Commuting preferences in Eastern Europe: case study in Town of Šiauliai
Abstract
This article presents a study conducted in the Town of Šiauliai with a population of 100 thousand, located in the Republic of Lithuania, where the market economy has been operating for 32 years and which is a member of the European Union for 20 years. In the town, the share of commuting travels by car is significantly higher than by public transport. Since the availability of the public transport network is identified in scientific publications as one of the many criteria for choosing public transport, it was decided to conduct a study and check to what extent the availability of the public transport network determines the choice to travel by bus or car. The research hypothesizes that residents who live in neighbourhoods with worse access to bus routes and stops choose more cars than those who live in neighbourhoods with better access to public transport. The results of the study showed that residents choose to travel by bus or car regardless of the availability of the route network. It was found that the origin–destination pairs and relative proportions of those commuting to work match both those traveling by car and by bus. The results of this study may not necessarily be the same in Western European cities or towns. The main limitation of this article is that the trip matrices were compiled from population survey data, as statistical information on origin–destination pairs in Town of Šiauliai is not regularly collected.
Keyword : commuting, transport network, public transport, personal car, survey
How to Cite
Jaržemskis, A., Bazaras, D., & Jaržemskienė, I. (2023). Commuting preferences in Eastern Europe: case study in Town of Šiauliai. Transport, 38(1), 31–43. https://doi.org/10.3846/transport.2023.19181
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abrantes, P. A. L.; Wardman, M. R. 2011. Meta-analysis of UK values of travel time: an update, Transportation Research Part A: Policy and Practice 45(1): 1–17. https://doi.org/10.1016/j.tra.2010.08.003
Anderson, M. K.; Nielsen, O. A.; Prato, C. G. 2017. Multimodal route choice models of public transport passengers in the greater Copenhagen area, EURO Journal on Transportation and Logistics 6(3): 221–245. https://doi.org/10.1007/s13676-014-0063-3
Averchenkova, A.; Fankhauser, S.; Finnegan, J. J. 2021. The impact of strategic climate legislation: evidence from expert interviews on the UK climate change act, Climate Policy 21(2): 251–263. https://doi.org/10.1080/14693062.2020.1819190
Badami, M. G.; Haider, M. 2007. An analysis of public bus transit performance in Indian cities, Transportation Research Part A: Policy and Practice 41(10): 961–981. https://doi.org/10.1016/j.tra.2007.06.002
Basagaña, X.; Triguero-Mas, M.; Agis, D.; Pérez, N.; Reche, C.; Alastuey, A.; Querol, X. 2018. Effect of public transport strikes on air pollution levels in Barcelona (Spain), Science of the Total Environment 610–611: 1076–1082. https://doi.org/10.1016/j.scitotenv.2017.07.263
Beck, M. J.; Hensher, D. A. 2020. Insights into the impact of COVID-19 on household travel and activities in Australia – the early days of easing restrictions, Transport Policy 99: 95–119. https://doi.org/10.1016/j.tranpol.2020.08.004
Beck, M. J.; Hess, S.; Ojeda Cabral, M.; Dubernet, I. 2017. Valuing travel time savings: A case of short-term or long term choices?, Transportation Research Part E: Logistics and Transportation Review 100: 133–143. https://doi.org/10.1016/j.tre.2017.02.001
Beirão, G.; Cabral, J. A. S. 2007. Understanding attitudes towards public transport and private car: a qualitative study, Transport Policy 14(6): 478–489. https://doi.org/10.1016/j.tranpol.2007.04.009
Benenson, I.; Martens, K.; Rofé, Y.; Kwartler, A. 2011. Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan area, The Annals of Regional Science 47(3): 499–515. https://doi.org/10.1007/s00168-010-0392-6
