Modelling perceived pedestrian level of service of sidewalks: a structural equation approach
Abstract
A disparity between developed and developing countries is not only in the terms of economy and geography, but also on the pedestrians’ perceptions and expectations about the level of service of sidewalks. Therefore, it is paramount to find the effect of various built environment measures, that impact perceived Pedestrian Level Of Service (PLOS) in the context of developing nations. This study investigates the most influential factors of the built environment that affect perceived PLOS of sidewalks in the Indian context. This is one of the first studies in India that utilize Structural Equation Modelling (SEM) technique to assess pedestrian satisfaction and thereby qualitative PLOS of sidewalks. A total of 502 personal interviews was conducted to extract the pedestrian perception about the quality of sidewalks of Thiruvananthapuram city, a typical Indian city. The results identified four latent exogenous constructs named “Safety”, “Security”, “Mobility and infrastructure” and “Comfort and convenience” that represent the main aspects of the PLOS of sidewalks among which factors of security has exhibited highest loading (λ = 0.60). The study identified that parameters like police patrolling, street lighting, cleaner sidewalks, sidewalk obstructions, sidewalk surface have an evident impact on the level of service of sidewalks. The results of the study provide a significant information for interpreting the aspects of the walking environment that mainly influences the PLOS. This information can help city planners to prepare new strategies, policy interventions that enhance the quality of sidewalks and thus making the city more walkable.
Keyword : pedestrian, structural equation modelling, level of service, sidewalks, satisfaction
How to Cite
Bivina, G. R., & Parida, M. (2019). Modelling perceived pedestrian level of service of sidewalks: a structural equation approach. Transport, 34(3), 339-350. https://doi.org/10.3846/transport.2019.9819
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Hair, J. F.; Black, W. C.; Babin, B. J.; Anderson, R. E. 2013. Multivariate Data Analysis. Pearson. 729 p.
Hidayat, N.; Choocharukul, K.; Kishi, K. 2010. Investigating structural relationships among pedestrian perception, behavior, traffic, and level of service, Journal of Japan Society of Civil Engineers 27(1): 99–108. https://doi.org/10.2208/journalip.27.99
Holmes-Smith, P.; Coote, L.; Cunningham, E. 2006. Structural Equation Modelling: from the Fundamentals to Advanced Topics. Melbourne: School Research, Evaluation and Measurement Services (SREAMS). 218 p.
Hooper, D.; Coughlan, J.; Mullen, M. R. 2008. Structural equation modelling: guidelines for determining model fit, Electronic Journal of Business Research Methods 6(1): 53–60.
Hu, L.-T.; Bentler, P. M. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling: a Multidisciplinary Journal 6(1): 1–55. https://doi.org/10.1080/10705519909540118
IRC: 103-2012. Guidelines for Pedestrian Facilities. New Delhi, The Indian Roads Congress (IRC).
Jensen, S. U. 2007. Pedestrian and bicyclist level of service on roadway segments, Transportation Research Record: Journal of the Transportation Research Board 2031: 43–51. https://doi.org/10.3141/2031-06
Johnson, M. D.; Anderson, E. W.; Fornell, C. 1995. Rational and adaptive performance expectations in a customer satisfaction framework, Journal of Consumer Research 21(4): 695–707. https://doi.org/10.1086/209428
Khisty, C. J. 1994. Evaluation of pedestrian facilities: beyond the level-of-service concept, Transportation Research Record: Journal of the Transportation Research Board 1438: 45–50.
