•  
  •  
 

Abstract

This study explores the psychological factors that influence applying a technology acceptance model to KAI Commuter Jabodetabek. The model focuses on the primary variables of perceived usefulness and attitude toward the service, with passenger loyalty serving as the key indicator of successful public transportation acceptance. Data was collected via surveys from 352 purposively selected commuter workers in the Greater Jakarta area using a cross-sectional, quantitative design. The measurement tools used are adaptations of the Passenger Loyalty Measure to Public Transportation Modes, the Attitude Measure to Public Transportation, and the Perceived Usefulness Measure. The results indicate that attitude toward KAI Commuter Jabodetabek partially mediates the relationship between perceived usefulness and passenger loyalty (B = 1.2, t = 7.35, p < .001). This indicates that passengers’ decision to use or reject KAI Commuter Jabodetabek services depends on the ratio of benefits. By integrating principles from the technology acceptance model with psychological theories of attitude and behavior, this study addresses a critical gap in understanding how psychological and perceptual factors drive transit behavior. The insights gained provide valuable guidance for the design and management of PTSs , enhancing user adoption and long-term loyalty.

References

Abdul Hamid, N., Tan, P.-L., & Mokhlas, H. (2016). Factors Predicting the Desire to Walk among Pedestrian Rail Commuters within Transit-oriented Development Areas. The International Journal of Interdisciplinary Social and Community Studies, 11(4), 63–79. https://doi.org/10.18848/2324-7576/CGP/v11i04/63-79

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Alenazy, W. M., Mugahed Al-Rahmi, W., & Khan, M. S. (2019). Validation of TAM Model on Social Media Use for Collaborative Learning to Enhance Collaborative Authoring. IEEE Access, 7, 71550–71562. https://doi.org/10.1109/ACCESS.2019.2920242

Alkhawaja, M. I., Abd Halim, M. S., Abumandil, M. S. S., & Al-Adwan, A. S. (2022). System Quality and Student’s Acceptance of the E-learning System: The Serial Mediation of Perceived Usefulness and Intention to Use. Contemporary Educational Technology, 14(2), ep350. https://doi.org/10.30935/cedtech/11525

Annur, C. M. (2023, March 20). Jumlah Kendaraan Bermotor di DKI Jakarta Terus Meningkat dalam 5 Tahun Terakhir. Katadata.Co.Id.

Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and Test of a Theory of Technological Learning and Usage. Human Relations, 45(7), 659–686. https://doi.org/10.1177/001872679204500702

Baron, R. A., & Branscombe, N. R. (2012). Social psychology (13th ed.). Pearson Education.

Bell, M. G. H. (1995). Traffic restraint and urban decay. IEE Colloquium on Urban Congestion Management, 2–2. https://doi.org/10.1049/ic:19951294

Bertolini, L., Curtis, C., & Renne, J. (2012). Station Area projects in Europe and Beyond: Towards Transit Oriented Development? Built Environment, 38(1), 31–50. https://doi.org/10.2148/benv.38.1.31

Bian, F., Qiao, S., & Yeh, A. G.-O. (2023). Mobility resilience: Transit-oriented development, ride-hailing, and car ownership. Transportation Research Part D: Transport and Environment, 123, 103924. https://doi.org/10.1016/j.trd.2023.103924

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

Carrus, G., Tiberio, L., Mastandrea, S., Chokrai, P., Fritsche, I., Klöckner, C. A., Masson, T., Vesely, S., & Panno, A. (2021). Psychological Predictors of Energy Saving Behavior: A Meta-Analytic Approach. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.648221

Cervero, R., & Sullivan, C. (2011). Green TODs: marrying transit-oriented development and green urbanism. International Journal of Sustainable Development & World Ecology, 18(3), 210–218. https://doi.org/10.1080/13504509.2011.570801

Chen, C.-F., & Chao, W.-H. (2011a). Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit. Transportation Research Part F: Traffic Psychology and Behaviour, 14(2), 128–137. https://doi.org/10.1016/j.trf.2010.11.006

Chen, C.-F., & Chao, W.-H. (2011b). Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit. Transportation Research Part F: Traffic Psychology and Behaviour, 14(2), 128–137. https://doi.org/10.1016/j.trf.2010.11.006

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008

Dütschke, E., Engel, L., Theis, A., & Hanss, D. (2022). Car driving, air travel or more sustainable transport? Socio-psychological factors in everyday mobility and long-distance leisure travel. Travel Behaviour and Society, 28, 115–127. https://doi.org/10.1016/j.tbs.2022.03.002

Fadli, A. (2022, May 30). Lima Alasan Orang Membenci Transportasi Umum. Kompas.Com.

