Statistical Prediction and Marketing Recommendation of Foreign International Students’ Consumer Behavior


  • Xinting Shen



Cross-border; Consumer behaviors research; regression model; Integrated factor analysis model.


Under a dynamic and complex educational market, it forces shape the educational environment. In the context of China, accelerating economic growth produces multiple newly Chinese multinational education institutions, which lack accurate analysis of consumer preference’s inherent characteristics with educational needs. Therefore, this research is vital in helping new Chinese multinational education institutions make decisions based on foreign countries’ students’ consumer preference and further filling the Chinese multinational education institution preference analysis’ gap. In statistics, this paper uses the Data collected from OECD/UIS/Eurostat (2021) Table B6.1, throughout 45 countries, ranging including bachelor's degree, master and doctorates foreign countries students studying in China, to conduct regression analysis intensely observing foreign international students’ Country of Attendance preference. In Marketing, Multi-factor integration model authenticates the overall international student's consumer performance. It is proved that Chinese educational institutions’ attraction is dominantly attributed to stable economic growth, advanced information, and communication technology. Specifically, China has a higher affinity towards OECD country students for courses of tertiary, bachelor, master, and doctoral studies. Foreign international students' preference statistics prediction improved the accuracy of foreign international students’ behaviors towards the Chinese educational area, driving Chinese educational institutions to a more precise and effective marketing strategy. These results shed light on foreign international students' preference for Chinese education, and how should educational institutions change their marketing methods next.


Download data is not yet available.


G. C. Textor. “Leading destinations for Chinese students studying abroad 2015 and 2021.” Statista. Last modified July 21, 2021. Accessed May 3, 2022. Avaliable at:

B. B. Sousa, and F. C. Magalhães. “An Approach on Attachment in Public Marketing and Higher Education Management Contexts.” Higher Education and the Evolution of Management, Applied Sciences, and Engineering Curricula, vol. 1 2019, pp. 151–171.

W. Hu, and Y. Shi. “Prediction of Online Consumers’ Buying Behavior Based on LSTM-RF Model.” 2020 5th International Conference on Communication, Image and Signal Processing (CCISP), 2020.

G. Yang, and P. Zheng. “A Prediction Method of Consumer Behavior Transformation in K12 Educational Institutions.” Frontiers in Educational Research. Francis Academic Press, n.d. Accessed May 3, 2022.

A. Ang, “Multifactor Strategies.” BlackRock. Accessed May 3, 2022. Avaliable at:

N. Stebliuk, and N. Kuzmenko. “Research of Consumer Demand in the Market of Educational Services of Dnipropetrovsk Region.” Economies' Horizons, vol. 3(14), 2021, pp. 64–71.

I. Ajzen, “Consumer Attitudes and Behavior.” Handbook of Consumer Psychology, 2012.

H. Baumgartner, and J. E. M. Steenkamp. “Exploratory Consumer Buying Behavior: Conceptualization and Measurement.” International Journal of Research in Marketing vol. 13, no. 2 1996, pp. 121–137.

OECD/UIS/Eurostat, Table B6.1. See Source section for more information and Annex 3 for notes 2021. Avaliable at:

B. O. Рахманов, “Methodical Bases of Educational Information Environment Formation in the Technical Higher Educational Institutions.” Proceedings of the National Aviation University. Series: Pedagogy, Psychology, vol. 7, 2015.

N. T. Thomas, “A LSTM Based Tool for Consumer Complaint Classification.” 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018.

N. Bulotaite, “University Heritage—an Institutional Tool for Branding and Marketing.” Higher Education in Europe vol. 28, no. 4, 2003, pp. 449–454.

D. Tolbert, "An exploration of the use of branding to shape institutional image in the marketing activities of faith-based higher education institutions." Christian Higher Education vol. 13.4, 2014, pp. 233-249.




How to Cite

Shen, X. (2023). Statistical Prediction and Marketing Recommendation of Foreign International Students’ Consumer Behavior. BCP Business & Management, 36, 7–15.