Bieri, D. S.; Dawkins, C. J. 2016. Quality of life, transportation costs, and federal housing assistance: leveling the playing field, Housing Policy Debate 26(4–5). 646–669. https://doi.org/10.1080/10511482.2016.1188844
Bocarejo Suescún, J. P.; Oviedo, D. R. 2012. Transport accessibility and social inequities: a tool for identification of mobility needs and evaluation of transport investments, Journal of Transport Geography 24: 142–154. https://doi.org/10.1016/j.jtrangeo.2011.12.004
Bok, J.; Kwon, Y. 2016. Comparable measures of accessibility to public transport using the general transit feed specification, Sustainability 8(3): 224. https://doi.org/10.3390/su8030224
Brutus, S.; Javadian, R.; Panaccio, A. J. 2017. Cycling, car, or public transit: a study of stress and mood upon arrival at work, International Journal of Workplace Health Management 10(1): 13–24. https://doi.org/10.1108/IJWHM-10-2015-0059
Chai, J.; Lu, Q.-Y.; Wang, S.-Y.; Lai, K. K. 2016. Analysis of road transportation energy consumption demand in China, Transportation Research Part D: Transport and Environment 48: 112–124. https://doi.org/10.1016/j.trd.2016.08.009
Chatterjee, K.; Ching, S.; Clark, B.; Davis, A.; De Vos, J.; Ettema, D.; Handy, S.; Martin, A.; Reardon, L. 2020. Commuting and wellbeing: a critical overview of the literature with implications for policy and future research, Transport Reviews 40(1): 5–34. https://doi.org/10.1080/01441647.2019.1649317
Cheng, Y.-H.; Chen, S.-Y. 2015. Perceived accessibility, mobility, and connectivity of public transportation systems, Transportation Research Part A: Policy and Practice 77: 386–403. https://doi.org/10.1016/j.tra.2015.05.003
Czerliński, M.; Bańka, M. S. 2021. Ticket tariffs modelling in urban and regional public transport, Archives of Transport 57(1): 103–117. https://doi.org/10.5604/01.3001.0014.8041
Danesi, A.; Tengattini, S. 2020. Evaluating accessibility of small communities via public transit, Archives of Transport 56(4): 59–72. https://doi.org/10.5604/01.3001.0014.5601
De Oña, J.; De Oña, R.; Eboli, L.; Mazzulla, G. 2013. Perceived service quality in bus transit service: a structural equation approach, Transport Policy 29: 219–226. https://doi.org/10.1016/j.tranpol.2013.07.001
De Vos, J. 2019. Satisfaction-induced travel behaviour, Transportation Research Part F: Traffic Psychology and Behaviour 63: 12–21. https://doi.org/10.1016/j.trf.2019.03.001
Dell’Olio, L.; Ibeas, Á.; Cecin, P. 2011. The quality of service desired by public transport users, Transport Policy 18(1): 217–227. https://doi.org/10.1016/j.tranpol.2010.08.005
Diana, M.; Daraio, C. 2014. Evaluating the effectiveness of public transport operations: a critical review and some policy indicators, International Journal of Transport Economics 41(1): 75–108. https://doi.org/10.1400/220028
Dirgahayani, P. 2013. Environmental co-benefits of public transportation improvement initiative: the case of Trans-Jogja bus system in Yogyakarta, Indonesia, Journal of Cleaner Production 58: 74–81. https://doi.org/10.1016/j.jclepro.2013.07.013
Eboli, L.; Mazzulla, G. 2008. A stated preference experiment for measuring service quality in public transport, Transportation Planning and Technology 31(5): 509–523. https://doi.org/10.1080/03081060802364471
EC. 2019. Communication from the Commission to the European Parliament, the European Council, the Council, the European Economic and Social Committee and the Committee of the Regions: the European Green Deal. COM/2019/640 Final. 11 December 2019, European Commission (EC), Brussels, Belgium. 24 p. Available from Internet: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52019DC0640
Echaniz, E.; Dell’Olio, L.; Ibeas, Á. 2018. Modelling perceived quality for urban public transport systems using weighted variables and random parameters, Transport Policy 67: 31–39. https://doi.org/10.1016/j.tranpol.2017.05.006
