THE IMPACT OF ELECTRIC TRAIN SYSTEM (ETS) ON AIR AND ROAD TRANSPORTATION
DOI:
https://doi.org/10.24191/mjoc.v8i1.20521Keywords:
Chi-test, Electric Train System (ETS), Factor Analysis, Rotated Factor Matrix, SPSSAbstract
The development of effective and efficient public transportation services is crucial in order to attract more people to use public transport, as visualized by the Land Public Transport Agency or known as Agensi Pengangkutan Awam Darat (APAD) to have 60 percent of Malaysian citizens travel using public transport. This will greatly aid the purpose of overcoming the issue of traffic congestion in Malaysia. Thus, this research aims to determine the best value offered to the customers in terms of travel time, fare, and comfort by performing a survey using questionnaires on citizens that uses public transportation, which is then analyzed using the Chi-Square test, Kaiser-Meyer-Olkin (KMO) and Bartlett’s test, and Rotated Factor Matrix. Results from the analysis show that for a short distance, ETS and express bus provide the most value to their customers while air travel is preferable for long distance given the low travel time despite the travel cost. Value perception also varies based on the age given that young travelers put more emphasis on a low fare while older travellers value low travel time. Finally, other factors such as travel comfort, availability, and safety are gaining more awareness in value when choosing travel options hence these factors should not be ignored when operating a public transportation service.
References
Abd Rahman, H. A., Rahman, M. A., Rozaimi, A. N., & Zulnazar, I. B. (2022). The effectiveness of movement control order (MCO) phases implementation in Malaysia. Malaysian Journal of Computing (MJoC), 7(2), 1100-1107.
Beirão, G., & Cabral, J. A. (2007). Understanding attitudes towards public transport and private car: A qualitative study. Transportation Policy, 14(6), 478-489.
Bruun, E. (2005). Comparison of BRT and LRT Operating Costs Using a Parametric Cost Model. Transportation Research Record , 1927, 11-21.
Burhan, M. N., Rahmat, R. A. A. O. K., Ismail, A., & Ismail, R. (2011). Prediction of traveling behavior in Putrajaya. Malaysia. Research Journal of Applied Science, 3(5), 434-439.
Chester, M., & Horvath, A. (2008). Environmental Life- cycle Assessment of PassengerTransportation: A Detailed Methodology for Energy, Greenhouse Gas and Criteria Polmutant Inventories of Automobiles, Buses, Light Rail, Heavy Rail and Air v.2. UC Berkeley Center for Future Urban Transport: A Volvo Center of Excellence, Institute of Transportation Studies, UC Berkeley, Berkeley. Available at : https://escholarship.org/uc/item/5670921q
Hafezi, M. H., & Ismail, A. (2011). Interaction between bus stops location and traffic on bus operation. In Applied Mechanics and Materials (Vol. 97, pp. 1185-1188). Trans Tech Publications Ltd.
Hafezi, M. H., Ismail, A., & Shariff, A. A. (2012). A comparative analysis of fare collection system on bus operations. Journal of Applied Science, 12(4), 393-397.
Keller, P. (2001). Intermodality of network points: The planner’s view. Paper presented at the international workshop, Intermodal connectivity at European Transport Network Points.
Krygsman, S., Dijst, M., & Arentze, T. (2004). Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio. Transport Policy, 11(3), 265–275.
Ministry of Transport (2019). National Transport Policy 2019-2030. Available at : https://www.pmo.gov.my/wp-content/uploads/2019/10/National-Transport Policy2019_2030EN.pdf, [Access online 27 November 2020].
Mokhtarian, P., & Salomon, I. (2001), How Derived is the demand for Travel? Some Conceptual and Measurement Consideration. Transport Research A, 35(8), 695-719.
Park, Y., & Ha, H. K. (2006). Analysis of the impact of high speed railroad service on air transport demand. Transportation Research Part E: Logistics and Transportation Review, 42, 95-104.
Prasarana (2016). Public transportation in Malaysia. Available at: http://www.myrapid.com.my. [Access online 27 November 2016].
Shaaban, K., & Maher, A. (2020). Using the theory of planned behavior to predict the use of an upcoming public transportation service in Qatar. Case Studies on Transport Policy, 8(2), 484-491.
Tranter, P. J. (2004). Effective Speeds: Car Costs are Slowing Us Down. University of New South Wales, for the Australian Greenhouse Office.
Tuan Hassan, T. M. H., & Masrom, M. (2022). Determining optimal transportation allocation using linear programming methods. Malaysian Journal of Computing (MJoC), 7(2), 1082-1099.
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