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سالاری پور, علی اکبر, حمیدی, آرمان, یکتا لشکریانی, عارفه, گلپور, مریم. (1402). ارزیابی عوامل موثر بر میزان وابستگی شهروندان به خودروی شخصی مطالعه موردی: شهر رشت. , 11(3), 63-78. doi: 10.22059/jurbangeo.2023.360138.1828
علی اکبر سالاری پور; آرمان حمیدی; عارفه یکتا لشکریانی; مریم گلپور. "ارزیابی عوامل موثر بر میزان وابستگی شهروندان به خودروی شخصی مطالعه موردی: شهر رشت". , 11, 3, 1402, 63-78. doi: 10.22059/jurbangeo.2023.360138.1828
سالاری پور, علی اکبر, حمیدی, آرمان, یکتا لشکریانی, عارفه, گلپور, مریم. (1402). 'ارزیابی عوامل موثر بر میزان وابستگی شهروندان به خودروی شخصی مطالعه موردی: شهر رشت', , 11(3), pp. 63-78. doi: 10.22059/jurbangeo.2023.360138.1828
سالاری پور, علی اکبر, حمیدی, آرمان, یکتا لشکریانی, عارفه, گلپور, مریم. ارزیابی عوامل موثر بر میزان وابستگی شهروندان به خودروی شخصی مطالعه موردی: شهر رشت. , 1402; 11(3): 63-78. doi: 10.22059/jurbangeo.2023.360138.1828

ارزیابی عوامل موثر بر میزان وابستگی شهروندان به خودروی شخصی مطالعه موردی: شهر رشت

پژوهش‌های جغرافیای برنامه‌ریزی شهری
مقاله 4، دوره 11، شماره 3، آبان 1402، صفحه 63-78    اصل مقاله (1.48 M)
نوع مقاله: پژوهشی - کاربردی
شناسه دیجیتال (DOI): 10.22059/jurbangeo.2023.360138.1828
نویسندگان
علی اکبر سالاری پور* ؛ آرمان حمیدی؛ عارفه یکتا لشکریانی؛ مریم گلپور
گروه شهرسازی، دانشکده هنر و معماری، دانشگاه گیلان، رشت، ایران
چکیده
در سال‌های اخیر با توجه به رشد فزاینده جمعیت شهرها و به طبع آن افزایش نرخ مالکیت خودرو، وابستگی شهروندان به خودروی شخصی تشدید یافته است که همین امر موجب ازدحام و ترافیک سرسام‌آور در مراکز شهری و از همه مهم‌تر، موجب افزایش آلاینده‌های زیست‌محیطی در شهرها و درنتیجه تبدیل به یک تهدید برای سلامتی شهروندان شده است. پژوهش حاضر ازلحاظ هدف کاربردی می‌باشد. جهت بررسی و ارزیابی تأثیر عوامل مختلف بر وابستگی شهروندان به خودرو، پرسشنامه‌ای طراحی گردید و اطلاعات به‌دست‌آمده از پرسشنامه‌ها توسط نرم‌افزار SPSS مورد تحلیل و ارزیابی قرار گرفت. سپس با استفاده از آزمون‌های دوجمله‌ای، همبستگی پیرسون و آزمون رگرسیون خطی گام‌به‌گام به تجزیه‌وتحلیل یافته‌ها پرداخته‌شده است. جامعه آماری این پژوهش شامل ساکنین رشت که هر خانواده حداقل صاحب یک خودروی می‌باشند، است. در این پژوهش مجموعاً 405 پرسشنامه توسط ساکنین رشت، به‌صورت آنلاین تکمیل گردید. با توجه به نتایج حاصل‌شده شاخص "پاندمی کرونا" با میانگین 94/3 بالاترین میانگین را در بین شاخص‌ها به خود اختصاص داده است و پس‌ازآن شاخص "ارتباط و دسترسی" با کسب میانگین 64/3، در جایگاه دوم قرار دارد اما شاخص "حمل‌ونقل عمومی" با کسب میانگین 49/2، پایین‌ترین میانگین را در بین تمامی شاخص‌ها به خود اختصاص داده است. درنهایت نتایج این پژوهش نشان داد که به ترتیب سه شاخص پاندمی کرونا، نگرش زیست‌محیطی و سلامتی شهروندان و سبک زندگی و تمایلات بیشترین اثرگذاری را بر وابستگی به خودروی شهروندان دارند.