Eltved, M.; Nielsen, O. A.; Rasmussen, T. K. 2019. An assignment model for public transport networks with both schedule- and frequency-based services, EURO Journal on Transportation and Logistics 8(5): 769–793. https://doi.org/10.1007/s13676-019-00147-4
Fosgerau, M.; Frejinger, E.; Karlstrom, A. 2013. A link based network route choice model with unrestricted choice set, Transportation Research Part B: Methodological 56: 70–80. https://doi.org/10.1016/j.trb.2013.07.012
Fransen, K.; Neutens, T.; Farber, S.; De Maeyer, P.; Deruyter, G.; Witlox, F. 2015. Identifying public transport gaps using time-dependent accessibility levels, Journal Transport Geography 48: 176–187. https://doi.org/10.1016/j.jtrangeo.2015.09.008
Garcia-Martinez, A.; Cascajo, R.; Jara-Diaz, S. R.; Chowdhury, S.; Monzon, A. 2018. Transfer penalties in multimodal public transport networks, Transportation Research Part A: Policy and Practice 114: 52–66. https://doi.org/10.1016/j.tra.2018.01.016
Gkiotsalitis, K.; Cats, O. 2021. Public transport planning adaption under the COVID-19 pandemic crisis: literature review of research needs and directions, Transport Reviews 41(3): 374–392. https://doi.org/10.1080/01441647.2020.1857886
GOV.UK. 2019. Greenhouse Gas Reporting: Conversion Factors 2019. London, UK. Available from Internet: https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2019
Guglielmetti Mugion, R.; Toni, M.; Raharjo, H.; Di Pietro, L.; Sebathu, S. P. 2018. Does the service quality of urban public transport enhance sustainable mobility?, Journal of Cleaner Production 174: 1566–1587. https://doi.org/10.1016/j.jclepro.2017.11.052
Gundlach, A.; Ehrlinspiel, M.; Kirsch, S.; Koschker, A.; Sagebiel, J. 2018. Investigating people’s preferences for car-free city centers: a discrete choice experiment, Transportation Research Part D: Transport and Environment 63: 677–688. https://doi.org/10.1016/j.trd.2018.07.004
Gutiérrez, A.; Miravet, D.; Domènech, A. 2021. COVID-19 and urban public transport services: emerging challenges and research agenda, Cities & Health 5(Supplement 1): S177–S180. https://doi.org/10.1080/23748834.2020.1804291
Handy, S.; Thigpen, C. 2019. Commute quality and its implications for commute satisfaction: Exploring the role of mode, location, and other factors, Travel Behaviour and Society 16: 241–248. https://doi.org/10.1016/J.TBS.2018.03.001
Hernandez, D. 2018. Uneven mobilities, uneven opportunities: social distribution of public transport accessibility to jobs and education in Montevideo, Journal of Transport Geography 67: 119–125. https://doi.org/10.1016/j.jtrangeo.2017.08.017
Hu, X.; Chen, X.; Zhao, J.; Yu, K.; Long, B.; Dai, G. 2022. Comprehensive service quality evaluation of public transit based on extension cloud model, Archives of Transport 61(1): 103–115. https://doi.org/10.5604/01.3001.0015.8198
Jain, S.; Aggarwal, P.; Kumar, P.; Singhal, S.; Sharma, P. 2014. Identifying public preferences using multi-criteria decision making for assessing the shift of urban commuters from private to public transport: a case study of Delhi, Transportation Research Part F: Traffic Psychology and Behaviour 24: 60–70. https://doi.org/10.1016/j.trf.2014.03.007
Jánošíková, L.; Slavík, J.; Koháni, M. 2014. Estimation of a route choice model for urban public transport using smart card data, Transportation Planning and Technology 37(7): 638–648. https://doi.org/10.1080/03081060.2014.935570
Jarzemskis, A.; Jarzemskiene, I. 2017. Evolution of traveller experience quality perception in European level policy documents and the case study for Siauliai, Transport and Telecommunication 18(3): 220–230 https://doi.org/10.1515/ttj-2017-0019
Jiang, G.; Fosgerau, M.; Lo, H. K. 2020. Route choice, travel time variability, and rational inattention, Transportation Research Part B: Methodological 132: 188–207. https://doi.org/10.1016/j.trb.2019.05.020
Johnson, D.; Ercolani, M.; Mackie, P. 2017. Econometric analysis of the link between public transport accessibility and employment, Transport Policy 60: 1–9. https://doi.org/10.1016/j.tranpol.2017.08.001
