University Bus Services: Responding to Students’ Travel Demands?
Abstract
:1. Introduction
2. Shahid Bahonar University Bus Services (UBS)
3. Public Transportation Demands
4. Materials and Methods
4.1. Step 1: Grounded Theory
4.2. Step 2: Students’ Satisfaction
4.3. Step 3: Comparing Students Based on Their Frequent Transport Mode
4.4. Step 4: Structural Equation Modeling (SEM)
5. Data
6. Results
6.1. Step 1
6.2. Step 2
6.3. Step 3
6.4. Step 4
- -
- Path coefficients and t-values to demonstrate the relationship between factors (Figure 6).
- -
- Cronbach’s alpha and composite reliability coefficient (CRC) to determine latent variable reliability (Table 7).
- -
- Latent variable average variance (AVE) to prove validity (Table 7).
- -
- Factor loadings and t-values for each observed variable (Table 8).
- -
- Cross-loadings and Fornell–Larcker criterion to demonstrate discriminant validity (Table 9).
- -
- Goodness-of-fit index for the overall model.
Factors | Cronbach’s Alpha | CRC | AVE |
---|---|---|---|
UBP | 0.89 | 0.95 | 0.9 |
STC | 0.83 | 0.89 | 0.75 |
TIM | 0.71 | 0.83 | 0.63 |
SCF | 0.65 | 0.78 | 0.48 |
FLC | 0.8 | 0.87 | 0.62 |
Factors | FRE | UBP | STC | TIM | SCF | FLC |
---|---|---|---|---|---|---|
FRE | 1.000 | |||||
UBP | 0.177 | 0.942 | ||||
STC | 0.014 | −0.130 | 0.866 | |||
TIM | 0.233 | −0.174 | 0.368 | 0.799 | ||
SCF | −0.010 | −0.326 | 0.016 | 0.194 | 0.697 | |
FLC | 0.045 | −0.086 | 0.846 | 0.382 | 0.075 | 0.791 |
FRE | UBP | STC | TIM | SCF | FLC | |
AGE | 0.038 | −0.074 | 0.474 | 0.256 | 0.152 | 0.762 |
UBR | 0.172 | 0.986 | −0.133 | −0.173 | −0.311 | −0.092 |
UBF | 0.164 | 0.897 | −0.104 | −0.152 | −0.321 | −0.060 |
APC | −0.024 | −0.304 | 0.082 | 0.141 | 0.749 | 0.100 |
COM | 0.004 | −0.064 | 0.668 | 0.262 | 0.079 | 0.848 |
WLT | 0.117 | −0.112 | 0.301 | 0.701 | 0.181 | 0.302 |
FAM | 0.070 | −0.100 | 0.784 | 0.347 | 0.070 | 0.750 |
FRA | 1.000 | 0.177 | 0.014 | 0.233 | −0.010 | 0.045 |
INC | −0.106 | −0.236 | 0.051 | 0.189 | 0.768 | 0.071 |
JOS | 0.100 | −0.192 | −0.033 | 0.182 | 0.727 | 0.040 |
SSA | −0.016 | −0.143 | 0.928 | 0.327 | 0.017 | 0.737 |
SSE | −0.012 | −0.075 | 0.881 | 0.274 | −0.068 | 0.721 |
TRT | 0.221 | −0.150 | 0.293 | 0.826 | 0.125 | 0.299 |
FSA | 0.060 | −0.081 | 0.807 | 0.395 | 0.012 | 0.825 |
FSE | 0.033 | −0.041 | 0.785 | 0.278 | −0.046 | 0.722 |
WAT | 0.206 | −0.151 | 0.296 | 0.860 | 0.167 | 0.320 |
GEN | 0.062 | −0.115 | −0.183 | −0.040 | 0.516 | −0.081 |
7. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Dehghanmongabadi, A.; Hoşkara, Ş. Challenges of Promoting Sustainable Mobility on University Campuses: The Case of Eastern Mediterranean University. Sustainability 2018, 10, 4842. [Google Scholar] [CrossRef]
- Cherry, C.R.; Riggs, W.; Appleyard, B.; Dhakal, N.; Frost, A.; Jeffers, S.T. New and Unique Aspects of University Campus Transportation Data to Improve Planning Methods. Transp. Res. Rec. J. Transp. Res. Board 2018, 2672, 742–753. [Google Scholar] [CrossRef]
- Bouhouras, E.; Basbas, S.; Mintsis, G.; Taxiltaris, C.; Miltiadou, M.; Nikiforiadis, A.; Konstantinidou, M.N.; Mavropoulou, E. Level of Satisfaction among University Students Using Various Transport Modes. Sustainability 2022, 14, 4001. [Google Scholar] [CrossRef]
- Nadimi, N.; Sangdeh, A.K.; Kamkar, H. Developing sustainable transportation for university trips in low-income countries. Proc. Inst. Civ. Eng. Eng. Sustain. 2021, 14, 160–173. [Google Scholar] [CrossRef]
