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This paper aims to investigate the impact of perceived usefulness of online reviews and crowd cues on restaurant selection. In addition, the authors also examine the moderating role of perceived crowding and gender in this process.

The proposed hypotheses were tested with survey data (N = 200) collected from customers visiting full-service restaurants in Malaysia. The data were analyzed using SEM through Smart PLS.

The findings supported that the perceived usefulness of online reviews and perceived crowding have a positive effect on a consumer's purchase intentions, i.e. their decision of restaurant selection. Besides, a higher level of perceived crowding strengthens the relationship between the perceived usefulness of online reviews and their purchase intentions. This finding delineates that consumers prefer to dine in a crowded place with useful online reviews in an unfamiliar place. Finally, the results show that the effect of the usefulness of online reviews on purchase intentions does not vary with respect to gender (no significant contingent effect). However, the effect of perceived crowding varies with respect to gender – male customers have higher intentions to join crowded restaurants as compared to females.

Limitation of this study is its cross-sectional research design; data were collected in a single time frame. Longitudinal research design can be used to get in-depth knowledge of this phenomenon. Secondly, a non-probability sampling technique was used in this study, future research can used probability sampling technique to enhance generalizability of the study. Moreover, this study focused on the human crowding aspect, future studies can cover both aspects of crowding (human crowding and spatial crowding) in retailing or other service sectors (Blut and Iyer, 2020).

This study has multiple practical implications.

This study extends the current research on usefulness of online reviews and perceived crowding by investigating its direct and conditional effects. Specifically, the authors contribute in extant research by explaining its differential effects for male and female customers, when they select which restaurants to dine.

Prior hospitality studies have reviewed review trustworthiness and perceived price as predictors of restaurant selection. However, the impacts of these two factors may vary by sales promotion and customer types. This study aims to determine whether sales promotions and customer type are the key elements that facilitate behavioral intentions by moderating the linkage between perceived price and behavioral intentions as well as the linkage between online review trustworthiness and behavioral intentions.

Analysis of the responses of 533 individuals familiar with the Michelin Guide for restaurants in Seoul provided evidence supporting a sales promotion theory wherein promotions signal benefits in consumers’ minds.

The findings show that when perceived price is positive and the trustworthiness of online reviews is high, repeat customers prefer mixed coupons to price discounts. Notably, the results indicate that when the trustworthiness of online reviews is high, first-time customers also prefer mixed coupons to price discounts. Furthermore, the findings suggest that negative evaluations of perceived price increase the impact of mixed coupons by signaling to first-time customers that given restaurants’ offerings provide monetary benefits regardless of their intentions to revisit said restaurants.

The study findings provide insights that should help managers better understand various levels of promotion. Managers can design their pricing strategies to strengthen customers’ motivations to visit their restaurants – the very thing customers often seek in sales promotions.

This study provides indisputable evidence for a sales promotion theory, wherein promotions signal benefits in consumers’ minds; however, it also shows that first-time and repeat customers do not respond equally to sales promotions.

This study aims to investigate how prior reviews posted by other consumers affect subsequent consumers’ evaluations and to what extent the review temporal distance can increase or reduce the social influence of prior reviews. In this study’s restaurant context, review temporal distance refers to the duration between dining time and review time of a dining experience.

The data of paired online restaurant reservations and reviews are analyzed using Ordered Logit Model. Two robustness checks are conducted to test the stability of the main estimation results.

The empirical results demonstrate that consumers’ restaurant evaluation is socially influenced by both the prior average review rating and number of prior reviews; review temporal distance has a direct negative effect on consumers’ restaurant evaluation; and review temporal distance increases the social influence of prior reviews.

This study suggests that online review matters. Both restaurants and the online review platforms should encourage consumers to share their experiences and post online reviews immediately after their consumption.

The study contributes to the literature on electronic word-of-mouth, social influence and psychological distance. First, the bi-directional nature of social influence on electronic word-of-mouth for experience-oriented product is documented. Second, for the first time, this study examines how review temporal distance could affect the social influence on consumers’ restaurant evaluation.

Building on a small body of work, the authors' study aims to investigate some important antecedents of online review characteristics in the Chinese restaurant industry.

Using a data set of restaurant reviews collected from a most popular review platform in China, the authors conduct a series of analyses to examine the influence of travel experience and travel distance on travelers' review characteristics in terms of review rating and media richness. The moderating effect of restaurant price on the influence is also investigated.

Travelers with a longer travel distance and more travel experience tend to provide higher and lower online ratings, respectively, which can be explained by the construal level theory (CLT) and the expectation-confirmation theory (ECT), respectively. Furthermore, these strong feelings can then induce travelers to post enriched reviews with more pictures, more words and more affective words to release consumption tension. Besides, restaurant price can moderate these relationships.

Distinguished from most studies which mainly focus on the consequences of online review characteristics or antecedents of review helpfulness, the authors pay attention to the effects of travelers' individual differences in terms of travel distance and travel experience on travelers' online reviewing behavior. In addition to review rating, the authors also focus on media richness in terms of visual and textual information. The authors' research findings can benefit restaurant consumers and managers for their online word-of-mouth utilization and management.

