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Study On The Evaluation Of Logistics Development Level In Guangxi Beibu Gulf Economic Zone Based On Fuzzy Matter-element

Posted on:2024-01-20Degree:MasterType:Thesis
Country:ChinaCandidate:Z L MaFull Text:PDF
GTID:2569307157483954Subject:Management Science and Engineering
Abstract/Summary:
At present,the logistics industry is recognized by the international community as an important guarantee for the vigorous development of the world economy,and is one of the indicators to measure a country’s national strength and the overall state of consumption.With the continuous development of intelligent information technology and e-commerce,the importance of logistics in the development of national economy is gradually increasing.The Implementation Plan for Promoting High-quality Construction of the New Land-Sea Corridor in Western China issued by the National Development and Reform Commission emphasizes that the construction of the international gateway port of Guangxi Beibu Gulf should be accelerated,and the construction of the new land-sea corridor in Western China and an important hub for the double-circulation traffic at home and abroad should be constructed at a high level.In recent years,the development of Beibu Gulf Economic Zone in regional economic development level,logistics infrastructure level,logistics transportation capacity,logistics informatization ability and other aspects is different,leading to the overall development of logistics industry is not coordinated.Therefore,it is more and more important to improve the logistics development level of Guangxi Beibu Gulf Economic Zone.This paper takes the logistics development level of Guangxi Beibu Gulf Economic Zone as the research objective,focuses on the use of fuzzy matter-element analysis method to evaluate it,combined with literature research method,entropy weight method and grey prediction model for comprehensive analysis.First of all,by reading relevant literature,the review of domestic and foreign scholars on the development level of logistics and its evaluation is sorted out.Secondly,the status quo of logistics development in Guangxi Beibu Gulf Economic Zone is sorted out and explained through investigation,and the construction principle and method of evaluation index are combined.Four first-level indicators,including regional economic development level,logistics infrastructure level,logistics transportation capacity and logistics informatization capacity,were determined,and 16 second-level indicators were constructed under the four first-level indicators to evaluate the logistics development level of Guangxi Beibu Gulf Economic Zone.Finally,the entropy weight method and fuzzy matter-element analysis method are combined to evaluate the development level of regional logistics.The entropy weight method is used to calculate the weight of each evaluation index,and the fuzzy matter-element analysis method is combined with this weight to obtain the European proximity degree of each evaluation target,which reflects the development level of logistics of each city in Guangxi Beibu Gulf Economic Zone.The logistics development level of Guangxi Beibu Gulf Economic Zone is forecasted by grey forecasting model.The main findings are as follows: from the perspective of time dimension,the logistics development level of Guangxi Beibu Gulf Economic Zone in recent ten years shows an upward trend on the whole,indicating a good development trend.From the spatial dimension,there are obvious regional differences in the logistics development level of the four cities in Guangxi Beibu Gulf Economic Zone,indicating that the pace of logistics development among different regions is not coordinated and synchronous.According to the evaluation results and prediction results of time dimension and space dimension,relevant policies and suggestions are put forward for Beibu Gulf Economic Zone,in order to improve the overall logistics development level of Guangxi Beibu Gulf Economic Zone.
Keywords/Search Tags:fuzzy matter-element, development level evaluation, entropy weight method, European proximity, grey forecasting model
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