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基于粗糙集AHP农产品供应链信息共享评价指标体系研究 被引量:10

Study on information sharing level evaluation index weight of agricultural supply chain based on rough set and AHP
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摘要 针对农产品供应链信息共享程度评价指标权重求解过程中单一权重确定方法的不足,提出了基于粗糙集和AHP法的农产品供应链信息共享程度评价指标权重求解方法。结果表明:(1)基于影响农产品供应链信息共享的客观因素,构建了农产品供应链信息共享程度评价指标体系;(2)考虑到粗糙集求解权重的客观性优势和AHP法求解权重的主观性优势,提出了综合粗糙集和AHP法的供应链信息共享程度评价指标组合权重求解方法;(3)通过实例分析的方法,计算出IT能力、硬件设施、共享信息、共享信息状态和管理因素五个一级指标的组合权重依次为:0.174、0.172、0.247、0.223和0.184。基于粗糙集和AHP法的组合赋权法在农产品供应链信息共享评价指标权重确定中基本可行,可为农产品供应链信息共享评价及相关领域提供一个有效的思路。 For the problems of single determining weights method in information sharing level evaluation index weights determination of agricultural supply chain, aninformation sharing level evaluation index weights determination method of agricultural supply chain based on rough set and AHP is proposed. The results showed that:(1) Based on the objective factors that affect the agriculturalsupply chain information sharing, this paper constructed information sharing evaluation index system of agricultural supply chain;(2)Considering the subjectivity of determining weight while using rough set and the subjectivity of determining weight while using AHP,a combination determining weights method ofagricultural supply chain information sharing level evaluation index is proposed which integrated rough set and AHP;(3) the combination weights of IT capacity, hardware facilities, sharing information, sharing information status and management factors are obtained to be 0.174, 0.172, 0.247, 0.233 and 0.184 by an example. Combination determining weights method based on rough set and AHP is feasible in determining information sharing evaluation index weights of agricultural supply chain, and it can provides a useful choice for information sharing evaluation of agricultural supply chain and other related fields.
出处 《中南林业科技大学学报》 CAS CSCD 北大核心 2016年第6期124-130,共7页 Journal of Central South University of Forestry & Technology
基金 国家社会科学基金项目:农产品物流存单质押盈利模式和风险防范研究(11BG057)
关键词 农产品供应链 信息共享 粗糙集 层次分析法 agricultural supply chain information sharing rough set analytic hierarchy process
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