Developing a service quality model for Chiang Mai Chinese restaurant

Abstract

With attractions like ancient temples, scenic natural landscapes and local culture, Chiang Mai is deeply beloved by Chinese visitors. However, the booming Chinese tourism in Chiang Mai also poses new challenges for local businesses to better serve the massive influx of Chinese tourists. As Chinese restaurants are pivotal for Chinese travellers during their visit, issues related to their dining services deserve attention to improve customer satisfaction. This study analyzes customer reviews of Chiang Mai Chinese restaurants on Dianping, aiming to identify service issues from the perspective of Chinese tourists. This study aims to identify specific service issues in Chinese restaurants serving Chinese tourists in Chiang Mai, Thailand. The study first uses python to mine the reviews of Chiang Mai Chinese restaurants on Dianping.com, and then uses sentiment analysis software (weiciyun) to conduct a comprehensive analysis of the top 10 and bottom 10 reviews of Chiang Mai Chinese restaurants. The comprehensive analysis is mainly based on technologies such as text pre-processing, multi-rule joint matching, and machine deep learning to build an accurate and efficient Chinese word segmentation system. It effectively solves the main problems in Chinese word segmentation and greatly improves the quality of word segmentation by making full use of internal vocabulary and contextual information. Reviews are coded in terms of responsiveness, reliability, assurance, empathy and tangibility against relevant service quality criteria. The analysis showed that the most common service issues mentioned in reviews included Environmental and hygiene issues, Food quality issues, and Chinese service issues. The study recommends that Chinese restaurants in Chiang Mai improve these aspects to increase Chinese tourists' satisfaction. The results of this study can also provide a reference for service improvement for Chinese restaurants in Thailand and other Southeast Asian tourist countries when serving Chinese tourists.