Analyzing the students' moral obligation considering their carpooling intentions in Oman
Article Sidebar
Main Article Content
Abstract
The rise in private vehicle use causes traffic congestion on the road network and increases the social costs of the trips. Travel demand management (TDM) strategies are deployed to mitigate traffic congestion sustainably as these strategies spread travel needs in space and time by influencing individual travel behavior. Carpooling is a TDM measure used to decrease the use of single occupancy vehicles and promote shared mobility among travelers sharing the same origin-destination and following the same route. This study attempts to identify the correlations between the socioeconomic demographics of travelers and their carpooling potential considering the moral obligations. A questionnaire survey was conducted with the students of the University of Nizwa, Oman, and a total of 156 samples were collected. The results revealed a high interest of respondents in carpooling as a passenger as well as a driver. The respondent's moral obligations are high to carpool for the reduction in traffic congestion, air pollution, and energy consumption. The category analysis showed some differences in interests among different groups. The ordered regression analysis revealed that variables of gender, present travel mode, trip distance, car driving, and carpooling as passengers are significant in determining the moral obligations of the travelers. These results implicate that specific carpooling programs based on specific market segments have the potential for consideration and implementation.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
The World Bank. Institutional and governance structure of Oman’s transport sector: challenges and options for reforms [Internet]. Sultanate of Oman: Ministry of Transport and Communications; 2014 [cited 2020 Jul 26]. Available from: http://documents1.worldbank.org/curated/en/678831468097754481.
Al Maqbali N, Refeque M. Smart transportation for smart Oman: an enquiry into its potentials and implications. J Stud Res. 2017:1-7.
Javid MA, Al-Khayyat MA. Factors affecting the student’s intentions to choose carpooling: a case study in Oman. J Chin Inst Eng. 2021;44(4):332-41.
Meyer MD. Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior. Transp Res A: Policy Pract. 1999;33(7-8):575-99.
Eriksson L, Nordlund AM, Garvill J. Expected car use reduction in response to structural travel demand management measures. Transp Res F Traffic Psychol Behav. 2010;13(5):329-42.
Manzini R, Pareschi A. A decision-support system for the car pooling problem. J Transp Technol. 2012;2(2):85-101.
Jain T, Johnson M, Rose G. Exploring the process of travel behaviour change and mobility trajectories associated with car share adoption. Travel Behav Soc. 2020;18:117-31.
Taylor BD. Putting a price on mobility: cars and contradictions in planning. J Am Plan Assoc. 2006;72(3):279-84.
Shoup DC. Evaluating the effects of cashing out employer-paid parking: eight case studies. Transp Policy. 1997;4(4):201-16.
Olsson LE, Maier R, Friman M. Why do they ride with others? meta-analysis of factors influencing travelers to carpool. Sustainability. 2019;11(8):2414.
AlQuhtani S. Ridesharing as a potential sustainable transportation alternative in suburban universities: the case of Najran University, Saudi Arabia. Sustainability. 2022;14(8):4392.
Terrier L, Audrin B. Carpooling in times of crisis: organizational identification as a safety belt. Case Stud Transp Policy. 2022;10(3):1720-6.
Bachmann F, Hanimann A, Artho J, Jonas K. What drives people to carpool? explaining carpooling intention from the perspectives of carpooling passengers and drivers. Transp Res F Traffic Psychol Behav. 2018;59:260-8.
Mehdizadeh M, Nordfjaern T, Mamdoohi AR. Environmental norms and sustainable transport mode choice on children’s school travels: the norm-activation theory. Int J Sustain Transp. 2020;14(2):137-49.
Horton J. Carpooling cultures: learning from university students on-the-move [Internet]. Australia: University of Wollongong; 2020 [cited 2024 May 23]. Available from: https://ro.uow.edu.au/thss.
Julagasigorn P, Banomyong R, Grant DB, Varadejsatitwong P. What encourages people to carpool? a conceptual framework of carpooling psychological factors and research propositions. Transp Res Interdiscip Perspect. 2021;12:100493.
Hsieh FS. Comparison of a hybrid firefly–particle swarm optimization algorithm with six hybrid firefly–differential evolution algorithms and an effective cost-saving allocation method for ridesharing recommendation systems. Electronics. 2024;13(2):324.
Hsieh FS. A self-adaptive meta-heuristic algorithm based on success rate and differential evolution for improving the performance of ridesharing systems with a discount guaranteeo. Algorithms. 2024;17(1):9.
Hsieh FS. Trust-based recommendation for shared mobility systems based on a discrete self-adaptive neighborhood search differential evolution algorithm. Electronics. 2022;11(5):776.
Delhomme P, Gheorghiu A. Comparing French carpoolers and non-carpoolers: which factors contribute the most to carpooling?. Transp Res D Transp Environ. 2016;42:1-15.
Simancas W, Vinasco C, Rosas-Satizábal D, Ortiz-Ramirez HA, Rodriguez-Valencia A. Decision-making in open carpooling programs: perspectives of drivers versus passengers. Travel Behav Soc. 2024;36:100759.
Tahmasseby S, Kattan L, Barbour B. Propensity to participate in a peer-to-peer social-network-based carpooling system. J Adv Transp. 2016;50:240-54.
Park Y, Chen N, Akar G. Who is interested in carpooling and why: the importance of individual characteristics, role preferences and carpool markets. Transp Res Rec. 2018;2672(8):708-18.
Li L, Zhang H, Gan Z. Factors affecting college students’ attitudes towards carpooling. Transp Saf Environ. 2024;6(2):1-8.
Al-Khayyat MA, Al-rahbi AYH, Nasser H, Sinani SA, Al-kharusi AK, Javid MA. Assessment of parking demand & supply: a case of University Of Nizwa. The 8th National Symposium on Engineering Final Year Projects; 2018; Nizwa, Oman. p. 1-4.
Erdoğan S, Cirillo C, Tremblay JM. Ridesharing as a green commute alternative: a campus case study. Int J Sustain Transp. 2015;9(5):377-88.
Shrestha N. Factor analysis as a tool for survey analysis. Am J Appl Math Stat. 2021;9(1):4-11.
Tavakol M, Dennick R. Making sense of Cronbach’s alpha. Int J Med Educ. 2011;2:53-5.
Malodia S, Singla H. A study of carpooling behaviour using a stated preference web survey in selected cities of India. Transp Plan Technol. 2016;39(5):538-50.
Galland S, Knapen L, Yasar AUH, Gaud N, Janssens D, Lamotte O, et al. Multi-agent simulation of individual mobility behavior in carpooling. Transp Res C Emerg Technol. 2014;45:83-98.
Li J, Embry P, Mattingly SP, Sadabadi KF, Rasmidatta I, Burris MW. Who chooses to carpool and why? examination of Texas carpoolers. Transp Res Rec. 2007;2021(1):110-7.
Seyedabrishami S, Mamdoohi A, Barzegar A, Hasanpour S. Impact of carpooling on fuel saving in urban transportation: case study of Tehran. Procedia Soc Behav Sci. 2012;54:323-31.
Buliung RN, Soltys K, Habel C, Lanyon R. Driving factors behind successful carpool formation and use. Transp Res Rec. 2009;2118(1):31-8.
Yang H, Huang HJ. Carpooling and congestion pricing in a multilane highway with high-occupancy-vehicle lanes. Transp Res A Policy Pract. 1999;33(2):139-55.
Xia J, Curtin KM, Li W, Zhao Y. A new model for a carpool matching service. PLoS One. 2015;10(6):e0129257.