Determination of E-Commerce Shopping Intentions among Students in Manado City: A Theory of Planned Behavior Approach: JEL Classification: D12, D91, M31, O33, L81

Paske Victory Modaso; Durand Fernandito Freddy  Setlight; Titya Advianti P.  Barek

doi:10.55885/jmap.v6i1.886

Authors

Paske Victory Modaso Akademi Bisnis dan Keuangan Primaniyarta, Indonesia
Durand Fernandito Freddy Setlight Akademi Bisnis dan Keuangan Primaniyarta, Indonesia
Titya Advianti P. Barek Akademi Bisnis dan Keuangan Primaniyarta, Indonesia

DOI:

https://doi.org/10.55885/jmap.v6i1.886

Keywords:

E-Commerce, Shopping Intention, Theory of Planned Behavior, Students

Abstract

This study aims to analyze the determinants of e-commerce shopping intentions among students in Manado City using the Theory of Planned Behavior (TPB) framework. A quantitative explanatory approach was employed, with data collected through structured questionnaires distributed to 90 school and university students who had prior experience using e-commerce platforms. The data were analyzed using multiple linear regression with SPSS. The results indicate that attitude, subjective norm, and perceived behavioral control all have a positive and significant effect on students’ e-commerce shopping intentions. Attitude was found to be the strongest predictor, followed by perceived behavioral control and subjective norm. The regression model demonstrates strong explanatory power, with the TPB variables explaining 71.7% of the variance in shopping intention. These findings confirm the relevance of the Theory of Planned Behavior in explaining e-commerce shopping intentions among students in a regional urban context. The study contributes to the literature on digital consumer behavior by providing empirical evidence from Manado City and offers practical insights for e-commerce platforms and educational stakeholders in designing strategies that align with students’ psychological and social characteristics.

References

Al‐Maghrabi, T., & Dennis, C. (2011). What drives consumers' continuance intention to e‐shopping? Conceptual framework and managerial implications in the case of Saudi Arabia. International Journal of Retail & Distribution Management, 39(12), 899-926. https://doi.org/10.1108/09590551111183308

Al-Mamary, Y. H. S., Siddiqui, M. A., Abdalraheem, S. G., Jazim, F., Abdulrab, M., Rashed, R. Q., ... & Aliyu Alhaji, A. (2024). Factors impacting Saudi students’ intention to adopt learning management systems using the TPB and UTAUT integrated model. Journal of Science and Technology Policy Management, 15(5), 1110-1141. https://doi.org/10.1108/JSTPM-04-2022-0068

Bujang, M. A., Sa’at, N., & Bakar, T. M. I. T. A. (2017). Determination of minimum sample size requirement for multiple linear regression and analysis of covariance based on experimental and non-experimental studies. Epidemiology, biostatistics, and public health, 14(3). https://doi.org/10.2427/12117

Darley, W. K., Blankson, C., & Luethge, D. J. (2010). Toward an integrated framework for online consumer behavior and decision making process: A review. Psychology & marketing, 27(2), 94-116. https://doi.org/10.1002/mar.20322

Delfmann, W., Albers, S., & Gehring, M. (2002). The impact of electronic commerce on logistics service providers. International journal of physical distribution & logistics management, 32(3), 203-222. https://doi.org/10.1108/09600030210426539

Dewi, G. D. P., & Lusikooy, A. E. (2023). E-commerce transformation in Indonesia: Innovation and creative destruction. Nation State: Journal of International Studies, 6(2), 117-138. https://doi.org/10.24076/nsjis.v6i2.1304

Dodor, J. B. K., & Rana, D. S. (2009). Investigating business schools' intentions about offering e‐commerce education using an extended theory of planned behavior. Decision Sciences Journal of Innovative Education, 7(1), 195-220. https://doi.org/10.1111/j.1540-4609.2008.00213.x

Downes, J. M., & Bishop, P. (2012). Educators engage digital natives and learn from their experiences with technology: Integrating technology engages students in their learning. Middle School Journal, 43(5), 6-15. https://doi.org/10.1080/00940771.2012.11461824

Ebert, J. F., Huibers, L., Christensen, B., & Christensen, M. B. (2018). or web-based questionnaire invitations as a method for data collection: cross-sectional comparative study of differences in response rate, completeness of data, and financial cost. Journal of medical Internet research, 20(1), e24. https://doi.org/10.2196/jmir.8353

Evans, C., & Robertson, W. (2020). The four phases of the digital natives debate. Human behavior and emerging technologies, 2(3), 269-277. https://doi.org/10.1002/hbe2.196

Fashola, A. A., & Kusuma, F. (2024). E-Commerce Development for the Digital Economy in Indonesia. Act. Yuris J. Huk, 4(2).

