Spatial economics model predicting transport volume

• Autorzy: Lu B.
• Języki publikacji: EN

Abstrakty

EN

It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics

• Wydawca: -
• Czasopismo: Polish Maritime Research
• Rocznik: 2016
• Tom: 23
• Numer: Special Issue S1
• Opis fizyczny: p.36-43,fig.,ref.

Twórcy

autor

Lu B.

• Institute of Electronic Commerce and Modern Logistics, Dalian University, Dalian, China

Bibliografia

• 1. Adolf K.Y. Ng, Flavio Padilha, Athanasios A. Pallis, (2013). Institutions, bureaucratic and logistical roles of dry ports: the Brazilian experiences [J] Journal of Transport Geography, Vol. 27, No. 2, Pages 46–55, 2013.
• 2. Andrawis, R. R., Atiya, A. F., El–Shishiny, H., (2011). Combination of long term and short term forecasts, with application to tourism demand forecasting [J] International Journal of Forecasting, Vol. 27, Pages 870–886, 2011.
• 3. Anna, B., Maurizio, C., Claudio, F., Alessio T., (2014). Ports and regional development: A spatial analysis on a panel of European regions [J] Transportation Research Part A: Policy and Practice, Vol. 65, Pages 44-55, 2014.
• 4. Babai, M.Z., Ali, M., Nikolopoulos, K., (2012). Impact of temporal aggregation on stock control performance of intermittent demand estimators: empirical analysis. [J] International Journal of Management Science, Vol. 40, Pages 713–721, 2012.
• 5. Bacchetti, A., Saccani, N., (2012). Spare parts classification and demand forecasting for stock control: investigating the gap between research and practice [J] International Journal of Management Science, Vol. 40, Pages 722–737, 2012.
• 6. Bandyopadhyay, S., Bhattacharya, R. (2013). A generalized measure of bullwhip effect in supply chain with ARMA demand process under various replenishment policies [J] International Journal of Advance Manufacturing Technology, Vol. 68, Pages 963–979, 2013.
• 7. Briant, A., Combes, P.–P., Lafourcade, M., (2010). Dots to boxes: do the size and shape of spatial units jeopardize economic geography estimations? [J] Urban Economics, Vol. 67, No. 3, Page 287–302, 2010.
• 8. Cang, S., Yu, H., (2014). A combination selection algorithm on forecasting [J] European Journal of Operational Research, Vol. 234, Pages 127–139, 2014.
• 9. Chris Jacobs–Crisioni, Piet Rietveld, Eric Koomen, (2014). The impact of spatial aggregation on urban development analyses [J] Applied Geography, Vol. 47, Pages 46–56, 2014.
• 10. Colin Wren, (2012). Geographic concentration and the temporal scope of agglomeration economies: an index decomposition [J] Regional Science and Urban Economics, Vol. 42, Issue 4, Pages 681–690, 2012.
• 11. Crone, S. F., Hibon, M., Nikolopoulos, K., (2011). Advances in forecasting with neural networks? empirical evidence from the NN3 competition on time series prediction [J] International Journal of Forecasting, Vol. 27, Pages 635– 660, 2011.
• 12. David A. Hensher, Truong P. Truong, Corinne Mulley, Richard Ellison, (2012). Assessing the wider economy impacts of transport infrastructure investment with an illustrative application to the north–west rail link project in Sydney, Australia [J] Journal of Transport Geography, Vol. 24, No. 9, Pages 292–305, 2012.
• 13. Dongya Li, Yi Lu, Mingqin Wu, (2012). Industrial agglomeration and firm size: evidence from China [J] Regional Science and Urban Economics, Vol. 42, Issues 1–2, Pages 135–143, 2012.
• 14. Dixit, A.K., Stigiitz, J.E., (1977). Monopolistic competition and optimum product diversity [J] American Economic Review, Vol. 67, Pages 298–302, 1977.
