IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i9p4981-d545869.html
   My bibliography  Save this article

Analyzing Restaurant Customers’ Evolution of Dining Patterns and Satisfaction during COVID-19 for Sustainable Business Insights

Author

Listed:
  • Susan (Sixue) Jia

    (School of Finance and Business, Shanghai Normal University, Shanghai 200234, China)

Abstract

Observing and interpreting restaurant customers’ evolution of dining patterns and satisfaction during COVID-19 is of critical importance in terms of developing sustainable business insights. This study describes and analyzes customers’ dining behavior before and after the pandemic outbreak by means of statistically aggregating and empirically correlating 651,703 restaurant-user-generated contents posted by diners during 2019–2020. Twenty review topics, mostly food, were identified by latent Dirichlet allocation, whereas analysis of variation and rating-review regression were performed to explore whether and why customers became less satisfied. Results suggest that customers have been paying fewer visits to restaurants since the outbreak, assigning lower ratings, and showing limited evidence of spending more. Interestingly, queuing, the most annoying factor for restaurant customers during normal periods, turns out to receive much less complaint during COVID-19. This study contributes by discovering business knowledge in the context of COVID-19 based on big data that features accessibility, relevance, volume, and information richness, which is transferable to future studies and can benefit additional population and business. Meanwhile, this study also provides practical suggestions to managers regarding the framework of self-evaluation, business mode, and operational optimization.

