Tourism management studies of the smart era

Tourism management studies of the smart era

Prioritizing Service Quality Indicators from the Perspective of Border Tourists Using an Intelligent Approach Based on the Pareto Principle

Document Type : Original Article- original research

Author
Assistant Professor, Department of Management and Economics, Faculty of Faculty of Humanities and Social Sciences, Golestan University, Gorgan, Iran.
10.22072/tmsse.2025.2068944.1038
Abstract
Identifying and prioritizing service quality indicators from the perspective of tourists -particularly in less-studied border destinations- can improve visitor experiences and increase their loyalty. This study, employing an intelligent approach based on the Pareto principle, analyzed the factors influencing the satisfaction of tourists at the Incheh-Borun border market, providing a scientific foundation for managing and enhancing the tourist experience. The research was conducted as a descriptive-applied, cross-sectional study. The statistical population included tourists visiting the Incheh-Borun border market; given the unlimited population, the sample size was determined using Cochran’s formula, and 384 tourists were selected through random sampling. Data were collected using a standardized questionnaire with a five-point Likert scale. In the first step, using the Pareto principle (80/20) and the Local Outlier Factor algorithm, tourists were divided into two groups: “vital minority” and “trivial majority.” Then, employing the Relief index, 34 service marketing mix indicators (P7 model) were weighted and ranked for each group. The results showed that within the vital minority group, appropriate public advertising in newspapers and across the city ranked highest in evaluating destination hospitality, whereas in the trivial majority group, drinking water facilities were prioritized. Accordingly, it is recommended that border tourism managers and stakeholders focus on improving the priority indicators identified for the vital minority group. The novelty of this study lies in simultaneously applying data mining techniques and marketing models to enhance intelligence in tourism destination management.
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Articles in Press, Accepted Manuscript
Available Online from 13 April 2026