تحلیل موانع فردی در تمایل شهروندان رشت به پیاده‌روی در سفرهای کاری روزانه

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی عمران و محیط زیست، دانشگاه صنعتی امیرکبیر، تهران، ایران

چکیده

الگوی پیاده‌مدار، یک الگوی سفر جایگزین برای سفرهای روزانه است؛ به طوری که فرد در آن پیاده‌روی بیشتری انجام می‌دهد. از این رو، در راستای بررسی تمایل افراد به الگوی پیاده‌مدار، ضرورت دارد که اهمیت موانع پیاده‌روی فعلی شهروندان نیز بررسی شود. این مطالعه قصد دارد به بررسی نقش پنج مانع مرتبط با فرد در عدم تمایل به پیاده‌روی بیشتر در سفرهای کاری روزانه شهروندان بپردازد. موانع مرتبط با فرد مورد بررسی در این مطالعه شامل تنبلی/ میل به دیر بیدار شدن از خواب، مشکلات جسمی و حرکتی، علاقه نداشتن به پیاده‌روی بیشتر، مهم بودن آراستگی ظاهر شدن در محل کار و احساس خوب نداشتن از دیده شدن در خیابان می‌باشد. به همین منظور، از یک نمونه شامل 432 نفر از شاغلین ساکن در شهر رشت استفاده شده است. بر اساس اهداف این مطالعه، متغیرهای استخراج شده از مجموعه داده مورد مطالعه را می‌توان در سه دسته ویژگی‌های اقتصادی-اجتماعی، ویژگی‌های سفر و ویژگی‌های محیطی طبقه‌بندی کرد. در این مطالعه برای بررسی اهمیت موانع پیاده‌روی به ساخت پنج مدل لوجیت ترتیبی پرداخته شده که در مجموع 11 متغیر از ویژگی‌های اقتصادی-اجتماعی، 6 متغیر از ویژگی‌‌های سفر و 5 متغیر از ویژگی‌های محیطی در این مدل‌ها معنادار شده‌اند. نتایج نشان می‌دهد که اولا تاثیر ویژگی‌های اقتصادی-اجتماعی بر هر یک از موانع فردی مورد مطالعه متفاوت است و ثانیا، سهم این ویژگی‌ها بر هر یک از پنج مانع تنبلی/ میل به دیر بیدار شدن از خواب، مشکلات جسمی و حرکتی، علاقه نداشتن به پیاده‌روی بیشتر، مهم بودن آراستگی ظاهر شدن در محل کار و احساس خوب نداشتن از دیده شدن در خیابان به ترتیب 41، 30، 13، 7 و 8 درصد است. همچنین، متغیر تجربه حداقل 5 دقیقه پیاده‌روی روزانه در سفرهای غیرشغلی از ویژگیهای اقتصادی-اجتماعی، متغیر کل مدت‌ زمان سفر از ویژگی‌های سفر و متغیر شاخص قابلیت پیاده‌روی از ویژگی‌های محیطی حایز اهمیت هستند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Role of personal barriers on willingness to walk in daily work trips across Rasht citizens

نویسندگان [English]

  • Zeinab Etemadi Naeini
  • Meeghat Habibian
Amirkabir University of technology
چکیده [English]

The walk-oriented pattern is an alternative travel pattern for daily trips; that a person walks more than her/his regular pattern. In order to examine the tendency to fulfill this pattern, it is necessary to examine the role of different types of barriers on pedestrian walking. This study intends to address the role of personal barriers which avoid people to walk more in their daily work trips. The studied barriers include laziness/tend to wake up late, physical/health problems, not interested in more walking, the importance of neat appearance at workplace and not feeling good about being seen on the streets. For this purpose, a sample of 432 employees living in the city of Rasht, Iran has been used. The studied variables are classified into three categories: socio-economic, travel and environmental characteristics. Five ordered logit models have been calibrated to investigate the importance of personal barriers including 11 variables of socio-economic characteristics, 6 variables of travel characteristics and 5 variables of environmental characteristics. The results show that while the effect of socio-economic characteristics on each of the personal barriers studied is different, the contribution of these characteristics on each of the five barriers: laziness/tend to wake up late, physical and health problems, not interested in more walking, the importance of neat appearance at work and not feeling good about being seen on streets are 41, 30, 13, 7 and 8 percent, respectively. Furthermore, the background variable of having at least 5 minutes daily walking in non-work trips of socio-economic characteristics, the total travel time variable of travel characteristics and the variable of walkability index of environmental characteristics are effective in tendency to walk more.

