Determining the effectiveness of the forest regionaldirectorates by data envelopment analysis

In today's world, where scarce resources are even more valuable, achieving the targets set by using fewer resources has been the most important competitive factor. Organizations should utilize their resources more effectively and they have to aim the increase in their effectiveness continuously. To increase their effectiveness, organizations should analyze whether they are effective or not. While, effective organizations should search for the way that how to be more effective, organizations that are less effective than others should realize why they are ineffective by taking sample the others who are working for the same targets and they should make planned arrangements in their input or output variables. Data Envelopment Analysis is a method that is non-parametric based on math equations to calculate the activity levels by evaluating input and output variables together. In this study, the effectiveness analysis of 28 different Forestry Regional Directorates was carried out by using Data Envelopment Analysis. Seven different variables of four were input variables and three were output variables determined. Data envelopment analysis; Output oriented CCR, output-oriented BCC, output-oriented super BCC, and output-oriented super BCC models are used. According to the results of the output-oriented CCR model, 11 regional directorates are considered as "1" effective, while 17 regional directorates are not fully effective. In the output-oriented BCC model, the number of effective KVBs increased from 11 to 21. In BCC model, efficiency values are equal to or greater than CCR model. The reason for this is the local efficiency with the BCC model and the general efficiency value with the CCR model.