Performance evaluation based on multiple attributes with nonparametric frontiers

Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framewor...

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Bibliographic Details
Published in:Omega (Oxford) 1999-12, Vol.27 (6), p.637-645
Main Authors: Caporaletti, L.E, Dulá, J.H, Womer, N.K
Format: Article
Language:English
Subjects:
Applied sciences
Data envelopment analysis
Data Envelopment Analysis (DEA)
Exact sciences and technology
Linear programming
Mathematical programming
Operational research and scientific management
Operational research. Management science
Performance evaluation
Performance evaluation Data Envelopment Analysis (DEA) Linear programming
Studies
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Summary:Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framework 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 attribute 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 evaluating and comparing performance using standard specifications. We illustrate 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.
ISSN:0305-0483
1873-5274
DOI:10.1016/S0305-0483(99)00022-5