Kim, S.; Choi, J.; Kim, S. 2013. Roadside walking environments and major factors affecting pedestrian level of service, International Journal of Urban Sciences 17(3): 304–315. https://doi.org/10.1080/12265934.2013.825422
Kim, S.; Park, S.; Lee, J. S. 2014. Meso- or micro-scale? Environmental factors influencing pedestrian satisfaction, Transportation Research Part D: Transport and Environment 30: 10–20. https://doi.org/10.1016/j.trd.2014.05.005
Krejcie, R. V.; Morgan, D. W. 1970. Determining sample size for research activities, Educational and Psychological Measurement 30(3): 607–610. https://doi.org/10.1177/001316447003000308
Landis, B. W.; Vattikuti, V. R.; Ottenberg, R. M.; McLeod, D. S.; Guttenplan, M. 2001. Modeling the roadside walking environment: pedestrian level of service, Transportation Research Record: Journal of the Transportation Research Board 1773: 82–88. https://doi.org/10.3141/1773-10
Mitra-Sarkar, S. S. 1994. A Method for Evaluation of Urban Pedestrian Spaces. PhD Dissertation. University of Pennsylvania, Philadelphia, PA, US. 388 p. Available from Internet: https://repository.upenn.edu/dissertations/AAI9521086
Muraleetharan, T.; Adachi, T.; Uchida, K.-E.; Hagiwara, T.; Kagaya, S. 2004. A study on evaluation of pedestrian level of service along sidewalks and at crosswalks using conjoint analysis, Infrastructure Planning Review 21(3): 727–735. https://doi.org/10.2208/journalip.21.727
Muthén, B.; Kaplan, D. 1985. A comparison of some methodologies for the factor analysis of non‐normal Likert variables, British Journal of Mathematical and Statistical Psychology 38(2): 171–189. https://doi.org/10.1111/j.2044-8317.1985.tb00832.x
NATPAC. 2014. Annual Report 2013–’14. National Transportation Planning and Research Centre (NATPAC), India. 141 p. Available from Internet: http://www.natpac.kerala.gov.in/index.php/publications/annual-report
NCRB. 2016. Crime in India 2015: Compendium. National Crime Record Bureau (NCRB), Ministry of Home Affairs, Government of India. 222 p. Available from Internet: http://ncrb.gov.in/StatPublications/CII/CII2015/FILES/Compendium-15.11.16.pdf
Parida, P.; Najamuddin, D.; Parida, M. 2007. Planning, design and operation of sidewalk facilities in Delhi, Highway Research Bulletin 77: 81–95.
Pikora, T. J.; Bull, F. C.; Jamrozik, K.; Knuiman, M.; Giles-Corti, B.; Donovan, R. J. 2002. Developing a reliable audit instrument to measure the physical environment for physical activity, American Journal of Preventive Medicine 23(3): 187–194. https://doi.org/10.1016/S0749-3797(02)00498-1
Said, M.; Abou-Zeid, M.; Kaysi, I. 2017. Modeling satisfaction with the walking environment: the case of an urban university neighborhood in a developing country, Journal of Urban Planning and Development 143(1). https://doi.org/10.1061/(ASCE)UP.1943-5444.0000347
Schermelleh-Engel, K.; Moosbrugger, H.; Müller, H. 2003. Evaluating the fit of structural equation models: test of significance and descriptive goodness-of-fit measures, Methods of Psychological Research Online 8(2): 23–74.
Steiger, J. H.; Lind, J. C. 1980. Statistically based tests for the number of common factors, in Annual Spring Meeting of the Psychometric Society, 28–30 May 1980, Iowa City, IA, US.
TNN. 2017. Lack of street lights poses threat to motorists and pedestrians, The Times of India, 7 February 2017. Available from Internet: https://timesofindia.indiatimes.com/city/kochi/lack-of-street-lights-poses-threat-to-motorists-and-pedestrians/articleshow/57008220.cms
Vale, D. S.; Pereira, M. 2016. Influence on pedestrian commuting behavior of the built environment surrounding destinations: A structural equations modeling approach, International Journal of Sustainable Transportation 10(8): 730–741. https://doi.org/10.1080/15568318.2016.1144836
Vandenberg, R. J. 2006. Statistical and methodological myths and urban legends: where, pray tell, did they get this idea?, Organizational Research Methods 9(2): 194–201. https://doi.org/10.1177/1094428105285506
Walk Score®. 2018. Walk Score Methodology. Available from Internet: https://www.walkscore.com/methodology.shtml
Zainol, R.; Ahmad, F.; Nordin, N. A.; Aripin, A. W. M. 2014. Evaluation of users’ satisfaction on pedestrian facilities using pair-wise comparison approach, IOP Conference Series: Earth and Environmental Science 18(1): 012175. https://doi.org/10.1088/1755-1315/18/1/012175
Asadi-Shekari, Z.; Moeinaddini, M.; Zaly Shah, M. 2013. Disabled pedestrian level of service method for evaluating and promoting inclusive walking facilities on urban streets, Journal of Transportation Engineering 139(2): 181–192. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000492
Awang, Z. 2012. Structural Equation Modeling Using AMOS Graphic. UiTM Press. 167 p.
