FROM DATA TO DINE: INTEGRATING BIG DATA AND SURVEY INSIGHTS ON GEN Z PREFERENCES FOR MICHELIN-STARRED RESTAURANTS IN THAILAND

Abstract

This study aimed to explore the factors influencing customer satisfaction and visiting intention at Thailand's popular Michelin-starred restaurants, which have become a significant attraction for both locals and tourists. The findings offer valuable implications for the gastronomy industry. Initially, the study collected 11,887 Google Maps reviews of these restaurants and performed frequency and co-occurrence analyses using KH Coder, identifying four clusters: Time Risk, Value for Money, Food Quality, and Service & Ambiance. These clusters were then analyzed using Exploratory Factor Analysis (EFA) and linear regression with IBM SPSS 26 to assess their impact on customer satisfaction. The results revealed that Service & Ambiance, Value for Money, and Time Risk had a significant negative impact on customer satisfaction, whereas Food Quality demonstrated a significant positive effect. Furthermore, a survey was conducted with 291 Generation Z respondents to understand their attitudes and visiting intentions based on these clusters. The survey results indicated that Food Quality (β = 0.201, p < 0.001), Service & Ambiance (β = 0.331, p < 0.001), and Value for Money (β = 0.317, p < 0.007) positively influenced attitudes, which in turn (β = 0.802, p < 0.001) positively impacted visiting intentions. These findings offer crucial insights for the gastronomy industry, highlighting the paramount importance of Food Quality in driving customer satisfaction and shaping the dining preferences of Generation Z. The study suggests that Michelin-starred restaurants and similar establishments should prioritize enhancing food quality to maintain a competitive edge in the evolving culinary landscape.