Garg, P., Kumar, A., & Mittal, Raj. (2023). What drives consumers’ sustainable mobility behaviour? An empirical investigation of Delhi consumers. 19. Visions for Sustainability, 19(7064), 289–319.

Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 1–28. https://doi.org/10.17705/1jais.00008.

Gordon, P., Richardson, H. W., & Jun, M.-J. (1991). The commuting paradox evidence from the top twenty. Journal of the American Planning Association, 57(4), 416–420.

Hamidi, Z., & Zhao, C. (2020). Shaping sustainable travel behaviour: Attitude, skills, and access all matter. Transportation Research Part D: Transport and Environment, 88, 102566. https://doi.org/10.1016/j.trd.2020.102566

Han, H., Linda Lho, H., & Lee, H. (2019). Perceived corporate social responsibility affects airline passengers’ service evaluation and loyalty. Social Behavior and Personality: An International Journal, 47(11), 1–9. https://doi.org/10.2224/sbp.8477

Hartoft-Nielsen, P. (2007). Deconcentration of workplaces in greater Copenhagen: Successes and failures of location strategies in regional planning (pp. 53–87). https://doi.org/10.1007/978-1-4020-5762-5_3

Kartikasari, A. D., Jaryono, J., & Daryono, D. (2017). TECHNOLOGY OF E-GOVERNMENT ACCEPTANCE ANALYSIS ON ELECTRONIC RESIDENT IDENTIFICATION CARD (E-KTP) ADOPTION. Performance, 23(2), 77. https://doi.org/10.20884/1.performance.2016.23.2.272

Kim, S., & Ulfarsson, G. F. (2004). Travel Mode Choice of the Elderly: Effects of Personal, Household, Neighborhood, and Trip Characteristics. Transportation Research Record: Journal of the Transportation Research Board, 1894(1), 117–126. https://doi.org/10.3141/1894-13.

Kohler, M., Corsmeier, U., Vogt, U., & Vogel, B. (2005). Estimation of gaseous real-world traffic emissions downstream a motorway. Atmospheric Environment, 39(31), 5665–5684. https://doi.org/10.1016/j.atmosenv.2004.09.088

Lai, Y.-H. (2019). The Application of Meta-Analytic SEM on Exploring Factors that Influence Teachers’ Usage of Interactive Whiteboard. Pedagogical Research, 4(3). https://doi.org/10.29333/pr/5854

Lin, D., Allan, A., & Cui, J. (2015). The impacts of urban spatial structure and socio-economic factors on patterns of commuting: a review. International Journal of Urban Sciences, 19(2), 238–255. https://doi.org/10.1080/12265934.2015.1016092

Losada-Rojas, L. L., Gkartzonikas, C., Pyrialakou, V. D., & Gkritza, K. (2019). Exploring intercity passengers’ attitudes and loyalty to intercity passenger rail: Evidence from an on-board survey. Transport Policy, 73, 71–83. https://doi.org/10.1016/j.tranpol.2018.10.011

Mahardhika, L. A. (2023, January 15). Pengguna KRL Jabodetabek Naik, Tembus 800.000 Orang per Hari. Bisnis.Com.

Maphosa, V. (2021). Teachers’ Perspectives on Remote-based Teaching and Learning in the COVID-19 Era: Rethinking Technology Availability and Suitability in Zimbabwe. European Journal of Interactive Multimedia and Education, 2(1), e02105. https://doi.org/10.30935/ejimed/9684

Murray, S. J., Walton, D., & Thomas, J. A. (2010). Attitudes towards public transport in New Zealand. Transportation, 37(6), 915–929. https://doi.org/10.1007/s11116-010-9303-z

Myers, D. G. (2010). Social Psychology :9th Edition. McGrawHill.