Kawabata, M.; Shen, Q. 2006. Job accessibility as an indicator of auto-oriented urban structure: a comparison of Boston and Los Angeles with Tokyo, Environment and Planning B: Planning and Design 33(1): 115–130. https://doi.org/10.1068/b31144
König, A.; Grippenkoven, J. 2020. Modelling travelers’ appraisal of ridepooling service characteristics with a discrete choice experiment, European Transport Research Review 12: 1. https://doi.org/10.1186/s12544-019-0391-3
Lättman, K.; Friman, M.; Olsson, L. E. 2016. Perceived accessibility of public transport as a potential indicator of social inclusion, Social Inclusion 4(3): 36–45. https://doi.org/10.17645/si.v4i3.481
Leng, N.; Corman, F. 2020. The role of information availability to passengers in public transport disruptions: An agent-based simulation approach, Transportation Research Part A: Policy and Practice 133: 214–236. https://doi.org/10.1016/j.tra.2020.01.007
Mackett, R. L.; Thoreau, R. 2015. Transport, social exclusion and health, Journal of Transport & Health 2(4): 610–617. https://doi.org/10.1016/j.jth.2015.07.006
Marra, A. D.; Corman, F. 2020. Determining an efficient and precise choice set for public transport based on tracking data, Transportation Research Part A: Policy and Practice 142: 168–186. https://doi.org/10.1016/j.tra.2020.10.013
Mulley, C.; Rizzi, L. I.; Millett, C.; Shiftan, Y. 2016. Public transport and health: publicising the evidence, Journal of Transport & Health 3(2): 131–132. https://doi.org/10.1016/j.jth.2016.05.129
Nassir, N.; Hickman, M.; Malekzadeh, A.; Irannezhad, E. 2015. Modeling transit passenger choices of access stop, Transportation Research Record: Journal of the Transportation Research Board 2493: 70–77. https://doi.org/10.3141/2493-08
Paulley, N.; Balcombe, R.; Mackett, R.; Titheridge, H.; Preston, J.; Wardman, M.; Shires, J.; White, P. 2006. The demand for public transport: the effects of fares, quality of service, income and car ownership, Transport Policy 13(4): 295–306. https://doi.org/10.1016/j.tranpol.2005.12.004
Pons Rotger, G.; Sick Nielsen, T. 2015. Effects of job accessibility improved by public transport system: natural experimental evidence from the Copenhagen metro, European Journal of Transport and Infrastructure Research 15(4): 419–441. https://doi.org/10.18757/ejtir.2015.15.4.3090
Poudenx, P. 2008. The effect of transportation policies on energy consumption and greenhouse gas emission from urban passenger transportation, Transport Research Part A: Policy Practice 42(6): 901–909. https://doi.org/10.1016/j.tra.2008.01.013
Prato, C. G. 2009. Route choice modeling: past, present and future research directions, Journal of Choice Modelling 2(1): 65–100. https://doi.org/10.1016/S1755-5345(13)70005-8
Rudyk, T.; Szczepański, E.; Jacyna, M. 2019. Safety factor in the sustainable fleet management model, Archives of Transport 49(1): 103–114. https://doi.org/10.5604/01.3001.0013.2780
Saghapour, T.; Moridpour, S.; Thompson, R. G. 2016. Public transport accessibility in metropolitan areas: A new approach incorporating population density, Journal of Transport Geography 54: 273–285. https://doi.org/10.1016/j.jtrangeo.2016.06.019
Saif, M. A.; Zefreh, M. M.; Torok, A. 2019. Public transport accessibility: a literature review, Periodica Polytechnica Transportation Engineering 47(1): 36–43. https://doi.org/10.3311/PPtr.12072
Saleh, W.; Sammer, G. 2009. Travel Demand Management and Road User Pricing: Success, Failure and Feasibility. Routledge. 268 p. https://doi.org/10.4324/9781315549743
Šiaulių miesto savivaldybė. 2022. Priemonių įgyvendinimo rodikliai ir stebėsenos mechanizmas pagal patvirtintą „darnaus judumo“ variantą Nr. 1. 5 p. Available from Internet: https://www.siauliai.lt/upload/media/user/21/Judumas/Siauliu%20miesto%20darnaus%20judumo%20plano%20igyvendinimo%202018-2021%20m%20ataskaita.pdf (in Lithuanian).
