•   Sushant Siddharth Wanjari


Transportation a primary step in the supply chain of goods. The responsive time between the parts of this chain may critically affect the duration of the processes. By accounting on an integrated system, warehouses can increase the accuracy and reliability of the processes. This paper analyzes the feasibility of integrated transportation and warehousing platforms from two points of view: infrastructure (e.g. physical place, geographical location) and organizational perspective (e.g. software, data, models). This paper contributes to fill the gap between practitioners and researchers about the needs of both systems. This paper found that transportation and warehousing are two inherently linked systems. However, the current practice lacks substantial improvements in data collection and modeling of these systems. Future directions point towards the use of big data and the implementation of econometric concepts (i.e. choice models), together with a spatial understanding of the impact of warehousing locations (i.e. accessibility concept) in transport costs. E-commerce, big data, and autonomous driving are the future challenges to integrating these two systems of warehousing and transportation. Finally, with the current pandemic of COVID-19, improving freight services is becoming a basic need. This paper contributes to a better understanding of the needs of integrating transportation and warehousing in the current challenging times.

Keywords: Supply Chain, Warehousing, Transportation Models, Cross-Docking


(ABS), A.B.O.S. 2020. Transport [Online]. Available: https://www.bitre.gov.au/statistics/external/transport [Accessed July 2020].J. U. Duncombe, “Infrared navigation—Part I: An assessment of feasibility,” IEEE Trans. Electron Devices, vol. ED-11, pp. 34-39, Jan. 1959.

ANDANI, I. G. A., LA PAIX PUELLO, L. & GEURS, K. T. 2019. Effects of toll road construction on local road projects in Indonesia. Journal of Transport and Land Use, 12, 179–199.

BEN-AKIVA, M. & LERMAN, S. R. 1985. Discrete Choice Analysis, Cambridge, MA, MIT Press.


BÖRSCH-SUPAN, A., DELQUIÉ, P., LARICHEV, O., MORIKAWA, T., POLYDOROPOULOU, A. & RAO, V. 1999. Extended Framework for Modeling Choice Behaviour. Marketing Letters, 10, 187-203.

BOWEN, J. T. 2008. Moving places: the geography of warehousing in the US. Journal of Transport Geography, 16, 379-387.

CARTENÌ, A. 2014. Accessibility Indicators for Freight Transport Terminals. Arabian Journal for Science and Engineering, 39, 7647-7660.

CLAUSEN, U., GEIGER, C. & PÖTING, M. 2016. Hands-on Testing of Last Mile Concepts. Transportation Research Procedia, 14, 1533-1542.

COMMITTEE, A. I. A. S. 2020. Transport and Logistics [Online]. [Accessed].

DABLANC, L., OGILVIE, S. & GOODCHILD, A. 2014. Logistics Sprawl: Differential Warehousing Development Patterns in Los Angeles, California, and Seattle, Washington. Transportation Research Record, 2410, 105-112.

DE JONG, G. 2014. 6 - Mode Choice Models. In: TAVASSZY, L. & DE JONG, G. (eds.) Modelling Freight Transport. Oxford: Elsevier.

GOOGLE. 2020. See how your community is moving around differently due to COVID-19 [Online]. Available: https://www.google.com/covid19/mobility/ [Accessed July 2020].

GOVERNMENT, A. I. 2019. Australian Infrastructure Audit: Transport

GRAMATIKOV, S., KITANOVSKI, I., MISHKOVSKI, I. & JOVANOVIK, M. 2019. Last Mile Delivery with Autonomous Vehicles: Fiction or Reality?

GU, J., GOETSCHALCKX, M. & MCGINNIS, L. F. 2007. Research on warehouse operation: A comprehensive review. European Journal of Operational Research, 177, 1-21.

HANDOKO, S. D. & LAU, H. C. 2016. Enabling Carrier Collaboration via Order Sharing Double Auction: A Singapore Urban Logistics Perspective. Transportation Research Procedia, 12, 777-786.

HOLL, A. & MARIOTTI, I. 2018. The Geography of Logistics Firm Location: The Role of Accessibility. Networks and Spatial Economics, 18, 337-361.

JONG, G. D., TAVASSZY, L., BATES, J., GRØNLAND, S. E., HUBER, S., KLEVEN, O., LANGE, P., OTTEMÖLLER, O. & SCHMORAK, N. 2016. The issues in modelling freight transport at the national level. Case Studies on Transport Policy, 4, 13-21.

