Sequential data envelopment analysis

We consider a new class of Data Envelopment Analysis (DEA) modeling, which we call 'sequential DEA'. This new approach is a relatively simple generalization of the standard and popular in practice DEA. It allows for analyzing efficiency of the decision making units that consist of a sequence of sub-DMUs (e.g., branches of banks, hospital holding company running a number of hospitals at different locations, hotel chains, etc.). The approach is embedded in the Hilbert sequence space (l(2)) and therefore it allows for potentially different numbers of the sub-DMUs as well as different numbers of inputs and outputs used by different decision making units. We hope this approach will open up a new stream of literature in the sense that many existing variations from the already rich literature on DEA can be adapted to this approach.

Automated summary

Sequential DEA is a new class of DEA modeling that allows for analyzing the efficiency of decision-making units consisting of a series of sub-DMUs. Embedded in the Hilbert sequence space, it can accommodate different numbers of sub-DMUs and inputs/outputs.