Transactions on Transport Sciences 2022, 13(3):14-23

Analysis of the effects of the first phase of COVID-19 pandemic on mobility choices in Italy by a multi-criteria approach

Tiziana Campisia*, Sarbast Moslemb, Szabolcs Dulebab, c, Nurten Akgün Tanbayd, Agnieszka Szmelter-Jarosze, Giovanni Tesorierea
a.* Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, 94100 Enna, Italy
b. Department of Transport Technology and Economics, Budapest University of Technology and Economics, Budapest, Hungary
c. Institute of Mathematics and Informatics, University of Nyíregyháza, Nyíregyháza, Hungary
d. Bursa Technical University, Faculty of Engineering and Natural Sciences, Bursa, Turkey;
e. Department of Logistics, Faculty of Economics, University of Gdańsk, Gdańsk, Poland

COVID-19 pandemic has caused changes in logistics and mobility. Concerning Italian road mobility, between March and April 2020, there has been a reduction in traffic for both light vehicles and heavy goods vehicles. Italy was the first European country to implement a total lockdown, starting on March 9th, causing a deep contraction in road traffic. This paper explores the main differences in mobility choices before and after the COVID-19 pandemic in 2020. A multi-criteria decision-making method was selected for the analysis of questionnaire survey data. The fuzzy Analytic Hierarchy Process was applied, considering eight mobility types: bus, tram, taxi, train, shared vehicles, multiple modes, walking and car. An evaluation process was adopted for the modal mobility choices of the residents of Sicily, Italy. The results show a significant decline in mobility demand during the first phase of the pandemic, especially in public transport mode. The findings provide a deeper understanding of the need to implement strategies to respect the constraints generated by the pandemic and revive the penalised transport and mobility-related sectors. Furthermore, the study's findings provide valuable insights for the policymakers, both national and local, about the mobility results of the lockdown and can be used as a forecast benchmark for planning the restrictions in the future, in case of another unexpected phenomenon, e.g., pandemic.

Keywords: Mobility patterns; Sustainable mobility; Analytic Hierarchy Process; Fuzzy set; COVID-19.

Received: September 20, 2021; Revised: June 28, 2022; Accepted: June 29, 2022; Prepublished online: August 17, 2022; Published: January 9, 2023  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Campisi, T., Moslem, S., Duleba, S., Tanbay, N.A., Szmelter-Jarosz, A., & Tesoriere, G. (2022). Analysis of the effects of the first phase of COVID-19 pandemic on mobility choices in Italy by a multi-criteria approach. Transactions on Transport Sciences, 13(3), 14-23
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Aktay, A., Bavadekar, S., Cossoul, G., Davis, J., Desfontaines, D., Fabrikant, A., Gabrilovich, E., Gadepalli, K., Gipson, B., Guevara, M., Kamath, C., Kansal, M., Lange, A., Mandayam, C., Oplinger, A., Pluntke, C., Roessler, T., Schlosberg, A., Shekel, T., Vispute S., Vu M., Wellenius G., Williams B., Wilson, R. J. (2020). Google COVID-19 Community Mobility Reports: Anonymization Process Description (version 1.0). http://arxiv.org/abs/2004.04145
    2. Alkharabsheh, A., Moslem, S., & Duleba, S. (2019). Evaluating passenger demand for development of the urban transport system by an AHP model with the real-world application of Amman. Applied Sciences (Switzerland). https://doi.org/10.3390/app9224759 Go to original source...
    3. Aloi, A., Alonso, B., Benavente, J., Cordera, R., Echániz, E., González, F., Ladisa, C., Lezama-Romanelli, R., López-Parra, Á., Mazzei, V., Perrucci, L., Prieto-Quintana, D., Rodríguez, A., & Sañudo, R. (2020). Effects of the COVID-19 Lockdown on Urban Mobility: Empirical Evidence from the City of Santander (Spain). Sustainability, 12(9), 3870. https://doi.org/10.3390/su12093870 Go to original source...
    4. ANIASA. (n.d.). Retrieved June 3rd, 2020, from https://www.aniasa.it/
    5. Bargain, O., & Aminjonov, U. (2020). Trust and compliance to public health policies in times of COVID-19. Journal of Public Economics, 192. https://doi.org/10.1016/j.jpubeco.2020.104316 Go to original source...
    6. Basbas, S., Campisi, T., Canale, A., Nikiforiadis, A., & Gruden, C. (2020). Pedestrian level of service assessment in an area close to an under-construction metro line in Thessaloniki, Greece. Transportation Research Procedia, 45 https://doi.org/10.1016/j.trpro.2020.02.067 Go to original source...
