Online purchasing intention using the technology acceptance model (TAM) approach

Economic Annals-ХХI: Volume 193, Issue (9-10), Pages: 85-91

Citation information:
Sidanti, H., Murwani, F. D., Wardhana, E. T. D. R. W., & Sopiah (2021). Online purchasing intention using the technology acceptance model (TAM) approach. Economic Annals-XXI, 193(9-10), 85-91. doi: https://doi.org/10.21003/ea.V193-10


Heny Sidanti
PhD Student (Economics),
Department of Management,
Universitas Negeri Malang;
Lecturer,
University PGRI Madiun
Jl. Semarang 5 Malang, East Java, 65145, Indonesia
henysidanti1904139@students.um.ac.id
heny.sidanti@unipma.ac.id
ORCID ID: https://orcid.org/0000-0002-8785-9883

Fulgentius Danardana Murwani
PhD (Economics),
Professor,
Faculty of Economics,
Universitas Negeri Malang
Jl. Semarang 5 Malang, East Java, 65145, Indonesia
f.danardana.fe@um.ac.id
ORCID ID: https://orcid.org/0000-0002-1379-9136

Ery Tri Djatmika Rudijanto Wahyu Wardhana
PhD (Economics),
Professor,
Faculty of Economics,
Universitas Negeri Malang
Jl. Semarang 5 Malang, East Java, 65145, Indonesia
ery.tri.fe@um.ac.id
ORCID ID: https://orcid.org/0000-0003-0222-0827

Sopiah
Lecturer,
Faculty of Economics,
Universitas Negeri Malang
Jl. Semarang 5 Malang, East Java, 65145, Indonesia
sopiah.fe@um.ac.id
ORCID ID: https://orcid.org/0000-0003-1063-0906

Online purchasing intention using the technology acceptance model (TAM) approach

Abstract. The purpose of this research is to exposure review about several factors of online Purchasing Intention as a form of how consumers behave in accepting digital technology and have an interest in doing behavior. In fact, that the individuals tend to do this behavior, this study uses the Technology Acceptance Model (TAM) approach. The importance of understanding one’s behavior in acceptance technology, the technology acceptance model known as the TAM is growing along with the advancement of information technology itself and changes in user behavior, TAM Model 1, the actual technology use variable is influenced by the perceived usefulness variable, perceived ease of use, attitude towards using technology, and behavioral intention to use. Due to the actual technology use cannot be observed by researchers using a list of questions, it is replaced by the name of perceived usage, TAM 2, external variables are added directly, namely social influence processes which include Subjective Norm and Image with moderator variables Voluntariness and Experience; and cognitive instrumental processes which include Job Relevance, Output Quality, and Result Demonstrability. TAM 3, by adding one of them the Computer Self-Efficacy variable as an external variable that affects Perceived Ease of Use, Online Purchasing Intention influenced by the existence of transactional interest in online.

Keywords: E-commerce; Online Purchasing Intention; Technology Acceptance Model (TAM); Micro, Small and Medium-Sized Enterprises

JEL Classifications: C63; L24; L32

Acknowledgments and Funding: The authors received no direct funding for this research.

Contribution: The authors contributed equally to this work.

Data Availability Statement: The dataset is available from the authors upon request.

