Abstract: An improved Grey RelationalAnalysis (GRA) is used to quantitatively investigate the impact of Jiangxi provinceregional economy on local logistics demand. The grey characteristics of datafrom regional economy and logistics is studied, which shows GRA is applicable; thena multi-sequence GRA is proposed, which generates total 8 groups of greyrelational sequence from three indices of industrial added value and logisticsdemand based on GRA, while traditionally it is from just one index. It showsthat the descending order of grey relational sequence is primary industry,tertiary industry and secondary industry, while the coefficient of tertiaryindustry will gradually increase along with economic development. Finallystatement and explanation are given based on the Jiangxi Provincial industrialsituation.
Key words: Logistics Demand; Grey System; Grey Rational Analysis(GRA); Industry
1. Introduction
The planning of regional logisticsindustry is influenced by multiple complex factors, however, the main factor isalways depended on the development of local industries, so an analytical model forrelationship between these factors is hard to setup. Hence a study to thedevelopment of local economy and its impact on logistics industry will lay themilestone to the logistics planning.
The level of regional economicaldevelopment, industrial structure, industrial distribution and industrialupgrading has direct impact on the demand and the level of regional logistics.So in this paper, the gray relational theory is used to analyze the impact of Jiangxi provincialregional economy on the local logistics demand from a quantitative respective.
2. Applicabilityof Grey Relational Analysis and Its Improvement
2.1 Applicability of grey relational analysis
TheGrey System theory proposed by Deng (1982) has been proven to be useful fordealing with poor, incomplete and uncertain information system called greysystem. The Grey System theory is aimed at problems with no experience and insufficient,uncertainty data, which fuzzy mathematics, statistics and probability theorycan not solve. Grey Relational Analysis (GRA) is part of Grey System theory,which is suitable for solving problems with complicated interrelationshipsbetween multiple factors and variables. GRA is to establish gray correlationmodel to make grey relationship whose operating mechanism and the physicalprototype is not clear or non-existent quantification, sequence and obvious.GRA can define system or factor boundary, analyze influence of system andbehavior, distinguish primary and secondary factors, identify patterns and soon. Technical connotation of GRA