کلیدواژه‌ها [English]

  • Pedestrian
  • Ordered logit model
  • Individual barriers
  • Walk oriented pattern
  • Rasht
[1] W. Elias, Y. Shiftan, The influence of individual’s risk perception and attitudes on travel behavior, Transportation research part A: policy and practice, 46(8) (2012) 1241-1251.
[2] J.M. Rippe, A. Ward, J.P. Porcari, P.S. Freedson, Walking for health and fitness, Jama, 259(18) (1988) 2720-2724.
[3] T. Yousefinezhadi, H. Soori, Study of obstacles and restrictions of pedestrians for commuting on foot in the city of Tehran: a qualitative study, Safety promotion and injury prevention (Tehran), 5(4) (2018) 185-192.
[4] G. Kash, N. McDonald, Travel Behavior and Perceived Barriers to Walking More Frequently: An Analysis of the Relationship Between Mode Choice and Attitudes in California, 2012.
[5] A.F. Clark, D.M. Scott, Barriers to walking: an investigation of adults in Hamilton (Ontario, Canada), International journal of environmental research and public health, 13(2) (2016) 179.
[6] Z. Aliyas, Fear of Crime and Individual Factors as Barriers to Leisure Walking in Neighborhoods, Iran University of Science & Technology, 29(2) (2019) 269-275.
[7] E.A. Richards, S. Woodcox, Barriers and motivators to physical activity prior to starting a community-based walking program, International journal of environmental research and public health, 18(20) (2021) 10659.
[8] G.F. Dunton, M. Schneider, Peer Reviewed: Perceived Barriers to Walking for Physical Activity, Preventing chronic disease, 3(4) (2006).
[9] A. Tajik, P. Partovi, Walkability Conceptual Model and Analytical Framework with the Emphasis on New Urbanism Approach (case study): 4th phase of Mehrshahr, Scientific Journal Management System, 3(9) (2014) 81-96.
[10] A. Razzaghi, A. Pourrajabi, S. Daneshi, Obstacles and problems related to elderly pedestrians: a qualitative study,  (2017).
[11] Y. Hatamzadeh, M. Habibian, A. Khodaii, Measuring walking behaviour in commuting to work: Investigating the role of subjective, environmental and socioeconomic factors in a structural model, International Journal of Urban Sciences, 24(2) (2020) 173-188.
[12] Y. Hatamzadeh, M. Habibian, A. Khodaii, Walking behaviors by trip purposes, Transportation Research Record, 2464(1) (2014) 118-125.
[13] A. Timperio, K. Ball, J. Salmon, R. Roberts, B. Giles-Corti, D. Simmons, L.A. Baur, D. Crawford, Personal, family, social, and environmental correlates of active commuting to school, American journal of preventive medicine, 30(1) (2006) 45-51.
[14] R.C. Brownson, E.A. Baker, R.A. Housemann, L.K. Brennan, S.J. Bacak, Environmental and policy determinants of physical activity in the United States, American journal of public health, 91(12) (2001) 1995-2003.
[15] J.E. Gomez, B.A. Johnson, M. Selva, J.F. Sallis, Violent crime and outdoor physical activity among inner-city youth, Preventive medicine, 39(5) (2004) 876-881.
[16] T.E. McMillan, The relative influence of urban form on a child’s travel mode to school, Transportation Research Part A: Policy and Practice, 41(1) (2007) 69-79.
[17] M.F. Zavareh, V. Abolhasannejad, A. Mamdoohi, T. Nordfjærn, Barriers to children’s walking to school in Iranian and Chinese samples, Transportation research part F: traffic psychology and behaviour, 73 (2020) 399-414.
[18] M. Thomas, A New Attitude: Achieving Personal and Professional Success by Keeping a Positive Mental Outlook, Red Wheel/Weiser, 1998.
[19] M. Ben-Akiva, J. Walker, A.T. Bernardino, D.A. Gopinath, T. Morikawa, A. Polydoropoulou, Integration of choice and latent variable models, Perpetual motion: Travel behaviour research opportunities and application challenges,  (2002) 431-470.
[20] K.M. Ralph, M.J. Smart, R.B. Noland, S. Wang, L. Cintron, Is it really too far? Overestimating walk time and distance reduces walking, Transportation research part F: traffic psychology and behaviour, 74 (2020) 522-535.
