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Study On The Forecast Of Logistics Demand In

Posted on:2017-03-13Degree:MasterType:Thesis
Country:ChinaCandidate:W C HongFull Text:PDF
GTID:2209330503484556Subject:Regional Economics
Abstract/Summary:PDF Full Text Request
the rocketing development of e-commerce in recent years has endowed the industry of logistics with unprecedented opportunities. To help grow logistics, the central government has not only published several laws and regulations, but also launched some related projects. Therefore, Sichuan Province, one of the significant provinces of large population, soaring economy and thriving logistics market in the west of China, attaches great importance to it. In addition to the solid support given by government and companies, the accurate analysis and profound insight of the development of logistics and its demand are also in great need. In this case, this thesis is going to do a predictive survey of the demand of logistics in Sichuan Province in some aspects below.firstly, the thesis demonstrates the related concepts of Regional economics and logistics as well as those studies of some scholars. Then, the writer analyzes the status quo of regional economics and logistics in Sichuan Province. Based on the predecessors’ studies and the current economic development of Sichuan Province,The writer selects the independent viarable and grey relational model to analyse the synchronous development of them. Furthermore, with the aid of scenario analysis, the writer creates three independent situations where economic data are calculated and measured under a regression model respectively. Last but not least, the integrated predictive model of the logistics demand system is built to analyze the demand of regional logistics from 2014 to 2018 of Sichuan Province under three independent situations. In terms of the application of model, the thesis performs soundly. Thus the writer draws a reasonable conclusion and puts forward stategies and suggestions accordingly in the end.
Keywords/Search Tags:The demand of logistics, Regional logistics, Grey model, Prediction of trend
PDF Full Text Request
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