Applying a Decision-making Technique to Evaluate ‎the Key Factors Affecting Customer Churn Using a ‎Text-mining Approach: A Case Study in the Hotel ‎Industry

الموضوعات :

Leila Taherkhani ¹ (Department of Information Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Amir Daneshvar ² (Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran)
hossein Amoozad-khalili ³ (: Department of Industrial Engineering, Sari Branch, Islamic Azad University, Sari, Iran.)
MohamadReza Sanaei ⁴ (Department of Information Technology Management, College of Management and Economics, Qazvin Branch, Islamic Azad University, Qazvin, Iran)

تاريخ الإرسال : 15 الأربعاء , محرم, 1445 تاريخ التأكيد : 03 الإثنين , ربيع الأول, 1445 تاريخ الإصدار : 16 الجمعة , صفر, 1445

الکلمات المفتاحية: Customer churn, Hotel Industry, Text Mining, Analytic Hierarchical Processing,

ملخص المقالة :

Customer churn is a critical challenge faced by the hotel industry, impacting revenue and profitability. Identifying and prioritizing the factors that contribute to customer churn is essential for hotel managers to devise effective retention strategies. The prioritization of these factors enables hotel managers to allocate resources efficiently towards implementing targeted retention initiatives. By understanding the factors that influence customer churn, hotels can proactively tailor their services and improve customer experiences to enhance loyalty and reduce churn rates. This study aims to determine and prioritize the key factors influencing customer churn in the hotel industry. The data is analyzed using advanced text mining techniques, including tokenizing, stemming, and eliminating stop words, to identify the significant factors affecting customer churn. The findings highlight factors such as room conditions, the beauty of the hotel, food quality, staff interactions, hotel hygiene, restrooms, and proximity to important centers. To prioritize these factors, we utilized the AHP technique in Expert Choice software. According to the findings, among these factors, staff interaction with 32%, room conditions with 22%, restrooms with 19%, food quality with 12%, proximity to important centers with 8%, hotel hygiene with 4%, and beauty of the hotel with 3%are respectively the most important factors affecting customer churn.

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