Explaining travel behaviour with limited socio-economic data: Case study of Vishakhapatnam, India
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Amekudzi, 2009, Using the sustainability footprint model to assess development impacts of transportation systems, Transport. Res. Part A: Pol. Pract., 43, 339
Anciaes, 2017, The distribution of walkability in an African city: Praia, Cabo Verde, Cities, 67, 9, 10.1016/j.cities.2017.04.008
Appleton, B., Davies, M., Tansey, J., Atwal, P., Dore, G. P., Muzyka, D. 2008, GreenApple Canada 2008: SMART Transportation Ranking Report, Appleton Charitable Foundation.
Arora, A., Gadepalli, R., Sharawat, P. K., Vaid, A., Keshri, A. 2014, Low carbon Comprehensive Mobility Plan: Vishakhapatnam, UNEP DTU Partnership, Technical University of Denmark.
Balen, 2010, Comparison of two approaches for measuring household wealth via an asset-based index in rural and peri-urban settings of Hunan province, China, Emerg. Themes Epidemiol., 7, 7, 10.1186/1742-7622-7-7
Buchs, 2013, Who emits most? Associations between socio-economic factors and UK households' home energy, transport, indirect and total CO2 emissions, Ecol. Econ., 90, 114, 10.1016/j.ecolecon.2013.03.007
Burguillo, 2017, Car use behaviour of Spanish households: Differences for quartile income groups and transport policy implications, Case Stud. Transport Pol., 5, 150, 10.1016/j.cstp.2016.09.005
Carlsson-Kanyama, 1999, Travel patterns and environmental effects now and in the future: implications of differences in energy consumption among socio-economic groups, Ecol. Econ., 30, 405, 10.1016/S0921-8009(99)00006-3
Carruthers, 2005
Census of India 2011, Primary Census Abstract, Government of India.
Chalasani, 2005, Precision of geocoded locations and network distance estimates, J. Transport. Statist., 8, 1
Cheng, 2013, Travel behavior of the urban low-income in china: case study of Huzhou City, Procedia – Soc. Behav. Sci., 96, 231, 10.1016/j.sbspro.2013.08.030
Cordova, 2008, Methodological note: measuring relative wealth using household asset indicators, Am. Barometer Insights, 6
CRISIL 2013, New CRISIL indices measure prosperity and equality.
de Palma, 2000, Mode choices for trips to work in Geneva: an empirical analysis, J. Transp. Geogr., 8, 43, 10.1016/S0966-6923(99)00026-5
Devkota, 2014, Principal components analysis of the socioeconomic conditions of biogas users-with example from Nepal, Int. J. Renew. Energy Res. (IJRER), 4, 655
Diaz Olvera, 2015, Assessment of mobility inequalities and income data collection. Methodological issues and a case study (Douala, Cameroon), J. Transp. Geogr., 46, 180, 10.1016/j.jtrangeo.2015.06.020
Falavigna, 2016, Assessing inequalities on public transport affordability in two latin American cities: Montevideo (Uruguay) and C+¦rdoba (Argentina), Transp. Policy, 45, 145, 10.1016/j.tranpol.2015.09.011
Fernandes, 1998
Field, 2007
Filmer, 2001, Estimating wealth effects without expenditure data-or tears: an application to educational enrollments in states of India, Demography, 38, 115
Fry, 2014
Harttgen, 2013, Using an asset index to simulate household income, Econ. Lett., 121, 257, 10.1016/j.econlet.2013.08.014
Houweling, 2003, Measuring health inequality among children in developing countries: does the choice of the indicator of economic status matter?, Int. J. Eq. Health, 2, 8, 10.1186/1475-9276-2-8
Immers, 1993, Slum Relocation and NMTs in Bangkok, Trans. Res. Board
Jain, 2017, Sustainable mobility indicators for Indian cities: Selection methodology and application, Ecol. Ind., 79, 310, 10.1016/j.ecolind.2017.03.059
Jain, 2010, Discrete Route Choice Model for Bicyclists in Pune, India, Urban Transport J., 9, 1
Kitamura, R., Yoshii, T., & Yamamoto, T. 2009. The expanding sphere of travel behaviour research: selected papers from the 11th International conference on travel behaviour research Emerald Group Publishing.
Kohli, 2016, Urban slum detection using texture and spatial metrics derived from satellite imagery, J. Spat. Sci., 61, 405, 10.1080/14498596.2016.1138247
Kotval, 2015, The socio-economics of travel behavior and environmental burdens: a Detroit, Michigan regional context, Transport. Res. Part D: Transp. Environ., 41, 477, 10.1016/j.trd.2015.10.017
Lee, 2009
Lehmbrock, 2007
Li, 2015, Differentiating metropolitan transport disadvantage by mode: Household expenditure on private vehicle fuel and public transport fares in Brisbane, Australia, J. Transp. Geogr., 49, 16, 10.1016/j.jtrangeo.2015.10.001
Limtanakool, 2006, The influence of socioeconomic characteristics, land use and travel time considerations on mode choice for medium- and longer-distance trips, J. Transp. Geogr., 14, 327, 10.1016/j.jtrangeo.2005.06.004
Litman, 2009, Sustainable transportation indicators: a recommended research program for developing sustainable transportation indicators and data, Transport. Res. Board Annual Meet., 2009, 09
Mallett, W.J. 2001. Long-distance travel by low-income households. TRB Transportation Research Circular E-C026ΓÇöPersonal Travel: The Long and Short of It 169-177.
