A mode shift Bayesian network model for active travel demand management policies

Ashita, 2020, Incentivised travel and mobile application as multiple policy intervention for mode shift, KSCE J. Civ. Eng., 24, 3074, 10.1007/s12205-020-2325-y BayesFusion LLC (2021). GeNIe Modeler: Complete Modeling Freedom. < https://www.bayesfusion.com/genie/> Accessed 30th September 2021. Bliemer, M.C.J., Dicke-Ogenia, M., Ettema, D. (2010). Rewarding for avoiding the peak period: A synthesis of four studies in the Netherlands. https://www.researchgate.net/publication/41536630 Accessed 28th September 2021. Bluman, 2011 Brazil, 2013, Does green make a difference: The potential role of smartphone technology in transport behaviour, Transp. Res. Part C, 37, 93, 10.1016/j.trc.2013.09.016 Brownie Ceder, 2009, Measuring public transport connectivity performance applied in Auckland, New Zealand, Transp. Res. Rec., 10.3141/2111-16 Chakraborty, 2016, A Bayeisna Network-based customer satisfaction model: a tool for management decisions in railway transport, Decision Anal., 3 Chowdhury, 2014, Measuring public-transport network connectivity using Google Transit with comparison across cities, J. Public Transp., 17, 76, 10.5038/2375-0901.17.4.5 Department of Statistics Malaysia Department of Statistics Malaysia (2021b) Household Income Estimates and Incidence of Poverty Report, Malaysia, 2020. < shorturl.at/nuKPQ> Accessed 30th September 2021. Fast, 2010 Federal Highway Administration (FHWA) (2021) Expanding traveller choices through the use of incentives: A compendium of examples. <shorturl.at/pOVX4> Accessed 28th September 2021. Frei, 2015, Mode-switching behavior with the provision of real-time multimodal traveler information, Transp. Res. Rec., 2496, 20, 10.3141/2496-03 Friman, 2020, Public transport quality, safety, and perceived accessibility, Sustainability., 12, 3563, 10.3390/su12093563 Gneezy, 2011, When and why incentives (Don't) work to modify behavior, J. Econ. Perspect., 25, 191, 10.1257/jep.25.4.191 Hadas, 2014, Public transport systems' connectivity: Spatiotemporal analysis and failure detection, Transp. Res. Procedia, 3, 309, 10.1016/j.trpro.2014.10.011 Hu, 2015, Behavior insights for an incentive-based active demand management platform, Int. J. Transp. Sci. Technol., 4, 119, 10.1260/2046-0430.4.2.119 Huang, Z., R., Liu, 2012 Optimizing feeder bus routes based on access mode shifts: A network modeling approach. The 91st Annual Meeting of Transportation Research Board, Washington D.C. Date: 22nd January 2012 to 26th January 2012. Islam, 2015, Exploring the mode change behavior of park-and-ride users, Math. Probl. Eng., 2015, 1, 10.1155/2015/282750 Janssens, 2004, Improving performance of multiagent rule-based model for activity pattern decisions with Bayesian Networks, Transp. Res. Rec., 1894, 75, 10.3141/1894-09 Joseph, C., 2014. How providing Wi-Fi can increase mass transit ridership. The City Fix. https://thecityfix.com/blog/wifi-increase-mass-transit-transport-ridership-bus-metro-coby-joseph/ Accessed 28th September 2021. Joubert, 2020, Activity-based travel demand generation using Bayesian Networks, Transp. Res. Part C, 120, 10.1016/j.trc.2020.102804 Julie, B., 2012. The future of driving and finding the right incentives for behavior change. Transport for Development. < https://rb.gy/fouvbm> Accessed 15th March 2023. Khoo, 2018, Modeling of passengers' safety perception for buses on mountainous roads, Accid. Anal. Prev., 113, 106, 10.1016/j.aap.2018.01.025 Khoo, 2016, An impact analysis of traffic image information system on driver travel choice, Transp. Res. A Policy Pract., 88, 175, 10.1016/j.tra.2016.03.014 Khoo, 2016, User requirements and route choice response to smart phone traffic applications (apps), Travel Behav. Soc., 3, 59, 10.1016/j.tbs.2015.08.004 Khoo, 2012, Short-term impact analysis of fuel price policy change on travel demand in Malaysian cities, Transp. Plan. Technol., 35, 715, 10.1080/03081060.2012.710039 Knockaert, 