    7. Bieliński, T., Kwapisz, A., & Wazna, A. (2019). Bike-sharing systems in Poland. Sustainability (Switzerland). https://doi.org/10.3390/su11092458 Go to original source...
    8. Borgomeo, V. (n.d.). Addio al trasporto pubblico, dopo il Coronavirus tutti in auto privata. Retrieved June 2nd, 2020, from https://www.repubblica.it/motori/sezioni/attualita/2020/04/11/news/addio_al_trasporto_pubblico_dopo_il_coronavirus_tutti_in_auto-253727779/
    9. Borkowski, P., Jażdżewska-Gutta, M., & Szmelter-Jarosz, A. (2021). Lockdowned: Everyday mobility changes in response to COVID-19. Journal of Transport Geography, 90, https://doi.org/10.1016/j.jtrangeo.2020.102906 Go to original source...
    10. Camargo Pérez, J., Carrillo, M. H., & Montoya-Torres, J. R. (2014). Multicriteria approaches for urban passenger transport systems: a literature review. Annals of Operations Research, 226(1), https://doi.org/10.1007/s10479-014-1681-8 Go to original source...
    11. Campisi, T., Tibljaą, A. D., Tesoriere, G., Canale, A., Rencelj, M., & ©urdonja, S. (2020). Cycling traffic at turbo roundabouts: Some considerations related to cyclist mobility and safety. Transportation Research Procedia. https://doi.org/10.1016/j.trpro.2020.03.048 Go to original source...
    12. Campisi, T., Torrisi, V., Ignaccolo, M., Inturri, G., & Tesoriere, G. (2020). University propensity assessment to car sharing services using mixed survey data: The Italian case study of Enna city. Transportation Research Procedia. https://doi.org/10.1016/j.trpro.2020.03.155 Go to original source...
    13. Canale, A., Tesoriere, G., & Campisi, T. (2019). The MAAS development as a mobility solution based on the individual needs of transport users. AIP Conference Proceedings. https://doi.org/10.1063/1.5138073 Go to original source...
    14. Cieplińska, J. R., & Szmelter-jarosz, A. (2020). Toward Most Valuable City Logistics Initiatives : Crowd Logistics Solutions ' Assessment Model. 28(2) https://doi.org/10.7206/cemj.2658-0845.21 Go to original source...
    15. Cui, Z., Zhu, M., Wang, S., Wang, P., Zhou, Y., Cao, Q., Kopca, C., & Wang, Y. (2020). Traffic performance score for measuring the impact of covid-19 on urban mobility. arXiv:2007.00648. https://doi.org/10.48550/arXiv.2007.00648Dahlberg, M., Edin, P.-A., Grönqvist, E., Lyhagen, J., Östh, J., Siretskiy, A., & Toger, M. (n.d.). Effects of the COVID-19 Pandemic on Population Mobility under Mild Policies: Causal Evidence from Sweden. Go to original source...
    16. De Girolamo, A. (2020). Ripensare il trasporto pubblico messo in crisi dal Covid-19. https://www.huffingtonpost.it/entry/ripensare-il-trasporto-pubblico-messo-in-crisi-dal-covid-19_it_5ea00064c5b6b2e5b83a5d97
    17. De Vos, J. (2020). The effect of COVID-19 and subsequent social distancing on travel behavior. Transportation Research Interdisciplinary Perspectives, 5. https://doi.org/10.1016/j.trip.2020.100121 Go to original source...
    18. DPCM 9 marzo 2020 - G.U. 9.3.2020;https://www.altalex.com/documents/news/2020/03/09/coronavirus-decreto-anticontagio-lombardia-14-province-in-isolamento
    19. Duleba, S., & Moslem, S. (2019). Examining Pareto optimality in analytic hierarchy process on real Data: An application in public transport service development. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2018.08.049 Go to original source...
    20. Ebrahim, S. H., Ahmed, Q. A., Gozzer, E., Schlagenhauf, P., & Memish, Z. A. (2020). Covid-19 and community mitigation strategies in a pandemic. The BMJ, 368(March), 1-2. https://doi.org/10.1136/bmj.m1066 Go to original source...
    21. Echaniz, E., Ho, C. Q., Rodriguez, A., & dell'Olio, L. (2019). Comparing best-worst and ordered logit approaches for user satisfaction in transit services. Transportation Research Part A: Policy and Practice, 130. https://doi.org/10.1016/j.tra.2019.10.012 Go to original source...