Suggested Citation

  • Susan (Sixue) Jia, 2021. "Analyzing Restaurant Customers’ Evolution of Dining Patterns and Satisfaction during COVID-19 for Sustainable Business Insights," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4981-:d:545869
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/9/4981/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/9/4981/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    2. Seungju Nam & Hyun Cheol Lee, 2019. "A Text Analytics-Based Importance Performance Analysis and Its Application to Airline Service," Sustainability, MDPI, vol. 11(21), pages 1-24, November.
    3. Michael Anderson & Jeremy Magruder, 2012. "Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database," Economic Journal, Royal Economic Society, vol. 122(563), pages 957-989, September.
    4. Yongping Zhong & Segu Oh & Hee Cheol Moon, 2021. "What Can Drive Consumers’ Dining-Out Behavior in China and Korea during the COVID-19 Pandemic?," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    5. Benito Umaña-Hermosilla & Hanns de la Fuente-Mella & Claudio Elórtegui-Gómez & Marisela Fonseca-Fuentes, 2020. "Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    6. Yufan Jian & Irina Y. Yu & Morgan X. Yang & Kevin J. Zeng, 2020. "The Impacts of Fear and Uncertainty of COVID-19 on Environmental Concerns, Brand Trust, and Behavioral Intentions toward Green Hotels," Sustainability, MDPI, vol. 12(20), pages 1-14, October.
    7. Joachim Büschken & Greg M. Allenby, 2016. "Sentence-Based Text Analysis for Customer Reviews," Marketing Science, INFORMS, vol. 35(6), pages 953-975, November.
    8. Andrea Appolloni & Nathalie Colasanti & Chiara Fantauzzi & Gloria Fiorani & Rocco Frondizi, 2021. "Distance Learning as a Resilience Strategy during Covid-19: An Analysis of the Italian Context," Sustainability, MDPI, vol. 13(3), pages 1-12, January.
    9. Fabio Giudice & Rocco Caferra & Piergiuseppe Morone, 2020. "COVID-19, the Food System and the Circular Economy: Challenges and Opportunities," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    10. Xiang, Zheng & Du, Qianzhou & Ma, Yufeng & Fan, Weiguo, 2017. "A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism," Tourism Management, Elsevier, vol. 58(C), pages 51-65.
    11. Susan (Sixue) Jia, 2018. "Leisure Motivation and Satisfaction: A Text Mining of Yoga Centres, Yoga Consumers, and Their Interactions," Sustainability, MDPI, vol. 10(12), pages 1-17, November.
    12. Yuanyuan Guo & Yanqing Wang & Chaoyou Wang, 2019. "Exploring the Salient Attributes of Short-Term Rental Experience: An Analysis of Online Reviews from Chinese Guests," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    13. Hany Kim & Hyo Jae Joun & Yeongbae Choe & Ashley Schroeder, 2019. "How Can a Destination Better Manage Its Offering to Visitors? Observing Visitor Experiences via Online Reviews," Sustainability, MDPI, vol. 11(17), pages 1-19, August.
    14. Ian Sutherland & Youngseok Sim & Seul Ki Lee & Jaemun Byun & Kiattipoom Kiatkawsin, 2020. "Topic Modeling of Online Accommodation Reviews via Latent Dirichlet Allocation," Sustainability, MDPI, vol. 12(5), pages 1-15, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mian Yang & Wenjie Fan & Jian Qiu & Sining Zhang & Jinting Li, 2022. "The Evaluation of Rural Outdoor Dining Environment from Consumer Perspective," IJERPH, MDPI, vol. 19(21), pages 1-16, October.
    2. Zibarzani, Masoumeh & Abumalloh, Rabab Ali & Nilashi, Mehrbakhsh & Samad, Sarminah & Alghamdi, O.A. & Nayer, Fatima Khan & Ismail, Muhammed Yousoof & Mohd, Saidatulakmal & Mohammed Akib, Noor Adelyna, 2022. "Customer satisfaction with Restaurants Service Quality during COVID-19 outbreak: A two-stage methodology," Technology in Society, Elsevier, vol. 70(C).
    3. Hyo-Sun Jung & Hye-Hyun Yoon & Min-Kyung Song, 2021. "A Study on Dining-Out Trends Using Big Data: Focusing on Changes since COVID-19," Sustainability, MDPI, vol. 13(20), pages 1-23, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Woohyuk Kim & Sung-Bum Kim & Eunhye Park, 2021. "Mapping Tourists’ Destination (Dis)Satisfaction Attributes with User-Generated Content," Sustainability, MDPI, vol. 13(22), pages 1-16, November.
    2. Yi Luo & Xiaowei Xu, 2019. "Predicting the Helpfulness of Online Restaurant Reviews Using Different Machine Learning Algorithms: A Case Study of Yelp," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    3. Jose Ramon Saura & Pedro Palos-Sanchez & Antonio Grilo, 2019. "Detecting Indicators for Startup Business Success: Sentiment Analysis Using Text Data Mining," Sustainability, MDPI, vol. 11(3), pages 1-14, February.
    4. Seungju Nam & Hyun Cheol Lee, 2019. "A Text Analytics-Based Importance Performance Analysis and Its Application to Airline Service," Sustainability, MDPI, vol. 11(21), pages 1-24, November.
    5. Xin Zhang & Jiaming Liu & He Zhu & Zongcai Huang & Shuying Zhang & Ping Li, 2021. "A Comparative Study of Customer Perceptions of Urban and Rural Bed and Breakfasts in Beijing: An Analysis of Online Reviews," Sustainability, MDPI, vol. 13(20), pages 1-15, October.
    6. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    7. Zuo, Wenming & Bai, Weijing & Zhu, Wenfeng & He, Xinming & Qiu, Xinxin, 2022. "Changes in service quality of sharing accommodation: Evidence from airbnb," Technology in Society, Elsevier, vol. 71(C).
    8. Carmela Iorio & Giuseppe Pandolfo & Antonio D’Ambrosio & Roberta Siciliano, 2020. "Mining big data in tourism," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1655-1669, December.
    9. Ian Sutherland & Kiattipoom Kiatkawsin, 2020. "Determinants of Guest Experience in Airbnb: A Topic Modeling Approach Using LDA," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    10. Sunyoung Hlee & Hanna Lee & Chulmo Koo, 2018. "Hospitality and Tourism Online Review Research: A Systematic Analysis and Heuristic-Systematic Model," Sustainability, MDPI, vol. 10(4), pages 1-27, April.
    11. Wenzhi Cao & Xingen Yang & Yi Yang, 2023. "A Large-Scale Reviews-Driven Multi-Criteria Product Ranking Approach Based on User Credibility and Division Mechanism," Mathematics, MDPI, vol. 11(13), pages 1-19, July.
    12. Reyes-Menendez, Ana & Clemente-Mediavilla, Jorge & Villagra, Nuria, 2023. "Understanding STI and SDG with artificial intelligence: A review and research agenda for entrepreneurial action," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    13. Xiao-kang Wang & Sheng-hui Wang & Hong-yu Zhang & Jian-qiang Wang & Lin Li, 2021. "The Recommendation Method for Hotel Selection Under Traveller Preference Characteristics: A Cloud-Based Multi-Criteria Group Decision Support Model," Group Decision and Negotiation, Springer, vol. 30(6), pages 1433-1469, December.
    14. Han, Chunjia & Yang, Mu, 2021. "Revealing Airbnb user concerns on different room types," Annals of Tourism Research, Elsevier, vol. 89(C).
    15. Gang Ren & Taeho Hong, 2017. "Investigating Online Destination Images Using a Topic-Based Sentiment Analysis Approach," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    16. Ziye Shang & Jian Ming Luo, 2022. "Topic Modeling for Hiking Trail Online Reviews: Analysis of the Mutianyu Great Wall," Sustainability, MDPI, vol. 14(6), pages 1-16, March.
    17. Yuan Yuan & Tianhui You & Tian’ai Xu & Xun Yu, 2022. "Customer-Oriented Strategic Planning for Hotel Competitiveness Improvement Based on Online Reviews," Sustainability, MDPI, vol. 14(22), pages 1-30, November.
    18. Zajadacz Alina & Minkwitz Aleksandra, 2020. "Using Social Media Data to Plan for Tourism," Quaestiones Geographicae, Sciendo, vol. 39(3), pages 125-138, September.
    19. Kolomoyets, Yuliya & Dickinger, Astrid, 2023. "Understanding value perceptions and propositions: A machine learning approach," Journal of Business Research, Elsevier, vol. 154(C).
    20. Jimenez-Marquez, Jose Luis & Gonzalez-Carrasco, Israel & Lopez-Cuadrado, Jose Luis & Ruiz-Mezcua, Belen, 2019. "Towards a big data framework for analyzing social media content," International Journal of Information Management, Elsevier, vol. 44(C), pages 1-12.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4981-:d:545869. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.