Main Article Content
Abstract
Although public transport provides many benefits, such as a cleaner environment, reduced congestion, and increased sustainable transportation, many people still prefer private transport. This motivates the exploration of users’ intention to choose and use public transportation. This study explores the psychological factors of public transport users based on the theory of planned behavior (TPB). TPB assumes behavior built because of the intention. Attitude (ATT) does not determine the intention to influence behavior directly but through a combination of Subjective Norms (SN) and Perceived Behavioral Control (PBC). Responses from public transport users in Greater Bandung were collected using a questionnaire. The results show that attitude (ATT) is the most vital factor that positively influences user intention, based on standardized estimates of 0.866 (ATT), 0.301 (PBC), and 0.202 (SN). Environmental and climate issues have the most significant influence on user attitudes when compared to quality factors sorted by standardized estimated values such as travel time, safety, and fare. Previous research revealed that the dominant factor was quality, but in this study, it switched to factors of transportation activities that affect the environment. In fact, the factor of ease of use and encouragement of information media is crucial to be considered by stakeholders.
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Copyright @2017. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted non-commercial used, distribution and reproduction in any medium
References
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Sottile. E., Meloni. I., & Cherchi. E. (2015). A hybrid discrete choice model to assess the effect of awreness and attitude towards environmentally friendly travel modes. Transportation Research Procedia 5. 44-55.
Klöckner, C. A. (2013). A comprehensive model of the psychology of environmental behaviour—A meta-analysis. Global environmental change, 23(5), 1028-1038.
Sonja. E. F. (2019). Views on Public Transport and How Personal Experiences Can Contribute to a More Positive Attide and Behavioural Change. Social Sciences. 8(2). 47
Gao, K., Yang, Y., Sun, L., & Qu, X. (2020). Revealing psychological inertia in mode shift behavior and its quantitative influences on commuting trips. Transportation research part F: traffic psychology and behaviour, 71, 272-287.
Thøgersen, J., & Møller, B. (2008). Breaking car use habits: The effectiveness of a free one-month travelcard. Trans. (Amst), 35, 329-345.
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Chowdhury, S., & Ceder, A. (2013). A psychological investigation on public-transport users’ intention to use routes with transfers. International Journal of Transportation, 1(1), 1-20.
Kwan, S., Sutan, R., & Hashim, J. (2020). Behavioral Framework of Attitude, Service Quality, Environmental Health Concerns and Intention to Use Rail Transport among Private Motor Vehicle Users. Malaysian Journal of Medicine and Health Sciences, 16(4).
Zailani, S., Iranmanesh, M., Masron, T. A., & Chan, T.-H. (2016). Is the intention to use public transport for different travel purposes determined by different factors? Transportation Research Part D: Transport and Environment, 49, 18–24. doi:10.1016/j.trd.2016.08.038
Li, L., Xiong, J., Chen, A., Zhao, S., & Dong, Z. (2015). Key strategies for improving public transportation based on planned behavior theory: Case study in Shanghai, China. Journal of Urban Planning and Development, 141(2), 04014019.
Ajzen, I. (2015). The theory of planned behaviour is alive and well, and not ready to retire: a commentary on Sniehotta, Presseau, and Araújo Soares. Health Psychol. Rev. 9,131–137.https://doi.org/10.1080/17437199.2014.883474.
Lanzini, P., Khan, S.A. (2017). Shedding light on the psychological and behavioral determinants of travel mode choice: A meta-analysis. Res. Part F Traffic Psychol. Behav Transp. https://doi.org/10.1016/j.trf.2017.04.020.
Paundra, J., Rook, L., van Dalen, J., & Ketter, W. (2017). Preferences for car sharing services: Effects of instrumental attributes and psychological ownership. Journal of environmental psychology, 53, 121-130.
Hasim, A. H. (2016). Model Perilaku Masyarakat Pengguna Kendaraan Bermotor Pribadi Di Kota Makassar Berdasarkan Theory of Planned Behavior. Makassar: Universitas Muslim Indonesia Makassar.
Ajzen, I. (2006). Behavioral interventions based on the theory of planned behavior.
Tavousi, M., Montazeri, A., Hidarnia, A., Hajizadeh, E., Taremian, F., & Haerimehrizi, A. (2015). Substance use avoidance among Iranian male adolescents: A comparison of three versions of the theory of reasoned action. International journal of adolescent medicine and health, 27(3), 329-334
Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324.
Midayanti. N., Rangkuti. H., Luswara. I., Windiarto. T., Savitridina. R., Amin. Y. F., & Soblia. H. T. (2017). Statistik Komuter Bandung Raya. Bandung: Badan Pusat Statistik.