Soza-Parra, J.; Raveau, S.; Muñoz, J. C.; Cats, O. 2019. The underlying effect of public transport reliability on users’ satisfaction, Transportation Research Part A: Policy and Practice 126: 83–93. https://doi.org/10.1016/j.tra.2019.06.004
Tan, R.; Adnan, M.; Lee, D.-H.; Ben-Akiva, M. E. 2015. New path size formulation in path size logit for route choice modeling in public transport networks, Transportation Research Record: Journal of the Transportation Research Board 2538(1): 11–18. https://doi.org/10.3141/2538-02
Vickerman, R. 2021. Will Covid-19 put the public back in public transport? A UK perspective, Transport Policy 103: 95–102. https://doi.org/10.1016/j.tranpol.2021.01.005
Veeneman, W.; Mulley, C. 2018. Multi-level governance in public transport: Governmental layering and its influence on public transport service solutions, Research in Transportation Economics 69: 430–437. https://doi.org/10.1016/j.retrec.2018.07.005
Widiyani, W. 2019. The influences of public transport on parking space: a study on travel choice behaviour between private cars and public transport, IOP Conference Series: Earth and Environmental Science 352: 012002. https://doi.org/10.1088/1755-1315/532/1/012002
Yatskiv, I.; Budilovich, E.; Gromule, V. 2017. Accessibility to Riga public transport services for transit passengers, Procedia Engineering 187: 82–88. https://doi.org/10.1016/j.proeng.2017.04.353
Zimmermann, M.; Frejinger, E. 2020. A tutorial on recursive models for analyzing and predicting path choice behavior, EURO Journal on Transportation and Logistics 9(2): 100004. https://doi.org/10.1016/j.ejtl.2020.100004
Anderson, M. K.; Nielsen, O. A.; Prato, C. G. 2017. Multimodal route choice models of public transport passengers in the greater Copenhagen area, EURO Journal on Transportation and Logistics 6(3): 221–245. https://doi.org/10.1007/s13676-014-0063-3
Averchenkova, A.; Fankhauser, S.; Finnegan, J. J. 2021. The impact of strategic climate legislation: evidence from expert interviews on the UK climate change act, Climate Policy 21(2): 251–263. https://doi.org/10.1080/14693062.2020.1819190
Badami, M. G.; Haider, M. 2007. An analysis of public bus transit performance in Indian cities, Transportation Research Part A: Policy and Practice 41(10): 961–981. https://doi.org/10.1016/j.tra.2007.06.002
Basagaña, X.; Triguero-Mas, M.; Agis, D.; Pérez, N.; Reche, C.; Alastuey, A.; Querol, X. 2018. Effect of public transport strikes on air pollution levels in Barcelona (Spain), Science of the Total Environment 610–611: 1076–1082. https://doi.org/10.1016/j.scitotenv.2017.07.263
Beck, M. J.; Hensher, D. A. 2020. Insights into the impact of COVID-19 on household travel and activities in Australia – the early days of easing restrictions, Transport Policy 99: 95–119. https://doi.org/10.1016/j.tranpol.2020.08.004
Beck, M. J.; Hess, S.; Ojeda Cabral, M.; Dubernet, I. 2017. Valuing travel time savings: A case of short-term or long term choices?, Transportation Research Part E: Logistics and Transportation Review 100: 133–143. https://doi.org/10.1016/j.tre.2017.02.001
Beirão, G.; Cabral, J. A. S. 2007. Understanding attitudes towards public transport and private car: a qualitative study, Transport Policy 14(6): 478–489. https://doi.org/10.1016/j.tranpol.2007.04.009
Benenson, I.; Martens, K.; Rofé, Y.; Kwartler, A. 2011. Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan area, The Annals of Regional Science 47(3): 499–515. https://doi.org/10.1007/s00168-010-0392-6
Bieri, D. S.; Dawkins, C. J. 2016. Quality of life, transportation costs, and federal housing assistance: leveling the playing field, Housing Policy Debate 26(4–5). 646–669. https://doi.org/10.1080/10511482.2016.1188844
Bocarejo Suescún, J. P.; Oviedo, D. R. 2012. Transport accessibility and social inequities: a tool for identification of mobility needs and evaluation of transport investments, Journal of Transport Geography 24: 142–154. https://doi.org/10.1016/j.jtrangeo.2011.12.004
Bok, J.; Kwon, Y. 2016. Comparable measures of accessibility to public transport using the general transit feed specification, Sustainability 8(3): 224. https://doi.org/10.3390/su8030224