Barker, L. 2012. Exploring the Relationship between Walkability and the Built Environment: a Case Study of Three Intersections in Seattle’s University District. MSc Thesis. University of Washington, US. 49 p. Available from Internet: https://digital.lib.washington.edu/researchworks/handle/1773/20287
Bentler, P. M. 1990. Comparative fit indexes in structural models, Psychological Bulletin 107(2): 238–246. https://doi.org/10.1037/0033-2909.107.2.238
Bentler, P. M.; Bonett, D. G. 1980. Significance tests and goodness of fit in the analysis of covariance structures, Psychological Bulletin 88(3): 588–606. https://doi.org/10.1037/0033-2909.88.3.588
Bollen, K. A. 1989. A new incremental fit index for general structural equation models, Sociological Methods & Research 17(3): 303–316. https://doi.org/10.1177/0049124189017003004
Christopoulou, P.; Pitsiava-Latinopoulou, M. 2012. Development of a model for the estimation of pedestrian level of service in Greek urban areas, Procedia – Social and Behavioral Sciences 48: 1691–1701. https://doi.org/10.1016/j.sbspro.2012.06.1144
Clifton, K. J.; Livi Smith, A. D.; Rodriguez, D. 2007. The development and testing of an audit for the pedestrian environment, Landscape and Urban Planning 80(1–2): 95–110. https://doi.org/10.1016/j.landurbplan.2006.06.008
CPD. 2011. Population Census 2011. Census Population Data (CPD), India. Available from Internet: http://www.census2011.co.in
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
Dixon, L. B. 1996. Bicycle and pedestrian level-of-service performance measures and standards for congestion management systems, Transportation Research Record: Journal of the Transportation Research Board 1538: 1–9. https://doi.org/10.1177/0361198196153800101
Dowling, R.; Flannery, A.; Landis, B.; Petritsch, T.; Rouphail, N.; Ryus, P. 2008. Multimodal level of service for urban streets, Transportation Research Record: Journal of the Transportation Research Board 2071: 1–7. https://doi.org/10.3141/2071-01
Eboli, L.; Mazzulla, G. 2007. Service quality attributes affecting customer satisfaction for bus transit, Journal of Public Transportation 10(3): 21–34. http://doi.org/10.5038/2375-0901.10.3.2
Fan, X.; Thompson, B.; Wang, L. 1999. Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes, Structural Equation Modeling: A Multidisciplinary Journal 6(1): 56–83. https://doi.org/10.1080/10705519909540119
Gallin, N. 2001. Quantifying pedestrian friendliness: guidelines for assessing pedestrian level of service, Road and Transport Research 10(1): 47–55.
George, D.; Mallery, P. 2002. SPSS for Windows Step by Step: A Simple Guide and Reference, 11.0 Update. Allyn & Bacon. 400 p.
Gerbing, D. W.; Anderson, J. C. 1984. On the meaning of within-factor correlated measurement errors, Journal of Consumer Research 11(1): 572–580. https://doi.org/10.1086/208993
Gliem, J. A.; Gliem, R. R. 2003. Calculating, interpreting, and reporting Cronbach’s alpha reliability coefficient for Likerttype scales, in 2003 Midwest Research to Practice Conference in Adult, Continuing, and Community Education, 8–10 October 2003, Columbus, OH, US, 82–88.
Goldberger, A. S. 1972. Structural equation methods in the social sciences, Econometrica 40(6): 979–1001. https://doi.org/10.2307/1913851
Golob, T. F. 2003. Structural equation modeling for travel behavior research, Transportation Research Part B: Methodological 37(1): 1–25. https://doi.org/10.1016/S0191-2615(01)00046-7
Hair, J. F.; Black, W. C.; Babin, B. J.; Anderson, R. E. 2013. Multivariate Data Analysis. Pearson. 729 p.
Hidayat, N.; Choocharukul, K.; Kishi, K. 2010. Investigating structural relationships among pedestrian perception, behavior, traffic, and level of service, Journal of Japan Society of Civil Engineers 27(1): 99–108. https://doi.org/10.2208/journalip.27.99
Holmes-Smith, P.; Coote, L.; Cunningham, E. 2006. Structural Equation Modelling: from the Fundamentals to Advanced Topics. Melbourne: School Research, Evaluation and Measurement Services (SREAMS). 218 p.
Hooper, D.; Coughlan, J.; Mullen, M. R. 2008. Structural equation modelling: guidelines for determining model fit, Electronic Journal of Business Research Methods 6(1): 53–60.
Hu, L.-T.; Bentler, P. M. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling: a Multidisciplinary Journal 6(1): 1–55. https://doi.org/10.1080/10705519909540118
IRC: 103-2012. Guidelines for Pedestrian Facilities. New Delhi, The Indian Roads Congress (IRC).
Jensen, S. U. 2007. Pedestrian and bicyclist level of service on roadway segments, Transportation Research Record: Journal of the Transportation Research Board 2031: 43–51. https://doi.org/10.3141/2031-06
Johnson, M. D.; Anderson, E. W.; Fornell, C. 1995. Rational and adaptive performance expectations in a customer satisfaction framework, Journal of Consumer Research 21(4): 695–707. https://doi.org/10.1086/209428
Khisty, C. J. 1994. Evaluation of pedestrian facilities: beyond the level-of-service concept, Transportation Research Record: Journal of the Transportation Research Board 1438: 45–50.