• 15. Echeverri–Carroll, E., Ayala, S.G., (2010). Gender wage differentials and the spatial concentration of high– technology industries [J] Progress in Spatial Analysis, Pages 287–309, 2010.
• 16. Eric Nitzsche, Stefan Tscharaktschiew, (2013). Efficiency of speed limits in cities: a spatial computable general equilibrium assessment [J] Transportation Research Part A: Policy and Practice, Vol. 56, No. 10, Pages 23–48, 2013.
• 17. Feo–Valero, M., García–Menéndez, L., Sáez–Carramolino, L., Furió–Pruñonosa, S., (2011). The importance of the inland leg of containerized maritime shipments: an analysis of modal choice determinants in Spain [J] Transportation Research Part E, Vol. 47, Pages 446–460, 2011.
• 18. Frank P.van den Heuvel,Peter W.de Langen, Karel H.van Donselaar, Jan C.Fransoo, (2013). Regional logistics land allocation policies: stimulating spatial concentration of logistics firms [J] Transport Policy, Vol. 30, Pages 275–282, 2013.
• 19. Frank, P., Liliana, R., Karel, H., Jong, A., Yossi, S., Peter, W., Jan, C., (2014). Relationship between freight accessibility and logistics employment in US counties [J] Transportation Research Part A: Policy and Practice, Vol. 59, Pages 91-105, 2014.
• 20. Frémont, A., Franc, P., (2010). Hinterland transportation in Europe: combined transport versus road transport [J] Journal of Transport Geography, Vol. 18, No. 4, Pages 548–556, 2010.
• 21. Fujita M, Krugman P., (2004). The new economic geography: Past, present and the future [J] Regional Science, Vol. 83, Pages 139–164, 2004.
• 22. Garcia–Alonso, L., Sanchez–Soriano, J., (2010). Analysis of the evolution of the inland traffic distribution and provincial hinterland share of the Spanish port system [J] Transport Reviews, Vol. 30, No. 3, Pages 275–297, 2010.
• 23. Gianmarco I.P. Ottaviano, (2012). Agglomeration, trade and selection [J] Regional Science and Urban Economics, Vol. 42, Issue 6, Pages 987–997, 2012.
• 24. Hyok–Joo Rhee, Sanggyun Yu, Georg Hirte, (2014). Zoning in cities with traffic congestion and agglomeration economies [J] Regional Science and Urban Economics, Vol. 44, No. 1, Pages 82–93, 2014.
• 25. Ingrid Ott, Susanne Soretz, (2010). Productive public input, integration and agglomeration [J] Regional Science and Urban Economics, Vol. 40, Pages 538–549, 2010.
• 26. Lei Fan, William W. Wilson, Bruce Dahl, (2012). Congestion, port expansion and spatial competition for US container imports [J] Transportation Research Part E: Logistics and Transportation Review, Vol. 48, Issue 6, Pages 1121–1136, 2012.
• 27. Marufuzzaman, M., Eksioglu, S.D., Li, X.P., Wang, J., (2014). Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain [J] Transportation Research Part E: Logistics and Transportation Review, Vol. 69, Pages 122-145, 2014.
• 28. Tomasicchio, GR; D’Alessandro, F. Wave energy transmission through and over low crested breakwaters [J] Journal of Coastal Research. SI 65, Pages 398-403, 2013.
• 29. Zastempowski, M; Bochat, A. Mathematical modelling of elastic deflection of a tubular cross-section [J] Polish Maritime Research. Vol. 22(2), Pages 93-100, 2015.
• 30. Masahisa Fujita, Nobuaki Hamaguchi, (2001). Intermediate goods and the spatial structure of an economy [J] Regional Science and Urban Economics, Vol. 31, Issue 1, Pages 79–109, 2001.
• 31. Masahisa Fujita, Tomoya Mori, (1996). The role of ports in the making of major cities: self–agglomeration and hub– effect [J] Development Economics, Vol. 49, Pages 93–120, 1996.
• 32. Krugman, Paul, (1991). Increasing returns and economic geography [J] Political Economy, Vol. 99, Pages 483–499, 1991.

Identyfikatory

DOI

10.1515/pomr-2016-0044