Nogueira, M., Dias, F., & Santos, V. (2023). Sustainable mobility choices: Exploring the impact of consumers’ values, attitudes, perceived behavioural control and subjective norms on the likelihood to choose sustainable mobility options. Journal of Consumer Behaviour, 22(2), 511–528. https://doi.org/10.1002/cb.2144

Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63(4_suppl1), 33–44. https://doi.org/10.1177/00222429990634s105

Pratiwi, N. O., & Amarul, A. (2021). Persepsi Risiko Fisik dan Psikologis Terhadap Minat Menggunakan Commuter Line di Indonesia. Jurnal Inovasi Dan Kreativitas (JIKa), 1(1), 9–14. https://doi.org/10.30656/jika.v1i1.3285

Quinta, F. A., & Prakoso, H. B. S. E. (2016). Kajian Pemanfaatan Moda Transportasi Kereta Rel Listrik (KRL) Commuter Line dalam Pergerakan Komuter Bekasi-Jakarta. Jurnal Bumi Indonesia, 5(2).

Rizqiya, V. A., Rini, I., Ari, D., & Firdausiyah, N. (2022). Evaluasi Kinerja Operasional Dan Pelayanan Krl Cikarang – Jakarta Kota. Planning For Urban Region And Environment (PURE), 11(3), 177–186.

Santika, E. F. (2024, January 15). KRL Commuter Jabodetabek Sumbang 290 Juta Penumpang pada 2023. Katadata.Co.Id.

Schwanen, T., Dieleman, F. M., & Dijst, M. (2003). Car Use in Netherlands Daily Urban Systems: Does Polycentrism Result in Lower Commute Times? 1. Urban Geography, 24(5), 410–430. https://doi.org/10.2747/0272-3638.24.5.410

Schwarz, N., & Bohner, G. (2001). The construction of attitudes. In Blackwell hand- book of social psychology: Intrapersonal processes (pp. 436–457). Blackwell.

Secha, K. N. (2022, May 30). Penumpang KRL Keluhkan Transit Di Manggarai: Berdesakan-Capek. Detiknews.

Shiftan, Y., Barlach, Y., & Shefer, D. (2015). Measuring Passenger Loyalty to Public Transport Modes. Journal of Public Transportation, 18(1), 1–16. https://doi.org/10.5038/2375-0901.18.1.7

Si, H., Shi, J., Tang, D., Wu, G., & Lan, J. (2020). Understanding intention and behavior toward sustainable usage of bike sharing by extending the theory of planned behavior. Resources, Conservation and Recycling, 152, 104513. https://doi.org/10.1016/j.resconrec.2019.104513

Stojanovski, T. (2020). Urban design and public transportation – public spaces, visual proximity and Transit-Oriented Development (TOD). Journal of Urban Design, 25(1), 134–154. https://doi.org/10.1080/13574809.2019.1592665

Su, F., & Bell, M. G. H. (2009). Transport for older people: Characteristics and solutions. Research in Transportation Economics, 25(1), 46–55. https://doi.org/10.1016/j.retrec.2009.08.006

Sung, H., & Oh, J.-T. (2011). Transit-oriented development in a high-density city: Identifying its association with transit ridership in Seoul, Korea. Cities, 28(1), 70–82. https://doi.org/10.1016/j.cities.2010.09.004

Wen, L., & Bai, L. (2017). System Dynamics Modeling and Policy Simulation for Urban Traffic: a Case Study in Beijing. Environmental Modeling & Assessment, 22(4), 363–378. https://doi.org/10.1007/s10666-016-9539-x

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x

Wibisono, B. H. (2011). The Slow and Chaotic Cities in Indonesia: A Study of Urban Morphology, Crowding and Inefficiencies in a Developing Country. Spaces & Flows: International Conference on Urban and ExtraUrban Studies., 1, 35–48.

Yang, H., Lin, K., Zhou, Y., & Du, X. (2013). The Governance of Urban Traffic Jam Based on System Dynamics: In Case of Beijing, China. In LTLGB 2012 (pp. 197–207). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-34651-4_32

Zhao, P., Lu, B., & de Roo, G. (2011). The impact of urban growth on commuting patterns in a restructuring city: Evidence from Beijing. Papers in Regional Science, 90(4), 735–755. https://doi.org/10.1111/j.1435-5957.2010.00343.x

Download

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.