What factors affect consumers’ dining sentiments and their ratings: Evidence from restaurant online review data

Guang, Tian; Lu, Liang; McIntosh, Christopher S.

doi:10.1016/j.foodqual.2020.104060

Cited by 68 publications

(62 citation statements)

References 28 publications

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“…The following analysis consisted of particle analysis according to the level of feelings strength. Sentiment analysis has been already proven as the most reliable and realistic tool in the consumer dining experience analysis, because it secures the usage of spontaneous consumer data in natural consumption settings (Tian et al, 2021;Vidal, Ares, Machín, & Jaeger, 2015). SentiStrength software was used in this particle analysis to assess the strength of positive and negative feelings for identified particles within each dimension.…”

Section: Discussionmentioning

confidence: 99%

“…According to Nakayama & Wan (2019), restaurant reviews can be analysed in at least four aspects: food quality, service, ambiance, and price fairness. There are already some studies that have applied sentiment analysis to analyse online restaurant reviews (Yu et al, 2017;Nakayama & Wan, 2019;Mehraliyev et al, 2020;Tian, Lu, & McIntosh, 2021). This method has been shown to be useful in capturing and measuring individual opinion and determining the polarity of sentiment.…”

Section: Online Reviews Of Restaurantsmentioning

confidence: 99%

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Content Analysis of Michelin Restaurants Online Reviews in Croatia

Marković¹,

Dorčić²,

Rašan³

et al. 2021

International Scientific Conference EMAN – Economics and Management: How to Cope With Disrupted Times

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The Michelin Guide is considered by many to be the hallmark of global fine dining and quality cuisine. For five years now, renowned and selected Croatian restaurants have been included in the worldwide Michelin Guide. In the latest edition of Michelin Guide, seventy Croatian restaurants were included. Nowadays, to find the ideal restaurant, diners are increasingly using TripAdvisor and reviews on social media. Online reviews are a great source for capturing unique customer experiences. The purpose of this study is to gain insight into the components of restaurant guest experiences. The most recent online reviews on TripAdvisor of 17 Croatian Michelin guide listed restaurants (7 one-star restaurants and 10 Bib Gourmand) were analysed. This study follows a content analysis approach. Simple frequency counts were performed on the number of positive, negative and neutral comments. The empirical results showed that the overall customer satisfaction in the analysed restaurants was positive. The content analysis revealed that customers mainly focused on the food, menu offerings, ambiance, and service in the online reviews. This study contributes to the customer experience literature by applying data mining techniques and content analysis of online reviews to understand customers’ views of the restaurant experience. The findings of this study also provide practical implications for restaurateurs by identifying the key determinants in customer reviews of restaurants.

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Section: Discussionmentioning

confidence: 99%

Section: Online Reviews Of Restaurantsmentioning

confidence: 99%

Content Analysis of Michelin Restaurants Online Reviews in Croatia

Marković¹,

Dorčić²,

Rašan³

et al. 2021

International Scientific Conference EMAN – Economics and Management: How to Cope With Disrupted Times

View full text Add to dashboard Cite

show abstract

“…Meituan expanded into other types of services such as travel and hotel booking and food delivery. During COVID‐19, Meituan pivoted its delivery service and started “contactless delivery.” Moreover, since restaurant service plays an important role in the value‐added provided to the consumers (Tian et al., 2021) and the restaurant service is being replaced by delivery service during COVID‐19, it is important to know whether consumer satisfaction/dissatisfaction comes from the restaurant or the delivery service. To deal with this issue, in November 2020, Meituan added a new feature on its review platform allowing delivery workers to leave reviews about the restaurants they delivery for, thereby helping “copivoters” to provide better information to consumers dining options.…”

Section: Downstream Firms’ Pivoting During Covid‐19mentioning

confidence: 99%

“…Ninjacart also started working with large-scale wholesalers and retailers in early 2020. Just two months before COVID, Walmart-Flipkart acquired part of Ninjacart to develop its sourcing from farms for the grocery e-commerce of Flipkart and for Walmart's "India's Best Price" B2B cash and carry stores (Vankipuram & Nandy, 2020). In a strategy widely implemented by e-commerce firms in several countries during COVID-19, Flipkart started rapid "hyperlocal" service in July 2020 and used Ninjacart's supply chain to implement that and help Flipkart compete with Amazon Fresh, BigBasket, and Grofers (Velayanikal, 2020).…”

