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An Ordered Logit Model for Predicting the Willingness of Renting Micro Mobility in Urban Shared Streets: A Case Study in Palermo, Italy

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12250))

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Abstract

Sustainable transport modes, particularly micro-mobility, allows to reduce possible congestion phenomena in urban traffic. In this study, the aim is to make a contribution to increase micro-mobility use by exploring the impacts of socio-demographic, vehicle ownership (car, bicycle and micro mobility), level of infrastructure service and road users’ perception in safety, comfort and chaotic environment on renting micro-mobility in a shared urban street. The study area is a historical center called Via Maqueda in Palermo, Italy, which is rich in commercial and cultural activities. A survey with 200 individuals is carried out for the data collection regarding the aim of the study.

The analysis starts with a descriptive statistics in order to illustrate the characteristics of the predictor variables. This is followed by relaxing p-value method for selecting the statistically significant predictor variables with 90% confidence level. These selected predictor variables are applied into an ordinal logit model. The results suggest that one unit increase in car ownership decrease the willingness of renting a micro mobility by log odds of −0.74, given all the other predictors are held constant. One unit increase in age group decrease the willingness of renting micro-mobility in shared urban streets. The outcomes will guide decision makers to understand who the average road users are and what are their needs in terms of further developments of the micro-mobility system in urban shared streets. The originality of this paper consists the perceptions of road users, such as safety and comfort, on micro-mobility that can encourage to use this sustainable urban travel mode in restricted traffic areas.

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References

This paper is the result of the joint work of the authors. ‘Abstract’ ‘Introduction’ ‘Methodology’ and ‘Results’ were written jointly by the authors. TC and NA focused on the state of the art. TC designed the methodological approach and discussion. Supervision and research funding NA, TC and GT.

  1. Zagorskas, J., Burinskienė, M.: Challenges caused by increased use of e-powered personal mobility vehicles in european cities. Sustainability 12(1), 273 (2020). https://doi.org/10.3390/su12010273

    Article  Google Scholar 

  2. Loukopoulos, P., Jakobsson, C., Gärling, T., Meland, S., Fujii, S.: Understanding the process of adaptation to car-use reduction goals. Transp. Res. Part F Traff. Psychol. Behav. 9(2), 115–127 (2006). https://doi.org/10.1016/j.trf.2005.09.003

  3. Olia, A., Abdelgawad, H., Abdulhai, B., Razavi, S.N.: Assessing the potential impacts of connected vehicles: mobility, environmental, and safety perspectives. J. Intell. Transp. Syst. 20(3), 229–243 (2016). https://doi.org/10.1080/15472450.2015.1062728

  4. Lia, F., Nocerino, R., Bresciani, C., Colorni Vitale, A., Luè, A.: Promotion of E-bikes for delivery of goods in European urban areas: an Italian case study. In: Transport Research Arena (TRA) 5th Conference: Transport Solutions from Research to Deployment, pp. 1–10 (2014)

    Google Scholar 

  5. Torrisi, V., Ignaccolo, M., Inturri, G.: Toward a sustainable mobility through a dynamic real-time traffic monitoring, estimation and forecasting system: The RE.S.E.T. project. In: Town and Infrastructure Planning for Safety and Urban Quality - Proceedings of the 23rd International Conference on Living and Walking in Cities, LWC 2017, pp. 241–247 (2018). https://doi.org/10.1201/9781351173360-32

  6. Torrisi, V., Ignaccolo, M., Inturri, G.: Innovative transport systems to promote sustainable mobility: developing the model architecture of a traffic control and supervisor system. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10962, pp. 622–638. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95168-3_42

    Chapter  Google Scholar 

  7. Ignaccolo, C., Giuffrida, N., Torrisi, V.: The queensway of New York city. A proposal for sustainable mobility in queens. In: Town and Infrastructure Planning for Safety and Urban Quality, pp. 69–76 (2018). https://doi.org/10.1201/9781351173360-12