[21] Y. Hatamzadeh, M. Habibian, A. Khodaii, Walking and jobs: A comparative analysis to explore factors influencing flexible and fixed schedule workers, a case study of Rasht, Iran, Sustainable cities and society, 31 (2017) 74-82.
[22] R. Pueboobpaphan, S. Pueboobpaphan, S. Sukhotra, Acceptable walking distance to transit stations in Bangkok, Thailand: Application of a stated preference technique, Journal of Transport Geography, 99 (2022) 103296.
[23] A. Tennøy, M. Knapskog, F. Wolday, Walking distances to public transport in smaller and larger Norwegian cities, Transportation research part D: transport and environment, 103 (2022) 103169.
[24] P. Amini-Behbahani, L. Meng, N. Gu, Walking distances from services and destinations for residential aged-care centres in Australian cities, Journal of transport geography, 85 (2020) 102707.
[25] M. Gaume, R. Pietton, R. Vialle, C. Chaves, T. Langlais, Is daily walking distance affected in adolescent idiopathic scoliosis? An original prospective study using the pedometer on smartphones, Archives de Pédiatrie, 27(6) (2020) 333-337.
[26] Y. Yang, A.V. Diez-Roux, Walking distance by trip purpose and population subgroups, American journal of preventive medicine, 43(1) (2012) 11-19.
[27] S.A. Saidi Hosseini, M. Habibian, Identification of factors affecting the duration of walking in educational trips using the accelerated risk model, a case study: Rasht city, 16th International Conference on Transportation and Traffic Engineering, Tehran, (2015). (in Persian)
[28] R.C. Brownson, C.M. Hoehner, K. Day, A. Forsyth, J.F. Sallis, Measuring the built environment for physical activity: state of the science, American journal of preventive medicine, 36(4) (2009) S99-S123. e112.
[29] L.D. Frank, J.F. Sallis, B.E. Saelens, L. Leary, K. Cain, T.L. Conway, P.M. Hess, The development of a walkability index: application to the Neighborhood Quality of Life Study, British journal of sports medicine, 44(13) (2010) 924-933.
[30] L.D. Frank, P. Engelke, Multiple impacts of the built environment on public health: walkable places and the exposure to air pollution, International regional science review, 28(2) (2005) 193-216.
[31] L.D. Frank, J.F. Sallis, T.L. Conway, J.E. Chapman, B.E. Saelens, W. Bachman, Many pathways from land use to health: associations between neighborhood walkability and active transportation, body mass index, and air quality, Journal of the American planning Association, 72(1) (2006) 75-87.
[32] L. Herbert, V. Owen, L. Pascarella, R. Streisand, Text message interventions for children and adolescents with type 1 diabetes: a systematic review, Diabetes technology & therapeutics, 15(5) (2013) 362-370.
[33] M. Habibian, A. Hosseinzadeh, Walkability index across trip purposes, Sustainable cities and society, 42 (2018) 216-225.
[34] L.D. Frank, T.L. Schmid, J.F. Sallis, J. Chapman, B.E. Saelens, Linking objectively measured physical activity with objectively measured urban form: findings from SMARTRAQ, American journal of preventive medicine, 28(2) (2005) 117-125.
[35] E. Berjisian, M. Habibian, Walking Accessibility, Gravity-Based Versus Utility-Based Measurement, 2017.
[36] S. Gori, M. Nigro, M. Petrelli, Walkability indicators for pedestrian-friendly design, Transportation Research Record, 2464(1) (2014) 38-45.
[37] S. Zadvali, & Zadvali, F, Effective Factors in Pedestrian Accidents in Urmia, Rahvar, 27(11) (2014) 27-50.
[38] K.S. Al-Hagla, Evaluating new urbanism's walkability performance: A comprehensive approach to assessment in Saifi Village, Beirut, Lebanon, Urban Design International, 14(3) (2009) 139-151.
[39] A. Sharbati, Analysis of factors affecting the reluctance of citizens to use pedestrian bridges (Case study: Gorgan),  (2017).
