The effect of college students’ technology acceptance on e-commerce adoption
DOI:
https://doi.org/10.26740/bisma.v14n1.p46-62Keywords:
TAM, self-efficacy, anxiety, e-commerce, intention, anxiety; e-commerce; intention; self-efficacy; TAMAbstract
This study aims to investigate e-commerce adoption using extended technology acceptance model (TAM) by adding self-efficacy and anxiety. The research samples included 233 undergraduate students were collected using an online survey form distributed through chat groups and social media. The collected data were analysed using partial least square-structural equation modelling (PLS-SEM) to investigate the proposed hypotheses in the model. This study found that self-efficacy has no impact towards perceived usefulness, self-efficacy has positive significant impact towards perceived ease of use, anxiety has no impact on both perceived usefulness and perceived ease of use, perceived usefulness has positive significant impact towards attitude, perceived ease of use has no impact towards attitude, perceived ease of use has positive significant impact on perceived usefulness, perceived usefulness has no impact towards e-commerce adoption, perceived ease of use has positive significant impact towards e-commerce adoption, and attitude has a positive significant impact towards e-commerce adoption. These findings further confirmed that TAM not only could be used to predict e-ticketing, e-learning, e-payment, and e-commerce purchase adoption but also e-commerce entrepreneurship. This study also further confirmed that the relationship between extended variable such as self-efficacy and anxiety with TAM variables might vary according to where the investigation was being held.
References
APJII. (2017). Infografis Penetrasi & Perilaku Pengguna Internet Indonesia. Jakarta: Asosiasi Penyelenggara Jasa Internet Indonesia. Retrieved July 14th 2020 from https://apjii.or.id/content/read/39/342/Hasil-Survei-Penetrasi-dan-Perilaku-Pengguna-Internet-Indonesia-2017.
APJII. (2019). Infografis Penetrasi & Perilaku Pengguna Internet Indonesia. Jakarta: Asosiasi Penyelenggara Jasa Internet Indonesia Retrieved July 14th 2020 from https://apjii.or.id/survei.
Bailey, A. A., Pentina, I., Mishra, A. S., & Mimoun, M. S. Ben. (2017). Mobile payments adoption by US consumers: An extended TAM. International Journal of Retail & Distribution Management, 45(6), 626-640. https://doi.org/10.1108/ijrdm-08-2016-0144.
Baki, R., Birgoren, B., & Aktepe, A. (2018). A meta analysis of factors affecting perceived usefulness and perceived ease of use in the adoption of e-learning systems. Turkish Online Journal of Distance Education, 19(4), 4-42. https://doi.org/10.17718/tojde.471649
Bennani, A., & Oumlil, R. (2014). Acceptance of E-Entrepreneurship by Future Entrepreneurs in Developing Countries : Case of Morocco. 2014. https://doi.org/10.5171/2014.700742.
BPS. (2019). Berita Resmi Statistik 5 November 2019. Badan Pusat Statistik. Retrieved July 14th 2020 from https://www.bps.go.id/pressrelease/2019/11/05/1565/agustus-2019--tingkat-pengangguran-terbuka--tpt--sebesar-5-28-persen.html
Calisir, F., Altin Gumussoy, C., Bayraktaroglu, A. E., & Karaali, D. (2014). Predicting the intention to use a web?based learning system: Perceived content quality, anxiety, perceived system quality, image, and the technology acceptance model. Human Factors and Ergonomics in Manufacturing & Service Industries, 24(5), 515-531. https://doi.org/10.1002/hfm.20548
Chen, H., & Tseng, H. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and Program Planning, 35(3), 398-406. https://doi.org/10.1016/j.evalprogplan.2011.11.007
Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. Advances in Hospitality and Leisure, 8(2). https://www.researchgate.net/publication/311766005_The_Partial_Least_Squares_Approach_to_Structural_Equation_Modeling.
Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). New York: Elsevier Science.
