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出 处:《工业工程与管理》2006年第3期6-10,共5页Industrial Engineering and Management
基 金:国家自然科学基金资助项目(70271040)
摘 要:在研究企业竞争力评价时,指标变量间信息的高度重叠和高度相关性,即存在多重共线性,将给统计方法的应用带来许多障碍,致使回归方程参数不准确甚至模型不可用。因子分析是主成分分析的推广和发展。本文运用实证分析将因子分析法引入企业竞争力评价中,通过对解释变量提取彼此无关的主成分,把相关性较强的自变量综合在一起,各因子彼此独立,尽可能取小残差绝对值和大累计方差百分比,使企业竞争力评价模型既克服了共线性的干扰,又能够充分利用原有的信息。Multi-collinearity, i.e. the lack of independence between variances is a cause to the inaccuracy of regression models, which sets obstacles of statistical methods to evaluation of corporation competence. Through an empirical study, factor analysis is applied to the evaluation of corporation competence. It attempts to identify underlying variables, or factors, that explain the pattern of correlations within a set of observed variables, and to eliminate multi-collinearity. And it helps to extract a few integrated indices from a larger number of variables, thereby decreasing the dimension of established model. The result shows that this method is satisfying in the fact of model interpretability, reliability, etc.
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