Abstract
Freight transportation has received limited attention in the past compared to passenger transportation, especially in developing economies. However, the importance of freight transportation for the efficient functioning of any urban transportation system is gradually being realized. Estimating freight trips generated by the various manufacturing and service sectors in an urban setup is the primary step in freight transportation and management. For this purpose, segregating the various sectors and estimating freight trip generation is imperative. The primary aim of this study is to develop freight trip generation equations for one of the booming sectors in India, the restaurant service sector. The regions of Mumbai and Delhi-NCR are the focus of this study. About 150 restaurants (101 in Delhi-NCR, and 49 in Mumbai) were surveyed for this study. The face-to-face interview method at the establishments was adopted as the primary mode of data collection, primarily due to its high response rate. The daily average freight trips produced and attracted are observed to be approximately three vehicles and six vehicles, respectively. Separate models are estimated for freight trip attraction and production. It is observed that Poisson regression models for both attraction and production outperform the respective linear regression models. Poisson regression models are particularly useful when the dependent variable values are non-negative integers with sparse dispersion and a low mean. As far as the influencing variables are concerned, employment, vehicle ownership, and seating capacity are found to be significant for the freight trip models. The interaction variable formed by employment and vehicle ownership is used in the trip attraction model; similarly, a variable is created form the interaction of seating capacity and vehicle ownership in the trip production models.
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References
LEA Associates (2008) Comprehensive transportation study for Mumbai metropolitan region, vol I. Mumbai Metropolitan Region Development Authority, Mumbai
Holguín-Veras J, Patil G (2005) A multi-commodity integrated freight origin-destination synthesis model. Netw Spat Econ 8:309–326
Holguín-Veras J, Patil G (2008) Observed trip chain behavior of commercial vehicles. Transp Res Rec 1906:74–80
Nuzzolo A, Comi A (2014) Urban freight demand forecasting: a mixed quantity/delivery/vehicle-based model. Transp Res Part E: Logist Transp Rev 65:84–98
Cherrett T, Allen J, McLeod F, Maynard S, Hickford A, Browne M (2012) Understanding urban freight activity–key issues for freight planning. J Transp Geogr 24:22–32
de Oliveira LK, de Nobrega Albuquerque RA, Ebias DG, Correa BGeS (2017) Analysis of freight trip generation model for food and beverage in belo horizonte (Brazil). Region 4(1):17–30. https://doi.org/10.18335/region.v4i1.102
Holguín-Veras J, Jaller M, Destro L, Ban X, Lawson C, Levinson H (2011) Freight generation, freight trip generation and the perils of using constant trip rates. Transp Res Rec 2224:68–81
Holguín-Veras, J., Jaller, M., Sanchez-Diaz, I., Wojtowicz, J., Campbell, S., Levinson, H., Lawson, C., Powers, E., and Tavasszy, L. (2012). “Freight Trip Generation and Land Use”. NCHRP Report 739, NCFRP Report 19, Transportation Reseach Board, Washington D.C.
Jaller, M., Holguín-Veras, J., Sánchez-Díaz, I., and Lawson, C. (2014). “Area based freight trip generation models”. Transportation Research Board 93rd Annual Meeting, Washington D.C., USA.
Lawson C, Holguín-Veras J, Sanchez-Diaz I, Jaller M, Campbell S, Powers E (2012) Estimation of freight trip generation based on land use. Transp Res Rec 2269:65–72
McCormack E, Ta C, Bassok A, Fishkin E (2010) Truck trip generation by grocery stores. TransNow, Transportation Northwest, University of Washington, Washington
Sanchez-Diaz. I, Holguín-Veras, J., and Wang, C. (2013). “Assessing the Role of Land-Use, Network Characteristics, and Spatial Effects on Freight Trip Attraction”. Transportation Research Board 92nd Annual Meeting, Washington D.C., USA.
Asuncion J (2014) The geographic adaptive potential of freight transportation and production system in the context of fuel and emission constraints. University of Canterbury, New Zealand
Iding, H. E. M., Meester, J. W., and Tavasszy, L. (2002). “Freight trip generation by firms”. 42nd European Congress of the Regional Science Association.
