Visitors' Spending on Accommodation: A Segmentation Model using Two-Step CHAID Analysis

Abstract

Tourism receipt through visitors' spending is one of the contributors that stimulate the local economy. Therefore, it is crucial to determine the factors influencing these spending preferences. This study determines factors and average spending on accommodations using segmentation techniques for Perhentian Island's visitors. Determinant factors include demographic, trip-related, and psychographic characteristics. Data were collected through a survey and run for 929 visitors using two-step Chi-Square Automatic Interaction Detection (CHAID) analysis. The analysis produces a three-level regression tree and later a classification tree. The findings documented that, level 1 consisted of four segments and were segmented according to the country of origin (COO). Overall, the Italian is a segment that has the highest average spending. The fourth segment of level 1, namely Malaysia, branched out further to level 2 and level 3. These levels were segmented based on the number of dependents during the trip and length of stay, respectively. For domestic visitors, Malaysian with dependents on the trip spend the highest. Based on the results, recommendations for the Perhentian Islands accommodation operator were to provide infrastructure to accommodate families for domestic market and marketing strategy that target Italians for the international market. The results could also assist local authorities outlining tourism planning.