Abstract Considering the inconsistency among the evaluation outcomes derived by different methods and the shortcomings of static evaluation in current small and micro businesses credit assessment researches, an improved dynamic combined evaluation method is proposed. The initial methods are grouped using fuzzy clustering analysis and SOM-K-means algorithm, and information inside and outside the groups are combined twice according to the principles of homogeneity, heterogeneity and scale. Then, based on the definition of growth factor, the trends of combined evaluation values are quantified to obtain dynamic combined evaluation results. The paper conducted an empirical study on 11 small and micro manufacturing businesses, whose results verify that this method not only effectively combines the evaluation information obtained using different methods, but also takes into account the evaluation values at different times, and its outcomes are consistent with the conclusions cross-validated by the customer managers, which proves the feasibility and effectiveness of the proposed method.
ZHANG Faming,LI Aimin,HAN Yuanyuan. Study on Small and Micro Businesses Credit Assessment Based on Improved Dynamic Combined Evaluation Method[J]. Chinese Journal of Management, 2019, 16(2): 286-.
