关键词: 中国文化, 酒店顾客情感, 在线评论, 文本分析

Abstract: The hotel industry in China has suffered immensely due to the COVID-19 pandemic on top of some traditional challenges, including guest expectations for altered values, surging costs, fierce competition with international rivals and market share lost to peer-to-peer accommodation rentals. While many are struggling to keep their businesses afloat, the industry is witnessing a wave of culture-themed properties being launched across the country amidst market uncertainties. Therefore, it is quite necessary to carry out research in order to measure the effects of cultural offerings on customer sentiment, aiming to find out whether incorporating Chinese culture in the portfolio of hotel offerings could serve as a solution to achieving greater efficiency at less cost for the upcoming post-epidemic era, replacing the traditional asset-heavy approach which has been wide applied in the industry but is beyond the affordability of many a pandemic-stricken Chinese hotels, so that hoteliers can make better-informed decisions on strategic adjustments in their operations in the post-epidemic era. To serve the purpose, this study focuses on two research questions: (1)Do Chinese hotels' cultural offerings significantly enhance the positive sentiment of domestic and international guests? If so, what can be the correlation between the two?(2)What other attributes of hotel service also affect guest sentiment?
We conduct text analytics of online reviews from Chinese hotels' guests from both home and abroad markets, which are collected from TripAdvisor, the most visited travel and tourism website worldwide applying strict supervision on its guest review mechanism. Based on the widely applied topic model LDA, which has been proven highly efficient in extracting dimensions from a large corpus of text customer reviews, the method of manual annotation-aided LDA is established to obtain from the positive and negative online guest reviews the hotel service attributes that affect guest sentiment, with Chinese culture as our most concerned target attribute. Then a Logit regression is carried out, resulting in an econometric model with the correlation between Chinese culture, along with other Chinese hotel offerings, and the sentiment of domestic and international guests.
The findings of our research are as follows: (1)Our research results in an econometric model of guest sentiment for both domestic and international markets. Chinese culture as an attribute of Chinese hotel offerings is found to significantly contribute to the positive sentiment of both domestic and international guests. (2)Besides cultural offerings, other attributes that positively affect guest sentiment are found to be location, food and staff service. (3)A higher correlation is also proved between Chinese culture and positive guest sentiment than the correlation between Chinese hotels' other attributes and guest sentiment. (4)The quality of rooms and value for money are found to negatively affect guest sentiment.
Our research findings reveal the significant positive correlation between Chinese hotels' cultural offerings and guest sentiment, which can serve as empirical evidence for the effectiveness of some Chinese hotels' experimental practice in tapping into the potential of traditional culture as a solution to achieving greater efficiency at less cost. The novelty of our research lies in our following contributions: (1)We first introduce cultural offerings as an independent variable into the model for the measurement of hotel guest sentiment and suggest the significant positive correlation between the two. Our findings are expected to offer insights for hoteliers eager for an optimized portfolio of offerings that can enhance their guests' positive sentiment. (2)We extend the guest sentiment management literature by developing a model with cultural offerings incorporated respectively for the domestic market and the international markets with cultural offerings. Our research is intended to enrich existing literature that help Chinese hoteliers to evaluate the role of cultural offerings as part of their service portfolio and assist in decisions on optimized fine management.

Key words: Chinese culture, hotel guest sentiment, online reviews, text analytics