- Beaudoin, J.; Farzin, Y.H.; Lin Lawell, C.-Y.C. Public transit investment and sustainable transportation: A review of studies of transit’s impact on traffic congestion and air quality. Res. Transp. Econ. 2015, 52, 15–22. [Google Scholar] [CrossRef]
- Nadimi, N.; Sangdeh, A.K.; Berangi, M. Finding effective parameters for mitigating traffic congestion near universities. Proc. Inst. Civ. Eng. Munic. Eng. 2023, 1–11. [Google Scholar] [CrossRef]
- Fallah Zavareh, M.; Mehdizadeh, M.; Nordfjærn, T. Active travel as a pro-environmental behaviour: An integrated framework. Transp. Res. Part D Transp. Environ. 2020, 84, 102356. [Google Scholar] [CrossRef]
- Shatnawi, N.; Al-Omari, A.A.; Al-Qudah, H. Optimization of Bus Stops Locations Using GIS Techniques and Artificial Intelligence. Proc. Manuf. 2020, 44, 52–59. [Google Scholar] [CrossRef]
- Lu, J.; Li, B.; Li, H.; Al-Barakani, A. Expansion of city scale, traffic modes, traffic congestion, and air pollution. Cities 2021, 108, 102974. [Google Scholar] [CrossRef]
- Abdel Wahed Ahmed, M.M.; Abd El Monem, N. Sustainable and green transportation for better quality of life case study greater Cairo—Egypt. HBRC J. 2020, 16, 17–37. [Google Scholar] [CrossRef]
- Hidalgo-González, C.; Rodríguez-Fernández, M.P.; Pérez-Neira, D. Energy consumption in university commuting: Barriers, policies and reduction scenarios in León (Spain). Transp. Policy 2022, 116, 48–57. [Google Scholar] [CrossRef]
- Nadimi, N.; Sangdeh, A.K.; Amiri, A.M. Deciding about the effective factors on improving public transit popularity among women in developing countries. Transp. Lett. 2021, 13, 707–715. [Google Scholar] [CrossRef]
- Mehdizadeh, M.; Shariat-Mohaymany, A. Who are more likely to break the rule of congestion charging? Evidence from an active scheme with no referendum voting. Transp. Res. Part A Policy Pract. 2020, 135, 63–79. [Google Scholar] [CrossRef]
- Ikram, S.Z.; Hu, Y.; Wang, F. Disparities in Spatial Accessibility of Pharmacies in Baton Rouge, Louisiana. Geogr. Rev. 2015, 105, 492–510. [Google Scholar] [CrossRef]
- Nash, S.; Mitra, R. University students’ transportation patterns, and the role of neighbourhood types and attitudes. J. Transp. Geogr. 2019, 76, 200–211. [Google Scholar] [CrossRef]
- Wang, Y.; Cao, M.; Liu, Y.; Ye, R.; Gao, X.; Ma, L. Public transport equity in Shenyang: Using structural equation modelling. Res. Transp. Bus. Manag. 2022, 42, 100555. [Google Scholar] [CrossRef]
- Ibarra-Rojas, O.J.; Delgado, F.; Giesen, R.; Muñoz, J.C. Planning, operation, and control of bus transport systems: A literature review. Transp. Res. Part B Methodol. 2015, 77, 38–75. [Google Scholar] [CrossRef]
- Gholi, H.; Kermanshah, M.; Reza Mamdoohi, A. Investigating the sources of heterogeneity in passengers’ preferences for transit service quality. J. Public Transp. 2022, 24, 100014. [Google Scholar] [CrossRef]
- Carvalho dos Reis Silveira, T.; Romano, C.A.; Gadda, T.M.C. Loyalty and public transit: A quantitative systematic review of the literature. Transp. Rev. 2021, 42, 362–383. [Google Scholar] [CrossRef]
- El-Geneidy, A.; Buliung, R.; Diab, E.; van Lierop, D.; Langlois, M.; Legrain, A. Non-stop equity: Assessing daily intersections between transit accessibility and social disparity across the Greater Toronto and Hamilton Area (GTHA). Environ. Plan. B Plan. Des. 2015, 43, 540–560. [Google Scholar] [CrossRef]
