The Use of English Business Terminology in Commercial Livestreams on Gen Z Customers’ Purchase Intention

Authors

Dang Tien Thang

Saigon University (Vietnam)

Nguyen Bao Giang

Saigon University (Vietnam)

Pham Ngoc Diem

Saigon University (Vietnam)

Le Quoc Thang

Saigon University (Vietnam)

Article Information

DOI: 10.51584/IJRIAS.2026.11030040

Subject Category: language

Volume/Issue: 11/3 | Page No: 412-426

Publication Timeline

Submitted: 2026-03-04

Accepted: 2026-03-09

Published: 2026-04-03

Abstract

English plays a crucial role in advancing the connection between customer and seller in the international market, especially in e-commerce. The use of English business terminology has become increasingly common in commercial livestream sessions on TikTok. However, proving that its use affects the purchase intention has still not been explored in prior studies.
Therefore, this study would fill this gap by surveying 242 Gen Z customers in Ho Chi Minh City through the questionnaire. The findings demonstrated that customers' trust and engagement are affected significantly by English business terminology, but the purchase intention is not affected. Additionally, customers’ trust and engagement play the mediating role between the use of English business terminology and purchase intention.
These detections showed the important part of English business terminology in enhancing the trust and interaction during livestream commerce. Furthermore, it also provides some implications for exploring the influence of language in online trading.

Keywords

Commercial livestream, English business terminology, purchase intention, interaction, influence.

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References

1. Ahn, J., La Ferle, C., & Lee, D. (2017). Language and advertising effectiveness: Codeswitching in the Korean marketplace. International Journal of Advertising, 36(3), 477–495. https://doi.org/10.1080/02650487.2015.1128869 [Google Scholar] [Crossref]

2. Ariffin, N. M., Fikry, A., Shobri, N. D. M., & Ilias, I. S. C. (2024). A Review of Tiktok Livestreaming Commerce. Information Management and Business Review, 16(3), 67-77. [Google Scholar] [Crossref]

3. Bagozzi, R. and Yi, Y. (1988) On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16, 74-94. http://dx.doi.org/10.1007/BF02723327 [Google Scholar] [Crossref]

4. Blom, J. P., & Gumperz J. (1972). Social meaning in linguistic structure: Code-switching in Norway. In J. Gumperz, & D. Hymes (Eds.), Directions in sociolinguistics. New York: Holt, Rinehart and Winston. [Google Scholar] [Crossref]

5. Chuang S. C., Tsai C. C., Cheng Y. H., and Sun Y. C. (2009) The effect of terminologies on attitudes toward advertisements and brands:Consumer product knowledge as a moderator. Journal of Business and Psychology, 24(4):485–491 [Google Scholar] [Crossref]

6. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale. NJ: Lawrence Erlbaum Associates Inc, 19. [Google Scholar] [Crossref]

7. DataReportal. (2025, March 12). TikTok Users, Stats, Data & Trends for 2025. Retrieved January 30, 2026, from https://datareportal.com/essential-tiktok-stats. [Google Scholar] [Crossref]

8. DeVellis, R.F. (2012) Scale development: Theory and applications. Los Angeles: Sage. pp. 109–110 [Google Scholar] [Crossref]

9. Djafarova, E., & Rushworth, C. (2017). Exploring the credibility of online celebrities' Instagram profiles in influencing the purchase decisions of young female users. Computers in Human Behavior, 68, 1–7. https://doi.org/10.1016/j.chb.2016.11.009 [Google Scholar] [Crossref]

10. Dondolo, B., & Mushaathoni, M. (2025). Communication through Shifting Lingua Franca: Surveying Followers’ Perceptions of Influencers’ Code-Switching in Social Media. African Journal of Inter Multidisciplinary Studies, 7(1), 1–11. [Google Scholar] [Crossref]

11. Fang, Y., Y. Zhang, and Y. Sun. 2022. “Trust or Doubt? Understanding the Mechanisms of Jargon Use on Doubt From the Source Credibility Perspective.” PACIS 2022 Proceedings, Article 157. https://aisel.aisnet.org/pacis2022/157 [Google Scholar] [Crossref]

12. Ferdous, S., Joher, U. H. M., & Rony, H. A. Z. (2023). Influence of social media on code-switching and code-mixing behaviour among the young generation of Bangladesh. BELTA Journal, 7(1), 1–12. https://doi.org/10.36832/beltaj.2023.0701.06 [Google Scholar] [Crossref]

13. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519 [Google Scholar] [Crossref]

14. Haarmann, H. (1989). Symbolic Values of Foreign Language Use: From the Japanese Case to a General Sociolinguistic Perspective. Berlin: Mouton de Gruyter. [Google Scholar] [Crossref]

15. Hair, J.F., Sarstedt, M., Ringle, C.M. and Mena, J.A. (2012). An assessment of the use of partial leastsquares structural equation modeling in marketing research”, Journal of the Academy of MarketingScience, 40(3), pp. 414-433. [Google Scholar] [Crossref]

16. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (1st ed.). Thousand Oaks, CA: Sage publications. [Google Scholar] [Crossref]

17. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. [Google Scholar] [Crossref]

18. Hair, J.F., Risher, J.J., Sarstedt, M.and Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), pp. 2-24. [Google Scholar] [Crossref]

