Investigation of the Students Behavior in Using Ride-Hailing Applications: Perspectives of Perceived Risk and Environmental Awareness in Technology Acceptance Model (TAM)

Authors

  • Silvani Febriliani Universitas Negeri Surabaya
  • Jaka Nugraha Universitas Negeri Surabaya
  • Jiunn-Woei Lian National Taichung University

DOI:

https://doi.org/10.26740/joaep.v5n3.p187-201

Keywords:

Technology Acceptance Model, Ride-Hailing, Perceived Risk, Environmental Awareness

Abstract

This study aims to provide an analysis of the influence of personal innovativeness on perceived ease of use and perceived risk, the influence of perceived ease of use and perceived risk on behavioral intention, and the influence of environmental awareness on behavioral intention. This study uses the Technology Acceptance Model (TAM) and was conducted on students in the Office Administration Education program from the 2021-2024 cohort, with a sample size of 274 students. Data analysis techniques employed Structural Equation Modeling (SEM)-Generalized Structured Component Analysis (GSCA) using the GSCA-pro software version 1.2.1.0. The results of this study indicate that personal innovativeness has a significant positive influence on perceived ease of use and perceived risk, perceived ease of use has a significant positive influence on behavioral intention, but perceived risk does not have a significant positive influence on behavioral intention, and environmental awareness has a significant positive influence on behavioral intention. This study contributes to the development of ride-hailing applications, particularly Gojek, in evaluating the determinants of behavior that influence user intent, as well as providing relevant supplementary learning material, particularly in related courses such as management information systems, organizational behavior, and office technology

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References

Adu, I. N., Boakye, K. O., Suleman, A.-R., & Bingab, B. B. B. (2020). Exploring the factors that mediate the relationship between entrepreneurial education and entrepreneurial intentions among undergraduate students in Ghana. Asia Pacific Journal of Innovation and Entrepreneurship, 14(2), 215–228. https://doi.org/10.1108/apjie-07-2019-0052

Al-Maroof, R. S., Alhumaid, K., Alhamad, A. Q., Aburayya, A., & Salloum, S. (2021). User acceptance of smart watch for medical purposes: An empirical study. Future Internet, 13(5), 1–19. https://doi.org/10.3390/fi13050127

Alfaisal, R., Hashim, H., & Azizan, U. H. (2024). Exploring the Adoption of the Metaverse System among Elementary Students. Journal of Advanced Research in Applied Sciences and Engineering Technology, 40(2), 117–126. https://doi.org/10.37934/araset.40.2.117126

Ali, R., Bashir, F., & Ahmad, R. (2021). Imprints of Lower Socioeconomic Class in English Speaking Anxieties and Academic Performance of Rural and Urban Students. IRASD Journal of Economics, 3(3), 412–425. https://doi.org/10.52131/joe.2021.0303.0055

Boru, T. (2018). Chapter Five Research Design and Methodology [University of South Africa]. http://rgdoi.net/10.13140/RG.2.2.21467.62242

Chauhan, V., Yadav, R., & Choudhary, V. (2019). Analyzing the impact of consumer innovativeness and perceived risk in internet banking adoption: A study of Indian consumers. International Journal of Bank Marketing, 37(1), 323–339. https://doi.org/10.1108/IJBM-02-2018-0028

Chin, W. W., & Newsted, P. R. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research. Statistical Strategies for Small Sample Research, January 1998, 295-336. http://books.google.com.sg/books?hl=en&lr=&id=EDZ5AgAAQBAJ&oi=fnd&pg=PA295&dq=chin+1998+PLS&ots=47qB7ro0np&sig=rihQBibvT6S-Lsj1H9txe9dX6Zk#v=onepage&q&f=false

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.23.07.249008

Duan, S. X., & Deng, H. (2022). Exploring privacy paradox in contact tracing apps adoption. Internet Research, 32(5), 1725–1750. https://doi.org/10.1108/INTR-03-2021-0160

Duan, Y., Wang, J., Li, H., Yan, Y., & Zhang, X. (2023). A Comparison in Travel Characteristics of Bike-Sharing between College Students and Office Workers Based on Theory of Planned Behavior. Behavioral Sciences, 13(4). https://doi.org/10.3390/bs13040329

Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research‏. Advances Methods of Marketing Research, 18(3), 382-388.