- Jin, C.; Cheng, J.; Lu, Y.; Huang, Z.; Cao, F. Spatial inequity in access to healthcare facilities at a county level in a developing country: A case study of Deqing County, Zhejiang, China. Int. J. Equity Health 2015, 14, 67. [Google Scholar] [CrossRef] [PubMed]
- Lucas, K. Transport and social exclusion: Where are we now? Transp. Policy 2012, 20, 105–113. [Google Scholar] [CrossRef]
- Wan, C.; Su, S. China’s social deprivation: Measurement, spatiotemporal pattern and urban applications. Habitat Int. 2017, 62, 22–42. [Google Scholar] [CrossRef]
- Cuthill, N.; Cao, M.; Liu, Y.; Gao, X.; Zhang, Y. The Association between Urban Public Transport Infrastructure and Social Equity and Spatial Accessibility within the Urban Environment: An Investigation of Tramlink in London. Sustainability 2019, 11, 1229. [Google Scholar] [CrossRef]
- Di Ciommo, F.; Shiftan, Y. Transport equity analysis. Transp. Rev. 2017, 37, 139–151. [Google Scholar] [CrossRef]
- Litman, T. Evaluating Transportation Equity Guidance for Incorporating Distributional Impacts in Transportation Planning. ITE J. 2020, 92, 43–49. [Google Scholar]
- Low, W.-Y.; Cao, M.; De Vos, J.; Hickman, R. The journey experience of visually impaired people on public transport in London. Transp. Policy 2020, 97, 137–148. [Google Scholar] [CrossRef]
- Etminani-Ghasrodashti, R.; Paydar, M.; Hamidi, S. University-related travel behavior: Young adults’ decision-making in Iran. Sustain. Cities Soc. 2018, 43, 495–508. [Google Scholar] [CrossRef]
- Haggar, P.; Whitmarsh, L.; Skippon, S.M. Habit discontinuity and student travel mode choice. Transp. Res. Part F Traffic Psychol. Behav. 2019, 64, 1–13. [Google Scholar] [CrossRef]
- Zofia, L.; Pulawska, Z. Equity in transportation: New approach in transport planning. Transp. Probl. 2014, 9, 67–74. [Google Scholar]
- Lachapelle, U.; Manaugh, K.; Hamelin-Pratte, S. Providing discounted transit passes to younger university students: Are there effects on public transit, car and active transportation trips to university? Case Stud. Transp. Policy 2022, 10, 811–820. [Google Scholar] [CrossRef]
- Rotaris, L.; Danielis, R. The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste, Italy. Transp. Res. Part A Policy Pract. 2014, 67, 127–140. [Google Scholar] [CrossRef]
- Nadimi, N.; Camporeale, R.; Khaleghi, M.; Haghani, M.; Sheykhfard, A.; Shaaban, K. A Method to Determine an Equity Score for Transportation Systems in the Cities. Sustainability 2023, 15, 5818. [Google Scholar] [CrossRef]
- Tahmasbi, B.; Mansourianfar, M.H.; Haghshenas, H.; Kim, I. Multimodal accessibility-based equity assessment of urban public facilities distribution. Sustain. Cities Soc. 2019, 49, 101633. [Google Scholar] [CrossRef]
- Martens, K.; Golub, A.; Robinson, G. A justice-theoretic approach to the distribution of transportation benefits: Implications for transportation planning practice in the United States. Transp. Res. Part A Policy Pract. 2012, 46, 684–695. [Google Scholar] [CrossRef]
- Ahmed, Q.I.; Lu, H.; Ye, S. Urban transportation and equity: A case study of Beijing and Karachi. Transp. Res. Part A Policy Pract. 2008, 42, 125–139. [Google Scholar] [CrossRef]
- Ricciardi, A.M.; Xia, J.; Currie, G. Exploring public transport equity between separate disadvantaged cohorts: A case study in Perth, Australia. J. Transp. Geogr. 2015, 43, 111–122. [Google Scholar] [CrossRef]
- Behbahani, H.; Nazari, S.; Jafari Kang, M.; Litman, T. A conceptual framework to formulate transportation network design problem considering social equity criteria. Transp. Res. Part A Policy Pract. 2019, 125, 171–183. [Google Scholar] [CrossRef]