19. Hong, C. (2002). The influence of the terminology to the customer’s attitude and purchase intension—The interfering effect of the product’s innovativeness. Master’s Thesis, Department of Business Administration, Fu-jun University, Taiwan. [Google Scholar] [Crossref]

20. Henseler, J., Ringle, C.M. and Sarstedt, M. (2015). A new criterion for assessing discriminant validity invariance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), pp. 115-135 [Google Scholar] [Crossref]

21. Hermanda, A., Sumarwan, U., & Tinaprillia, N. (2019). The effect of social media influencer on brand image, self-concept, and purchase intention. Journal of Consumer Sciences, 4(2), 76-89. https://doi.org/10.29244/jcs.4.2.76-89 [Google Scholar] [Crossref]

22. Jurayeva, M. M. (2024). Features of International Advertising Terms. Information Horizons: American Journal of Library and Information Science Innovation, 2(12), 36-39. [Google Scholar] [Crossref]

23. Junsom, R., & Jeanjaroonsri, R. (2021). The attitudes of Instagram users toward code-mixing in Instagram advertising: A case study of an international study consulting company (Doctoral dissertation, Thammasat University). [Google Scholar] [Crossref]

24. Kelly-Holmes, H. (2000) Bier, parfum, kaas: Language fetish in European advertising. European Journal of Cultural Studies, 3(1), 67-82. [Google Scholar] [Crossref]

25. Ketut, P. N. S. N., Islam, R. F., Miswaty, T. C., Suparlan, S., & Reliubun, A. S. (2024). Language strategies in tourism: Analysing code-switching among Sasak tour guides on Social Media. J-CEKI: Jurnal Cendekia Ilmiah, 4(1), 1525-1533. https://doi.org/10.56799/jceki.v4i1.6295 [Google Scholar] [Crossref]

26. Kuo, Y. F., Hou, J. R., & Hsieh, Y. H. (2021). The advertising communication effectiveness of using netizen language code-switching in Facebook ads. Internet Research, 31(5), 1940–1962. https://doi.org/10.1108/INTR-04-2020-0231 [Google Scholar] [Crossref]

27. Luna, D., & Peracchio, L. A. (2005). Advertising to Bilingual Consumers: The Impact of Code‐Switching on Persuasion. Journal of Consumer Research, 31(4), 760–765. https://doi.org/10.1086/426609 [Google Scholar] [Crossref]

28. Myers-Scotton, C. (1993). Common and uncommon ground: Social and structural factors in codeswitching. Language in Society, 22(4), 475–503. https://doi.org/10.1017/S0047404500017449 [Google Scholar] [Crossref]

29. Nguyen, T. T. H. (2025). Nghiên cứu hiện tượng đồng nghĩa thuật ngữ kinh tế thương mại trong tiếng Anh. VNU Journal of Foreign Studies, 41(2), 58-72. [Google Scholar] [Crossref]

30. Oktaviana, A. A., Mahyuni, A., & Yusra, K. (2024). The use of translanguaging in social media: A case study of Gen Z. Journal of English Education Forum, 1. [Google Scholar] [Crossref]

31. Phuong, N. N. Y., & Long, N. N. (2025). CÁC YẾU TỐ TÁC ĐỘNG TỪ LIVESTREAM BÁN HÀNG TRÊN NỀN TẢNG TIKTOK ĐẾN Ý ĐỊNH MUA HÀNG CỦA GIỚI TRẺ TẠI THÀNH PHỐ HỒ CHÍ MINH. Journal of Science and Technology-IUH, 74(2). [Google Scholar] [Crossref]

32. Priporas, C. V., Stylos, N., & Fotiadis, A. K. (2017). Generation Z consumers’ expectations of interactions in smart retailing: A future agenda. Computers in Human Behavior, 77, 374–381. https://doi.org/10.1016/j.chb.2017.01.058 [Google Scholar] [Crossref]

33. Putri, D. M. J., & Luthfia, A. (2025). Persuasive Linguistic Style and Customer Trust in TikTok Live Streaming Commerce: The Mediating Role of Customer Engagement. PaperASIA, 41(5b), 513–529. https://doi.org/10.59953/paperasia.v41i5b.742 [Google Scholar] [Crossref]

34. Roslini, F.N., Mohamad, F., Kadir, Z.A., Johar, E.M., & Yuan, W. (2025). Viewers’ Perceptions towards the Use of Code-Switching in Tiktok Advertisements in Relation to Brand Recognition, Viewers’ Trust and Viewers’ Engagement. International Journal of Research and Innovation in Social Science. [Google Scholar] [Crossref]

35. Sanjaya, D. E., Barkah, N. A., & Sulistiowati, I. D. (2023). The Effect of Price Promotion, Promotion Time Limit, and Interpersonal Interaction on Indonesian Consumers’ Online Purchase Intention through the TikTok Live Streaming Platform. Scientific Research Journal of Economics and Business Management, 3(1), 76-87. [Google Scholar] [Crossref]

36. Tran, Q.V. (2016). Thuật ngữ kinh tế thương mại tiếng Anh và các biểu thức tương đương của chúng trong tiếng Việt [Google Scholar] [Crossref]

37. Xie, C., Yu, J., Huang, S., & Zhang, J. (2022). Tourism e-commerce live streaming: identifying and testing a value-based marketing framework from the live streamer perspective. Tourism Management, 91, 104513. https://doi.org/10.1016/j.tourman.2022.104513 [Google Scholar] [Crossref]

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