DOI: https://doi.org/10.21003/ea.V193-10

References

  1. Aderonke, O., & Ayo, C. K. (2010). An Empirical Investigation of the Level of Users’ Acceptance of E-Banking in Nigeria. Journal of Internet Banking and Commerce, 15(1), 1-13.
    http://eprints.covenantuniversity.edu.ng/id/eprint/83
  2. Almousa, M. (2011). Perceived risk in apparel online shopping: a multi dimensional perspective. Canadian Social Science, 7, 23-31.
    https://www.researchgate.net/publication/317039089_Perceived_Risk_
    in_Apparel_Online_Shopping_A_Multi_Dimensional_Perspective_LE_RISQUE_
    PERCU_DANS_DES_ACHATS_EN_LIGNE_D’HABILLEMENT_UNE_PERSPECTIVE_
    DE_DIMENSIONNELLE_MULTIPLE
  3. Ariff, M. M. Sh., Yeow, S. M., Norhayati, Z., Ahamad, Z., Jusoh, A., & Bahari, A. Z. (2012). The Effects of Computer Self-Efficacy and Technology Acceptance Model on Behavioral Intention in Internet Banking Systems. Procedia Social and Behavioral Sciences, 57, 448-452.
    https://doi.org/10.1016/j.sbspro.2012.09.1210
  4. Ajzen, I. (2002). Perceived behavioral control, self‐efficacy, locus of control, and the theory of planned behavior. Journal of applied social psychology, 32(4), 665-683.
    https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
  5. Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324.
    https://doi.org/10.1002/hbe2.195
  6. Chau, P. Y. K., & Hu, P., J. (2002). Examining a model of information technology acceptance by individual professionals: An exploratory study. Journal of Management Information Systems, 18(4), 191-229.
    https://doi.org/10.1080/07421222.2002.11045699
  7. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
    https://www.jstor.org/stable/2632151
  8. Fawzy, S. F., & Esawai, N. (2017). Internet banking adoption in Egypt: Extending technology acceptance model. Journal of Business and Retail Management Research, 12(1), 109-118.
    https://doi.org/10.24052/JBRMR/V12IS01/IBAIEETAM
  9. Fauzi, Irviani, R., Jatiningrum, C., Halim, A., & Supriyadi (2019). Financial management information system within government institution and supply chain strategy: Implementation Technology Acceptance Model (TAM). International Journal of Supply Chain Management, 8(3), 380-388.
    https://ojs.excelingtech.co.uk/index.php/IJSCM/article/view/3222
  10. Fauzi, F., & Jatiningrum, C. (2021). Strengthening institutions theory on modification of technology acceptance model: A study of financial information system for local government. Journal of Socioeconomics and Development, 4(1), 109-119.
    https://doi.org/10.31328/jsed.v4i1.2254
  11. Kim, Y. H., & Kim, D. J. (2005). A study of online transaction self-efficacy, consumer trust, and uncertainty reduction in electronic commerce transaction. Proceedings of the 38th Annual Hawaii International Conference on System Sciences (pp. 170c-170c).
    https://doi.org/10.1109/HICSS.2005.52
  12. Maditinos, D. I., Sarigiannidis, L., & Dimitriadis, E. (2010). The role of perceived risk on Greek internet users’ purchasing intention: an extended TAM approach. International Journal of Trade and Global Markets, 3(1), 99-114.
    https://doi.org/10.1504/IJTGM.2010.030411
  13. Marakarkandy, B., Yajnik, N., & Dasgupta, Ch. (2017). Enabling internet banking adoption: An empirical examination with an augmented technology acceptance model (TAM). Journal of Enterprise Information Management, 30(2), 263-294.
    https://doi.org/10.1108/JEIM-10-2015-0094
  14. Mansour, K. B. (2016). An analysis of business’ acceptance of internet banking: an integration of e-trust to the TAM. Journal of Business & Industrial Marketing, 31(8), 982-994.
    https://doi.org/10.1108/JBIM-10-2016-271
  15. Sharif, A., & Raza, S. A. (2017). The influence of hedonic motivation, self-efficacy, trust and habit on adoption of internet banking: a case of developing country. International Journal of Electronic Customer Relationship Management, 11(1), 1-22.
    https://doi.org/10.1504/IJECRM.2017.10007736
  16. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
    https://doi.org/10.1287/mnsc.46.2.186.11926
  17. Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & management, 41(6), 747-762,
    https://doi.org/10.1016/j.im.2003.08.011
  18. Wessels, L., & Drennan, J. (2010). An investigation of consumer acceptance of M-banking. International Journal of bank marketing, 28(7), 547-568.
    https://doi.org/10.1108/02652321011085194

Received 16.06.2021
Received in revised form 9.07.2021
Accepted 29.07.2021
Available online 19.10.2021