Brutus, S.; Javadian, R.; Panaccio, A. J. 2017. Cycling, car, or public transit: a study of stress and mood upon arrival at work, International Journal of Workplace Health Management 10(1): 13–24. https://doi.org/10.1108/IJWHM-10-2015-0059
Chai, J.; Lu, Q.-Y.; Wang, S.-Y.; Lai, K. K. 2016. Analysis of road transportation energy consumption demand in China, Transportation Research Part D: Transport and Environment 48: 112–124. https://doi.org/10.1016/j.trd.2016.08.009
Chatterjee, K.; Ching, S.; Clark, B.; Davis, A.; De Vos, J.; Ettema, D.; Handy, S.; Martin, A.; Reardon, L. 2020. Commuting and wellbeing: a critical overview of the literature with implications for policy and future research, Transport Reviews 40(1): 5–34. https://doi.org/10.1080/01441647.2019.1649317
Cheng, Y.-H.; Chen, S.-Y. 2015. Perceived accessibility, mobility, and connectivity of public transportation systems, Transportation Research Part A: Policy and Practice 77: 386–403. https://doi.org/10.1016/j.tra.2015.05.003
Czerliński, M.; Bańka, M. S. 2021. Ticket tariffs modelling in urban and regional public transport, Archives of Transport 57(1): 103–117. https://doi.org/10.5604/01.3001.0014.8041
Danesi, A.; Tengattini, S. 2020. Evaluating accessibility of small communities via public transit, Archives of Transport 56(4): 59–72. https://doi.org/10.5604/01.3001.0014.5601
De Oña, J.; De Oña, R.; Eboli, L.; Mazzulla, G. 2013. Perceived service quality in bus transit service: a structural equation approach, Transport Policy 29: 219–226. https://doi.org/10.1016/j.tranpol.2013.07.001
De Vos, J. 2019. Satisfaction-induced travel behaviour, Transportation Research Part F: Traffic Psychology and Behaviour 63: 12–21. https://doi.org/10.1016/j.trf.2019.03.001
Dell’Olio, L.; Ibeas, Á.; Cecin, P. 2011. The quality of service desired by public transport users, Transport Policy 18(1): 217–227. https://doi.org/10.1016/j.tranpol.2010.08.005
Diana, M.; Daraio, C. 2014. Evaluating the effectiveness of public transport operations: a critical review and some policy indicators, International Journal of Transport Economics 41(1): 75–108. https://doi.org/10.1400/220028
Dirgahayani, P. 2013. Environmental co-benefits of public transportation improvement initiative: the case of Trans-Jogja bus system in Yogyakarta, Indonesia, Journal of Cleaner Production 58: 74–81. https://doi.org/10.1016/j.jclepro.2013.07.013
Eboli, L.; Mazzulla, G. 2008. A stated preference experiment for measuring service quality in public transport, Transportation Planning and Technology 31(5): 509–523. https://doi.org/10.1080/03081060802364471
EC. 2019. Communication from the Commission to the European Parliament, the European Council, the Council, the European Economic and Social Committee and the Committee of the Regions: the European Green Deal. COM/2019/640 Final. 11 December 2019, European Commission (EC), Brussels, Belgium. 24 p. Available from Internet: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52019DC0640
Echaniz, E.; Dell’Olio, L.; Ibeas, Á. 2018. Modelling perceived quality for urban public transport systems using weighted variables and random parameters, Transport Policy 67: 31–39. https://doi.org/10.1016/j.tranpol.2017.05.006
Eltved, M.; Nielsen, O. A.; Rasmussen, T. K. 2019. An assignment model for public transport networks with both schedule- and frequency-based services, EURO Journal on Transportation and Logistics 8(5): 769–793. https://doi.org/10.1007/s13676-019-00147-4
Fosgerau, M.; Frejinger, E.; Karlstrom, A. 2013. A link based network route choice model with unrestricted choice set, Transportation Research Part B: Methodological 56: 70–80. https://doi.org/10.1016/j.trb.2013.07.012
Fransen, K.; Neutens, T.; Farber, S.; De Maeyer, P.; Deruyter, G.; Witlox, F. 2015. Identifying public transport gaps using time-dependent accessibility levels, Journal Transport Geography 48: 176–187. https://doi.org/10.1016/j.jtrangeo.2015.09.008
Garcia-Martinez, A.; Cascajo, R.; Jara-Diaz, S. R.; Chowdhury, S.; Monzon, A. 2018. Transfer penalties in multimodal public transport networks, Transportation Research Part A: Policy and Practice 114: 52–66. https://doi.org/10.1016/j.tra.2018.01.016
Gkiotsalitis, K.; Cats, O. 2021. Public transport planning adaption under the COVID-19 pandemic crisis: literature review of research needs and directions, Transport Reviews 41(3): 374–392. https://doi.org/10.1080/01441647.2020.1857886