- Eckhart, M.; Ekelhart, A.; Biffl, S.; Lüder, A.; Weippl, E. QualSec: An Automated Quality-Driven Approach for Security Risk Identification in Cyber-Physical Production Systems. IEEE Trans. Ind. Inform. 2023, 19, 5870–5881. [Google Scholar] [CrossRef]
- Yang, L.; Sun, Q.; Zhang, N.; Li, Y. Indirect Multi-Energy Transactions of Energy Internet with Deep Reinforcement Learning Approach. IEEE Trans. Power Syst. 2022, 37, 4067–4077. [Google Scholar] [CrossRef]
- Loukaitou-Sideris, A.; Fink, C. Addressing Women’s Fear of Victimization in Transportation Settings: A Survey of U.S. Transit Agencies. Urban Aff. Rev. 2008, 44, 554–587. [Google Scholar] [CrossRef]
- Cox, A.; Prager, F.; Rose, A. Transportation security and the role of resilience: A foundation for operational metrics. Transp. Policy 2011, 18, 307–317. [Google Scholar] [CrossRef]
- Dunckel Graglia, A. Finding mobility: Women negotiating fear and violence in Mexico City’s public transit system. Gender Place Cult. 2016, 23, 624–640. [Google Scholar] [CrossRef]
- Amiri, A.M.; Nadimi, N.; Yousefian, A. Comparing the efficiency of different computation intelligence techniques in predicting accident frequency. IATSS Res. 2020, 44, 285–292. [Google Scholar] [CrossRef]
- Quinones, L.M. Sexual harassment in public transport in Bogotá. Transp. Res. Part A Policy Pract. 2020, 139, 54–69. [Google Scholar] [CrossRef]
- García, I.; Albelson, M.; Puczkowskyj, N.; Maheruma Khan, S.; Fagundo-Ojeda, K. Harassment of low-income women on transit: A photovoice project in Oregon and Utah. Transp. Res. Part D Transp. Environ. 2022, 112, 103466. [Google Scholar] [CrossRef]
- Orozco-Fontalvo, M.; Soto, J.; Arévalo, A.; Oviedo-Trespalacios, O. Women’s perceived risk of sexual harassment in a Bus Rapid Transit (BRT) system: The case of Barranquilla, Colombia. J. Transp. Health 2019, 14, 100598. [Google Scholar] [CrossRef]
- Klöckner, C.A.; Friedrichsmeier, T. A multi-level approach to travel mode choice—How person characteristics and situation specific aspects determine car use in a student sample. Transp. Res. Part F Traffic Psychol. Behav. 2011, 14, 261–277. [Google Scholar] [CrossRef]
- Zhou, J. From better understandings to proactive actions: Housing location and commuting mode choices among university students. Transp. Policy 2014, 33, 166–175. [Google Scholar] [CrossRef]
- Nguyen-Phuoc, D.Q.; Amoh-Gyimah, R.; Tran, A.T.P.; Phan, C.T. Mode choice among university students to school in Danang, Vietnam. Travel Behav. Soc. 2018, 13, 1–10. [Google Scholar] [CrossRef]
- Whalen, K.E.; Páez, A.; Carrasco, J.A. Mode choice of university students commuting to schooland the role of active travel. J. Transp. Geogr. 2013, 31, 132–142. [Google Scholar] [CrossRef]
- Danaf, M.; Abou-Zeid, M.; Kaysi, I. Modeling travel choices of students at a private, urban university: Insights and policy implications. Case Stud. Transp. Policy 2014, 2, 142–152. [Google Scholar] [CrossRef]
- Zhou, J. Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students. Transp. Res. Part A Policy Pract. 2012, 46, 1013–1029. [Google Scholar] [CrossRef]
- Khattak, A.; Wang, X.; Son, S.; Agnello, P. Travel by university students in Virginia: Is this travel different from travel by the general population? Transp. Res. Rec. 2011, 2255, 137–145. [Google Scholar] [CrossRef]
- Zhan, G.; Yan, X.; Zhu, S.; Wang, Y. Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China. Transp. Policy 2016, 45, 55–65. [Google Scholar] [CrossRef]
