scholarly journals Exploring Consumer Emotions in Pre-Pandemic and Pandemic Times. A Sentiment Analysis of Perceptions in the Fine-Dining Restaurant Industry in Bucharest, Romania

2021 ◽  
Vol 18 (24) ◽  
pp. 13300
Author(s):  
Jacqueline-Nathalie Harba ◽  
Gabriela Tigu ◽  
Adriana AnaMaria Davidescu
Keyword(s):  
Content Analysis ◽  
Sentiment Analysis ◽  
Online Reviews ◽  
Restaurant Industry ◽  
Capital City ◽  
Choice Making ◽  
Consumer Emotions ◽  
Cognitive Choice ◽  
Media Sentiment

This research paper aims to analyse how consumer emotions have evolved during the pandemic period in comparison with the pre-pandemic period in relation to restaurant demand in the Romanian fine-dining industry and uses valuable information based on social-media sentiment analysis and content analysis. Focusing on theories of consumer behaviour, the study aims to emphasize how, under the influence of an epidemic crisis caused by an infectious disease, individual behaviour adapts to the “new normal”, embracing a series of changes in the preferences, attitudes, and cognitive choice-making processes. The article takes into account a comparative analysis of the consumer emotions between the pre-COVID-19 pandemic period (2010–2019) and the pandemic period (2020–present), based on the online reviews provided by customers for five fine-dining restaurants from Bucharest, the capital city of Romania: The Artist, Relais & Chateaux Le Bistrot Francais, Casa di David, Kaiamo, and L’Atelier. The research was based on two mining analyses—content analysis and sentiment analysis—and explored the emotional intent of words, with the data being collected from TripAdvisor through web-scrapping. The empirical results defined the fine-dining experience during the pandemic as being associated with the quality of the dishes and also with the quality of the service. The overall consumer sentiment in the direction of the restaurants analyzed is positive. The sentiment research found that throughout the epidemic, the consumers’ attitudes about restaurants deteriorated. In this sense, consumers seem to be less satisfied with the restaurants’ services than before the pandemic. This is another thing that the restaurants had difficulties in when adapting their operations for the pandemic.

scholarly journals The Influence of Service Quality, Price, and Environment on Customer Loyalty in the Restaurant's Industry: The Mediating Role of Customer Satisfaction

2021 ◽  
Vol 7 (1) ◽  
pp. 143-154
Author(s):  
Danish Ali ◽  
Mohammad Alam ◽  
Hazrat Bilal
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Customer Loyalty ◽  
Positive Association ◽  
Restaurant Industry ◽  
Capital City ◽  
Mediating Role ◽  
Service Fairness

The purpose of this research is to examine the influence of service quality (SQ), Price (P) and Restaurant Environment (RE) on customer loyalty (LOY), via the mediating role of customer satisfaction (SAT) in the context of the restaurant industry in the capital city of Pakistan (Islamabad). Five hundred questionnaires were distributed at various restaurants in a different location at Islamabad, and 385 were returned. Multiple Regression Analysis was used to test hypothesis relationships. The outcome of this research shows that SQ, Pand RE have a positive association with the SAT. In contrast, customer satisfaction also leads to customer loyalty. Moreover, customer satisfaction significantly mediates the association among SQ, P, RE, and customer loyalty. The restaurant operators need to consider that good quality of service, fairness in price, pleasant and attractive restaurant the environment can increase customer satisfaction, which often contributes to customer loyalty.

eWOW of Guests Regarding Their Hotel Experience

2020 ◽  
pp. 295-308
Author(s):  
Zelia Breda ◽  
Rui Costa ◽  
Gorete Dinis ◽  
Amandine Angie Martins
Keyword(s):  
Sentiment Analysis ◽  
Online Reviews ◽  
User Generated Content ◽  
Sources Of Information ◽  
Value For Money ◽  
Quality Of Sleep ◽  
Online Comments ◽  
Analytical Response ◽  
Source Of Information

Online comments are increasingly mentioned as an important source of information, simplifying consumers' buying decisions. Online user-generated content has become one of the main sources of information for tourists, who themselves become creators of their own online content. This chapter focuses on sentiment analysis of comments made on TripAdvisor regarding one resort located in the Algarve region, in Portugal. The resort has good reviews, which means that the eWOM is positive. The highest scores relate to the resort's cleanliness, location and quality of sleep, and those that were less relevant were the value for money, the rooms and the service. The most dominant emotion is joy, followed by an analytical response. Negative emotions, such as sadness and anger, were not found very often in the online reviews. These results could be explained by the quality of the service, the kindness of the staff, the facilities for children, the entertainment, and the location, attributes that were often highlighted in the comments.

scholarly journals CUSTOMER RESTAURANT SELECTION FACTORS IN VEGAN RESTAURANTS: AN EVALUATION OF ONLINE REVIEWS IN MELBOURNE VEGAN RESTAURANTS