GOV.UK. 2019. Greenhouse Gas Reporting: Conversion Factors 2019. London, UK. Available from Internet: https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2019
Guglielmetti Mugion, R.; Toni, M.; Raharjo, H.; Di Pietro, L.; Sebathu, S. P. 2018. Does the service quality of urban public transport enhance sustainable mobility?, Journal of Cleaner Production 174: 1566–1587. https://doi.org/10.1016/j.jclepro.2017.11.052
Gundlach, A.; Ehrlinspiel, M.; Kirsch, S.; Koschker, A.; Sagebiel, J. 2018. Investigating people’s preferences for car-free city centers: a discrete choice experiment, Transportation Research Part D: Transport and Environment 63: 677–688. https://doi.org/10.1016/j.trd.2018.07.004
Gutiérrez, A.; Miravet, D.; Domènech, A. 2021. COVID-19 and urban public transport services: emerging challenges and research agenda, Cities & Health 5(Supplement 1): S177–S180. https://doi.org/10.1080/23748834.2020.1804291
Handy, S.; Thigpen, C. 2019. Commute quality and its implications for commute satisfaction: Exploring the role of mode, location, and other factors, Travel Behaviour and Society 16: 241–248. https://doi.org/10.1016/J.TBS.2018.03.001
Hernandez, D. 2018. Uneven mobilities, uneven opportunities: social distribution of public transport accessibility to jobs and education in Montevideo, Journal of Transport Geography 67: 119–125. https://doi.org/10.1016/j.jtrangeo.2017.08.017
Hu, X.; Chen, X.; Zhao, J.; Yu, K.; Long, B.; Dai, G. 2022. Comprehensive service quality evaluation of public transit based on extension cloud model, Archives of Transport 61(1): 103–115. https://doi.org/10.5604/01.3001.0015.8198
Jain, S.; Aggarwal, P.; Kumar, P.; Singhal, S.; Sharma, P. 2014. Identifying public preferences using multi-criteria decision making for assessing the shift of urban commuters from private to public transport: a case study of Delhi, Transportation Research Part F: Traffic Psychology and Behaviour 24: 60–70. https://doi.org/10.1016/j.trf.2014.03.007
Jánošíková, L.; Slavík, J.; Koháni, M. 2014. Estimation of a route choice model for urban public transport using smart card data, Transportation Planning and Technology 37(7): 638–648. https://doi.org/10.1080/03081060.2014.935570
Jarzemskis, A.; Jarzemskiene, I. 2017. Evolution of traveller experience quality perception in European level policy documents and the case study for Siauliai, Transport and Telecommunication 18(3): 220–230 https://doi.org/10.1515/ttj-2017-0019
Jiang, G.; Fosgerau, M.; Lo, H. K. 2020. Route choice, travel time variability, and rational inattention, Transportation Research Part B: Methodological 132: 188–207. https://doi.org/10.1016/j.trb.2019.05.020
Johnson, D.; Ercolani, M.; Mackie, P. 2017. Econometric analysis of the link between public transport accessibility and employment, Transport Policy 60: 1–9. https://doi.org/10.1016/j.tranpol.2017.08.001
Kawabata, M.; Shen, Q. 2006. Job accessibility as an indicator of auto-oriented urban structure: a comparison of Boston and Los Angeles with Tokyo, Environment and Planning B: Planning and Design 33(1): 115–130. https://doi.org/10.1068/b31144
König, A.; Grippenkoven, J. 2020. Modelling travelers’ appraisal of ridepooling service characteristics with a discrete choice experiment, European Transport Research Review 12: 1. https://doi.org/10.1186/s12544-019-0391-3
Lättman, K.; Friman, M.; Olsson, L. E. 2016. Perceived accessibility of public transport as a potential indicator of social inclusion, Social Inclusion 4(3): 36–45. https://doi.org/10.17645/si.v4i3.481
Leng, N.; Corman, F. 2020. The role of information availability to passengers in public transport disruptions: An agent-based simulation approach, Transportation Research Part A: Policy and Practice 133: 214–236. https://doi.org/10.1016/j.tra.2020.01.007
Mackett, R. L.; Thoreau, R. 2015. Transport, social exclusion and health, Journal of Transport & Health 2(4): 610–617. https://doi.org/10.1016/j.jth.2015.07.006
Marra, A. D.; Corman, F. 2020. Determining an efficient and precise choice set for public transport based on tracking data, Transportation Research Part A: Policy and Practice 142: 168–186. https://doi.org/10.1016/j.tra.2020.10.013