[40] K. Ball, A. Bauman, E. Leslie, N. Owen, Perceived environmental aesthetics and convenience and company are associated with walking for exercise among Australian adults, Preventive medicine, 33(5) (2001) 434-440.
[41] N.A. Gallagher, K.A. Gretebeck, J.C. Robinson, E.R. Torres, S.L. Murphy, K.K. Martyn, Neighborhood factors relevant for walking in older, urban, African American adults, Journal of aging and physical activity, 18(1) (2010) 99-115.
[42] W.H. Organization, Global status report on road safety 2015, World Health Organization, 2015.
[43] M. Ahadi, M. Hassanpour, P. Bashiri, P. Bashiri, Strategies to promote safety to prevent pedestrian accidents in the city of Qazvin, Safety promotion and injury prevention (Tehran), 4(3) (2016) 143-150.
[44] A. Osama, T. Sayed, Evaluating the impact of connectivity, continuity, and topography of sidewalk network on pedestrian safety, Accident Analysis & Prevention, 107 (2017) 117-125.
[45] D. Lockett, A. Willis, N. Edwards, Through seniors' eyes: an exploratory qualitative study to identify environmental barriers to and facilitators of walking, Canadian Journal of Nursing Research Archive,  (2005) 48-65.
[46] S. Strath, R. Isaacs, M.J. Greenwald, Operationalizing environmental indicators for physical activity in older adults, Journal of aging and physical activity, 15(4) (2007) 412-424.
[47] R. Mitra, H. Siva, M. Kehler, Walk-friendly suburbs for older adults? Exploring the enablers and barriers to walking in a large suburban municipality in Canada, Journal of aging studies, 35 (2015) 10-19.
[48] A.P. Vanky, S.K. Verma, T.K. Courtney, P. Santi, C. Ratti, Effect of weather on pedestrian trip count and duration: City-scale evaluations using mobile phone application data, Preventive medicine reports, 8 (2017) 30-37.
[49] Y. Hatemzadeh, Modeling the tendency of citizens to walk during daily trips, PhD Thesis, Amir Kabir University of Technology, School of Civil Engineering and Environment, 2017. (in Persian)
[50] R. Williams, Generalized ordered logit/partial proportional odds models for ordinal dependent variables, The Stata Journal, 6(1) (2006) 58-82.
[51] R. Brant, Assessing proportionality in the proportional odds model for ordinal logistic regression, Biometrics,  (1990) 1171-1178.
[52] S. Jackman, Models for ordered outcomes, Political Science C, 200 (2000) 1-20.
[53] W.H. Greene, Econometric Analysis, 2007.
[54] General population and housing census. The information base of Iran Statistics Center. (2015). Online, access on 15/01/1400 (available at https://www.amar.org.ir).
[55] Master plan of Rasht city. Housing and Urban Development Organization, Volume 8. (2016). (in Persian)
[56] D.A. Hensher, J.M. Rose, J.M. Rose, W.H. Greene, Applied choice analysis: a primer, Cambridge university press, 2005.
[57] J.R. Hauser, Testing the accuracy, usefulness, and significance of probabilistic choice models: An information-theoretic approach, Operations Research, 26(3) (1978) 406-421.
[58] E.A. Raney, P.L. Mokhtarian, I. Salomon, Modeling individuals' consideration of strategies to cope with congestion, Transportation research part F: traffic psychology and behaviour, 3(3) (2000) 141-165.
[59] Y. Javid, Modeling the perceived walking distance and walking behavior of workers in Rasht city, Master's thesis, Amirkabir University of Technology, Faculty of Civil and Environmental Engineering, 2017. (in Persian)
[60] N. Habib, M. Alauddin, R. Cramb, P. Rankin, A differential analysis for men and women's determinants of livelihood diversification in rural rain-fed region of Pakistan: An ordered logit model (OLOGIT) approach, Social Sciences & Humanities Open, 5(1) (2022) 100257.
[61] Q. Zeng, W. Gu, X. Zhang, H. Wen, J. Lee, W. Hao, Analyzing freeway crash severity using a Bayesian spatial generalized ordered logit model with conditional autoregressive priors, Accident Analysis & Prevention, 127 (2019) 87-95.