  8. Madapur, B., Madangopal, S., Chandrashekar, M.N.: Micro-mobility infrastructure for redefining urban mobility. Euro. J. Eng. Sci. Tech. 3(1), 71–85 (2020).https://doi.org/10.33422/ejest.v3i1.163

  9. McKenzie, G.: Urban mobility in the sharing economy: A spatiotemporal comparison of shared mobility services. Comput. Environ. Urban Syst. 79, 101418 (2020). https://doi.org/10.1016/j.compenvurbsys.2019.101418

    Article  Google Scholar 

  10. Basbas, S., Campisi, T., Canale, A., Nikiforiadis, A., Gruden, C.: Pedestrian level of service assessment in an area close to an under-construction metro line in Thessaloniki, Greece. Transp. Res. Procedia 45, 95–102 (2020)

    Article  Google Scholar 

  11. Hardt, C., Bogenberger, K.: Usage of e-scooters in urban environments. Transp. Res. Procedia 37, 155–162 (2019). https://doi.org/10.1016/j.trpro.2018.12.178

    Article  Google Scholar 

  12. Shaheen, S., Cohen, A.: Shared Micromobility Policy Toolkit: Docked and Dockless Bike and Scooter Sharing (2019)

    Google Scholar 

  13. Campisi, T., Torrisi, V., Ignaccolo, M., Inturri, G., Tesoriere, G.: University propensity assessment to car sharing services using mixed survey data: the Italian case study of Enna city. Transp. Res. Procedia 47,433–44 (2020). https://doi.org/10.1016/j.trpro.2020.03.155

  14. Moreau, H., de Jamblinne de Meux, L., Zeller, V., D’Ans, P., Ruwet, C., Achten, W.M.: Dockless e-scooter: a green solution for mobility? Comparative case study between dockless e-scooters, displaced transport, and personal e-scooters. Sustainability 12(5), 1803 (2020). https://doi.org/10.3390/su12051803

  15. CoMoUK in 2019

    Google Scholar 

  16. McKenzie, G.: Shared micro-mobility patterns as measures of city similarity: Position Paper. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data, pp. 1–4 (2019). https://doi.org/10.1145/3356392.3365221

  17. Barnes, F.: A Scoot, Skip, and a JUMP Away: Learning from Shared Micromobility Systems in San Francisco (2019)

    Google Scholar 

  18. Gössling, S.: Integrating e-scooters in urban transportation: Problems, policies, and the prospect of system change. Transp. Res. Part D Transp. Environ. 79, 102230 (2020). https://doi.org/10.1016/j.trd.2020.102230

    Article  Google Scholar 

  19. Campisi, T., Acampa, G., Marino, G., Tesoriere, G.: Cycling master plans in Italy: the I-BIM feasibility tool for cost and safety assessments. Sustainability 12(11), 4723. https://doi.org/10.3390/su12114723

  20. Warnick, A.: Shareable scooters offer risks, benefits for transportation. Am. J. Public Health 109(11), 1479 (2019). https://doi.org/10.2105/AJPH.2019.305354

    Article  MathSciNet  Google Scholar 

  21. Ishmael, C.R., et al.: An early look at operative orthopaedic injuries associated with electric scooter accidents: bringing high-energy trauma to a wider audience. JBJS 102(5), e18 (2020). https://doi.org/10.2106/JBJS.19.00390

    Article  Google Scholar 

  22. Nellamattathil, M., Amber, I.: An evaluation of scooter injury and injury patterns following widespread adoption of E-scooters in a major metropolitan area. Clin. Imaging 60(2), 200–203 (2020). https://doi.org/10.1016/j.clinimag.2019.12.012

    Article  Google Scholar 

  23. Sikka, N., Vila, C., Stratton, M., Ghassemi, M., Pourmand, A.: Sharing the sidewalk: a case of E-scooter related pedestrian injury. Am. J. Emerg. Med. 37(9), 1807-e5 (2019).https://doi.org/10.1016/j.ajem.2019.06.017