- Volosin, S.E. A Study of University Student Travel Behavior; Arizona State University: Tempe, AZ, USA, 2014. [Google Scholar]
- De Angelis, M.; Mantecchini, L.; Pietrantoni, L. A cluster analysis of university commuters: Attitudes, personal norms and constraints, and travel satisfaction. Int. J. Environ. Res. Public Health 2021, 18, 4592. [Google Scholar] [CrossRef] [PubMed]
- Mehdizadeh, M.; Zavareh, M.F.; Nordfjaern, T. Mono- and multimodal green transport use on university trips during winter and summer: Hybrid choice models on the norm-activation theory. Transp. Res. Part A Policy Pract. 2019, 130, 317–332. [Google Scholar] [CrossRef]
- Nordfjærn, T.; Egset, K.S.; Mehdizadeh, M. “Winter is coming”: Psychological and situational factors affecting transportation mode use among university students. Transp. Policy 2019, 81, 45–53. [Google Scholar] [CrossRef]
- Mehdizadeh, M.; Nordfjaern, T.; Mamdoohi, A. Environmental norms and sustainable transport mode choice on children’s school travels: The norm-activation theory. Int. J. Sustain. Transp. 2020, 14, 137–149. [Google Scholar] [CrossRef]
- Zhou, J. Proactive sustainable university transportation: Marginal effects, intrinsic values, and university students’ mode choice. Int. J. Sustain. Transp. 2016, 10, 815–824. [Google Scholar] [CrossRef]
- Godavarthy, R.; Mattson, J.; Hough, J. Impact of bike share on transit ridership in a smaller city with a university-oriented bike share program. J. Public Transp. 2022, 24, 100015. [Google Scholar] [CrossRef]
- Shaaban, K.; Kim, I. The influence of bus service satisfaction on university students’ mode choice. J. Adv. Transp. 2016, 50, 935–948. [Google Scholar] [CrossRef]
- Hashim, R.; Haron, S.; Mohamad, S.; Hassan, F. Assessment of Campus Bus Service Efficacy: An Application towards Green Environment. Proc. Soc. Behav. Sci. 2013, 105, 294–303. [Google Scholar] [CrossRef]
- Anwar, A.H.M.M.; Yang, J. Examining the Effects of Transport Policy on Modal Shift from Private Car to Public Bus. Proc. Eng. 2017, 180, 1413–1422. [Google Scholar] [CrossRef]
- Zeng, B.; He, Y. Factors influencing Chinese tourist flow in Japan—A grounded theory approach. Asia Pacific J. Tour. Res. 2019, 24, 56–69. [Google Scholar] [CrossRef]
- Corbin, J.; Strauss, A. Basics of Qualitative Research Techniques and Procedures for Developing Grounded Theory, 4th ed.; SAGE Publications: San Jose, CA, USA, 2014. [Google Scholar]
- Soltaninejad, M.; Fardhosseini, M.S.; Kim, Y.W. Safety climate and productivity improvement of construction workplaces through the 6S system: Mixed-method analysis of 5S and safety integration. Int. J. Occup. Saf. Ergon. 2022, 28, 1811–1821. [Google Scholar] [CrossRef]
- Lewis, S. Qualitative Inquiry and Research Design: Choosing Among Five Approaches. Health Promot. Pract. 2015, 16, 473–475. [Google Scholar] [CrossRef]
- Mac Donald, K.; Rezania, D.; Baker, R. A grounded theory examination of project managers’ accountability. Int. J. Proj. Manag. 2020, 38, 27–35. [Google Scholar] [CrossRef]
- Liu, F.; Kang, J. A grounded theory approach to the subjective understanding of urban soundscape in Sheffield. Cities 2016, 50, 28–39. [Google Scholar] [CrossRef]
- Mirbaha, B.; Saffarzadeh, M.; Seyed Abrishami, S.E.; Pirdavani, A. Evaluating the Willingness to Pay for Urban Congestion Priced Zones (Case Study of Tehran). Int. J. Transp. Eng. 2014, 1, 199–210. [Google Scholar] [CrossRef]
