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A Tool for Appraising Mobility Environment with a Percept Based Index Measure

AbdulMajeed Olaremi Shittu, Muhammad Zaly Shah


Diverse methods, approaches and models have been employed in explaining mobility in both the urban and human context. However, there has been the ever-present drawback premised on data unavailability, “dyrtiness” or scantiness. More so, the techniques and parameters used, does not provide clues about mobility complexities engendered by attributes of “mobility environments”, as a result, determinants of mobility complexities are hardly fully described. To narrow the gap, it is conjectured that systematic evaluation of traveler perception of “mobility environments”, may provide hints about the degree to which specified spatial units enhance or hinder mobility, by rating such environment with a perception based index construct we hope will help improve assessments of “mobility environments”. This need is underscored by the necessity to explore alternative decision support tools, for mobility evaluations, especially where it may be implausible to apply advanced, high end, data hungry models of mobility evaluation. The method involved a two-pronged survey of transport professionals and randomly selected travelers. The professionals helped with “mobility environment” attributes identification and selection of contextually relevant ones from a list of potential attributes of influence, extracted from relevant literature using the Delphi method. Randomly selected travelers were in turn presented with the short listed attributes for rating on a five point Likert scale. Ratings were then used to determine attribute rankings and their commensurate index equivalents, as a basis for classification. Travelers indicated that a high activity mix, high road and pedestrian network density are good mobility enhancing qualities a city should possess. However, aggregate indexing indicated that enhancing development characteristics, mode characteristics, travel and economic attributes, are the most important for the study area. The measures are targeted at facilitating development of cost effective and parsimonious means of identifying urban mobility challenges by local authorities, to provide a strategic pathway for a city’s “mobility environments” qualities to be identified and objectively appraised, in order to satisfactorily target interventions at improving both the “mobility environment” and the quality of life of city inhabitants.


Mobility Appraisal; Mobility Environment; Index Measure; Mobility Influencers; Mobility Complexities; Traveler Perception.

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Riferimenti bibliografici

Aderamo, A.J. (2000) City Planning and Management Techniques. In: Jimoh and Ifabiyi (Eds.), Contemporary Issues in Environmental Studies, (pp. 32-43). Ilorin, Nigeria: University Press.

Aderamo, A. J. (2003). Changing Structure of Intra-Urban Road Network in Ilorin, Nigeria (1963 – 1999). Ilorin Journal of Business and Social Sciences, vol. 8 Nos1 and 2, 65-76. MJT press.

Aderamo, A. I. (2008). Urbanization and transportation in Nigeria. In Urbanization, Resource Exploitation and environmental stability in Nigeria. Proceeding of the 49th Annual Conferences of Association of Nigerian Geographers (pp. 134-149).

Ahmed, Y. A. (1996). Problems of Physical Planning in Ilorin City, Nigeria (Unpublished Msc. Thesis). Geography Department, University of llorin, Nigeria.

Alton, D., Adab, P., Roberts, L., & Barrett, T. (2007). Relationship between walking levels and perceptions of the local neighbourhood environment. Archives of disease in childhood, 92(1), 29-33. doi:10.1136/adc.2006.100826.

Asiyanbola, R. A. (2007, June). Intra-urban transportation, gender and psychological distress in developing countries: Nigeria. In PRIPODE Workshop on Urban Population, Development and Environment Dynamics in Developing Countries. Nairobi, Kenya (pp. 11-13). Available at: ASIYANBOLA_paperNairobi2007-2.pdf.

Bertolini, L. (2006). Fostering urbanity in a mobile society: Linking concepts and practices. Journal of Urban Design, 11(3), 319–334. doi: 10.1080/13574800600888269.

Bertolini, L., & Djist, M. (2003). Mobility Environments and Network Cities. Journal of Urban Design, 8(1), 27-43. doi: 10.1080/1357480032000064755.

Florindo, A. A., Guimarães, V. V., Galvao Cesar, C. L., de Azevedo Barros, M. B., Goi Porto Alves, M. C., & Goldbaum, M. (2009). Epidemiology of leisure, transportation, occupational, and household physical activity: prevalence and associated factors. Journal of Physical Activity and Health, 6(5), 625.

Available at:

Howard, C., & Burns, E. (2001). Cycling to Work in Phoenix: Route Choice, Travel Behavior, and Commuter Characteristics. Transportation Research Record: Journal of the Transportation Research Board, (1773), 39-46. doi:10.3141/1773-05.