Boomsma, A. (1985). Nonconvergence, improper solutions, and starting values in LISREL maximum likelihood estimation. Psychometrika, 50, 229-242.
Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling. Sociological methods & research, 16(1), 78-117.
Nunnally, J. C. (1967). Psychometric theory.
Sumaedi, S., Bakti, I., Astrini, N., Rakhmawati, T., Widianti, T., & Yarmen, M. (2014a). Public Transport Passengers' Behavioral Intentions: Paratransit in Jabodetabek, Indonesia. SpringerBriefs in Business, Springer.
Van, H. T., Choocharukul, K., & Fujii, S. (2014). The effect of attitudes toward cars and public transportation on behavioral intention in commuting mode choice—A comparison across six Asian countries. Transportation research part A: policy and practice, 69, 36-44.
Joewono, T. B. (2009). Exploring the Willingness and Ability to Pay for Paratransit in Bandung, Indonesia. Journal of Public Transportation, 12(2), 85-103.
Brohi, S., Kalwar, S., Memon, I. A., & Ghaffar, A. (2021). Using the theory of planned behavior to identify the behavioral intention to use public transportation service: the case study of Karachi circular railway. Int. J. Emerg. Technol, 12(6), 317-322.
Chen, C. F., & Chao, W. H. (2011). 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.
Ngueutsa, R., & Kouabenan, D. R. (2017). Accident history, risk perception and traffic safe behaviour. Ergonomics, 60(9), 1273-1282.
Currie. G., Delbosc. A., & Mahmoud. S. (2013). Factors influencing young people's perception of personal safety on public transport. Journal of public transportation. 16(1). 1.
ITF. (2018). Women's Safety and Security. Retrieved from www.itf-oecd.org
Fu, X., & Juan, Z. (2017). Exploring the psychosocial factors associated with public transportation usage and examining the “gendered” difference. Transportation research part A: policy and practice, 103, 70-82.
Castel, D., Chatain, S., Anegmar, S., & Parant, A. (2019). Modal Shift from Car to Bus: A French Case Study in a Rural Context Based on an Integrated Psychosocial Approach. Transportation Journal, 58(3), 149-167.
Borhan, M. N., Syamsunur, D., Mohd Akhir, N., Mat Yazid, M. R., Ismail, A., & Rahmat, R. A. (2014). Predicting the use of public transportation: a case study from Putrajaya, Malaysia. The Scientific World Journal, 2014.
Bolarinwa, O. A. (2015). Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Nigerian Postgraduate Medical Journal, 22(4), 195.
Sugiyono. (2011). Metode Penelitian Kuantitatif Kualitatif dan R&D. Bandung: Alfabeta.
Hair, J., Black, W., Babin, B., & Anderson, R. (2019). Multivariate data analysis. 7th ed. Harlow: Pearson Limited Education.
Ghozali. I. (2017). Model Persamaan Struktural: Konsep dan APlikasi dengan Program AMOS 24 Update Bayesian SEM. Edisi 7. Semarang. Indonesia: Badan Penerbit Universitas Dipenegoro.
Shi, D., Lee, T., & Maydeu-Olivares, A. (2019). Understanding the model size effect on SEM fit indices. Educational and psychological measurement, 79(2), 310-334.
Borhan, M. N., Syamsunur, D., Mohd Akhir, N., Mat Yazid, M. R., Ismail, A., & Rahmat, R. A. (2014). Predicting the use of public transportation: a case study from Putrajaya, Malaysia. The Scientific World Journal, 2014.
Joewono, T. B., & Kubota, H. (2005). The characteristics of paratransit and non-motorized transport in Bandung, Indonesia. Journal of the Eastern Asia Society for Transportation Studies, 6, 262-277.
Cariera, D. (2021). Ekplorasi Niat Pengguna Dalam Perpindahan Moda Transportasi Dari Moda Pribadi ke Transportasi Umum di Berbagai Negara. In Prosiding Forum Studi Transportasi antar Perguruan Tinggi (pp. 343-343).
VTPI. (2013). Transportation cost and benefit analysis II e Travel time costs. Victoria Transport Policy Institute. www.vtpi.org.
Salmiati, S., Manjang, S., & Nurtanio, I. (2017). Penerapan mobile GIS pada peta panduan jalur angkutan umum berbasis android dengan metode optimasi rute ant colony optimization. Jurnal Penelitian Enjiniring, 21(2), 25-33.