Fauzi, R. U. A., Juliana, J., Djakasaputra, A., Pramono, R., Antonio, F., & Purwanto, A. (2021). The role of attitude, subjective norms and usefullnes on e-commerce intention and behavior. Academic Journal of Digital Economics and Stability, 11, 55-72.

Gatta, V., Marcucci, E., & Le Pira, M. (2023). E-commerce and urban logistics: trends, challenges, and opportunities. Handbook on city logistics and urban freight, 422-443. https://doi.org/10.4337/9781800370173.00033

Gifford, R., & Nilsson, A. (2014). Personal and social factors that influence pro‐environmental concern and behaviour: A review. International journal of psychology, 49(3), 141-157. https://doi.org/10.1002/ijop.12034

Hamid, S., Azhar, M., & Sujood. (2023). Behavioral intention to order food and beverage items using e-commerce during COVID-19: an integration of theory of planned behavior (TPB) with trust. British Food Journal, 125(1), 112-131. https://doi.org/10.1108/BFJ-03-2021-0338

Han, F., & Li, B. (2021). Exploring the effect of an enhanced e-commerce institutional mechanism on online shopping intention in the context of e-commerce poverty alleviation. Information Technology & People, 34(1), 93-122. https://doi.org/10.1108/ITP-12-2018-0568

Heptariza, A. (2020). The effect of attitude, normal subjective and perceived behavioral control (PBC) on actual purchasing through purchases of online purchase in the online retail industry. Jurnal Ekonomi & Bisnis JAGADITHA, 7(1), 9-17. https://doi.org/10.22225/jj.7.1.583.9-17

Iqbal, I. (2020). The effect of attitude, subjective norm and perceived behavioral control on students’ intention to choose sharia economics study programs. The effect of attitude, subjective norm and perceived behavioral control on students’ intention to choose sharia economics study programs, 10(13), 1-8.

Jannah, M., Mahmuda, Z., & Alankrita, A. (2025). The Digital Economy Boom: How E-Commerce is Reshaping Indonesia’s Market. Indonesia Discourse, 2(1), 33-58.

Kashif, M., Zarkada, A., & Ramayah, T. (2018). The impact of attitude, subjective norms, and perceived behavioural control on managers’ intentions to behave ethically. Total Quality Management & Business Excellence, 29(5-6), 481-501.

Kelley, K., & Maxwell, S. E. (2003). Sample size for multiple regression: obtaining regression coefficients that are accurate, not simply significant. Psychological methods, 8(3), 305.

Knofczynski, G. T., & Mundfrom, D. (2008). Sample sizes when using multiple linear regression for prediction. Educational and psychological measurement, 68(3), 431-442. https://doi.org/10.1177/0013164407310131

Kobylińska, U. (2022). Attitudes, subjective norms, and perceived control versus contextual factors influencing the entrepreneurial intentions of students from Poland. WSEAS Transactions on Business and Economics, 19(1), 94-106.

Kowsar, A. M., Roy, S. S., & Kabir, A. J. (2025). Online Consumer Behavior in Bangladesh: A Comprehensive Review of Ecommerce Adoption, Trust, and Socio-Cultural Dynamics Online Consumer Behavior. International Journal of Social and Business Studies, 3(1), 90-110.

Lăzăroiu, G., Neguriţă, O., Grecu, I., Grecu, G., & Mitran, P. C. (2020). Consumers’ decision-making process on social commerce platforms: Online trust, perceived risk, and purchase intentions. Frontiers in psychology, 11, 890.

Lestari, A. P., Fatiha, S. A., & Putri, S. O. (2024). E-Commerce in Indonesia's Economic Transformation and Its Influence on Global Trade. International Journal of Computer in Law & Political Science, 4, 10-23.

Lester, D. H., Forman, A. M., & Loyd, D. (2006). Internet shopping and buying behavior of college students. Services Marketing Quarterly, 27(2), 123-138. https://doi.org/10.1300/J396v27n02_08

Mindell, J., Aresu, M., Bécares, L., & Tolonen, H. (2012). Representativeness of participants in a cross-sectional health survey by time of day and day of week of data collection. The European Journal of Public Health, 22(3), 364-369. https://doi.org/10.1093/eurpub/ckr093

Mishra, G. P., Mishra, K. L., & Sahdeo, S. N. (2025). An Empirical Study of the Synergistic Effect of the Theory of Planned Behaviour (TPB) & Unified Theory of Acceptance and Use of Technology (UTAUT) with Reference to the Purchase Intention of Electric Vehicles (EVS). Advances in Consumer Research, 2, 34-45.