    22. Engle, S., Stromme, J., & Zhou, A. (2020). Staying at Home: Mobility Effects of COVID-19 https://www.nytimes.com/interactive/2020/03/21/upshot/coronavirus-public- opinion.html Go to original source...
    23. Erdoğan, M., & Kaya, İ. (2020). A systematic approach to evaluate risks and failures of public transport systems with a real case study for bus rapid system in Istanbul. Sustainable Cities and Society. https://doi.org/10.1016/j.scs.2019.101951 Go to original source...
    24. Fahlenbrach, R., Rageth, K., & Stulz, R. M. (2020). How Valuable Is Financial Flexibility when Revenue Stops? Evidence from the COVID-19 Crisis. The Review of Financial Studies. https://doi.org/10.1093/rfs/hhaa134 Go to original source...
    25. Figuera, J., Greco, S., & Ehrgott, M. (Eds.). (2005). Multiple Criteria Decision Analysis, State of the Art Surveys. Springer, New York. Go to original source...
    26. Galeazzi, A., Cinelli, M., Bonaccorsi, G., Pierri, F., Schmidt, A. L., Scala, A., Pammolli, F., & Quattrociocchi, W. (2020). Human Mobility in Response to COVID-19 in France, Italy and UK. http://arxiv.org/abs/2005.06341
    27. Ghorbanzadeh, O., Moslem, S., Blaschke, T., & Duleba, S. (2018). Sustainable urban transport planning considering different stakeholder groups by an interval-AHP decision support model. Sustainability, 11(1), 9. https://doi.org/10.3390/su11010009 Go to original source...
    28. Giannotti, F., Nanni, M., Pappalardo, L., Rossetti, G., Rinzivillo, S., Cintia, P., Fadda, D., Lopalco, P. L., Mazzilli, S., Lara, D. P., Windtre, T., Bonato, P., Fabbri, F., Penone, F., & Savarese, M. (2020). MOBILE PHONE DATA ANALYTICS AGAINST THE COVID-19 EPIDEMICS IN ITALY. http://sobigdata.eu/covid_report
    29. Gössling, S., Scott, D., & Hall, C. M. (2020). Pandemics, tourism and global change: a rapid assessment of COVID-19. Journal of Sustainable Tourism. https://doi.org/10.1080/09669582.2020.1758708 Go to original source...
    30. Guglielmetti Mugion, R., Toni, M., Di Pietro, L., Pasca, M. G., & Renzi, M. F. (2019). Understanding the antecedents of car sharing usage: an empirical study in Italy. International Journal of Quality and Service Sciences, 11(4). https://doi.org/10.1108/IJQSS-02-2019-0029 Go to original source...
    31. Gündoğdu, F. K., Duleba, S., Moslem, S., & Aydin, S. (2021). Evaluating public transport service quality using picture fuzzy analytic hierarchy process and linear assignment model. Applied Soft Computing, 100, 106920. https://doi.org/10.1016/j.asoc.2020.106920 Go to original source...
    32. Iacus, S. M., Natale, F., Satamaria, C., Spyratos, S., & Vespe, M. (2020). Estimating and Projecting Air Passenger Traffic during the COVID-19 Coronavirus Outbreak and its Socio-Economic Impact. http://arxiv.org/abs/2004.08460
    33. Infografiche: Spostamenti quotidiani sul territorio prima del Covid-19. (2020). https://www.istat.it/it/archivio/243332
    34. Kabak, M., Erbaş, M., Çetinkaya, C., & Özceylan, E. (2018). A GIS-based MCDM approach for the evaluation of bike-share stations. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2018.08.033 Go to original source...
    35. Luther, W. J. (2020). Behavioral and Policy Responses to COVID-19: Evidence from Google Mobility Data on State-Level Stay-at-Home Orders. Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 36(Fall 2021) Go to original source...
    36. Macharis, C., & Bernardini, A. (2015). Reviewing the use of Multi-Criteria Decision Analysis for the evaluation of transport projects : Time for a multi-actor approach. Transport Policy, 37. https://doi.org/10.1016/j.tranpol.2014.11.002 Go to original source...
    37. Mardani, A., Zavadskas, E. K., Khalifah, Z., Jusoh, A., & Nor, K. M. D. (2016). Multiple criteria decision-making techniques in transportation systems: a systematic review of the state of the art literature. In Transport. https://doi.org/10.3846/16484142.2015.1121517 Go to original source...
