Performance evaluation based on multiple attributes with nonparametric frontiers

Performance rating and comparison of a group of entities is frequently base d on the values of several attributes. Such evaluations are often complicat ed by the absence of a natural or obvious way to weight the importance of t he individual dimensions of the performance. This paper proposes a framewor k based on nonparametric frontiers to rate and classify entities described by multiple performance attributes into 'performers' and 'underperformers', The method is equivalent to Data Envelopment Analysis (DEA) with entities defined only by outputs. In the spirit of DEA, the weights for each attribu te are selected to maximize each entity's performance score. This approach, however, results in a new linear program that is more direct and intuitive than traditional DEA formulations. The model can be easily understood and interpreted by practitioners since it conforms better to the practice of ev aluating and comparing performance using standard specifications. We illust rate the model's use with two examples. The first evaluates the performance of employees. The second is an application in manufacturing where multiple quality attributes are used to assess and compare performance of different manufacturing processes. (C) 1999 Elsevier Science Ltd. All rights reserve d.