The purpose of this study is to investigate the effect of online reviews on consumers’ intention to visit restaurants, with the moderating role of involvement.

The research framework was built on signaling theory, message appeals and involvement theory. To test the proposed framework, three experiments were conducted online with real customer samples. T-tests, ANOVA and SPSS PROCESS macro were used for data analysis.

The results revealed that online reviews with higher online ratings and emotional appeal led to higher restaurant visit intention. Review appeal significantly moderated the effect of online ratings on restaurant visit intention. Customers with low restaurant involvement were more impacted by emotional comments than by functional comments.

The present study extends our knowledge on the effects of online reviews moderated by levels of customer involvement. By combining signaling theory with involvement theory, it adds value to the literature on customer online behavior, especially in the foodservice context. The present study has limitations that might provide opportunities for future research. It used evaluations (TripAdvisor scores) and only positive reviews (texts), so customers’ intentions considering negative reviews could not be examined. The level of hedonism concerning consumption in restaurants and prior knowledge regarding restaurant reviews was not controlled for. It is possible that the level of hedonism perceived and prior review knowledge may moderate the customers’ intention to visit the restaurant.

The present study shows the importance of online comments for the promotion of restaurants that have low evaluation scores. It is essential that restaurant owners and managers encourage potential customers by using comments to elaborate on their marketing strategies and promotion. At the same time, they should invite customers to share their emotional experiences, and not just their views on service efficiency (a functional aspect). During the COVID-19 pandemic, the use of the internet and mobile devices has become more prominent. Managers could therefore use emotional messages on the restaurant’s website or apps to attract customers with low restaurant involvement. Also, a system to identify the involvement of customers with restaurants could be implemented online or on mobile devices to present specific messages. The present study also recommends the use of online tools as virtual tours, photographs taken from different angles, smiling faces, floor plans and sittings and pre-determined emotional expressions. Also, the restaurant could promote lives on cooking different dishes to motive customer’s interaction and comments. These would help to increase customers’ visit intentions.

This study extends knowledge about the effect of restaurant online reviews (both ratings and appeals) moderated by the level of customer involvement. The present study also adds value to the customer online behavior literature showing that customers with low involvement are more sensitive to emotional content as they use the affective route to process information rather than the central route.

在线评论对餐厅到访意愿的影响：运用信号理论和参与理论

本研究旨在探索以顾客参与度作为调节变量, 关于在线评论对餐厅到访意愿的影响。

本文以信号理论, 信息诉求, 参与理论来建立研究框架。为测试提出的理论框架, 本研究进行了三个在线消费者实验。T-检验, 方差分析, 和SPSS PROCESS 来作为统计方法。

研究发现评论分值越高, 运用感情诉求往往导致更高度的到访意愿。评论的诉求形式显著调节了评分对到访意愿的影响。对于参与度较低的顾客, 情感诉求比功能性诉求更加能影响顾客意愿。

本研究对餐厅在线评论（评分和诉求种类）对顾客到访意愿影响, 以及如何被消费者参与度所调节贡献了新知识。本研究对消费者在线行为做出了贡献, 发现参与度较低的顾客对和情感有关的内容更敏感, 相对于中央路径, 由于此类顾客更倾向于情感路径来处理信息。

This research investigates consumer intention to follow online community advice. Applying the technology acceptance model (TAM) to the context of online restaurant communities, the study empirically examines the effects of perceived usefulness, perceived ease of use, attitude and trust on the intention to follow online advice.

The data were collected from 360 members of online restaurant communities on Facebook and analyzed using structural equation modeling (SEM).

The findings revealed that trust, perceived usefulness and attitude are key predictors of the intention to follow online restaurant community advice.

Extant research on the influence of online reviews on consumer behavior in the restaurant industry has largely focused on the characteristics of the review, reviewers or readers. Moreover, other studies have investigated consumers' motivations to write online restaurant reviews. This study, however, takes a different approach and examines what drives consumers to follow the advice from online restaurant communities.

With the growing popularity of social media, it has become common practice for consumers to write online reviews to share their opinion and experience as well as consider others' reviews to inform purchase decision-making. This study investigated how online review sentiments towards four key aspects (food, service, ambience and price) change after a restaurant is awarded a Michelin Star to shed light on how the award of a Michelin Star affects online reviews as well as what factors contribute to positive online restaurant reviews.

The authors conducted a sentiment analysis of online restaurant reviews on TripAdvisor. A total of 8,871 English-written reviews from 87 restaurants located in Europe were extracted using a web crawler developed by Beautiful Soup, and data were then processed using Semantria.

The study findings revealed that overall sentiments decreased after restaurants were awarded a Michelin Star, in which service sentiment was the most affected aspect, followed by food and ambience. Yet, price sentiment showed a prominent increase. This provides valuable insights for Michelin-starred restaurant operators and owners to create a unique and compelling gastronomic experience that triggers positive online reviews.

