Asymmetric relationship between customer sentiment and online hotel ratings: the moderating effects of review characteristics

Purpose Despite a significant focus on customer evaluation and sentiment analysis, limited attention has been paid to discrete emotional perspective in terms of the emotionality used in text. This paper aims to extend the general-sentiment dictionary in Chinese to a restaurant-domain-specific dictionary, visualize spatiotemporal sentiment trends, identify the main discrete emotions that affect customers’ ratings in a restaurant setting and identify constituents of influential emotions. Design/methodology/approach A total of 683,610 online restaurant reviews downloaded from Dianping.com were analyzed by a sentiment dictionary optimized by the authors; the main emotions (joy, love, trust, anger, sadness and surprise) that affect online ratings were explored by using multiple linear regression methods. After tracking these sentiment review texts, Latent Dirichlet Allocation (LDA) and LDA models with term frequency-inverse document frequency as weights were used to find the factors that constitute influential emotions. Findings The results show that it is viable to optimize or expand sentiment dictionary by word similarity. The findings highlight that love and anger have the highest effect on online ratings. The main factors that constitute consumers’ anger (local characteristics, incorrect food portions and unobtrusive location) and love (comfortable dining atmosphere, obvious local characteristics and complete supporting services) are identified. Different from previous studies, negativity bias is not observed, which poses a question of whether it has to do with Chinese culture. Practical implications These findings can help managers monitor the true quality of restaurant service in an area on time. Based on the results, restaurant operators can better decide which aspects they should pay more attention to; platforms can operate better and can have more manageable webpage settings; and consumers can easily capture the quality of restaurants to make better purchase decisions. Originality/value This study builds upon the existing general sentiment dictionary in Chinese and, to the best of the authors’ knowledge, is the first to provide a restaurant-domain-specific sentiment dictionary and use it for analysis. It also reveals the constituents of two prominent emotions (love and anger) in the case of restaurant reviews.

Section: Discussioncontrasting

confidence: 99%

What affects the online ratings of restaurant consumers: a research perspective on text-mining big data analysis

Mehraliyev

et al. 2022

“…More specifically, this study focused on quantitative characteristics of user review ratings (i.e. review valence, volume and variance) and did not take into account users’ qualitative (textual) feedback, which has been shown to have a significant effect on hotel ratings (Lai et al , 2021). Future research may extend this study’s model by conducting a sentiment analysis of the qualitative reviews and incorporating this into the model.…”

Section: Discussionmentioning

confidence: 99%

User-generated reviews and the financial performance of restaurants

Abdullah

Cauwenberge

Bauwhede

et al. 2022

Purpose This paper aims to examine the impact of selected characteristics (rating, volume and variability) of online user-generated reviews on the bottom-line profitability of restaurants. Design/methodology/approach Restaurant-level review data are extracted from TripAdvisor and matched with firm-level data from the financial reports gathered from the Belfirst database of Bureau van Dijk. The resulting sample contains data on 2,297 Belgian firms over the period 2007–2018, for which 134,831 reviews are investigated. The author’s regression model of firm-level profitability is estimated against online review characteristics and various financial control variables, including past profitability. This research model and estimation technique address the endogeneity concerns that typically weaken this kind of study. Findings While comparable studies on hotels document a positive association between review characteristics and profitability, the authors find no relationship between review rating, volume and variability in the profitability of restaurants. Research limitations/implications Due to the format of the financial reports of small and medium-sized enterprises (SMEs), data on turnover and cost of materials/services was not available for most restaurants in the sample, limiting our potential for analysis. In addition, our assessment of electronic word of mouth (eWOM) was limited to measures derived from user-generated reviews on TripAdvisor. Practical implications In the literature on eWOM, the importance of online reputation is hardly disputed, especially in the context of the hospitality sector. However, most research to date has focused on the hotel sector and top-line measures of success. This study uses restaurant-level financial data, focuses on bottom-line profitability, considers potential endogeneity issues and pays careful attention to the estimation technique. The results fail to establish a direct relationship between eWOM metrics and financial performance and are surprising, meriting further investigation to establish the underlying causes. Originality/value In contrast to prior studies on the impact of eWOM on restaurant performance at a group level, this study examines the impact on unit-level profitability, taking into account several potential sources of estimation bias. In addition, the authors challenge this finding with a battery of sensitivity tests, revalidating the absence of a relationship in each case.

“…Tourism quality certificates can reduce the information asymmetry inherent in the uncertainty associated with the selection process among the existing hotel supply (Yang et al , 2016; Lai et al , 2021). Nevertheless, the development of new technologies and the use of the Internet as a means for searching and purchasing have popularized other quality signal alternatives to these certifications.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Although each individual review may have low reliability in the eyes of the user when the volume of reviews is high, the perceived reliability of the set of reviews will be high (Sparks and Browning, 2011; Filieri et al , 2020). In this regard, the literature has found a positive effect of the number of reviews on sales (Lai et al , 2021), booking intentions (Wu et al , 2020) and online search behavior (Ayeh et al , 2013). In sum, the power of the signal will be greater when the number of published reviews about a hotel is higher (Hernández-Maestro, 2020).…”

Section: Hypothesismentioning

confidence: 99%

“…Other studies analyze the connection between quality certification and other factors, such as hotel size, location, hotel performance and competitiveness (Mellinas et al, 2019;Hern andez-Perines et al, 2019). Tourism quality certificates can reduce the information asymmetry inherent in the uncertainty associated with the selection process among the existing hotel supply (Yang et al, 2016;Lai et al, 2021). Nevertheless, the development of new technologies and the use of the Internet as a means for searching and purchasing have popularized other quality signal alternatives to these certifications.…”

Section: Quality Certifications and Standards As Quality Signalsmentioning

confidence: 99%

See 1 more Smart Citation

Quality certifications in the TripAdvisor era. Are they outdated?

Fernández-Pacheco¹,

Argüelles

Ballina

2022

Purpose This study aims to analyzes the effects of the consumer-generated media (CGM) boom on hotel managers’ investment behavior concerning quality signals. Design/methodology/approach Survival analysis has been conducted, considering the permanence/dropout of the Spanish hotels in a quality certification system during the 1998–2020 period. Findings The number of hotels certified since 2010 has been progressively falling, pointing to a decreasing interest of the managers in these certifications. Nevertheless, this is not a generalized phenomenon: the hotel characteristics and the number and nature of reviews about them in CGM significantly affect their permanence decisions in certification systems. Practical implications The findings provide several keys to optimizing investment management in quality signals considering hotel characteristics and their positioning in CGM. Originality/value To the best of the authors’ knowledge, this is the first study that analyses the relationship between the presence of hotels in CGM and their investments in alternative quality signals. The results will allow future investment decisions based on previous real business experiences.