Hjorthol, R., Levin, L., and Siren, A. (2010). Mobility in Different Generation of Older Persons: The Development of Daily Travel in Different Cohorts in Denmark, Norway and Sweden. Journal of Transport Geography, 18 (5), 624 – 633. doi:

Hong, S. (2010). Human movement patterns, mobility models and their impacts on wireless applications. (Doctoral dissertation).North Carolina State University. ISBN: 978-1-124-92302-4. Available at:

Hume, C., Salmon, J., & Ball, K. (2005). Children's perceptions of their home and neighborhood environments, and their association with objectively measured physical activity: a qualitative and quantitative study. Health education research, 20(1), 1-13. doi:

Humpel, N., Marshall, A. L., Leslie, E., Bauman, A., and Owen, N. (2004). Changes in neighborhood walking are related to changes in perceptions of environmental attributes. Annals of Behavioral Medicine, 27(1), 60-67. doi:

Isaacman, S., Becker, R., Caceres, R., Kubourov, S,. Martonosi, M., Rowland, J,. and Varshavsky, A. (2011). Ranges of Human Mobility in Los Angeles and New York. In 8th IEEE Workshop on Managing Ubiquitous Communications and Services. doi:

Krejcie, R.V and Morgan, D.W. (1970). Determining Sample Size for Research Activities, Educational and Psychological Measurement, 1970 (30), 607 – 610.

Lotfi, S., & Koohsari, M. J. (2009). Analyzing accessibility dimension of urban quality of life: Where urban designers face duality between subjective and objective reading of place. Social Indicators Research, 94(3), 417-435. doi:10.1007/s11205-009-9438-5.

Mingshun, Z. (2002). Measuring urban Sustainability in China. (Doctoral dissertation). Institute for Housing and Urban Development Studies (IHS) and Erasmus University, Rotterdam, the Netherlands. Available at:

Morenikeji, W. (2006). Research and Analytical Methods. University Press Ltd: Jos, Nigeria.

Oluseyi, O. F. (2006). Analysis of inter-connectivity levels of urban street networks and social interactions in enclosed neighborhood in Johannesburg RSA. Humanity & Social Sciences Journal, 1(1), 79-95. ISSN 1818-4960.

Patla, A.E., and Shumway – Cook, A. (1999). Dimensions of Mobility: Defining the Complexity and Difficulty Associated with Community Mobility. Journal of Aging and Physical Activity. 7(1), 7-19.

Shittu, A.O., Zaly, M.S. and Chiroma, M.A. (2015). Perception based determinants of mobility dilemma in Ilorin metropolis. Open Journal of Social Sciences, 3(4), 61-70.


Sokołowska, K. (2014). Determinants and perceptions of social mobility in Poland, 1992-2008. Contemporary Economics, 8(1), 89-102. doi: 10.5709/ce.1897-9254.133.

Soria-Lara, J. A., Valenzuela-Montes, L. M., and Pinho, P. (2014): Using ‘Mobility Environments' in Practice: Lessons from a Metropolitan Transit Corridor in Spain. Journal of Environmental Policy & Planning, (ahead-of-print), 1-20. doi: 10.1080/1523908X.2014.991779.

Soria-Lara, J. (2012). Modelo de umbrales para la evaluacio´n ambiental de la movilidad urbana (Thesis diss.). University of Granada. Available at

Talavera-Garcıa, R., Soria-Lara, J. A., & Valenzuela-Montes, L. M. (2014). La calidad peatonal como metodo para evaluar entornos de movilidad urbanos. Documents d'anàlisi geogràfica, 60: 161-187, 60(1), 161–187. ISSN 0212-1573.

Timperio, A., Crawford, D., Telford, A., and Salmon, J. (2004). Perceptions about the local neighborhood and walking and cycling among children. Preventive Medicine, 38(1), 39-47. doi:

Vanwolleghem, G., Van Dyck, D., Ducheyne, F., Bourdeaudhuij, I., and Cardon, G. (2014). Assessing the Environmental Characteristics of Cycling Routes to School: A Study on the Reliability and Validity of a Google Street View-based audit. International Journal of Health Geographics, 13:19. Available at

Veal, A.J. (2006). Research Methods for Leisure and Tourism. A practical Guide: London: Prentice Hall. ISBN-13: 978-0273682004.

World Business Council for Sustainable Development (2004). Mobility 2030: Meeting the Challenges to Sustainability. WBCSD: Geneva, Switzerland.

Available at:

Zaly, M., 2010. Rating Pedestrian Facility with P – Index and The Application of Google Map (Monograph No.8). Centre for Innovative Planning and Development, Universiti Teknology Malaysia. Available at



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