KANG, S. 2018. Warehouse location choice: A case study in Los Angeles, CA. Journal of Transport Geography, 102297.

KOTAVAARA, O., POHJOSENPERÄ, T., JUGA, J. & RUSANEN, J. 2017. Accessibility in designing centralized warehousing: Case of health care logistics in Northern Finland. Applied Geography, 84, 83-92.

LANDERS, T. L., COLE, M. H., WALKER, B. & KIRK, R. W. 2000. The virtual warehousing concepts. Transportation Research Part E: Logistics and Transportation Review, 36, 115-126.

LEE, H. L., PADMANABHAN, V. & WHANG, S. 1997. Information Distortion in a Supply Chain: The Bullwhip Effect. Management Science, 43, 546-558.

LIM, H. & THILL, J. C. 2008. Intermodal freight transportation and regional accessibility in the United States. Environment and Planning A, 40, 2006-2025.

LUO, H., YANG, X. & WANG, K. 2019. Synchronized scheduling of make to order plant and cross-docking warehouse. Computers & Industrial Engineering, 138, 106108.

MASON, S. J., MAURICIO RIBERA, P., FARRIS, J. A. & KIRK, R. G. 2003. Integrating the warehousing and transportation functions of the supply chain. Transportation Research Part E: Logistics and Transportation Review, 39, 141-159.

MCFADDEN, D. 1981. Econometric Models of Probabilistic Choice. In: MANSKI, C. F. & MCFADDEN, D. (eds.) Structural analysis of discrete data with economic applications. Cambridge, MA: MIT Press.

OPENSTREETMAP. 2020. Shapefiles for Geographic Information Systems (GIS) [Online]. Available: https://download.geofabrik.de/. [Accessed July 2020].

PERL, J. & DASKIN, M. S. 1985. A warehouse location-routing problem. Transportation Research Part B: Methodological, 19, 381-396.

RAHMANI, Y., CHERIF-KHETTAF, W. R. & OULAMARA, A. 2015. A Local Search approach for the Two–Echelon Multi-products Location–Routing problem with Pickup and Delivery. IFAC-Papers Online, 48, 193-199.

SAKAI, T., KAZUYA, K. & TETSURO, H. 2016. Location Choice Models of Urban Logistics Facilities and the Impact of 1 Zoning on their Spatial Distribution and Efficiency. Proceedings of the 95th Annual Meeting of the Transportation Research Board. Washington D.C.

SHEN, L. & STOPHER, P. R. 2014. Review of GPS Travel Survey and GPS Data-Processing Methods. Transport Reviews, 34, 316-334.

STATISTICS, A. B. O. 2015. 9223.0 - Road Freight Movements, Australia, 12 months ended 31 October 2014 [Online]. Available: https://www.abs.gov.au/ausstats/abs@.nsf/mf/9223.0 [Accessed].

STATISTICS, A. B. O. 2020. Measuring the impacts of COVID-19 [Online]. Available: https://www.abs.gov.au/websitedbs/d3310114.nsf/home/Additional+ABS+products+to+measure+impact+of+COVID-19 [Accessed].

STEPHAN, K. & BOYSEN, N. 2011. Cross-docking. Journal of Management Control, 22, 129.

STREETLIGHTDATA. 2020. Streetlight data [Online]. Available: https://www.streetlightdata.com [Accessed 2020].

THILL, J.-C. & LIM, H. 2010. Intermodal containerized shipping in foreign trade and regional accessibility advantages. Journal of Transport Geography, 18, 530-547.

TSENG, Y., YUE, W. & TAYLOR, M. Year. The role of transportation in logistics chain in: Proceedings of the Eastern Asia Society for Transportation Studies, Vol 55, pp1657-1672, 2005, 2005.

WYGONIK, E. & GOODCHILD, A. V. 2018. Urban form and last-mile goods movement: Factors affecting vehicle miles travelled and emissions. Transportation Research Part D: Transport and Environment, 61, 217-229.

YALE, W. H. Year. Data warehouse tools. In: MILCOM 97 MILCOM 97 Proceedings, 3-5 Nov. 1997, 1997. 764-767 vol.2.


Download data is not yet available.


How to Cite
Wanjari, S. S. (2020). Investigating Warehousing Operations from an Integrated Supply-Chain and Transportation Approach. European Journal of Business and Management Research, 5(5). https://doi.org/10.24018/ejbmr.2020.5.5.527