Morfoulaki, M., Myrovali, G., & Kotoula, K. (2015). Increasing the attractiveness of public transport by investing in soft ICT based measures: Going from words to actions under an austerity backdrop–Thessaloniki's case, Greece. Research in Transportation Economics, 51, 40-48
References
Dirgahayani. P. & Sutanto. H. (2020). The effect of transport demand management policy on the intention to use public transport: A case in Bandung. Indonesia. Case Studies on Transport Policy. 8(3). 1062-1072.
Triani, A. (2019, November 5). Kemacetan Bandung dan "Big Data". Retrieved from Detik news: https://news.detik.com/kolom/d-4772429/kemacetan-bandung-dan-big-data
Saputra, I., & Mulyanisa, Z. M. (2018). Probabilitas Peralihan Moda Pengguna Kendaraan Kendaraan Pribadi (Mobil) ke Monorel Bandung Raya. Jurnal Wilayah dan Kota, 5 (01).
Sottile. E., Meloni. I., & Cherchi. E. (2015). A hybrid discrete choice model to assess the effect of awreness and attitude towards environmentally friendly travel modes. Transportation Research Procedia 5. 44-55.
Klöckner, C. A. (2013). A comprehensive model of the psychology of environmental behaviour—A meta-analysis. Global environmental change, 23(5), 1028-1038.
Sonja. E. F. (2019). Views on Public Transport and How Personal Experiences Can Contribute to a More Positive Attide and Behavioural Change. Social Sciences. 8(2). 47
Gao, K., Yang, Y., Sun, L., & Qu, X. (2020). Revealing psychological inertia in mode shift behavior and its quantitative influences on commuting trips. Transportation research part F: traffic psychology and behaviour, 71, 272-287.
Thøgersen, J., & Møller, B. (2008). Breaking car use habits: The effectiveness of a free one-month travelcard. Trans. (Amst), 35, 329-345.
Zhang, X., Guan, H., Zhu, H., & Zhu, J. (2019). Analysis of travel mode choice behavior considering the indifference threshold. Sustainability, 11(19), 5495.
Devika. R., Harikrishna. M., & Anjaneyulu. M. (2020). Influence of psychological factors in mode choice decision making: A structural equation modelling approach. Transportation Research Procedia. 48. 2821-2830.
Chowdhury, S., & Ceder, A. (2013). A psychological investigation on public-transport users’ intention to use routes with transfers. International Journal of Transportation, 1(1), 1-20.
Kwan, S., Sutan, R., & Hashim, J. (2020). Behavioral Framework of Attitude, Service Quality, Environmental Health Concerns and Intention to Use Rail Transport among Private Motor Vehicle Users. Malaysian Journal of Medicine and Health Sciences, 16(4).
Zailani, S., Iranmanesh, M., Masron, T. A., & Chan, T.-H. (2016). Is the intention to use public transport for different travel purposes determined by different factors? Transportation Research Part D: Transport and Environment, 49, 18–24. doi:10.1016/j.trd.2016.08.038
Li, L., Xiong, J., Chen, A., Zhao, S., & Dong, Z. (2015). Key strategies for improving public transportation based on planned behavior theory: Case study in Shanghai, China. Journal of Urban Planning and Development, 141(2), 04014019.
Ajzen, I. (2015). The theory of planned behaviour is alive and well, and not ready to retire: a commentary on Sniehotta, Presseau, and Araújo Soares. Health Psychol. Rev. 9,131–137.https://doi.org/10.1080/17437199.2014.883474.
Lanzini, P., Khan, S.A. (2017). Shedding light on the psychological and behavioral determinants of travel mode choice: A meta-analysis. Res. Part F Traffic Psychol. Behav Transp. https://doi.org/10.1016/j.trf.2017.04.020.
Paundra, J., Rook, L., van Dalen, J., & Ketter, W. (2017). Preferences for car sharing services: Effects of instrumental attributes and psychological ownership. Journal of environmental psychology, 53, 121-130.
Hasim, A. H. (2016). Model Perilaku Masyarakat Pengguna Kendaraan Bermotor Pribadi Di Kota Makassar Berdasarkan Theory of Planned Behavior. Makassar: Universitas Muslim Indonesia Makassar.
Ajzen, I. (2006). Behavioral interventions based on the theory of planned behavior.
Tavousi, M., Montazeri, A., Hidarnia, A., Hajizadeh, E., Taremian, F., & Haerimehrizi, A. (2015). Substance use avoidance among Iranian male adolescents: A comparison of three versions of the theory of reasoned action. International journal of adolescent medicine and health, 27(3), 329-334
Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324.
Midayanti. N., Rangkuti. H., Luswara. I., Windiarto. T., Savitridina. R., Amin. Y. F., & Soblia. H. T. (2017). Statistik Komuter Bandung Raya. Bandung: Badan Pusat Statistik.