Kulpa T (2014) Freight truck trip generation modelling at regional level. Procedia Soc Behav Sci 111:197–202
Middela MS, Ramadurai G (2020) Incorporating spatial interactions in zero-inflated negative binomial models for freight trip generation. Transportation. https://doi.org/10.1007/s11116-020-10132-w
Pani A, Sahu P, Patil G, Sarkar A (2018) Modelling urban freight production and attraction: a case study of seven cities in Kerala, India. Transp Policy 69:49–64. https://doi.org/10.1016/j.tranpol.2018.05.013
Patil G, Sahu P (2016) “Estimation of freight demand at mumbai port using regression and time series models. KSCE J Civil Eng 20(5):2022–2032. https://doi.org/10.1007/s12205-015-0386-0
Patil G, Sahu P (2017) Simultaneous dynamic demand estimation models for major seaports in India. Transp Lett 9(3):141–151. https://doi.org/10.1080/19427867.2016.1203582
Sahu, P., and Patil, G. (2015). “Handling short run disequilibrium in freight demand forecasting at major Indian ports using error correction approach. European Transport/ Trasporti Europei, Issue 59, paper no. (5), pp. 1–19.
Sahu P, Chandra A, Pani A, Majumdar B (2020) Designing freight traffic analysis zones for metropolitan areas: identification of optimal scale for macro-level freight travel analysis. Transp Plan Technol 43(6):620–637. https://doi.org/10.1080/03081060.2020.1780711
Pani A, Bhat F, Sahu P (2020) Effects of business age and size on freight demand: a decomposition analysis of indian establishments. Transp Res Rec 2674(2):112–126. https://doi.org/10.1177/0361198120902432
Pani A, Sahu P (2019) Comparative assessment of industrial classification systems for modelling freight production and freight trip production. Transp Res Rec 2673(3):210–224. https://doi.org/10.1177/0361198119834300
Pani A, Sahu P, Chandra A, Sarkar A (2019) Assessing the extent of modifiable areal unit problem in modelling freight (trip) generation: relationship between zone design and model estimation results. J Transp Geogr. https://doi.org/10.1016/j.jtrangeo.2019.102524
Sahu P, Pani A (2019) Freight generation and geographical effects: modelling freight needs of establishments in developing economies and analyzing their geographical disparities. Transportation. https://doi.org/10.1007/s11116-019-09995-5
Zomato (2016) How India at in 2016, https://community.zomato.com/post/155013027598/2016-on-a-plate (accessed on 18 September 2020)
Ye Z, Zhang Y, Lord D (2013) Goodness-of-fit testing for accident models with low means. Accid Anal Prev 61:78–86
Cameron AC, Windmeijer F (1996) R-squared measures for count data regression models with applications to health-care utilization. J Bus Econ Stat 14(2):209
Cameron AC, Windmeijer F (1997) An R-squared measure of goodness of fit for some common nonlinear regression models. J Econom 77(2):329–342
Ricci L (2010) Adjusted -squared type measure for exponential dispersion models. Stat Probab Lett 80(17–18):1365–1368
Coxe S, West S, Aiken L (2009) The Analysis of Count Data: A Gentle Introduction to Poisson Regression and Its Alternatives. J Pers Assess 91(2):121–136
Directorate of Economics & Statistics, Government of Maharashtra, Mumbai. (2005). “Fifth Economic Census Maharashtra State.”
Municipal Corporation of Greater Mumbai (MCGM). http://www.mcgm.gov.in/irj/portal/anonymous?NavigationTarget=navurl://745be63a8c86ec6b74ccad4690ad4100. Accessed 15 Sept 2020
Sahu P, Patil G (2017) Estimation of cargo demand at major seaports in India. J Marit Res 14(3):1–8
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Patil, G.R., Thadoju, S., Sahu, P.K. et al. Data Collection and Modeling of Restaurants’ Freight Trip Generation for Indian Cities. Transp. in Dev. Econ. 7, 9 (2021). https://doi.org/10.1007/s40890-021-00114-7
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DOI: https://doi.org/10.1007/s40890-021-00114-7