کلیدواژه‌ها
خودرو شخصی؛ وابستگی به خودرو؛ پاندمی کرونا؛ سبک زندگی؛ حمل‌ونقل عمومی
عنوان مقاله [English]
Evaluating the factors affecting the dependence of citizens on private cars : the case study of Rasht city
نویسندگان [English]
Aliakbar Salaripour؛ Arman Hamidi؛ Arefeh Yekta Lashkaryani؛ Maryam Golpour
Department of Urban Planning, Faculty of Architecture and Art, University of Guilan, Rasht, Iran
چکیده [English]
ABSTRACT
In recent years, due to the increasing growth of the population of cities and the increase in the rate of car ownership, the dependence of citizens on private cars has intensified, which causes congestion and overwhelming traffic in urban centers, and most importantly, it causes an increase in environmental pollutants. environment in cities and as a result has become a threat to the health of citizens. The current research is practical in terms of purpose. In order to investigate and evaluate the impact of various factors on the dependence of citizens on cars, a questionnaire was designed and the information obtained from the questionnaires was analyzed and evaluated by SPSS software. Then, by using binomial tests, Pearson correlation and linear regression test, the findings have been analyzed step by step. The statistical population of this research includes the residents of Rasht, where each family owns at least one car. In this research, a total of 405 questionnaires were completed online by residents of Rasht. According to the obtained results, the "corona pandemic" index with an average of 3.94 has the highest average among the indexes, and after that, the "communication and correctness" index is in the second place with an average of 3.64. However, the index of "public transportation" with an average of 2.49 has the lowest average among all indicators. Finally, the results of this research showed that the three indicators of corona pandemic, environmental attitude and health of citizens, and lifestyle and tendencies have the greatest effect on citizens' dependence on cars.
Extended Abstract
Introduction
In recent years, due to the increasing growth of the population of cities and the increase in the rate of car ownership, the dependence of citizens on private cars has intensified, which causes congestion and overwhelming traffic in urban centers, and most importantly, it causes an increase in environmental pollutants. environment in cities and as a result has become a threat to the health of citizens. On the other hand, the COVID-19 pandemic and social distancing in order to prevent this disease have had many social and economic consequences that have brought about a change in lifestyle and even urban structures, including in the field of urban transportation. He pointed out that the increasing dependence on the car in contrast to the less use of the public transportation system has caused urban planners and management to face a serious challenge in recent years. Environmental, social and economic trends also follow, which have faced urban policy makers with a serious challenge in solving this problem.
 
Methodology
The current research is applied in terms of purpose and according to the method of answering research questions and the method of answering is descriptive-quantitative. In order to investigate and evaluate the impact of various factors on citizens' dependence on cars, a questionnaire with a 5-level Likert scale was designed and data was collected using this method. The information obtained from the questionnaires was analysed and evaluated by SPSS software. Then, by using binomial tests, Pearson correlation and linear regression test, the findings have been analysed step by step. The statistical population of this research includes the residents of Rasht, where each family owns at least one car. In this research, in order to increase the confidence factor, a total of 405 questionnaires were completed online by the residents of Rasht, and then the questionnaire link was deactivated.
 
 
Results and discussion
According to the obtained results, the "corona pandemic" index with an average of 3.94 has the highest average among the indexes, and after that, the "communication and correctness" index is in the second place with an average of 3.64. And at the end, the index of "public transportation" has the lowest average among all indices, with an average of 2.49. On the other hand, the items "increasing the use of private cars during the Corona era" with an average of 4.29 and "decreasing the desire to use public transportation during the Corona pandemic" with an average of 4.10, respectively, have the highest average in among other subjects. Finally, according to the test of the regression results, the "corona pandemic" index has had the greatest impact on the dependence of citizens on personal cars in such a way that with a correlation coefficient of 0.387, it alone accounted for 14.8% of the variance share of the "dependence on cars" index. predict Also, in the seventh model, where all the effective indicators are included in the model, the model has a correlation coefficient of 0.629, which shows the high correlation of these factors and dependence on automobile citizens; It was able to form 38.5% of the share of variance of the variable "Dependence on the car".