  24. James, O., Swiderski, J.I., Hicks, J., Teoman, D., Buehler, R.: Pedestrians and e-scooters: an initial look at e-scooter parking and perceptions by riders and non-riders. Sustainability 11(20), 5591 (2019). https://doi.org/10.3390/su11205591

  25. Akgün, N., Dissanayake, D., Thorpe, N., Bell, M.C.: Cyclist casualty severity at roundabouts - to what extent do the geometric characteristics of roundabouts play a part? J. Saf. Res. 67, 83–91 (2018). https://doi.org/10.1016/j.jsr.2018.09.004

    Article  Google Scholar 

  26. Harrell, F.: Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. 1 edn. Springer, New York (2001). https://doi.org/10.1007/978-1-4757-3462-1

  27. Montgomery, D.C., Peck, E.A., Vining, G.G.: Introduction to Linear Regression Analysis. Fifth Edition. Wiley, New York (2012)

    Google Scholar 

  28. Schneider, A., Hommel, G., Blettner, M.: Linear regression analysis part 14 of a series on evaluation of scientific publications. Deutsches Ärzteblatt Int. 107(44), 776–782 (2010). http://dx.doi.org/10.3238/arztebl.2010.0776

  29. Akgün, N.: Investigating the Impacts on Cyclist Casualty Severity at Give Way Roundabouts with Mixed Traffic. Newcastle University (2019)

    Google Scholar 

  30. Field, A.: Discovering Statistics Using SPSS. 3 edn. SAGE Publications Ltd, London (2009)

    Google Scholar 

  31. Menard, S.: Applied logistic regression analysis. 2 edn. SAGE, London (2002). https://dx.doi.org/10.4135/9781412983433

  32. McKelvey, R.D., Zavoina, W.: A statistical model for the analysis of ordinal level dependent variables. J. Math. Sociol. 4(1), 103–120 (1975). https://doi.org/10.1080/0022250X.1975.9989847

    Article  MathSciNet  MATH  Google Scholar 

  33. Winship, C., Mare, R.D.: Regression models with ordinal variables. Am. Sociol. Rev. 512–525 (1984). https://doi.org/10.2307/2095465

  34. Peduzzi, P., Concato, J., Kemper, E., Holford, T.R., Feinstein, A.R.: A simulation study of the number of events per variable in logistic regression analysis. J. Clin. Epidemiol. 49(12), 1373–1379 (1996). https://doi.org/10.1016/S0895-4356(96)00236-3

    Article  Google Scholar 

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Acknowledgments

This study was supported by the MIUR (Ministry of Education, Universities and Research [Italy]) through a project entitled WEAKI TRANSIT: WEAK-demand areas Innovative TRANsport Shared services for Italian Towns (Project code: 20174ARRHT/CUP Code: J74I19000320008), financed with the PRIN 2017 (Research Projects of National Relevance) programme. We authorize the MIUR to reproduce and distribute reprints for Governmental purposes, notwithstanding any copyright notations thereon. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors, and do not necessarily reflect the views of the MIUR.

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Authors and Affiliations

  1. University of Enna Kore, Cittadella Universitaria, Enna, Italy

    Tiziana Campisi & Giovanni Tesoriere

  2. Faculty of Engineering and Natural Sciences, Bursa Technical University, 16330, Bursa, Turkey

    Nurten Akgün

Authors
  1. Tiziana Campisi
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  2. Nurten Akgün
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  3. Giovanni Tesoriere
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Correspondence to Tiziana Campisi .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Campisi, T., Akgün, N., Tesoriere, G. (2020). An Ordered Logit Model for Predicting the Willingness of Renting Micro Mobility in Urban Shared Streets: A Case Study in Palermo, Italy. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12250. Springer, Cham. https://doi.org/10.1007/978-3-030-58802-1_57

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  • DOI: https://doi.org/10.1007/978-3-030-58802-1_57

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