基于聚类分析的成本动因选择和合并研究  

Using Clustering Analysis for the Selection and Combination of Cost Drivers in Activity-Based Costing

作　　者：汪方军[1] 常华[1] 黄侃[1] 

机构地区：[1]西安交通大学管理学院,西安710049

出　　处：《管理评论》2009年第9期94-99,共6页Management Review

基　　金：国家自然科学基金项目资助(70471038;70902068);西安交通大学校长基金资助(2008-0112)

摘　　要：作业成本计算法(Activity-Based Costing,ABC)的应用已日趋普遍,然而成本动因数量增加使信息搜集、处理成本显著提高,因此对成本动因进行合理选择和合并就尤为重要。本文建立成本动因聚类分析模型,采用XAMC公司的成本数据,根据成本精确度目标确定成本动因初始聚类中心个数后,将所有成本动因依相关性强弱及经济涵义归入各聚类中心,选出代表性成本动因,进而对各聚类中心的成本动因进行合并。合并前后间接成本分配的差异分析表明:聚类分析能够对成本动因进行合理分类,且分类后能保证成本动因合并具有更高的准确性,这为成本动因选择与合并提供了一个新视角。With the widespread application of Activity-Based Costing System （ABCS）, the cost of collecting, storing and processing information will be significantly increasing for the rising numbers of cost drivers. It is important to reasonably select and combine cost drivers. This paper proposes a clustering analysis model to select and combine cost drivers in an ABCS; the data are quoted from a Chinese state-owned agricultural enterprise XAMC, and the initial number of clustering centers is determined by the required accuracy of cost calculation. All cost drivers will be classified to the centers in accordance with their relativity and economic meaning. Then, a representative cost driver should be selected form each clustering center, while the other cost drivers in the same cluster center are combined to it. The divergence of indirect cost allocation before and after the combination shows that the cluster analysis model can classify cost drivers into right groups and guarantee cost drivers＇ combination more accurately. That provides a new perspective to cost drivers＇ combination.

关 键 词：作业成本计算 成本动因 聚类分析 代表性成本动因 

分 类 号：F275.3[经济管理—企业管理]