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B2C电子商务信用评价模型研究
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摘要
一直以来,信用问题是阻碍电子商务进一步发展的重要因素。社会信用体系的缺失,导致电子商务信用问题层出不穷,电子商务信用体系作为社会信用体系的重要组成部分,被认为是社会信用体系的突破口。伴随着电子商务的持续高速发展,政府、社会和学术界都在对电子商务信用体系进行研究,作为信用体系的核心之一——信用评价模型,特别是B2C信用评价模型尚未进行深入的探讨,本文对B2C信用评价模型研究无论在理论研究,还是在实践应用上具有基础性和前沿性。
     本文通过对电子商务信用问题进行分析,对电子商务信用评价体系进行了研究,并分析了B2C信用评价体系存在的主要问题,指出了现有信用评价模型所存在的缺陷和待改进的问题,依据模糊理论建立科学、合理的信用评价模型和算法,改良现有的电子商务信用评价体系。
     论文重点对B2C电子商务信用评价模型进行了研究,提出了基于模糊理论的综合信用评价模型和算法,并详细论述了其构建过程。论文采用以定性分析与定量分析相结合的原则,结合B2C电子商务中交易主体的特点,采用融合性的观点,进行消费者和企业信用影响因素分析,构建了B2C信用评价指标体系,利用模糊算法和模糊评价矩阵计算出商家信用积分,为用户的交易决策提供了更可靠的依据,降低了交易中的信用风险。
All along, the credit issue is an important factor to impeding the further development of e-commerce. Lack of social credit architecture, resulting in endless e-commerce credit problems, as an important component of the social credit architecture, e-commerce architecture was considered a breakthrough. With the continued rapid development of e-commerce, government, society, the academic are all research on e-commerce credit system. Credit evaluation model as the core issue of credit architecture, especially in B2C credit evaluation model has not yet in-depth discussions. In theoretical research and practical application, B2C credit evaluation model has basic and frontier effect.
     First, we analysis the e-commerce credit issue, study e-commerce credit evaluation architecture and the credit evaluation architecture of B2C. Second, we point out the existence problems and improved suggestions. Third, we establish a scientific and rational credit evaluation model and algorithms based on fuzzy theory which can improve the existing e-commerce credit evaluation system.
     In this paper, we focus on the B2C e-commerce credit evaluation model which based on fuzzy theory and comprehensive credit evaluation algorithms, and discusses in detail the establish process. we adopt a qualitative and quantitative analysis, combined with the integration of point of view that consumer and business credit impact factor analysis, construct a B2C credit evaluation index architecture, using fuzzy algorithm and fuzzy evaluation matrix to calculate business credit score, which provides a more reliable environment for user's decision-making, and reduce the credit risk of the transaction.
引文
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