2011, Rewarding peak avoidance: the Dutch 'Spitsmijden' projects, 101 Litman, 2004, Transit price elasticities and cross-elasticities, J. Public Transp., 7, 37, 10.5038/2375-0901.7.2.3 Liu, 2020, The impact of purchase restriction policy on car ownership in china’s four major cities, J. Adv. Transp., 2020, 1, 10.1155/2020/8846955 Ma, 2015, Bayesian networks for multimodal mode choice behavior modelling: A case study for the cross border workers of Luxembourg, Transp. Res. Procedia, 10, 870, 10.1016/j.trpro.2015.09.040 Ma, 2017, Causal structure learning for travel mode choice using structural restrictions and model averaging algorithm, Transportmetrica A: Transport Sci., 13, 299, 10.1080/23249935.2016.1265019 Mei, Z., Lou, Q., Zhang, W., Zhang, L., Shi, F. (2017). Modeling the effects of parking charges and supply policy using system dynamics method. Journal of Advanced Transportation. Vol. 2017, Article ID 6463586. 10.1155/2017/6463586. Ministry of Transport, 2021. Yearly Statistics of Transport. <https://www.mot.gov.my/en/media/annual-report/yearly-statistic> Accessed 28th September 2021. National Center for Transit Research, 2021. TDM Commuter Tax Benefits. <https://www.nctr.usf.edu/programs/commutebenefits/> Accessed 28th September 2021. Norlida, 2008, Travel behaviour of the park and ride users and the factors influencing the demand for the use of the park and ride facility Nur Sabahiah, 2021, “More than a free bus ride”- Exploring young adults' perceptions of free bus services using a qualitative approach: A case study of Penang Malaysia, Sustainability, 13, 3294, 10.3390/su13063294 Onsel, 2013, Transport demand projections: A Bayesian Network approach Pluntke, C., Prabhakar, B., 2013. INSINC: A platform for managing peak demand in public transit. Journeys: Sharing urban transport solutions, pp. 31-38. Land Transport Authority Singapore. Ramos, 2019, Perceptions of the public transport service as a barrier to the adoption of public transport: A qualitative study, Soc. Sci., 8 Raux, 2012, The efficiency of congestion charging: Some lessons from cost-benefit analyses, Res. Transp. Econ., 36, 85, 10.1016/j.retrec.2012.03.006 Scuderi, 2011, Bayesian approaches to learning from data: Using NHTS data for the analysis of land use and transportation. Bureau of Transportation, Statistics Shaheen, 2016 Sun, 2006, A Bayesian Network approach to traffic flow forecasting, IEEE Trans. Intell. Transp. Syst., 7, 124, 10.1109/TITS.2006.869623 Tseng, 2013, A revealed-preference study of behavioural impacts of real-time traffic information, Transp. Res. Part C, 30, 196, 10.1016/j.trc.2011.11.006 Victoria Transport Policy Institute Wang, Q., H. Sun, Q. Zhang (2017). A Bayesian Network model on the public bicycle choice beahvior of residents: A case study of Xi'an. Mathematical Problems in Engineering. Vol. 2017. Article ID: 3023956. DOI:10.1155/2017/3023956. Wang, 2013, Mode shift behavior impacts from the introduction of metro service: Case study of Xi'an, China, J. Urban Plann. Dev., 139, 216, 10.1061/(ASCE)UP.1943-5444.0000148 Wardman, 2014, Valuing convenience in public transport: Roundtable summary and conclusions, International Transport Forum Wu, 2013, Modeling commuters' travel behavior by Bayesian Networks, Procedi-Social Behav. Sci., 96, 512, 10.1016/j.sbspro.2013.08.060 Wu, 2016, Exploring passenger assessments of bus service quality using Bayesian Networks, J. Public Transp., 19, 36, 10.5038/2375-0901.19.3.3 Xie, 2010, Estimation and application of a Bayesian Network model for discrete choice analysis, Transp. Lett., 2, 125, 10.3328/TL.2010.02.02.125-144 Zhang, 2014, How does commuting behavior change due to incentives? An empirical study of the Beijing Subway System, Transport. Res. F: Traffic Psychol. Behav., 24, 17, 10.1016/j.trf.2014.02.009 Zhu, C., J.S. Yue, C.V. Mandayam, D.Merugu, H.K. Abadi, B.Prabhakar (2015) Reducing road congestion through incentives: A case study. Transportation Research Board 94th Annual Meeting, Washington D.C.