Ali Mohammadi; Somayeh Mohammad Hosseinizadeh
Volume 7, Issue 26 , October 2007, , Pages 281-304
Abstract
This paper presents a two-stage model for fully ranking insurance where each agent has multiple outputs and inputs. In the first stage the Data Envelopment Analysis (DEA) is run for each pair of units separately. In the second stage, the pairwise evaluation matrix generated in the first stage is utilized ...
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This paper presents a two-stage model for fully ranking insurance where each agent has multiple outputs and inputs. In the first stage the Data Envelopment Analysis (DEA) is run for each pair of units separately. In the second stage, the pairwise evaluation matrix generated in the first stage is utilized to rank scale the units via the Analytical Hierarchy Process (AHP). Both DEA and AHP are commonly used in practice. Both have limitations. The hybrid model AHP/DEA takes the best of both models, by avoiding the pitfalls of each. AHP/DEA ranking does not replace the DEA classification model, rather it furthers the analysis by proving full ranking in the DEA context for all units, efficient and inefficient. This approach is applied for ranking 23 Iran insurance agents that worked for 2003 and 2004 years. The results reveal that 929 agents have the highest rank and 949 agents have the lowest rank in the studying period.