Section: B2b E-commerce Firms Helping Big and Small Retailers In Procurementmentioning

confidence: 99%

“Pivoting” by food industry firms to cope with COVID‐19 in developing regions: E‐commerce and “copivoting” delivery intermediaries

Reardon

Heiman

et al. 2021

Agricultural Economics

Self Cite

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Coronavirus disease 2019 and related lockdown policies in 2020 shocked food industry firms’ supply chains in developing regions. Firms “pivoted” to e‐commerce to reach consumers and e‐procurement to reach processors and farmers. “Delivery intermediaries” copivoted with food firms to help them deliver and procure. This was crucial to the ability of the food firms to pivot. The pandemic was a “crucible” that induced this set of fast‐tracking innovations, accelerating the diffusion of e‐commerce and delivery intermediaries, and enabling food industry firms to redesign, at least temporarily, and perhaps for the long term, their supply chains to be more resilient, and to weather the pandemic, supply consumers, and contribute to food security. We present a theoretical model to explain these firm strategies, and then apply the framework to classify firms’ practical strategies. We focus on cases in Asia and Latin America. Enabling policy and infrastructural conditions allowed firms to pivot and copivot fluidly.

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“…At the same time, in the face of massive text data, many scholars use text mining technology, combined with machine language deep learning to form a more complete algorithm to study natural language processing [ 11 ]. For example, Tian et al [ 12 ] used sensory analysis method to study the review data of the catering industry and found the internal relationship between customer emotion and customer rating. Kumar et al [ 13 ] comprehensively surveyed the evolution of the online social networks, their associated risks, and solutions.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of COVID-19 on Consumers’ Psychological Behavior Based on Data Mining for Online User Comments in the Catering Industry in China

Zhang

Jiang

et al. 2021

IJERPH

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The outbreak of COVID-19 in late 2019 has had a huge impact on people’s daily life. Many restaurant businesses have been greatly affected by it. Consumers’ preferences for catering industry in China have changed, such as environmental hygiene, variety of dishes, and service methods. Therefore, the analysis of consumer preference differences and changes before and after the epidemic can not only provide emergency strategies for the catering industry but further improve the catering industry’s ability to deal with public health emergencies. This paper takes five cities in China as representatives to explore the impact of COVID-19 on China’s catering industry. Based on catering review data from August 2019 to April 2020, this paper first carries out Latent Dirichlet Allocation (LDA) topic analysis and SNOWNLP (A Python library for processing Chinese text) sentiment analysis. Then this paper compares the results of topic classification and sentiment analysis before and after the epidemic. Furthermore, differences and changes of consumer preferences are obtained and preferences of consumers under COVID-19 are analyzed and forecasted. The results of LDA thematic analysis before the outbreak of COVID-19 show that consumers tend to punch in cyber celebrity restaurants and pay more attention to the taste of dishes, whereas after it consumers pay more attention to the changes of dishes, dining environment as well as epidemic prevention. The number of packages and takeout was also increasing. However, the waiting time is constantly considered by consumers before and after COVID-19. Firstly, to our surprise, final outcome of emotional analysis showed that consumers’ emotional state was more positive after the epidemic than before. COVID-19 has changed the lifestyle of consumers, consumption concepts, and consumption habits. Therefore, businesses also need to take positive and flexible measures to actively get feedback from consumers to adjust dishes and business methods. Secondly, the psychological attitude of catering consumers is relatively positive during the epidemic period, which indicates that consumers have great confidence in the recovery and development of the catering industry. Businesses can comply with consumers’ psychology and combine consumption vouchers with restaurant discounts to promote consumers’ consumption. Finally, the environment and service play more and more important effect on consumers’ emotional scores at present, which indicates that dining state and comfortable mealtime environment are becoming increasingly valuable. Therefore, businesses need to improve service standards.

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What factors affect consumers’ dining sentiments and their ratings: Evidence from restaurant online review data

Cited by 68 publications

References 28 publications

Content Analysis of Michelin Restaurants Online Reviews in Croatia

Content Analysis of Michelin Restaurants Online Reviews in Croatia

“Pivoting” by food industry firms to cope with COVID‐19 in developing regions: E‐commerce and “copivoting” delivery intermediaries

The Impact of COVID-19 on Consumers’ Psychological Behavior Based on Data Mining for Online User Comments in the Catering Industry in China

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