Falk, R. F., & Miller, N. B. (1992). A Primer for Soft Modeling. Ohio: University of Akron Press.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Boston: Addison-Wesley
Hair, J. F., Ringle, C. M., Hult, G. T. M., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling. New York: SAGE Publications, Inc.
Kala, J. R. K., Wamba, S. F., & Yombia, S. M. K. (2017). Determinants of Facebook adoption and use within the workspace in Catholic University of Central Africa. In World Conference on Information Systems and Technologies (pp. 217-224). Springer, Cham. https://doi.org/10.1007/978-3-319-56541-5_22
Koesmawardhani, N. W. (2015). Nadiem Makarim, Pendiri Go-Jek yang Sudah Bantu 10 Ribu Sopir Ojek. Detik News. Retrieved July 15th 2020 from https://news.detik.com/tokoh/d-2938089/nadiem-makarim-pendiri-go-jek-yang-sudah-bantu-10-ribu-sopir-ojek.
Kulas, J. (2008). SPSS Essentials: Managing and Analyzing Social Sciences Data. New Jersey: John Wiley & Sons.
Letchumanan, M., & Muniandy, B. (2013). Migrating to E?Book: A Study on Perceived Usefulness and Ease of use. Library Hi Tech News, 30(7), 10-16. https://doi.org/10.1108/LHTN-05-2013-0028
Lingga, M. A. (2019). 2020, Transaksi di e-Commerce Diprediksi Capai 12 Miliar Dollar AS. Kompas. Retrieved July 15th 2020 from https://ekonomi.kompas.com/read/2019/02/19/180700126/2020-transaksi-di-e-commerce-diprediksi-capai-12-miliar-dollar-as.
Mahajan, P., & Agarwal, M. (2015). Exploring the Potential of E-Commerce in the Digital Age: Challenges and Opportunities for Commerce Education. IUP Journal of Information Technology, 11(4). https://www.proquest.com/openview/709d47805cc87e04e57775537b8cd665/1?pq-origsite=gscholar&cbl=2029987.
Maranti, E. (2019). LPEM FEB UI: Tokopedia Berpengaruh Besar pada Perekonomian Indonesia. Marketeers. Retrieved July 15th 2020 from https://marketeers.com/lpem-feb-uitokopedia-berpengaruh-besar-pada-perekonomian-indonesia/
Park, Y., Son, H., & Kim, C. (2012). Investigating the determinants of construction professionals' acceptance of web-based training: An extension of the technology acceptance model. Automation in Construction, 22, 377-386. https://doi.org/10.1016/j.autcon.2011.09.016
Purnomo, S. H., & Lee, Y. (2013). E-learning adoption in the banking workplace in indonesia: An empirical study. Information Development, 29(2), 138-153. https://doi:10.1177/0266666912448258
Rahayu, N. (2019). Pertumbuhan E-Commerce Pesat di Indonesia. Warta Ekonomi. Retrieved July 15th 2020 from https://www.wartaekonomi.co.id/read216302/pertumbuhan-e-commerce-pesat-di-indonesia.html.
Saade, R., & Kira, D. (2006). The Emotional State of Technology Acceptance. The Journal of Issues in Informing Science and Information Technology, 3. https://doi.org/10.28945/2945.
Thakkar, S. R., & Joshi, H. D. (2018). Impact of technology availability and self-efficacy on e-learning usage. International Journal for Research in Applied Science & Engineering Technology, 6(4), 2956-2960. https://doi.org/10.22214/ijraset.2018.4492
Yadav, R., Sharma, S. K., & Tarhini, A. (2016). A multi-analytical approach to understand and predict the mobile commerce adoption. Journal of enterprise information management, 29(2), 222-237. https://doi.org/10.1108/JEIM-04-2015-0034
Yusuf, A. S., Busalim, A. H., & Hussin, A. R. C. (2018). Influence of e-WOM engagement on consumer purchase intention in social commerce. Journal of Service Marketing, 32(4), 493-504. https://doi.org/10.1108/JSM-01-2017-0031.
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