Manoj, 2015, Activity-travel behaviour of non-workers belonging to different income group households in Bangalore, India, J. Transp. Geogr., 49, 99, 10.1016/j.jtrangeo.2015.10.017
Matsushita, 2015, Socioeconomic position and work, travel, and recreation-related physical activity in Japanese adults: a cross-sectional study, BMC Pub. Health, 15, 916, 10.1186/s12889-015-2226-z
McKenzie, 2004, Measuring inequality with asset indicators, J. Popul. Econ., 18, 229, 10.1007/s00148-005-0224-7
Ministry of Housing and Urban Poverty Alleviation. Income Criteria for EWS & LIG Revised Upwards for Defining Beneficiaries under Government Schemes for Housing. 89039. 2012. Press Information Bureau, Government of India. Accessed on 12-9-2016.
Montgomery, 2000, Measuring living standards with proxy variables, Demography, 37, 155, 10.2307/2648118
Moser, C., Felton, A. 2007. The construction of an asset index measuring asset accumulation in Ecuador.
Munshi, 2016, Built environment and mode choice relationship for commute travel in the city of Rajkot, India, Transport. Res. Part D: Transp. Environ., 44, 239, 10.1016/j.trd.2015.12.005
Murakami, E. & Young, 1997. J. Daily Travel by Persons with Low Income. In: African American Mobility Symposium, Tampa, Florida.
Mushkudiani, N. 2014. Estimation of household income based on asset ownership.
National Sample Survey Organisation 2010, Housing Condition and Amenities in India: 2008-09, Ministry of Statistics & Programme Implementation, Government of India, NSS Report No. 535 (65.1.2.1).
National Sample Survey Organisation 2012, Informal Sector and Conditions of Employment in India – (July 2009–June 2010), Ministry of Statistics & Programme Implementation, Government of India, NSS 66th ROUND.
Nisar, 2014, Determinants of neonatal mortality in Pakistan: secondary analysis of Pakistan Demographic and Health Survey 2006–07, BMC Pub. Health, 663, 10.1186/1471-2458-14-663
OECD, 2013
Olvera, 2008, Household transport expenditure in Sub-Saharan African cities: measurement and analysis, J. Transp. Geogr., 16, 1, 10.1016/j.jtrangeo.2007.04.001
Palma, A.d. & Rochat, D, 2000, Mode choices for trips to work in Geneva: an empirical analysis, J. Transp. Geogr., 8, (1)
Po, J. Y. T., E.Finlay, J., B.Brewster, M., Canning, D. 2012, Estimating Household Permanent Income from Ownership of Physical Assets, Center for Population & Development Studies, Harvard university, PGDA Working Paper No. 97.
Saha, 2014, Public and private sector jobs, unreported income and consumption gap in India: Evidence from micro-data, North Am. J. Econ. Fin., 29, 285, 10.1016/j.najef.2014.07.002
Scholl, L. 2002, Transportation Affordability for Low Income Populations, Public Policy Institute of California.
Sisodia, 2012, Clustering techniques: a brief survey of different clustering algorithms, Int. J. Latest Trend. Eng. Technol. (IJLTET), 1, 82
Srinivasan, 2008, A spatial exploration of the accessibility of low-income women: Chengdu, China and Chennai, India, 143
Srinivasan, 2005, Travel behavior of low-income residents: studying two contrasting locations in the city of Chennai, India, J. Transp. Geograp., 13, 265, 10.1016/j.jtrangeo.2004.07.008
Stopher, 2007, Assessing the accuracy of the Sydney Household Travel Survey with GPS, Transportation, 34, 723, 10.1007/s11116-007-9126-8
Tirumalachetty, 2013, Forecasting greenhouse gas emissions from urban regions: microsimulation of land use and transport patterns in Austin, Texas, J. Transp. Geogr., 33, 220, 10.1016/j.jtrangeo.2013.08.002
Tiwari, 2002, Urban Transport priorities: meeting the challenge of socio-economic diversity in cities, a case study of Delhi, India, Cities, 19, 95, 10.1016/S0264-2751(02)00004-5
Tiwari, 2012, Accessibility and safety indicators for all road users: case study Delhi BRT, J. Transp. Geogr., 22, 87, 10.1016/j.jtrangeo.2011.11.020
Tiwari, 2016, Impact of public transport and non-motorized transport infrastructure on travel mode shares, energy, emissions and safety: Case of Indian cities, Transport. Res. Part D: Transp. Environ., 44, 277, 10.1016/j.trd.2015.11.004
UNEP, IIM Ahmedabad, IIT Delhi, & Cept University 2014, Comprehensive Mobility Plans (CMP): Preparation Toolkit – Revised, Institute of Urban Transport, Ministry of Urban Develoment, Government of India.
Vyas, 2006, Constructing socio-economic status indices: how to use principal components analysis, Health Policy Plan, 21, 459, 10.1093/heapol/czl029