi ;Azarnoush Ansari |
| Journal | bulletin of the malaysian mathematical sciences society |
| Year | 2016 |
| DOI |
10.22054/TMS.2017.7081
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| URL | |
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