4. Discussion
In this study, 25 laboratories were nominated to form a laboratory
network. The initial condition for determining the members of the
network is to calculate the efficiency values of the laboratory units.
For this reason, we used the efficiency values calculated by Ghafari
Someh et al. 8. Then, by assigning the performance
scores to the three clusters by the k-means algorithm, we determine the
network members. In the first cluster we put members who can form a
network, the second cluster includes members who need to have a strategy
for improvement in order to be accepted in the network, and the third
cluster includes members who have no chance of joining the network.
Since the network depends on the cooperation of the members, we use a
cooperative game called Shapley’s value which has the advantage of fair
profit sharing, and we propose a method for dividing profit. The results
show that managers can improve network performance by sharing fair
profits among network members, and in addition to network survival, they
can create incentive strategies for members of the network.
A limitation exists in this research. In a real-world situation, we are
faced with risk and uncertainty in healthcare systems. Therefore, labs
efficiency score might not correspond to actual values in this study.
Therefore, several interesting directions can be further studied. The
network of collaboration in an uncertain environment should be
considered and the use of uncertain DEA methods, such as Fuzzy DEA,
interval DEA, and robust DEA, may also be investigated and compared.