García-Salirrosas, E. E., Niño-de-Guzmán, J. C., Gómez-Bayona, L., & Escobar-Farfán, M. (2023). Environmentally Responsible Purchase Intention in Pacific Alliance Countries: Geographic and Gender Evidence in the Context of the Covid-19 Pandemic. Behavioral Sciences, 13(3). https://doi.org/10.3390/bs13030221

Goel, P., & Haldar, P. (2020). Does India need a shared ride-hailing now more than ever? Understanding commuter’s intentions to share rides. Asian Journal of Business and Accounting, 13(2), 277–305. https://doi.org/10.22452/ajba.vol13no2.10

Gunasinghe, A., Hamid, J. A., Khatibi, A., & Azam, S. M. F. (2018). Does the lecturer’s innovativeness drive VLE adoption in higher education institutes? (A study based on extended UTAUT). Journal of Information Technology Management, 10(3), 20–42. https://doi.org/10.22059/JITM.2019.285648.2382

Hair, J. F., & Sarstedt, M. (2019). Factors versus Composites: Guidelines for Choosing the Right Structural Equation Modeling Method. Project Management Journal, 50(6), 619–624. https://doi.org/10.1177/8756972819882132

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), https://doi.org/10.1007/s11747-014-0403-8 115–135.

Hwang, H., Cho, G., & Choo, H. (2021). GSCA Pro 1.1 user’s manual. June, 1–47. https://doi.org/10.13140/RG.2.2.28162.61127

JS, I. P. W. D., Usadi, M. P. P., & Wibawa, I. W. S. (2022). Predicting Millennials E-Loyalty Through Compatibility and Innovativeness on E-Commerce. Journal of International Conference Proceedings, 5(1), 268–277. https://doi.org/10.32535/jicp.v5i1.1476

Krejcie, R., V.Morgan, & W., D. (1970) “Determining sample Size for Research Activities”, Educational and Psychological Measurement. International Journal of Employment Studies, 18(1), 89–123.

Krouska, A., Kabassi, K., Troussas, C., & Sgouropoulou, C. (2022). Personalizing Environmental Awareness through Smartphones Using AHP and Promethee II. Future Internet, 14(2), 1–16. https://doi.org/10.3390/fi14020066

Lee, J. H., & Song, C. H. (2013). Effects of trust and perceived risk on user acceptance of a new technology service. Social Behavior and Personality, 41(4), 587–597. https://doi.org/10.2224/sbp.2013.41.4.587

Lin, Y., Zhou, X., & Fan, W. (2021). How do customers respond to robotic service? A scenario-based study from the perspective of uncertainty reduction theory. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-Janua, 576–585. https://doi.org/10.24251/hicss.2021.070

Meneau, L. K., & Moorthy, J. (2022). Struggling to make ends meet: can consumer financial behaviors improve? International Journal of Bank Marketing, 40(2), 263–296. https://doi.org/10.1108/IJBM-12-2020-0595

Mensah, I. K. (2022). Understanding the Drivers of Ghanaian Citizens’ Adoption Intentions of Mobile Health Services. Frontiers in Public Health, 10(June). https://doi.org/10.3389/fpubh.2022.906106

Mitra, S. K., Bae, Y., & Ritchie, S. G. (2019). Use of Ride-Hailing Services among Older Adults in the United States. Transportation Research Record, 2673(3), 700–710. https://doi.org/10.1177/0361198119835511

Na, S., Heo, S., Choi, W., Han, S., & Kim, C. (2023). Firm Size and Artificial Intelligence (AI)-Based Technology Adoption: The Role of Corporate Size in South Korean Construction Companies. Buildings, 13(4). https://doi.org/10.3390/buildings13041066

Ngatno. (2019). Analisis Data Penelitian dengan Program GeSCA (Generalized Structured Component Analysis). Undip Press.