- Tavakoli Kashani, A.; Jafari, M.; Azizi Bondarabadi, M. A new approach in analyzing the accident severity of pedestrian crashes using structural equation modeling. J. Inj. Violence Res. 2021, 13, 23. [Google Scholar] [PubMed]
- Sheykhfard, A.; Haghighi, F. Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran. J. Safety Res. 2020, 72, 1–8. [Google Scholar] [CrossRef] [PubMed]
- Sheykhfard, A.; Haghighi, F.; Nordfjærn, T.; Soltaninejad, M. Structural equation modelling of potential risk factors for pedestrian accidents in rural and urban roads. Int. J. Inj. Contr. Saf. Promot. 2021, 28, 46–57. [Google Scholar] [CrossRef] [PubMed]
- Amiri, A.M.; Ferguson, M.R.; Razavi, S. Adoption patterns of autonomous technologies in Logistics: Evidence for Niagara Region. Transp. Lett. 2022, 14, 685–696. [Google Scholar] [CrossRef]
- Lee, J.Y.; Chung, J.H.; Son, B. Analysis of traffic accident size for Korean highway using structural equation models. Accid. Anal. Prev. 2008, 40, 1955–1963. [Google Scholar] [CrossRef]
- Peng, D.X.; Lai, F. Using partial least squares in operations management research: A practical guideline and summary of past research. J. Oper. Manag. 2012, 30, 467–480. [Google Scholar] [CrossRef]
- Tenenhaus, M.; Vinzi, V.E.; Chatelin, Y.M.; Lauro, C. PLS path modeling. Comput. Stat. Data Anal. 2005, 48, 159–205. [Google Scholar] [CrossRef]
- Hair, J.F.; Sarstedt, M.; Hopkins, L.; Kuppelwieser, V.G. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. Eur. Bus. Rev. 2014, 26, 106–121. [Google Scholar] [CrossRef]
- Riha, C.; Güntensperger, D.; Oschwald, J.; Kleinjung, T.; Meyer, M. Chapter 6—Application of latent growth curve modeling to predict individual trajectories during neurofeedback treatment for tinnitus. In Tinnitus—An Interdisciplinary Approach towards Individualized Treatment: Results from the European Graduate School for Interdisciplinary Tinnitus Research; Langguth, B., Kleinjung, T., De Ridder, D., Schlee, W., Vanneste, S., Eds.; Elsevier: Amsterdam, The Netherlands, 2021; Volume 263, pp. 109–136. ISBN 0079-6123. [Google Scholar]
- Harrison, L.; Stephan, K.; Friston, K. Chapter 38—Effective connectivity. In Statistical Parametric Mapping; Friston, K., Ashburner, J., Kiebel, S., Nichols, T., Penny, W.B.T.-S.P.M., Eds.; Academic Press: London, UK, 2007; pp. 508–521. ISBN 978-0-12-372560-8. [Google Scholar]
- Nadimi, N.; Mansourifar, F.; Shamsadini Lori, H.; Soltaninejad, M. Analyzing traffic violations among motorcyclists using structural equation modeling. Int. J. Inj. Contr. Saf. Promot. 2021, 28, 454–467. [Google Scholar] [CrossRef]
- Johnson, R.; Wichern, D. Applied Multivariate Statistical Analysis, 6th ed.; Prentice Hall: Upper Saddle River, NJ, USA, 2002; ISBN 978-0131877153. [Google Scholar]
- Peterson, R.A.; Kim, Y. On the relationship between coefficient alpha and composite reliability. J. Appl. Psychol. 2013, 98, 194–198. [Google Scholar] [CrossRef]
- Chin, W.W. The partial least squares approach for structural equation modeling. In Modern methods for business research; Lawrence Erlbaum Associates Publishers: Mahwah, NJ, USA, 1998; pp. 295–336. [Google Scholar]
- Lam, L.W. Impact of competitiveness on salespeople’s commitment and performance. J. Bus. Res. 2012, 65, 1328–1334. [Google Scholar] [CrossRef]
- Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
- Lecompte, M.C.; Juan Pablo, B.S. Transport systems and their impact con gender equity. Transp. Res. Procedia 2017, 25, 4245–4257. [Google Scholar] [CrossRef]