 
Conclusion
According to the results obtained from the average indicators, "Corona Pandemic" has the highest average, which shows the importance of the issue of Corona disease and its impact on all aspects of people's lives. Also, on the other hand, the two indices "suitable environment for walking and cycling" and "public transportation" respectively have the lowest average among the indices, which shows the lack of attention of the city officials of Rasht to the issue of the city. It is without a car, which has led to the dissatisfaction of citizens due to the lack of a suitable platform for walking and cycling in the city, as well as the inefficiency of the public transportation system of this city. In this regard, according to the correlation between indicators, the indicators of "suitable environment for walking and cycling" and "public transportation" have the highest correlation among all research indicators, which shows the importance of paying more attention. According to these two indicators in the city of Rasht. In the continuation of the results of this research, based on the step-by-step regression test, the "corona pandemic" index is able to predict 14.8% of the variance share of the "car dependence" index. Therefore, with the emergence of this emerging phenomenon and its spread throughout the world, cities have faced new challenges that have never existed before, and one of these challenges is less use of public transportation during the outbreak of this disease and relying on Most of the citizens have a personal car for their health and their families. In the next step, the "environmental attitude and health of citizens" index has had the greatest effect on citizens' reliance on private cars. Based on this, it is possible to take an important step towards this goal by building culture in the society and increasing the environmental sensitivities of citizens and increasing people's awareness of environmental trends and the negative impact of using private cars on the health of citizens. In the next stage, the index of "Citizens' Lifestyle and Desires" has had the greatest impact on the citizens' use of private cars. In line with this, it is possible to change the citizens' lifestyles by taking advantage of collective communication spaces and appropriate culture in order to correct incorrect social patterns and an attitude in citizens can lead the society to less use of private cars. In the fourth stage of this modeling, we see the impact of "laws restricting car traffic" on the use of personal cars, which can be used to prevent more cars from moving around the city and downtown by applying physical restrictions. In the following, among the demographic and descriptive indicators of citizens, the indicators of "number of cars in each household" and "marital status" have an effect on the use of private cars by more and more citizens. In the last stage, the index of "public transportation" has an undeniable effect on the state of citizens' dependence on private cars, and finally, all the mentioned indicators together have been able to explain 38.5% of the variance of the dependence on cars among citizens. slow, which is a very significant amount, and paying attention to these indicators and improving the quality level of each of them can play a significant role in changing the pattern of citizens' use of private cars.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
 We are grateful to all the persons for scientific consulting in this paper.
کلیدواژه‌ها [English]
Personal car, car dependence, corona pandemic, lifestyle, public transport
مراجع
  1. حمیدی، آرمان؛ سالاری‌پور، علی‌اکبر و حسام، مهدی. (1400). ارزیابی سیاست‌های مدیریت شهری در بهره‌برداری از برند شهر خلاق (مطالعه موردی: رشت)، پژوهش‌های جغرافیای برنامه‌ریزی شهری، 9 (2)، 439-461. doi: 10.22059/jurbangeo.2021.314497
  2. مرکز آمار ایران (1392). نتایج آمارگیری از گردشگران ملی تابستان 139۲. تهران: سازمان مدیریت و برنامه‌ریزی کشور، مرکز آمار ایران.
  3. Basu, R., & Ferreira, J. (2021). Planning car-lite neighborhoods: Does bikesharing reduce auto-dependence?. Transportation research part D: transport and environment, 92, 102721. https://doi.org/10.1016/j.trd.2021.102721
  4. Basu, R., & Ferreira, J. (2021). Sustainable mobility in auto-dominated Metro Boston: Challenges and opportunities post-COVID-19. Transport Policy, 103, 197-210. https://doi.org/10.1016/j.tranpol.2021.01.006
  5. Buehler, R., Pucher, J., Gerike, R., & Götschi, T. (2017). Reducing car dependence in the heart of Europe: lessons from Germany, Austria, and Switzerland. Transport reviews, 37(1), 4-28. https://doi.org/10.1080/01441647.2016.1177799
  6. Carroll, P., Benevenuto, R., & Caulfield, B. (2021). Identifying hotspots of transport disadvantage and car dependency in rural Ireland. Transport policy, 101, 46-56. https://doi.org/10.1016/j.tranpol.2020.11.004
  7. De Vos, J. (2020). The effect of COVID-19 and subsequent social distancing on travel behavior. Transportation research interdisciplinary perspectives, 5, 100121. https://doi.org/10.1016/j.trip.2020.100121
  8. Elhorst, J. P., Madre, J. L., & Pirotte, A. (2020). Car traffic, habit persistence, cross-sectional dependence, and spatial heterogeneity: new insights using French departmental data. Transportation Research Part A: Policy and Practice, 132, 614-632. https://doi.org/10.1016/j.tra.2019.11.016
  9. Eriksson, L., Garvill, J., & Nordlund, A. M. (2008). Interrupting habitual car use: The importance of car habit strength and moral motivation for personal car use reduction. Transportation Research Part F: Traffic Psychology and Behaviour, 11(1), 10-23. https://doi.org/10.1016/j.trf.2007.05.004
  10. Fujii, S., Gärling, T., & Kitamura, R. (2001). Changes in drivers’ perceptions and use of public transport during a freeway closure: Effects of temporary structural change on cooperation in a real-life social dilemma. Environment and behavior, 33(6), 796-808. https://doi.org/10.1177/00139160121973241
  11. Gärling, T., & Schuitema, G. (2007). Travel demand management targeting reduced private car use: effectiveness, public acceptability and political feasibility. Journal of social issues, 63(1), 139-153. https://doi.org/10.1111/j.1540-4560.2007.00500.x
  12. Gärling, T., & Steg, L. (2007). Threats to the quality of urban life from car traffic: problems. causes, and solutions. Elsevier.