Kim, S.; Choi, J.; Kim, S. 2013. Roadside walking environments and major factors affecting pedestrian level of service, International Journal of Urban Sciences 17(3): 304–315. https://doi.org/10.1080/12265934.2013.825422
Kim, S.; Park, S.; Lee, J. S. 2014. Meso- or micro-scale? Environmental factors influencing pedestrian satisfaction, Transportation Research Part D: Transport and Environment 30: 10–20. https://doi.org/10.1016/j.trd.2014.05.005
Krejcie, R. V.; Morgan, D. W. 1970. Determining sample size for research activities, Educational and Psychological Measurement 30(3): 607–610. https://doi.org/10.1177/001316447003000308
Landis, B. W.; Vattikuti, V. R.; Ottenberg, R. M.; McLeod, D. S.; Guttenplan, M. 2001. Modeling the roadside walking environment: pedestrian level of service, Transportation Research Record: Journal of the Transportation Research Board 1773: 82–88. https://doi.org/10.3141/1773-10
Mitra-Sarkar, S. S. 1994. A Method for Evaluation of Urban Pedestrian Spaces. PhD Dissertation. University of Pennsylvania, Philadelphia, PA, US. 388 p. Available from Internet: https://repository.upenn.edu/dissertations/AAI9521086
Muraleetharan, T.; Adachi, T.; Uchida, K.-E.; Hagiwara, T.; Kagaya, S. 2004. A study on evaluation of pedestrian level of service along sidewalks and at crosswalks using conjoint analysis, Infrastructure Planning Review 21(3): 727–735. https://doi.org/10.2208/journalip.21.727
Muthén, B.; Kaplan, D. 1985. A comparison of some methodologies for the factor analysis of non‐normal Likert variables, British Journal of Mathematical and Statistical Psychology 38(2): 171–189. https://doi.org/10.1111/j.2044-8317.1985.tb00832.x
NATPAC. 2014. Annual Report 2013–’14. National Transportation Planning and Research Centre (NATPAC), India. 141 p. Available from Internet: http://www.natpac.kerala.gov.in/index.php/publications/annual-report
NCRB. 2016. Crime in India 2015: Compendium. National Crime Record Bureau (NCRB), Ministry of Home Affairs, Government of India. 222 p. Available from Internet: http://ncrb.gov.in/StatPublications/CII/CII2015/FILES/Compendium-15.11.16.pdf
Parida, P.; Najamuddin, D.; Parida, M. 2007. Planning, design and operation of sidewalk facilities in Delhi, Highway Research Bulletin 77: 81–95.
Pikora, T. J.; Bull, F. C.; Jamrozik, K.; Knuiman, M.; Giles-Corti, B.; Donovan, R. J. 2002. Developing a reliable audit instrument to measure the physical environment for physical activity, American Journal of Preventive Medicine 23(3): 187–194. https://doi.org/10.1016/S0749-3797(02)00498-1
Said, M.; Abou-Zeid, M.; Kaysi, I. 2017. Modeling satisfaction with the walking environment: the case of an urban university neighborhood in a developing country, Journal of Urban Planning and Development 143(1). https://doi.org/10.1061/(ASCE)UP.1943-5444.0000347
Schermelleh-Engel, K.; Moosbrugger, H.; Müller, H. 2003. Evaluating the fit of structural equation models: test of significance and descriptive goodness-of-fit measures, Methods of Psychological Research Online 8(2): 23–74.
Steiger, J. H.; Lind, J. C. 1980. Statistically based tests for the number of common factors, in Annual Spring Meeting of the Psychometric Society, 28–30 May 1980, Iowa City, IA, US.
TNN. 2017. Lack of street lights poses threat to motorists and pedestrians, The Times of India, 7 February 2017. Available from Internet: https://timesofindia.indiatimes.com/city/kochi/lack-of-street-lights-poses-threat-to-motorists-and-pedestrians/articleshow/57008220.cms
Vale, D. S.; Pereira, M. 2016. Influence on pedestrian commuting behavior of the built environment surrounding destinations: A structural equations modeling approach, International Journal of Sustainable Transportation 10(8): 730–741. https://doi.org/10.1080/15568318.2016.1144836
Vandenberg, R. J. 2006. Statistical and methodological myths and urban legends: where, pray tell, did they get this idea?, Organizational Research Methods 9(2): 194–201. https://doi.org/10.1177/1094428105285506
Walk Score®. 2018. Walk Score Methodology. Available from Internet: https://www.walkscore.com/methodology.shtml
Zainol, R.; Ahmad, F.; Nordin, N. A.; Aripin, A. W. M. 2014. Evaluation of users’ satisfaction on pedestrian facilities using pair-wise comparison approach, IOP Conference Series: Earth and Environmental Science 18(1): 012175. https://doi.org/10.1088/1755-1315/18/1/012175