Niu, H. J. (2013). Cyber peers’ influence for adolescent consumer in decision‐making styles and online purchasing behavior. Journal of Applied Social Psychology, 43(6), 1228-1237. https://doi.org/10.1111/jasp.12085

Noor, N. M., Noranee, S., Zakaria, M. F., Unin, N., & Suaee, M. A. H. M. (2020, February). Online shopping: The influence of attitude, subjective norm and perceived behavioral control on purchase intention. In Proceedings of the 2020 the 6th International Conference on E-Business and Applications (pp. 33-36). https://doi.org/10.1145/3387263.3387266

Ofori, D., & Appiah-Nimo, C. (2019). Determinants of online shopping among tertiary students in Ghana: An extended technology acceptance model. Cogent Business & Management, 6(1), 1644715.

Rahman, I., Muhtar, M. H., Mongdong, N. M., Setiawan, R., Setiawan, B., & Siburian, H. K. (2024). Harmonization of Digital laws and Adaptation Strategies in Indonesia focusing on E-Commerce and Digital transactions. Innovative: Journal Of Social Science Research, 4(1), 4314-4327. https://doi.org/10.31004/innovative.v4i1.8240

Rahman, M. M., Lesch, M. F., Horrey, W. J., & Strawderman, L. (2017). Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accident Analysis & Prevention, 108, 361-373. https://doi.org/10.1016/j.aap.2017.09.011

Rhodes, R. E., & Courneya, K. S. (2005). Threshold assessment of attitude, subjective norm, and perceived behavioral control for predicting exercise intention and behavior. Psychology of Sport and Exercise, 6(3), 349-361. https://doi.org/10.1016/j.psychsport.2004.04.002

Ruiz-Herrera, L. G., Valencia-Arias, A., Gallegos, A., Benjumea-Arias, M., & Flores-Siapo, E. (2023). Technology acceptance factors of e-commerce among young people: An integration of the technology acceptance model and theory of planned behavior. Heliyon, 9(6).

Saenghiran, T., & Chaipoopirutana, S. (2023). A dynamic model of factors influencing of trust, attitude, subjective norm, and perceived behavior control on e-commerce repurchase intention towards Generation Z in Thailand. Social Science Asia, 9(1).

Setijanto, D., & Bramantoro, T. (2019). The role of attitude, subjective norm, and perceived behavioral control (PBC) of mothers on teaching toothbrushing to preschool children–based on the theory of planned behavior: a cross-sectional study. Family Medicine & Primary Care Review, (1), 53-57.

Sujood, Bano, N., & Siddiqui, S. (2024). Consumers' intention towards the use of smart technologies in tourism and hospitality (T&H) industry: a deeper insight into the integration of TAM, TPB and trust. Journal of Hospitality and Tourism Insights, 7(3), 1412-1434. https://doi.org/10.1108/JHTI-06-2022-0267

Supriadi, A., Judijanto, L., & Rizani, A. (2024). Economic transformation of Indonesia in the era of digital 5.0: Challenges and opportunities. International Journal of Financial Economics, 1(6), 122-135.

Turunen, M., Paanala, A., Villman, J., Nevalainen, A., & Haverinen-Shaughnessy, U. (2010). Evaluating housing quality, health and safety using an Internet-based data collection and response system: a cross-sectional study. Environmental health, 9(1), 69. https://doi.org/10.1186/1476-069X-9-69

Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting Different Conceptualizations of System Use: The Competing Roles of Behavioral Intention, Facilitating Conditions, and Behavioral Expectation1. MIS quarterly, 32(3), 483-502. https://doi.org/10.2307/25148853

Wang, M., & Yang, W. (2021). What drives rural consumers to change e-commerce attitude and adopt e-commerce through the moderating role of corporate social responsibility in an emerging market? An empirical investigation in the Chinese context. Sustainability, 13(23), 13148. https://doi.org/10.3390/su132313148

Wang, Y., & Zhang, Z. (2023). A study on the willingness and factors influencing the digital upgrade of rural e-commerce. Behavioral Sciences, 13(2), 95. https://doi.org/10.3390/bs13020095

Weryani, W., Lisniawati, L., Hamsani, H., & Wardhani, R. S. (2024, December). E-Commerce Trends in Indonesia: A Literature Review on Adaptation and Consumer Behavior. In 1st International Conference of Economics, Management, Accounting, and Business Digital (pp. 35-41). Atlantis Press. https://doi.org/10.2991/978-94-6463-614-7_6