  13. Gärling, T., Eek, D., Loukopoulos, P., Fujii, S., Johansson-Stenman, O., Kitamura, R., ... & Vilhelmson, B. (2002). A conceptual analysis of the impact of travel demand management on private car use. Transport Policy, 9(1), 59-70. https://doi.org/10.1016/S0967-070X(01)00035-X
  14. Graham-Rowe, E., Skippon, S., Gardner, B., & Abraham, C. (2011). Can we reduce car use and, if so, how? A review of available evidence. Transportation Research Part A: Policy and Practice, 45(5), 401-418. https://doi.org/10.1016/j.tra.2011.02.001
  15. Hine, J., & Grieco, M. (2003). Scatters and clusters in time and space: implications for delivering integrated and inclusive transport. Transport Policy, 10(4), 299-306. https://doi.org/10.1016/S0967-070X(03)00055-6
  16. Holmgren, J. (2013). An analysis of the determinants of local public transport demand focusing the effects of income changes. European Transport Research Review, 5(2), 101-107. https://doi.org/10.1007/s12544-013-0094-0
  17. Holmgren, J. (2020). The effect of public transport quality on car ownership–A source of wider benefits?. Research in Transportation Economics, 83, 100957. https://doi.org/10.1016/j.retrec.2020.100957
  18. Huang, X. (2011). Car ownership modeling and forecasts for China, 1-41. https://doi.org/10.37099/mtu.dc.etds/444
  19. Lewis, S., & del Valle, E. G. (2019). San Francisco's neighborhoods and auto dependency. Cities, 86, 11-24. https://doi.org/10.1016/j.cities.2018.12.017
  20. Linda, S. T. E. G. (2003). Can public transport compete with the private car?. IATSS research, 27(2), 27-35. https://doi.org/10.1016/S0386-1112(14)60141-2
  21. Marletto, G. (2013). Car and the city: Socio-technical pathways to 2030. In Working Papers 2013/6. CRENoS Universita di Cagliari, Universita di Sassari, 1-15.
  22. Martens, K. (2016). Transport justice: Designing fair transportation systems. Routledge.
  23. Matthies, E., Klöckner, C. A., & Preißner, C. L. (2006). Applying a modified moral decision making model to change habitual car use: how can commitment be effective?. Applied Psychology, 55(1), 91-106. https://doi.org/10.1111/j.1464-0597.2006.00237.x
  24. Mattioli, G., Roberts, C., Steinberger, J. K., & Brown, A. (2020). The political economy of car dependence: A systems of provision approach. Energy Research & Social Science, 66, 101486. https://doi.org/10.1016/j.erss.2020.101486
  25. McIntosh, J., Trubka, R., Kenworthy, J., & Newman, P. (2014). The role of urban form and transit in city car dependence: Analysis of 26 global cities from 1960 to 2000. Transportation Research Part D: Transport and Environment, 33, 95-110. https://doi.org/10.1016/j.trd.2014.08.013
  26. Moradi, A., & Vagnoni, E. (2018). A multi-level perspective analysis of urban mobility system dynamics: what are the future transition pathways?. Technological Forecasting and Social Change, 126, 231-243. https://doi.org/10.1016/j.techfore.2017.09.002
  27. Motte-Baumvol, B., Massot, M. H., & Byrd, A. M. (2010). Escaping car dependence in the outer suburbs of Paris. Urban studies, 47(3), 604-619. https://doi.org/10.1177/0042098009349773
  28. Næss, P. (2014). Urban form, sustainability and health: the case of greater Oslo. European Planning Studies, 22(7), 1524-1543. https://doi.org/10.1080/09654313.2013.797383
  29. Newman, P., Kosonen, L., & Kenworthy, J. (2016). Theory of urban fabrics: Planning the walking, transit/public transport and automobile/motor car cities for reduced car dependency. Town Planning Review, 87(4), 429-459. http://hdl.handle.net/20.500.11937/11247
  30. Ochieng, M., & Jama, M. (2015). The implications of automobile dependency in Abu Dhabi city. Urban Transport XXI, 146, 143.
