ISSN: 2222-6990
Open access
This study investigates the relationship between four dimensions of CQ (metacognitive, cognitive, motivational, and behavioral) and satisfaction with the communication of Shopee's AI chatbots, as well as whether such relationships are statistically explained by the perception of the quality of communication. CQ in a multi-ethnic market, like Malaysia, in customers' encounters with chatbots has been under-researched. The subjects were recruited using purposive and snowball sampling to yield 196 valid responses from Malaysian consumers aged 18 to 24 who used Shopee's chatbot or in-app virtual customer service in the last six months and were sampled quantitatively in a cross-sectional design. There were 35 items on a Likert scale, which measured six constructs, and the data were analyzed using reliability analysis, Pearson correlation, multiple regression, and Sobel tests in SPSS. All constructs were reliable (? = .803–.852). The four CQ dimensions accounted for 58.0% of the variance in satisfaction, with motivational (? = .383), metacognitive (? = .357), behavioral (? = .162), and cognitive (? = .130) CQ having the largest standardized beta coefficients. The quality of communication was strongly correlated with satisfaction (r = .714), and Sobel tests were significant for all four dimensions of CQ (all between Z = 5.71 and 6.31, p < .001), with bootstrap confidence intervals excluding zero and direct effects remaining significant (partial mediation). The construct with the lowest score (M = 2.96) was Satisfaction (M = 2.96), while CQ means ranged between 3.68 and 4.22. The results bring CQ to human-AI service interactions and call for platforms to design for CQ. Since this information is cross-sectional and self-reported, these findings suggest associations, not causal relationships.
Ang, S., Van Dyne, L., Koh, C., Ng, K. Y., Templer, K. J., Tay, C., & Chandrasekar, N. A. (2007). Cultural intelligence: Its measurement and effects on cultural judgment and decision making, cultural adaptation and task performance. Management and Organization Review, 3(3), 335–371. https://doi.org/10.1111/j.1740-8784.2007.00082.x
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020). I, Chatbot: Modeling the determinants of users' satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473. https://doi.org/10.1016/j.tele.2020.101473
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587–595. https://doi.org/10.1016/j.jbusres.2018.10.004
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.
Costers, A., Van Vaerenbergh, Y., & Van den Broeck, A. (2019). How to boost frontline employee service recovery performance: The role of cultural intelligence. Service Business, 13(3), 581–602. https://doi.org/10.1007/s11628-019-00396-3
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE.
Crolic, C., Thomaz, F., Hadi, R., & Stephen, A. T. (2022). Blame the bot: Anthropomorphism and anger in customer–chatbot interactions. Journal of Marketing, 86(1), 132–148. https://doi.org/10.1177/00222429211045687
Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1(1), 16–29.
Department of Statistics Malaysia. (2026). Current population estimates, Malaysia, 2026. https://www.dosm.gov.my
Earley, P. C., & Ang, S. (2003). Cultural intelligence: Individual interactions across cultures. Stanford University Press.
Følstad, A., & Skjuve, M. (2019). Chatbots for customer service: User experience and motivation. In Proceedings of the 1st International Conference on Conversational User Interfaces (Article 1). ACM. https://doi.org/10.1145/3342775.3342784
Giles, H. (1973). Accent mobility: A model and some data. Anthropological Linguistics, 15(2), 87–105.
Giles, H., & Ogay, T. (2007). Communication accommodation theory. In B. B. Whaley & W. Samter (Eds.), Explaining communication: Contemporary theories and exemplars (pp. 293–310). Lawrence Erlbaum.
Green, S. B. (1991). How many subjects does it take to do a regression analysis? Multivariate Behavioral Research, 26(3), 499–510.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104–121. https://doi.org/10.1177/109442819800100106
Huang, M.-H., & Rust, R. T. (2021). Engaged to a robot? The role of AI in service. Journal of Service Research, 24(1), 30–41. https://doi.org/10.1177/1094670520902266
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7(1), 83–104. https://doi.org/10.1037/1082-989X.7.1.83
MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99–128. https://doi.org/10.1207/s15327906mbr3901_4
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. MIT Press.
Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103. https://doi.org/10.1111/0022-4537.00153
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405
Oliver, R. L. (1997). Satisfaction: A behavioral perspective on the consumer. McGraw-Hill.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.
Paparoidamis, N. G., Tran, T. T. H., & Leonidou, C. N. (2019). Building customer loyalty in intercultural service encounters: The role of service employees' cultural intelligence. Journal of International Marketing, 27(2), 56–75.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–731.
Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson.
Sharma, P., Tam, J. L. M., & Kim, N. (2009). Demystifying intercultural service encounters: Toward a comprehensive conceptual framework. Journal of Service Research, 12(2), 227–242. https://doi.org/10.1177/1094670509340209
Sheehan, B., Jin, H. S., & Gottlieb, U. (2020). Customer service chatbots: Anthropomorphism and adoption. Journal of Business Research, 115, 14–24. https://doi.org/10.1016/j.jbusres.2020.04.030
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312. https://doi.org/10.2307/270723
Van Dyne, L., Ang, S., Ng, K. Y., Rockstuhl, T., Tan, M. L., & Koh, C. (2012). Sub-dimensions of the four factor model of cultural intelligence: Expanding the conceptualization and measurement of cultural intelligence. Social and Personality Psychology Compass, 6(4), 295–313. https://doi.org/10.1111/j.1751-9004.2012.00429.x
West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). SAGE.
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31–46. https://doi.org/10.2307/1251928
Dilshad, S. K., Singh, J. S. K., Din, N. N. O., & Pereira, C. R. (2026). Measuring Consumer Cultural Intelligence and Customer Satisfaction through AI Chatbot Service with the Mediating Role of Communication: Evidence from Shopee Users in Malaysia. International Journal of Academic Research in Business and Social Sciences, 16(11), 581–602.
Copyright: © 2026 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode