DEA Models for Identifying Critical Performance Measures

In performance evaluation, it is important to identify both the efficient frontier and the critical measures. Data envelopment analysis (DEA) has been proven an effective tool for estimating the efficient frontiers, and the optimized DEA weights may be used to identify the critical measures. However, due to multiple DEA optimal weights, a unique set of critical measures may not be obtained for each decision making unit (DMU). Based upon a set of modified DEA models, this paper develops an approach to identify the critical measures for each DMU. Using a set of four Fortune's standard performance measures, capital market value, profit, revenue and number of employees, we perform a performance comparison between the Fortune's e-corporations and 1000 traditional companies. Profit is identified as the critical measure to the performance of e-corporations while revenue the critical measure to the Fortune's 1000 companies. This finding confirms that high revenue does not necessarily mean profit for e-corporations while revenue means a stable proportion of profit for the Fortune's 1000 companies.