  31. Paijmans, H., & Pojani, D. (2021). Living car-free by choice in a sprawling city: Desirable and… possible?. Case Studies on Transport Policy, 9(2), 823-829. https://doi.org/10.1016/j.cstp.2021.04.001
  32. Pooley, C. G., Horton, D., Scheldeman, G., Mullen, C., Jones, T., Tight, M., & Chisholm, A. (2013). Policies for promoting walking and cycling in England: A view from the street. Transport policy, 27, 66-72. https://doi.org/10.1016/j.tranpol.2013.01.003
  33. Smit, D. P. (2019). Reducing car dependency in Italy (Doctoral dissertation). https://frw.studenttheses.ub.rug.nl/id/eprint/2003
  34. Soltani, A., & Allan, A. (2006). Analyzing the impacts of microscale urban attributes on travel: Evidence from suburban Adelaide, Australia. Journal of urban planning and development, 132(3), 132-137. https://doi.org/10.1061/(ASCE)0733-9488
  35. Troko, J., Myles, P., Gibson, J., Hashim, A., Enstone, J., Kingdon, S., ... & Van-Tam, J. N. (2011). Is public transport a risk factor for acute respiratory infection?. BMC infectious diseases, 11(1), 1-6. https://doi.org/10.1186/1471-2334-11-16
  36. Verma, M. (2015). Growing car ownership and dependence in India and its policy implications. Case Studies on Transport Policy, 3(3), 304-310. https://doi.org/10.1016/j.cstp.2014.04.004
  37. Wiersma, J. K., Bertolini, L., & Harms, L. (2021). Spatial conditions for car dependency in mid-sized European city regions. European Planning Studies, 29(7), 1314-1330. https://doi.org/10.1080/09654313.2020.1854691
  38. Wiersma, J., Bertolini, L., & Straatemeier, T. (2016). How does the spatial context shape conditions for car dependency? An analysis of the differences between and within regions in the Netherlands. Journal of Transport and Land Use, 9(3), 35-55. https://www.jstor.org/stable/26203229
  39. Woodcock, J., Banister, D., Edwards, P., Prentice, A. M., & Roberts, I. (2007). Energy and transport. The Lancet, 370(9592), 1078-1088. https://doi.org/10.1016/S0140-6736(07)61254-9
  40. Yang, Z., Jia, P., Liu, W., & Yin, H. (2017). Car ownership and urban development in Chinese cities: A panel data analysis. Journal of Transport Geography, 58, 127-134. https://doi.org/10.1016/j.jtrangeo.2016.11.015
  41. Zhang, J., Hayashi, Y., & Frank, L. D. (2021). COVID-19 and transport: Findings from a world-wide expert survey. Transport policy, 103, 68-85. https://doi.org/10.1016/j.tranpol.2021.01.011
  42. Zhang, W., Zhao, Y., Cao, X. J., Lu, D., & Chai, Y. (2020). Nonlinear effect of accessibility on car ownership in Beijing: pedestrian-scale neighborhood planning. Transportation research part D: transport and environment, 86, 102445. https://doi.org/10.1016/j.trd.2020.102445
  43. Shen, Q., Chen, P., & Pan, H. (2016). Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city. Transportation Research Part A: Policy and Practice, 94, 31-44. https://doi.org/10.1016/j.tra.2016.08.027
  44. Donald, I. J., Cooper, S. R., & Conchie, S. M. (2014). An extended theory of planned behaviour model of the psychological factors affecting commuters' transport mode use. Journal of environmental psychology, 40, 39-4. https://doi.org/10.1016/j.jenvp.2014.03.003
  45. Vega-Gonzalo, M., Gomez, J., & Christidis, P. (2023). How has COVID-19 changed private car use in European urban areas? An analysis of the effect of socio-economic characteristics and mobility habits. Transportation research part A: policy and practice, 172, 10367. https://doi.org/10.1016/j.tra.2023.103679
  46. Hamidi, A., Salaripour, A., & Hesam, M. (2021). Evaluation of urban management policies in utilizing creative city brand, case study: Rasht city, Iran. Geographical Urban Planning Research (GUPR), 9(2), 439-461. doi: 10.22059/jurbangeo.2021.314497.1412. [in persian].
  47. Iran Statistics Center (2013), the results of national tourist statistics in the summer of 2013, Country Management and Planning Organization, Iran Statistics Center, Tehran [in Persian]
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