Abstract: There exists some time lag between the consumption of
inputs and the production of outputs. This time lag effect should be
considered in calculating efficiency of decision making units (DMU).
Recently, a couple of DEA models were developed for considering
time lag effect in efficiency evaluation of research activities. However,
these models can’t discriminate efficient DMUs because of the nature
of basic DEA model in which efficiency scores are limited to ‘1’. This
problem can be resolved a super-efficiency model. However, a super
efficiency model sometimes causes infeasibility problem. This paper
suggests an output oriented super-efficiency model for efficiency
evaluation under the consideration of time lag effect. A case example
using a long term research project is given to compare the suggested
model with the MpO model.
Abstract: In many cases, there are some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrate models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long term research project is given to compare the suggested model with the MpO model.
Abstract: Data Envelopment Analysis (DEA) is a methodology
that computes efficiency values for decision making units (DMU) in a
given period by comparing the outputs with the inputs. In many cases,
there are some time lag between the consumption of inputs and the
production of outputs. For a long-term research project, it is hard to
avoid the production lead time phenomenon. This time lag effect
should be considered in evaluating the performance of organizations.
This paper suggests a model to calculate efficiency values for the
performance evaluation problem with time lag. In the experimental
part, the proposed methods are compared with the CCR and an
existing time lag model using the data set of the 21st century frontier
R&D program which is a long-term national R&D program of Korea.