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Risk of B2B Customer Research Based on Combination Forecast Model

Wang Gui-zhi, Lu Jin-shuai, Lv Xiao-jun, Xia Ping-song

Abstract


Transaction security problem is the key to improve the level of B2B electronic commerce service. Build customer risk prediction model can avoid the potential risks in advance. Basing on Kuhn tucker condition, the optimal combination forecast model was established to quantify the customer risk level. Compare the accuracy of three kinds of single forecasting model and combination forecast model through the Kendall Concorde coefficient. Empirical analysis results show that Kuhn-tucker constraint’ application to the combination forecast model can effectively improve the prediction precision, and can modify model with the passage of time.

Keywords


Kuhn-tucker condition, Combination forecast model, B2B e-commerce platform, Consistency check

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