Cognitive Absorption: Its Effect on Online Shopping App User Interest

Astra Prima Budiarti, Awisal Fasyni, Rizki Sri Lasmini


The purpose of this study is to analyze the role of cognitive absorption in affecting a user's desire to use online shopping application on a regular basis. The methodologies used in this investigation are quantitative method. Primary data were collected through delivering questionnaires to individuals who met the criteria. Users of e-commerce application like Tokopedia, Shopee, Bukalapak, Lazada, Blibli, and others make up the study's demographic. A total of 253 respondents was randomly sampled using the accidental sampling method. Structural Equation Model (SEM) analysis is used in this study. The findings of this study indicate that cognitive absorption did not affect continuance intention directly, but the indirect effect construct a significant relationship. The indirect effect is derived from the mediation of the variables of perceived usefulness and satisfaction.


Continuance Intention, Cognitive Absorption, Perceived Usefulness, Satisfaction

Full Text:



Agarwal, R., Sambamurthy, V., & Stair, R. M. (1997). Cognitive absorption and the adoption of new information technologies. Academy of Management Proceedings,

Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly: Management Information Systems, 24(4), 665-694.

Balakrishnan, J., & Dwivedi, Y. K. (2021). Role of cognitive absorption in building user trust and experience. Psychology and Marketing, 38(4).643-668

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly: Management Information Systems, 25(3),251-370.

Daneji, A. A., Ayub, A. F. M., & Khambari, M. N. M. (2019). The effects of perceived usefulness, confirmation and satisfaction on continuance intention in using massive open online course (MOOC). Knowledge Management and E-Learning, 11(2), 201–214.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14). 1111-1132,

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319-339

Duy Phuong, N. N., Luan, L. T., van Dong, V., & le Nhat Khanh, N. (2020). Examining customers’ continuance intentions towards e-wallet usage: The emergence of mobile payment acceptance in Vietnam. Journal of Asian Finance, Economics and Business, 7(9), 505-516

Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. In European Business Review 26, (2), 106-121

Halilovic, S., & Cicic, M. (2013). Antecedents of information systems user behaviour-extended expectation-confirmation model. Behaviour and Information Technology, 32(4), 359-370

Hausman, A. v., & Siekpe, J. S. (2009). The effect of web interface features on consumer online purchase intentions. Journal of Business Research, 62(1, 5-13.

Hoffman, D. L., & Novak, T. P. (2009). Flow Online: Lessons Learned and Future Prospects. Journal of Interactive Marketing, 23(1), 23-34

Jahanmir, S. F., Silva, G. M., Gomes, P. J., & Gonçalves, H. M. (2020). Determinants of users’ continuance intention toward digital innovations: Are late adopters different? Journal of Business Research, 115(C), 225-233

Jumaan, I. A., Hashim, N. H., & Al-Ghazali, B. M. (2020). The role of cognitive absorption in predicting mobile internet users’ continuance intention: An extension of the expectation-confirmation model. Technology in Society, 63 (C)

Kim, M. (2022). How can I Be as attractive as a Fitness YouTuber in the era of COVID-19? The impact of digital attributes on flow experience, satisfaction, and behavioral intention. Journal of Retailing and Consumer Services, 64.

Koufaris, M. (2002). Applying the Technology Acceptance Model and flow theory to online Consumer Behavior. Information Systems Research, 13(2), 205-223

Leong, P. (2011). Role of social presence and cognitive absorption in online learning environments. Distance Education, 32(1),5-28

Lin, H. F. (2009). Examination of cognitive absorption influencing the intention to use a virtual community. Behaviour and Information Technology, 28(5), 421-431

Marmer, M., Herrmann, B. L., Dogrultan, E., Berman, R., Eesley, C. E., & Blank, S. (2011). Startup Genome Report Extra on Premature Scaling. Genome, 2(March).

Mpinganjira, M. (2019). Cognitive absorption and behavioural intentions in virtual health communities: A focus on content posters. Journal of Systems and Information Technology, 21(1), 122-145

Saadé, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information and Management, 42(2), 312-327

Schiffman, Leon. G., & Wisenblit, J. (2019). Consumer Behavior 12th Edition, UK: Pearson

Sekaran, U., & Bougie. (2017). Metode Penelitian untuk Bisnis Pendekatan Pengembangan-Keahlian, Jakarta: Salemba Empat

Song, J. H., & Zinkhan, G. M. (2003). Features of Web Site Design, Perceptions of Web Site Quality, and Patronage Behavior. ACME Proceedings.

Tseng, A. (2017). Why do online tourists need sellers’ ratings? Exploration of the factors affecting regretful tourist e-satisfaction. Tourism Management, 59,413-424

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425-478

Visinescu, L. L., Sidorova, A., Jones, M. C., & Prybutok, V. R. (2015). The influence of website dimensionality on customer experiences, perceptions and behavioral intentions: An exploration of 2D vs. 3D web design. Information and Management, 52(1).

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67. 221-232

Zhang, H., Lu, Y., Gupta, S., & Gao, P. (2015). Understanding group-buying websites continuance: An extension of expectation confirmation model. Internet Research, 25(5), 767-793.

Zhou, T. (2014). Understanding continuance usage intention of mobile internet sites. Universal Access in the Information Society, 13(3), 329–337.



  • There are currently no refbacks.

Indexing by:

width="150" crossref
width=150;SINTA - Science and Technology Index


Index Copernicus International (ICI)


TurnitinMendeley - Library 101 Citation Management Tools - Research guides at  University of Toronto


In Collaboration with:


Jurnal Manajemen dan Kewirausahaan

Management Department Faculty of Economics

University of Merdeka Malang

Terusan Dieng Street 62-64, Sukun, Malang City, East Java, 65146, Indonesia
Phone: 081332569864

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.