Oktaria, R., Naibaho, S. A., Muda, I., & Kesuma, S. A. (2024). Factors of acceptance of e-commerce technology among society: integration of technology acceptance model. Brazilian Journal of Development, 10(1), 118–130. https://doi.org/10.34117/bjdv10n1-008

Paganin, G., & Simbula, S. (2021). New technologies in the workplace: can personal and organizational variables affect the employees’ intention to use a work-stress management app? International Journal of Environmental Research and Public Health, 18(17). https://doi.org/10.3390/ijerph18179366

Perwira, T., & Dellyana, D. (2023). Technology Acceptance Model and Wearable ElectroCardioGraph (DubDub). Journal of Economics and Business UBS, 12(6), 3800–3816. https://doi.org/10.52644/joeb.v12i6.900

Rafique, H., Anwer, F., Shamim, A., Minaei-Bidgoli, B., Qureshi, M. A., & Shamshirband, S. (2018). Factors affecting acceptance of mobile library applications: Structural equation model. Libri, 68(2), 99–112. https://doi.org/10.1515/libri-2017-0041

Sanjaya, A. A., Sulaiman, A., & Rokhmah, S. N. (2023). Pengaruh environmental awareness terhadap gratitude to nature di sekolah menengah. Cognicia, 11(2), 149–157. https://doi.org/10.22219/cognicia.v11i2.24963

Sugiyono. (2019). Metode Penelitian Kuantitatif Kualitatif dan R&D. CV Alfabeta.

Triwijayati, A., Melany, & Wijayanti, D. (2020). Impact of consumer innovativeness on risk and new product adoption: A moderating role of Indonesia’s demographic factors. Innovative Marketing, 16(4), 48–61. https://doi.org/10.21511/im.16(4).2020.05

Vo, T. H. G., & Wu, K. W. (2022). Exploring Consumer Adoption of Mobile Shopping Apps From a Perspective of Elaboration Likelihood Model. International Journal of E-Services and Mobile Applications, 14(1), 1–18. https://doi.org/10.4018/IJESMA.296577

Wahyuni, A. E., Juraida, A., & Anwar, A. (2021). Readiness factor identification Bandung city MSMEs use blockchain technology. Jurnal Sistem Dan Manajemen Industri, 5(2), 53–62. https://doi.org/10.30656/jsmi.v5i2.2787

Wang, Y., Wang, S., Wang, J., Wei, J., & Wang, C. (2020). An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model. Transportation, 47(1), 397–415. https://doi.org/10.1007/s11116-018-9893-4

Wang, Y., Zhang, X., & Wang, L. (2022). Assessing the Intention to Use Sports Bracelets Among Chinese University Students: An Extension of Technology Acceptance Model With Sports Motivation. Frontiers in Psychology, 13(March), 1–11. https://doi.org/10.3389/fpsyg.2022.846594

Weina, A., & Yanling, Y. (2022). Role of Knowledge Management on the Sustainable Environment: Assessing the Moderating Effect of Innovative Culture. Frontiers in Psychology, 13(April), 1–15. https://doi.org/10.3389/fpsyg.2022.861813

Zaigham, M., Chin, C. P. Y., & Dasan, J. (2022). Disentangling Determinants of Ride-Hailing Services among Malaysian Drivers. Information (Switzerland), 13(12), 1–24. https://doi.org/10.3390/info13120584

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Published

2025-11-30

How to Cite

Febriliani, S., Nugraha, J., & Lian, J.-W. (2025). Investigation of the Students Behavior in Using Ride-Hailing Applications: Perspectives of Perceived Risk and Environmental Awareness in Technology Acceptance Model (TAM). Journal of Office Administration : Education and Practice, 5(3), 187–201. https://doi.org/10.26740/joaep.v5n3.p187-201

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