    38. Meier, K., Glatz, T., Guijt, M. C., Piccininni, M., Meulen, M. Van Der, Atmar, K., Jolink, A. C., Kurth, T., Rohmann, J. L., Najafabadi, A. H. Z., Andour, L., Blommaart, L., Fisher, F. L., Splinter, B., Teunissen, M., & Rohmann, G. (2020). Public perspectives on social distancing and other protective measures in Europe: a cross-sectional survey study during the COVID-19 pandemic. Go to original source...
    39. Mendoza-Arango, I. M., Echaniz, E., dell'Olio, L., & Gutiérrez-González, E. (2020). Weighted variables using best-worst scaling in ordered logit models for public transit satisfaction. Sustainability (Switzerland), 12(13). https://doi.org/10.3390/su12135318 Go to original source...
    40. Meyer, C., Kilpatrick, J. K., Yang, X., Caston, N., & Kim, H. H. (2017). U.S. Patent Application No. 14/949,197. Go to original source...
    41. . Morita,H. ,Nakamura, S. and Hayashi, Y.. Changes of Urban Activities and Behaviors Due to COVID-19 in Japan (May 6, 2020). Available at SSRN: https://ssrn.com/abstract=3594054 or http://dx.doi.org/10.2139/ssrn.3594054 Go to original source...
    42. Moslem, S., Campisi, T., Szmelter-Jarosz, A., Duleba, S., Nahiduzzaman, K. M., & Tesoriere, G. (2020). Best-Worst Method for Modelling Mobility Choice after COVID-19: Evidence from Italy. Sustainability, 12(17), 6824. https://doi.org/10.3390/su12176824 Go to original source...
    43. Moslem, S., & Duleba, S. (2019). Sustainable Urban Transport Development by Applying a Fuzzy-AHP Model: A Case Study from Mersin, Turkey. Urban Science. https://doi.org/10.3390/urbansci3020055 Go to original source...
    44. Moslem, S., Farooq, D., Ghorbanzadeh, O., & Blaschke, T. (2020). Application of the AHP-BWM model for evaluating driver behavior factors related to road safety: A case study for Budapest. Symmetry. https://doi.org/10.3390/sym12020243 Go to original source...
    45. Moslem, S., Ghorbanzadeh, O., Blaschke, T., & Duleba, S. (2019a). Analysing stakeholder consensus for a sustainable transport development decision by the fuzzy AHP and interval AHP. Sustainability (Switzerland). https://doi.org/10.3390/su10023271 Go to original source...
    46. Murgante, B., Borruso, G., Balletto, G., Castiglia, P., & Dettori, M. (2020). Why Italy First ? Health , Geographical and Planning aspects of the Covid-19 outbreak. May. https://doi.org/10.20944/preprints202005.0075.v1 Go to original source...
    47. Nassereddine, M., & Eskandari, H. (2017). An integrated MCDM approach to evaluate public transportation systems in Tehran. Transportation Research Part A: Policy and Practice. https://doi.org/10.1016/j.tra.2017.10.013 Go to original source...
    48. Nosal, K., & Solecka, K. (2014). Application of AHP method for multi-criteria evaluation of variants of the integration of Urban public transport. Transportation Research Procedia, 3. https://doi.org/10.1016/j.trpro.2014.10.006 Go to original source...
    49. Panchal, N., Kamal, R., Orgera, K., Cox, C., Garfield, R., Hamel, L., Mriya, C., & Chidambaram, P. (2020). The Implications of COVID-19 for Mental Health and Substance Use | KFF. In Kaiser Family Foundation.
    50. Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C., & Tizzoni, M. (n.d.). COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown. https://doi.org/10.1101/2020.03.22.20039933 Go to original source...
    51. Piemontese, A. (n.d.). Che futuro ha il car sharing? Retrieved May 31, 2020, from https://www.wired.it/economia/business/2020/05/06/car-sharing-futuro/
    52. Qu, M., Yu, S., & Yu, M. (2017). An improved approach to evaluate car sharing options. Ecological Indicators. https://doi.org/10.1016/j.ecolind.2016.07.018 Go to original source...
    53. Renaud, L. (2020). Reconsidering global mobility-distancing from mass cruise tourism in the aftermath of COVID-19. Tourism Geographies. https://doi.org/10.1080/14616688.2020.1762116 Go to original source...
    54. Rossi, R., Gastaldi, M., & Gecchele, G. (2013). Comparison of fuzzy-based and AHP methods in sustainability evaluation: A case of traffic pollution-reducing policies. European Transport Research Review, 5(1). https://doi.org/10.1007/s12544-012-0086-5 Go to original source...