Mulley, C.; Rizzi, L. I.; Millett, C.; Shiftan, Y. 2016. Public transport and health: publicising the evidence, Journal of Transport & Health 3(2): 131–132. https://doi.org/10.1016/j.jth.2016.05.129
Nassir, N.; Hickman, M.; Malekzadeh, A.; Irannezhad, E. 2015. Modeling transit passenger choices of access stop, Transportation Research Record: Journal of the Transportation Research Board 2493: 70–77. https://doi.org/10.3141/2493-08
Paulley, N.; Balcombe, R.; Mackett, R.; Titheridge, H.; Preston, J.; Wardman, M.; Shires, J.; White, P. 2006. The demand for public transport: the effects of fares, quality of service, income and car ownership, Transport Policy 13(4): 295–306. https://doi.org/10.1016/j.tranpol.2005.12.004
Pons Rotger, G.; Sick Nielsen, T. 2015. Effects of job accessibility improved by public transport system: natural experimental evidence from the Copenhagen metro, European Journal of Transport and Infrastructure Research 15(4): 419–441. https://doi.org/10.18757/ejtir.2015.15.4.3090
Poudenx, P. 2008. The effect of transportation policies on energy consumption and greenhouse gas emission from urban passenger transportation, Transport Research Part A: Policy Practice 42(6): 901–909. https://doi.org/10.1016/j.tra.2008.01.013
Prato, C. G. 2009. Route choice modeling: past, present and future research directions, Journal of Choice Modelling 2(1): 65–100. https://doi.org/10.1016/S1755-5345(13)70005-8
Rudyk, T.; Szczepański, E.; Jacyna, M. 2019. Safety factor in the sustainable fleet management model, Archives of Transport 49(1): 103–114. https://doi.org/10.5604/01.3001.0013.2780
Saghapour, T.; Moridpour, S.; Thompson, R. G. 2016. Public transport accessibility in metropolitan areas: A new approach incorporating population density, Journal of Transport Geography 54: 273–285. https://doi.org/10.1016/j.jtrangeo.2016.06.019
Saif, M. A.; Zefreh, M. M.; Torok, A. 2019. Public transport accessibility: a literature review, Periodica Polytechnica Transportation Engineering 47(1): 36–43. https://doi.org/10.3311/PPtr.12072
Saleh, W.; Sammer, G. 2009. Travel Demand Management and Road User Pricing: Success, Failure and Feasibility. Routledge. 268 p. https://doi.org/10.4324/9781315549743
Šiaulių miesto savivaldybė. 2022. Priemonių įgyvendinimo rodikliai ir stebėsenos mechanizmas pagal patvirtintą „darnaus judumo“ variantą Nr. 1. 5 p. Available from Internet: https://www.siauliai.lt/upload/media/user/21/Judumas/Siauliu%20miesto%20darnaus%20judumo%20plano%20igyvendinimo%202018-2021%20m%20ataskaita.pdf (in Lithuanian).
Soza-Parra, J.; Raveau, S.; Muñoz, J. C.; Cats, O. 2019. The underlying effect of public transport reliability on users’ satisfaction, Transportation Research Part A: Policy and Practice 126: 83–93. https://doi.org/10.1016/j.tra.2019.06.004
Tan, R.; Adnan, M.; Lee, D.-H.; Ben-Akiva, M. E. 2015. New path size formulation in path size logit for route choice modeling in public transport networks, Transportation Research Record: Journal of the Transportation Research Board 2538(1): 11–18. https://doi.org/10.3141/2538-02
Vickerman, R. 2021. Will Covid-19 put the public back in public transport? A UK perspective, Transport Policy 103: 95–102. https://doi.org/10.1016/j.tranpol.2021.01.005
Veeneman, W.; Mulley, C. 2018. Multi-level governance in public transport: Governmental layering and its influence on public transport service solutions, Research in Transportation Economics 69: 430–437. https://doi.org/10.1016/j.retrec.2018.07.005
Widiyani, W. 2019. The influences of public transport on parking space: a study on travel choice behaviour between private cars and public transport, IOP Conference Series: Earth and Environmental Science 352: 012002. https://doi.org/10.1088/1755-1315/532/1/012002
Yatskiv, I.; Budilovich, E.; Gromule, V. 2017. Accessibility to Riga public transport services for transit passengers, Procedia Engineering 187: 82–88. https://doi.org/10.1016/j.proeng.2017.04.353
Zimmermann, M.; Frejinger, E. 2020. A tutorial on recursive models for analyzing and predicting path choice behavior, EURO Journal on Transportation and Logistics 9(2): 100004. https://doi.org/10.1016/j.ejtl.2020.100004