Author(s)

Lei Xin^1*, HaoChuan Zhang², GuoDong Ding³

Affiliation(s)

¹Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, Aveiro 3810-193, Portugal.

²College of Tourism and Geographical Science, Leshan Normal University, Leshan 614000, Sichuan, China.

³Department of Finance, Tongling University, Tongling 244000, Anhui, China.

Corresponding Author

Lei Xin

ABSTRACT

The COVID-19 epidemic has rapidly changed the catering industry and food delivery platforms. Different food delivery platforms aim to different consumer groups, especially in metropolises, where different catering cultures interact. How to designate a targeted marketing strategy is vitally important for restaurant managers. Using the webQDA software and TripAdvisor network resources, we propose a qualitative analysis of consumers’ perceptions to three Chinese restaurants in Milan. The results reveal the apparent divergence in target clients of different Chinese restaurants. Cultural background is one of the factors affecting customers’ sentiments towards the food.

KEYWORDS

Consumers' perceptions; Qualitative analysis; webQDA; TripAdvisor

CITE THIS PAPER

Lei Xin, HaoChuan Zhang, GuoDong Ding. Qualitative analysis of restaurant consumers’ perceptions for differentiation of target clients under multi-catering culture. Trends in Social Sciences and Humanities Research. 2025, 3(3): 66-70. DOI: https://doi.org/10.61784/tsshr3155.

REFERENCES

[1] Chen Q, Huang R. Understanding the importance of food tourism to Chongqing, China. Journal of Vacation Marketing, 2016, 22(1): 42-54. DOI: 10.1177/1356766715589427.

[2] Smith M. Italian cuisine is world's most popular. YouGov, 2019. https://yougov.co.uk/topics/consumer/articles-reports/2019/03/12/italian-cuisine-worlds-most-popular.

[3] Costa A P, Souza F N D, Moreira A, et al. webQDA 2.0 Versus webQDA 3.0: a comparative study about usability of qualitative data analysis software. In Developments and Advances in Intelligent Systems and Applications, Springer, Cham, 2018: 229-240.  DOI: 10.1007/978-3-319-58965-7_16.

[4] Ribeiro D, Machado L P, Costa A P, et al. Analysis of booking. com comments with the support of the qualitative analysis software webQDA. In World Conference on Qualitative Research, 2019, 1: 173-175. https://www.proceedings.wcqr.info/index.php/wcqr2019/article/view/254.

[5] Carvalho A R, Santos C. Assessing teachers and peer teacher students’ perceptions of their motivations and participation impact in peer learning projects: The role of content analysis supported by WebQDA. In World Conference on Qualitative Research, Springer, Cham, 2021: 80-99. DOI: 10.1007/978-3-030-70187-1_7.

[6] Machado A L G, Vieira N F C. Use of webQDA software on qualitative nursing research: an experience report. Revista Brasileira de Enfermagem, 2020, 73. DOI: 10.1590/0034-7167-2018-0411.

[7] Fornari L F, Pinho I, Costa A P. Review of literature with support of webQDA Software. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2019: 1-6. DOI: 10.23919/CISTI.2019.8760950.

[8] Cantarero L, Espeitx E, Gil Lacruz M, et al. Human food preferences and cultural identity: The case of Aragón (Spain). International Journal of Psychology, 2013, 48(5): 881-890. DOI: 10.1080/00207594.2012.692792.

[9] Chen Q, Huang R. Understanding the role of local food in sustaining Chinese destinations. Current Issues in Tourism, 2019, 22(5): 544-560. DOI: 10.1080/13683500.2018.1444020.

[10] Rehman O U, Liu X, Rauf A, et al. Internet tradition and tourism development: A causality analysis on BRI listed economies. Tourism Economics, 2020, 26(6): 926-957. DOI: 10.1177/1354816619846251.

[11] Jia S. Behind the ratings: Text mining of restaurant customers’ online reviews. International Journal of Market Research, 2018, 60(6): 561-572. DOI: 10.1177/1470785317752048.

[12] Yu B, Zhou J, Zhang Y, et al. Identifying restaurant features via sentiment analysis on yelp reviews. arXiv preprint arXiv:1709.08698, 2018. DOI: 10.48550/arXiv.1709.08698.

[13] Yoo K H, Sigala M, Gretzel U. Exploring TripAdvisor. In Open tourism (pp. 239-255). Springer, Berlin, Heidelberg, 2016. DOI: 10.1007/978-3-642-54089-9_17.

[14] Lin M P, Marine-Roig E, Llonch-Molina N. Gastronomic experience (co) creation: Evidence from Taiwan region and Catalonia. Tourism Recreation Research, 2020, 47(3): 277-292. DOI: 10.1080/02508281.2021.1948718.

[15] Oliveira A S, Renda A I, Correia M B, et al. Hotel customer segmentation and sentiment analysis through online reviews: an analysis of selected European markets. Tourism & Management Studies, 2022, 18(1): 29-40. DOI: 10.18089/tms.2022.180103.