    55. Rossi, R., Gastaldi, M., & Gecchele, G. (2014). Sustainability evaluation of transportation policies: A fuzzy-based method in a "what to" analysis. Advances in Intelligent Systems and Computing, 223. https://doi.org/10.1007/978-3-319-00930-8_28 Go to original source...
    56. Rotaris, L., Danielis, R., & Maltese, I. (2019). Carsharing use by college students: The case of Milan and Rome. Transportation Research Part A: Policy and Practice, 120. https://doi.org/10.1016/j.tra.2018.12.017 Go to original source...
    57. Roy, B. (1990). Decision-aid and decision-making. European Journal of Operational Research. https://doi.org/10.1016/0377-2217(90)90196-I Go to original source...
    58. Rze¶ny-Cieplińska, J., & Szmelter-Jarosz, A. (2019). Assessment of the crowd logistics solutions-the stakeholders' analysis approach. Sustainability (Switzerland), 11(19). https://doi.org/10.3390/su11195361 Go to original source...
    59. Saaty, R. W. (1987). The Analytic Hierarchy Process - what it is and how it is used. Mathematical Modelling, 9(3-5), https://doi.org/https://doi.org/10.1016/0270-0255(87)90473-8 Go to original source...
    60. Schäfer, G., Kreisel, A., Rummler, D., & Stopka, U. (2017). Development of a concept for evaluation user acceptance and requirements for NFC based E-ticketing in public transport. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). https://doi.org/10.1007/978-3-319-58077-7_42 Go to original source...
    61. Serafimova, T. (2020). Covid-19: An Opportunity to Redesign Mobility Towards Greater Sustainability and Resilience?. Policy Briefs; 2020/19; Florence School of Regulation Transport; European University Institute. https://doi.org/ 10.2870/695530. Go to original source...
    62. Shang, J. S., Tjader, Y., & Ding, Y. (2004). A unified framework for multi-criteria evaluation of transportation projects. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2004.830848 Go to original source...
    63. Singh, A., Gurtu, A., & Singh, R. K. (2020). Selection of sustainable transport system: a case study. Management of Environmental Quality: An International Journal. https://doi.org/10.1108/MEQ-03-2020-0059 Go to original source...
    64. Site, P. D., & Filippi, F. (2009). Weighting methods in multi-attribute assessment of transport projects. European Transport Research Review. https://doi.org/10.1007/s12544-009-0018-1 Go to original source...
    65. Szmelter, A. (2018). Mobility-as-a-Service - a challenge for I.T. in the age of sharing economy. Information Systems in Management, 7(1), https://doi.org/10.22630/ISIM.2018.7.1.6 Go to original source...
    66. Tirachini, A., & Cats, O. (2020). COVID-19 and public transportation: Current assessment, prospects, and research needs. Journal of Public Transportation, 22(1), 1-34. https://doi.org/10.5038/2375-0901.22.1.1 Go to original source...
    67. Tsai, Y.-S., Huang, C.-Y., Wen, T.-H., Sun, C.-T., & Yen, M.-Y. (2011). Integrating epidemic dynamics with daily commuting networks: building a multilayer framework to assess influenza A (H1N1) intervention policies. SIMULATION, 87(5), 385-405. https://doi.org/10.1177/0037549710379481 Go to original source...
    68. Vazifeh, M. M., Santi, P., Resta, G., Strogatz, S. H., & Ratti, C. (2018). Addressing the minimum fleet problem in on-demand urban mobility. Nature, 557(7706). https://doi.org/10.1038/s41586-018-0095-1 Go to original source...
    69. White, P. R. (2008). Public transport: Its planning, management and operation: Fifth edition. In Public Transport: Its Planning, Management and Operation: Fifth Edition. https://doi.org/10.4324/9780203892282 Go to original source...
    70. Zhou, J. B., Ma, C. X., Dong, S., & Zhang, M. J. (2021). Unconventional prevention strategies for urban public transport in the COVID-19 epidemic: taking Ningbo City as a case study. China Journal of Highway and Transport, 33(12), . https://doi.org/10.1371/journal.pone.0253220. Go to original source...
    71. Zhou, Y., Xu, R., Hu, D., Yue, Y., Li, Q., & Xia, J. (2020). Effects of human mobility restrictions on the spread of COVID-19 in Shenzhen, China: a modelling study using mobile phone data. The Lancet Digital Health, 2(8). https://doi.org/10.1016/S2589-7500(20)30165-5 Go to original source...

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content