- Noor, H.M.; Nasrudin, N.; Foo, J. Determinants of Customer Satisfaction of Service Quality: City Bus Service in Kota Kinabalu, Malaysia. Proc. Soc. Behav. Sci. 2014, 153, 595–605. [Google Scholar] [CrossRef]
- Shaaban, K.; Khalil, R.F. Investigating the Customer Satisfaction of the Bus Service in Qatar. Proc. Soc. Behav. Sci. 2013, 104, 865–874. [Google Scholar] [CrossRef]
Variables | Case Study | Reference |
---|---|---|
Waiting time, fare, and safety | SBUK in Kerman, Iran | [6] |
Travel characteristics (weather, day of week, car ownership, weakness of public transit services, purpose of trip) and psychological variables | Ruhr University in Bochum, Germany | [48] |
Subsidy availability, proximity to the bus station, short distance to university, gender, and educational status (graduate or undergraduate) | UCLA in Los Angeles, CA, USA | [49] |
Gender, year of student, school location, residence status (rent or with family) distance, motorcycle license ownership, motorcycle ownership, and bicycle ownership | Six universities in Danang, Vietnam | [50] |
Cost, personal attitudes, environmental factors, and travel time | McMaster University, in Hamilton, ON, Canada | [51] |
Income, cost, travel time, car ownership, gender, residence location, and cost of parking | AUB in Beirut, Lebanon | [52] |
Distance, gender, educational status (graduate or undergraduate), age, feasibility of travel with friends, feasibility of using multimodal modes, transit passes and discounts for students | UCLA in Los Angeles, CA, USA | [53] |
Travel characteristics, personal behavior, socio-economic characteristics, and type of residence (on-campus or off-campus) | Four major universities in Virginia | [54] |
Grade, household income, public transit coverage rate, bicycle ownership, university location, distance, and gender | Eight universities in the three typical higher education cities in China | [55] |
Travel time, job status, and type of residence (on-campus, off campus, with friends, with family, or alone) | Arizona State University | [56] |
Convenience, accessibility, reliability, flexibility, distance, safety, travel time, cost, and car access | University of Bologna, Italy | [57] |
Status of bicycle lanes, on-campus security, bus costs, and frequency of busses | ULE, Spain | [11] |
Socio-economic characteristics, situational characteristics, and beliefs | Two largest university campuses in Trondheim, Norway (Dragvoll and Gløshaugen) | [58] |
Car ownership, walking distance, prioritizing physical activity, care about convenience, being aware of negative effects of using private cars | University campuses in Trondheim, Norway (Dragvoll and Gløshaugen) | [59] |
Socio-demographic characteristics, car ownership, access to public transport | Iran | [60] |
Access to bus service, subsidized transit, and short travel times | Los Angeles, CA, USA | [61] |
Bike sharing reduces bus ridership among students | North Dakota State University | [62] |
Ease of use, shade, cleanliness, safety, and level of crowding at bus stops | Qatar | [63] |
Punctuality and reliability of bus service, the shelters at bus stops, and seating capacity | Malaysia | [64] |
Travel time | University of Wollongong, Wollongong, Australia | [65] |
Students’ Characteristic Factors | Variable | Abbreviation | Categories | Frequency (%) |
---|---|---|---|---|
SCF | Gender | GEN | Men | 34.5 |
Women | 65.5 | |||
Age | AGE | 18–20 | 21.4 | |
20–22 | 47.7 | |||
