Citation:

Meenu, Dr. Manpreet Kaur. "Exploring the Link between Behavioural Intention and Actual Use Behaviour in Mobile Shopping Applications: A PLS-SEM Approach" International Research Journal of Economics and Management Studies, Vol. 5, No. 6, pp. 252-257, 2026. Crossref. http://doi.org/10.56472/25835238/IRJEMS-V5I6P128

Abstract:

This study investigates the relationship between behavioural intention and actual use behaviour of mobile shopping applications among consumers in Haryana, India. Using a quantitative research design, data were collected from 560 active mobile shopping app users through a structured questionnaire. The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed hypothesis. The results indicate that there is a highly positive and statistically significant correlation between behaviour intention and actual use behaviour. Suited to the measurement model, assessments of reliability and validity confirmed its robustness. This shows supports of the UTAUT framework which assumes that behavioral intention may lead to action and impact on consumer actual adoption as well as continued use of mobile shopping applications.

References:

[1] Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
[2] Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood-Cliffs, NJ: Prentice-Hall.
[3] Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125–138. https://doi.org/10.1016/ j.jretconser.2017.08.026
[4] Basuroy, T. (2025, April 30). Mobile app usage in India - statistics & facts. Statista. Retrieved July 27, 2025, from https://www.statista.com/topics/5600/mobile-app-usage-in-india/#topicOverview
[5] Basuroy, T. (2025, April 30). Mobile app usage in India - statistics & facts. Statista. Retrieved July 27, 2025, from https://www.statista.com/topics/5600/mobile-app-usage-in-india/#topicOverview
[6] Bellman, S., Potter, R. F., Treleaven-Hassard, S., Robinson, J. A., & Varan, D. (2011). The effectiveness of branded mobile phone apps. Journal of Interactive Marketing, 25(4), 191–200. https://doi.org/10. 1016/j.intmar.2011.06.001
[7] Byrne, B.M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). New York, Routledge.
[8] Celik, H. (2016). Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework. Asia Pacific Journal of Marketing and Logistics, 28(2), 278–307. https://doi.org/10.1108/APJML-05-2015-0077
[9] Chopdar, P. K., & Sivakumar, V. (2019). Impulsiveness and its impact on behavioural intention and use of mobile shopping apps: a mediation model. International Journal of Business Innovation and Research, 19(1), 29. https://doi.org/10.1504/ijbir.2019.099754
[10] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319‐340. https://doi.org/10.2307/249008
[11] Gupta, S. D. (2024a, January 16). Indians spent 12.84 bn hours on shopping apps in 2023, next only to China. www.business-standard.com. https://www.business-standard.com/industry/news/indians-spent-12-84-bn-hours-on-shopping-apps-in-2023-next-only-to-china-124011600795_1.html
[12] Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of multivariate data analysis, 1(2), 107-123.
[13] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24.
[14] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24.
[15] Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications. Long range planning, 45(5-6), 320-340.
[16] Hew, J., Lee, V., Ooi, K., & Wei, J. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems, 115(7), 1269–1291. https://doi.org/10.1108/imds-01-2015-0028
[17] Kaplan, H. E. (2018). Factors determining e-consumer behavior: An empirical research on the theory of planned behavior (TPB). International Review of Management & Business Research, 7(3), 699-711.
[18] Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. https://doi.org/ 10.1177/001316447003000308
[19] Kumar, D. S., Purani, K., & Viswanathan, S. A. (2018). Influences of ‘appscape’ on mobile app adoption and m-loyalty. Journal of Retailing and Consumer Services, 45, 132–141. https://doi.org/10.1016/j .jretconser.2018.08.012
[20] Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, S. (2016). Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention. Procedia Economics and Finance, 35, 401–410. https://doi.org/10.1016/s2212-5671(16)00050-2
[21] Minhas, A. (2025, June 4). E-commerce in India - statistics & facts. Statista. Retrieved July 27, 2025, from https://www.statista.com/topics/2454/e-commerce-in-india/ #topicOverview
[22] Rehman, S. U., Bhatti, A., Mohamed, R., & Ayoup, H. (2019). The moderating role of trust and commitment between consumer purchase intention and online shopping behavior in the context of Pakistan. Journal of Global Entrepreneurship Research, 9(1). https://doi.org/10.1186/s40497-019-0166-2
[23] Sawhney, A. (2025, June 6). ET Graphics: Who shops online the most? The Economic Times. https://economictimes.indiatimes.com/industry/services/retail/et-graphics-who-shops-online-the-most/articleshow/121683613.cms
[24] Singh, S., & Srivastava, S. (2018). Moderating effect of product type on online shopping behaviour and purchase intention: An Indian perspective. Cogent Arts & Humanities, 5, 1495043. https://doi.org/10.1080/23311983.2018.1495043
[25] Singh, V., Chaudhuri, R., & Verma, S. (2019). Psychological antecedents of apparel-buying intention for young Indian online shoppers: Scale development and validation. Journal of Modelling in Management, 14(2), 286–311. https://doi.org/10.1108/JM2-05-2018-0059
[26] Tak, P., & Panwar, S. (2017). Using UTAUT 2 model to predict mobile app based shopping: evidences from India. Journal of Indian Business Research, 9(3), 248–264. https://doi.org/10.1108/JIBR-11-2016-0132
[27] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/3003 6540
[28] Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412

Keywords:

Behavioural Intention, Mobile Shopping Apps, Consumer Adoption, Use Behaviour.