2021 ◽  
Author(s):  
Anh Viet Le ◽  
◽  
Thu Huong Nguyen ◽  
Joel Francis F. Hernandez ◽  
◽  
...  
Keyword(s):  
Content Analysis ◽  
Service Quality ◽  
Food Quality ◽  
Qualitative Content Analysis ◽  
Online Reviews ◽  
The World ◽  
Selection Factors

Restaurants are constantly adapting towards customers’ wants and needs. Vegan restaurants have become increasingly popular, particularly in Melbourne, which is one of the fastest growing vegan markets in the world. While there is literature and evidence of restaurant selection factors in general restaurants, there are no specific studies in vegan restaurants. The aim of this study is to determine the customer restaurant selection factors in vegan restaurants by way of a qualitative content analysis of 5 popular Melbourne vegan restaurants with 10 reviews each. This study found that similar to general restaurants that serve meat, vegan restaurants are chosen mainly because of their food quality and service quality. Vegan restaurants must continue to build on the quality of their food and prioritize putting the same amount of focus on service quality, as poor service quality can completely tarnish the entire dining experience.

scholarly journals How Can a Destination Better Manage Its Offering to Visitors? Observing Visitor Experiences via Online Reviews

2019 ◽  
Vol 11 (17) ◽  
pp. 4660 ◽  
Author(s):  
Hany Kim ◽  
Hyo Jae Joun ◽  
Yeongbae Choe ◽  
Ashley Schroeder
Keyword(s):  
Content Analysis ◽  
Significant Influence ◽  
Online Reviews ◽  
Star Rating ◽  
Analysis Techniques ◽  
Tour Guides ◽  
Visitor Experiences ◽  
Sustainable Income ◽  
And Behavior

Destinations are competing every day to attract more tourists and increase tourism receipts. In order to maintain tourists’ interests in the destination and expect sustainable income from tourism, understanding tourists’ perceptions of the destination is a critical task for destination managers. Tourists’ continuous visitation can be ensured when destinations are perceived to be positive and attractive. Therefore, this study examines destination attributes that are fundamental elements of the destination and tourists’ experiences. More specifically, this study investigates the destination attributes that are perceived to be positive by tourists using online reviews. Online reviews were analyzed with content analysis techniques and the quantified content was statically compared with the star rating provided by tourists. In addition, the influence of destination attributes on other conation dimensions-attitude and behavior-was analyzed. Destination attributes that have an influence on the star rating showed similar results to the attitude. However, behavior dimensions only had a significant influence for tour guides’ quality of the destination.

scholarly journals Insights from sentiment analysis to leverage local tourism business in restaurants

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ting Yu ◽  
Paulo Rita ◽  
Sérgio Moro ◽  
Cristina Oliveira
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Sentiment Analysis ◽  
Online Reviews ◽  
Restaurant Industry ◽  
Bench Mark ◽  
Quality Factors ◽  
Vast Number ◽  
Content Type ◽  
Food And Beverage

Purpose Social media has become the main venue for users to express their opinions and feelings, generating a vast number of available and valuable data to be scrutinized by researchers and marketers. This paper aims to extend previous studies analyzing social media reviews through text mining and sentiment analysis to provide useful recommendations for management in the restaurant industry. Design/methodology/approach The Lexalytics, a text mining artificial intelligence tool, is applied to analyze the text of the online reviews of the restaurants in a touristic Dutch village extracted from the most frequently used social media platforms focusing on the four restaurant quality factors, namely, food and beverage, service, atmosphere and value. Findings The findings of this research are presented by the identified key themes with comparisons of the customers’ review sentiment between a selected restaurant, Zwaantje, vis-à-vis its bench-mark restaurants set by a specific approach under the abovementioned quality dimensions, in which the food and beverage and service are the most commented by customers. Results demonstrate that text mining can generate insights from different aspects and that the proposed approach is valuable to restaurant management. Originality/value The paper provides a relatively big scale in numbers and resources of social media reviews to further explore the most important service dimensions in the restaurant industry in a specific tourist area. It also offers a useful framework to apply the text mining business intelligence tool by comparison of peers for local small business restaurant practitioners to improve their management skills beyond manually reading social media reviews.

scholarly journals Manufacturing the Image of Doha: From the Public Face of Architecture to the Printed Media

2013 ◽  
Vol 38 (4) ◽  
pp. 6-15
Author(s):  
Ashraf M. Salama
Keyword(s):  
Content Analysis ◽  
Critical Discussion ◽  
Capital City ◽  
Professional Discourse ◽  
Analysis Study ◽  
The Public ◽  
Printed Media ◽  
Critical Approaches ◽  
The City

This paper explores image-making efforts in the city of Doha. A multi-layered critical discussion is employed and articulated in a number of procedures that include conceptualizing theoretical underpinnings for understanding image making in terms of contextual and critical approaches, identifying the types of efforts that took place and that are currently taking place towards image making, mapping the contextual and critical approaches on actual examples from the city, and examining the printed media by conducting a content analysis study of two widely acknowledged magazines in an attempt to answer the question of how the country wants to portray its capital city through image-making to the global community. The results of this exploration convey a commitment toward image making, presenting an image of Doha as an emerging international hub. The paper concludes by arguing for the need of critical consciousness in response to that fact that image making practices in Doha continue to subdue the profession to client aspirations through oversimplified imaging while ignoring the professional discourse that scrutinizes the quality of those images and the meanings they convey.

Analytical review of approaches for tonality recognition of Russian text data

2020 ◽  
pp. 20-30
Author(s):  
Anastasiya Dvoynikova ◽  
Alexey Karpov
Keyword(s):  
Sentiment Analysis ◽  
Online Reviews ◽  
Russian Text ◽  
Software Systems ◽  
Text Data ◽  
World Languages ◽  
Analytical Review ◽  
Audio Data ◽  
Quality Of Products

Introduction: In recent years, sentiment analysis has found practical application in many areas, such as evaluating the quality of products and services based on customers’ online reviews, analyzing negative emotions in messages, forecasting stock markets or political situations based on news data. In this regard, a large number of systems and methods for Russian text sentiment analysis are being developed. Purpose: A detailed review of approaches, and comparative analysis of available databases in the field of Russian text sentimental analysis. Results: Our analytical review of the approaches to Russian text data sentiment analysis has shown that there are a large number of ways for preprocessing, vectorization and machine classification of the text data. Studying the available databases shows that the Russian text sentimental analysis is less developed than that for other major world languages. Studying the existing software systems for Russian text analysis reveals their low accuracy compared to English, which can be caused by the sophisticated structure of Russian. Discussion: In our further research, we plan to implement sentiment analysis of spoken speech using audio data. To do this, we will need to obtain a spelling transcription of speech for each speaker.

scholarly journals COMMENT ANALYSIS FOR PRODUCT AND SERVICE SATISFACTION FROM THAI CUSTOMERS' REVIEW IN SOCIAL NETWORK

2018 ◽  
Author(s):  
Todsanai Chumwatana
Keyword(s):  
Social Media ◽  
Quality Of Service ◽  
Social Network ◽  
Sentiment Analysis ◽  
Experimental Studies ◽  
Online Reviews ◽  
Huge Amount ◽  
Media Usage ◽  
The Social

In the last decade, the amount of social media usage has rapidly increased exponentially in Thailand. A huge amount of Thai online reviews and comments are available on social network every second. Because of this fact, comment analysis, also called sentiment analysis, has then become an essential task to analyze people’s emotions, opinion, attitudes and sentiments from the amount of these online posts. This paper proposed the technique for analyzing Thai customers’ comments or opinions about the products and services by counting the polarity words of the product and service domains. To demonstrate the proposed technique, experimental studies on analyzing Thai customers’ comments in the social media are presented in this paper. The comments are classified into neutral, positive or negative. The proposed technique benefits the business domain in guiding product improvement and quality of service. Hence, this paper also benefits the end-users in making a smart decision.

scholarly journals Exploring the Impact of Linguistic Signals Transmission on Patients’ Health Consultation Choice: Web Mining of Online Reviews

2021 ◽  
Vol 18 (19) ◽  
pp. 9969
Author(s):  
Adnan Muhammad Shah ◽  
Mudassar Ali ◽  
Abdul Qayyum ◽  
Abida Begum ◽  
Heesup Han ◽  
...  
Keyword(s):  
Decision Making ◽  
Sentiment Analysis ◽  
Signaling Theory ◽  
Online Reviews ◽  
Treatment Choice ◽  
Quality Of Information ◽  
Physician Rating ◽  
Sentic Computing ◽  
Negative Sentiment

Background: Patients face difficulties identifying appropriate physicians owing to the sizeable quantity and uneven quality of information in physician rating websites. Therefore, an increasing dependence of consumers on online platforms as a source of information for decision-making has given rise to the need for further research into the quality of information in the form of online physician reviews (OPRs). Methods: Drawing on the signaling theory, this study develops a theoretical model to examine how linguistic signals (affective signals and informative signals) in physician rating websites affect consumers’ decision making. The hypotheses are tested using 5521 physicians’ six-month data drawn from two leading health rating platforms in the U.S (i.e., Healthgrades.com and Vitals.com) during the COVID-19 pandemic. A sentic computing-based sentiment analysis framework is used to implicitly analyze patients’ opinions regarding their treatment choice. Results: The results indicate that negative sentiment, review readability, review depth, review spelling, and information helpfulness play a significant role in inducing patients’ decision-making. The influence of negative sentiment, review depth on patients’ treatment choice was indirectly mediated by information helpfulness. Conclusions: This paper is a first step toward the understanding of the linguistic characteristics of information relating to the patient experience, particularly the emerging field of online health behavior and signaling theory. It is also the first effort to our knowledge that employs sentic computing-based sentiment analysis in this context and provides implications for practice.

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