22–24 | 22 | |||
24–26 | 5.6 | |||
26–28 | 2 | |||
>28 | 1.3 | |||
Education level | EDU | B. S. | 83.9 | |
M.Sc. | 13.8 | |||
Ph.D. | 2.3 | |||
Job status | JOS | No Job | 77 | |
Part-time Job | 17.1 | |||
Full-time Job | 5.9 | |||
Income (USD) | INC | <10 | 26 | |
10–25 | 30.6 | |||
25–50 | 17.4 | |||
50–100 | 13.8 | |||
100–250 | 6.6 | |||
>250 | 5.6 | |||
Access to private car in a week | APC | No access (0 days a week) | 31.2 | |
Rarely (1 to 2 days a week) | 37.5 | |||
Occasionally (3 to 4 days a week) | 18.1 | |||
All workdays (5 days a week) | 13.2 |
Main Category | Acronym | Sub-Category | Acronym |
---|---|---|---|
Fleet characteristics | FLC | Comfort | COM |
Safety | FSA | ||
Security | FSE | ||
Age | FAG | ||
Station characteristics | STC | Facilities/Amenities | FAM |
Security | SSE | ||
Safety | SSA | ||
Time | TIM | Travel time | TRT |
Walking time | WLT | ||
Waiting time | WAT | ||
Fare | FRE | Fare amount | FRA |
Variable | Categories | Frequency of Using UBS | |||
---|---|---|---|---|---|
Never | Rarely | Occasionally | Frequently | ||
GEN | Female | 32.8 | 15.7 | 31.8 | 19.7 |
Male | 42.9 | 20.0 | 22.9 | 14.3 | |
APC | No access | 23.4 | 8.6 | 32.8 | 35.2 |
Rarely | 25.1 | 26.1 | 38.0 | 10.9 | |
Occasionally | 51.3 | 32.7 | 16.0 | 2.7 | |
All days | 68.6 | 11.6 | 19.8 | 0.0 | |
INC | <10 | 27.9 | 7.6 | 32.9 | 31.7 |
10–25 | 34.8 | 18.5 | 32.6 | 14.1 | |
25–50 | 30.2 | 22.6 | 28.3 | 18.9 | |
50–100 | 45.2 | 28.6 | 16.7 | 9.5 | |
100–250 | 50.0 | 20.0 | 25.0 | 5.0 | |
>250 | 64.7 | 5.9 | 23.5 | 5.9 | |
AGE | 18–20 | 36.9 | 15.4 | 32.3 | 15.4 |
20–22 | 33.3 | 16.0 | 27.8 | 22.9 | |
22–24 | 34.3 | 22.4 | 28.4 | 14.9 | |
24–26 | 70.6 | 17.7 | 5.9 | 5.9 | |
26–28 | 16.7 | 16.7 | 66.7 | 0.0 | |
>28 | 50.0 | 0.0 | 50.0 | 0.0 | |
EDU | B. Sc. | 36.6 | 16.9 | 29.1 | 17.3 |
M. Sc. | 34.7 | 18.4 | 26.5 | 20.4 |
Variable | Categories | APC | |||
---|---|---|---|---|---|
No Access | Rarely | Occasionally | All Days | ||
GEN | Female | 40.4 | 34.3 | 17.6 | 7.7 |
Male | 14.2 | 42.8 | 19.1 | 23.9 |
Variable | Categories | INC | |||||
---|---|---|---|---|---|---|---|
<10 | 10–25 | 25–50 | 50–100 | 100–250 | >250 | ||
GEN | Female | 31.3 | 30.8 | 17.6 | 12.1 | 6 | 2.2 |
Male | 16.2 | 29.6 | 17.1 | 17.1 | 7.6 | 12.4 |
Mode | Total Costs (Per Trip) | Average Walking Time to Stations (min) | Average Waiting Time (min) | Average Travel Speed (km/h) | Route |
---|---|---|---|---|---|
UBS | Free | <15 | 60 | 25 to 30 | Fixed |
Public Bus | USD 0.04 | <15 | 30–60 | 25 to 30 | Fixed |
Taxi | USD 0.01 to 0.024 | <10 | <15 | 35 to 40 | Semi-flexible |
Uber | USD 0.3 to 1 | 0 | <10 | 40 to 50 | Flexible |
Private car | USD 1 to 1.5 | 0 | 0 | 40 to 50 | Flexible |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Nadimi, N.; Zamzam, A.; Litman, T. University Bus Services: Responding to Students’ Travel Demands? Sustainability 2023, 15, 8921. https://doi.org/10.3390/su15118921
Nadimi N, Zamzam A, Litman T. University Bus Services: Responding to Students’ Travel Demands? Sustainability. 2023; 15(11):8921. https://doi.org/10.3390/su15118921
Chicago/Turabian StyleNadimi, Navid, Aliakbar Zamzam, and Todd Litman. 2023. "University Bus Services: Responding to Students’ Travel Demands?" Sustainability 15, no. 11: 8921. https://doi.org/10.3390/su15118921
APA StyleNadimi, N., Zamzam, A., & Litman, T. (2023). University Bus Services: Responding to Students’ Travel Demands? Sustainability, 15(11), 8921. https://doi.org/10.3390/su15118921