The results of this study argue that consumers tend to hold higher expectations for this type of upscale restaurants given its recognition and quality assurance, so they are more likely to have negative feelings when their expectations are disconfirmed. Therefore, restaurants should continuously improve their food and service while paying attention to small details such as ambience, through creativity and innovation. Also, high-end restaurants, especially Michelin-starred restaurants, usually have the edge in premium pricing, yet competitive pricing may backfire considering its perceived luxurious values.

This study analyzed changes in customer sentiments when a restaurant is awarded a Michelin Star through text analytics. Through the lens of online restaurant reviews, the study findings contribute to identifying aspects that are most or least affected by the award of a Michelin Star as well as highlight the role of ambience in customer satisfaction which might have been overlooked in previous studies.

隨著社交媒體日趨普及，消費者出現一種常見的做法，就是在網上書寫評論，分享他們的意見和體驗，他們也會參考其他消費者的評論，以在購物時能作出知情決定。本研究擬探討當餐館獲得米其林星級時，消費者對它們在四個主要方面 (即食物、服務、情調和價格) 的網上評價會如何改變。我們藉此能更容易了解、餐館獲得米其林星級會如何影響其網上評論，以及是哪些因素、會為這些餐館帶來正面的網上評價。

我們對貓途鷹平台上的網上餐館評論進行情感分析。透過BeautifulSoup 研發的網絡爬蟲，我們取出位於歐洲87間餐館、共8,871個以英文書寫的評論，並把這些數據以Semantria加以處理。

研究結果顯示、當餐館獲得米其林星級時，顧客的整體情緒會下降，而其中最受影響的是服務情懷，其次是食物和情調; 但價格情緒卻有明顯的上升。這研究結果給獲得米其林星級餐館的經營者及其東主提供寶貴的啟示，讓他們了解如何為顧客創造一個可帶來正面網上評價的獨特而難忘的美食體驗。

本研究透過文本挖掘、去分析當餐館獲得米其林星級時，顧客情緒會如何改變; 透過網上餐館評論這面透視鏡子，本研究得到的結果、幫助我們確定米其林星級的聲譽所影響最大和最小的是哪些方面，以及讓我們更深入了解餐館的情調在顧客滿意程度上所扮演的角色，而這個角色在過去的研究中似被忽視。

本研究的結果提供了論據、證明由於消費者對擁有相關的認可和品質保證的這類高檔餐館一般予以較高的期望，故當他們發現期望與現實不符時，他們更容易產生負面的情緒; 因此，餐館在關注如情調方面的細節的同時，也應透過創造力和新觀念、去不斷改善他們提供的食物素質和服務水平; 而且，高檔餐館，尤其是獲得米其林星級的餐館，通常在溢價定價方面享有優勢，但當考慮到感知的奢華價值時，具競爭力的價格或會為餐館帶來反效果。

Online reviews are often likely to be socially influenced by prior reviews. This study aims to examine key review and reviewer characteristics which may influence the social influence process.

Restaurant review data from Yelp.com are analyzed using an ordered logit model and text mining approach.

This study reveals that prior average review rating exerts a positive influence on subsequent review ratings for the same restaurant, but the effect is attenuated by the variance in existing review ratings. Moreover, social influence is stronger for consumers who had a moderate dining experience or invested less cognitive effort in writing online reviews. Compared to reviewers classified by Yelp as “elite,” non-elite reviewers appear more susceptible to the social influence of prior average review rating.

This study provides guidelines for mitigating the social influence of prior reviews and improving the accuracy of online product/service ratings, which will eventually enhance business and the reputation of online review platforms.

The findings from this study contribute to the electronic word-of-mouth (eWOM) literature and social influence literature in terms of the bidirectional nature of social influence on eWOM.

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.

The purpose of this paper is to detect predefined service attributes and their sentiments from online restaurant reviews, and then to measure the effects of customer sentiments toward service attributes on customer satisfaction (CS) and revisit intention (RVI) simultaneously.

This study proposed a supervised framework to model CS and RVI simultaneously from restaurant reviews. Specifically, the authors detected the predefined service dimensions from online reviews based on random forest. Then, the sentiment polarities of the reviews toward each predefined dimension were identified using light-gradient boosting machine (LightGBM). Finally, the effects of attribute-specific sentiments on CS and RVI were evaluated by a bagged neural network-based model. The proposed framework was evaluated by 305,000 restaurant comments collected from DianPing.com, a Yelp-like website in China.

The authors obtained a hierarchal importance order of the investigated service themes (i.e. location, service, environment, price and food). The authors found that food played the most important role in affecting both CS and RVI. The most salient attribute with respect to each service theme was also identified.

Unlike prior work relying on the data collected from surveys, this study is among the first to model the relationship among service attributes, CS and RVI simultaneously from real-world data. The authors established a hierarchal structure of eighteen attributes within five service themes and estimated their effects on both CS and RVI, which will broaden our understanding of customer perception and behavioral intention during service consumption.