Boomsma, A. (1985). Nonconvergence, improper solutions, and starting values in LISREL maximum likelihood estimation. Psychometrika, 50, 229-242.
Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling. Sociological methods & research, 16(1), 78-117.
Nunnally, J. C. (1967). Psychometric theory.
Sumaedi, S., Bakti, I., Astrini, N., Rakhmawati, T., Widianti, T., & Yarmen, M. (2014a). Public Transport Passengers' Behavioral Intentions: Paratransit in Jabodetabek, Indonesia. SpringerBriefs in Business, Springer.
Van, H. T., Choocharukul, K., & Fujii, S. (2014). The effect of attitudes toward cars and public transportation on behavioral intention in commuting mode choice—A comparison across six Asian countries. Transportation research part A: policy and practice, 69, 36-44.
Joewono, T. B. (2009). Exploring the Willingness and Ability to Pay for Paratransit in Bandung, Indonesia. Journal of Public Transportation, 12(2), 85-103.
Brohi, S., Kalwar, S., Memon, I. A., & Ghaffar, A. (2021). Using the theory of planned behavior to identify the behavioral intention to use public transportation service: the case study of Karachi circular railway. Int. J. Emerg. Technol, 12(6), 317-322.
Chen, C. F., & Chao, W. H. (2011). 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.
Ngueutsa, R., & Kouabenan, D. R. (2017). Accident history, risk perception and traffic safe behaviour. Ergonomics, 60(9), 1273-1282.
Currie. G., Delbosc. A., & Mahmoud. S. (2013). Factors influencing young people's perception of personal safety on public transport. Journal of public transportation. 16(1). 1.
ITF. (2018). Women's Safety and Security. Retrieved from www.itf-oecd.org
Fu, X., & Juan, Z. (2017). Exploring the psychosocial factors associated with public transportation usage and examining the “gendered” difference. Transportation research part A: policy and practice, 103, 70-82.
Castel, D., Chatain, S., Anegmar, S., & Parant, A. (2019). Modal Shift from Car to Bus: A French Case Study in a Rural Context Based on an Integrated Psychosocial Approach. Transportation Journal, 58(3), 149-167.
Borhan, M. N., Syamsunur, D., Mohd Akhir, N., Mat Yazid, M. R., Ismail, A., & Rahmat, R. A. (2014). Predicting the use of public transportation: a case study from Putrajaya, Malaysia. The Scientific World Journal, 2014.
Bolarinwa, O. A. (2015). Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Nigerian Postgraduate Medical Journal, 22(4), 195.
Sugiyono. (2011). Metode Penelitian Kuantitatif Kualitatif dan R&D. Bandung: Alfabeta.
Hair, J., Black, W., Babin, B., & Anderson, R. (2019). Multivariate data analysis. 7th ed. Harlow: Pearson Limited Education.
Ghozali. I. (2017). Model Persamaan Struktural: Konsep dan APlikasi dengan Program AMOS 24 Update Bayesian SEM. Edisi 7. Semarang. Indonesia: Badan Penerbit Universitas Dipenegoro.
Shi, D., Lee, T., & Maydeu-Olivares, A. (2019). Understanding the model size effect on SEM fit indices. Educational and psychological measurement, 79(2), 310-334.
Borhan, M. N., Syamsunur, D., Mohd Akhir, N., Mat Yazid, M. R., Ismail, A., & Rahmat, R. A. (2014). Predicting the use of public transportation: a case study from Putrajaya, Malaysia. The Scientific World Journal, 2014.
Joewono, T. B., & Kubota, H. (2005). The characteristics of paratransit and non-motorized transport in Bandung, Indonesia. Journal of the Eastern Asia Society for Transportation Studies, 6, 262-277.
Cariera, D. (2021). Ekplorasi Niat Pengguna Dalam Perpindahan Moda Transportasi Dari Moda Pribadi ke Transportasi Umum di Berbagai Negara. In Prosiding Forum Studi Transportasi antar Perguruan Tinggi (pp. 343-343).
VTPI. (2013). Transportation cost and benefit analysis II e Travel time costs. Victoria Transport Policy Institute. www.vtpi.org.
Salmiati, S., Manjang, S., & Nurtanio, I. (2017). Penerapan mobile GIS pada peta panduan jalur angkutan umum berbasis android dengan metode optimasi rute ant colony optimization. Jurnal Penelitian Enjiniring, 21(2), 25-33.
Morfoulaki, M., Myrovali, G., & Kotoula, K. (2015). Increasing the attractiveness of public transport by investing in soft ICT based measures: Going from words to actions under an austerity backdrop–Thessaloniki's case, Greece. Research in Transportation Economics, 51, 40-48