Forest Estates/Organisational Units Ranking Model - The MRG Model

Abstract

Background and Purpose: The fact that new organizational concepts require comparison and ranking of some business entities, implies the analogy that, in forestry, ranking should create the basis for differentiation of Forest Estates (FE) (seen as profit centers) according to their capability to allocate funds from rent for the utilization of forests and forest land. In this sense, it was necessary to determine the basic criteria and variables, and then to create the model for FE ranking on the basis of ecological and production potentials, and business results (economic indicators). The main idea was to create a model that can be used primarily by forest owners (which are, in certain countries such as Bosnia and Herzegovina, Croatia, Serbia, and Montenegro, mainly governments) and by public forest enterprises. The proposed models may serve to all other scientific, professional, research and other institutions, as the starting point for further research and as suggestions for possible improvements of the proposed solutions. Materials and Methods: The research was carried out within the project "Differential rent in the Republic of Srpska forestry". Total sample for the survey was 44 interviewed parties, with 118 questionnaires filled in. The methods of classification, content analysis, desk research, analysis, synthesis and comparison were used. In the concrete application of the Forest Estates/Organisational Units Ranking Model (hereinafter MRG Model; Model rangiranja šumskih gazdinstava, in Bosnian), the following methods were used: brainstorming, focus groups, survey, desk research method, Pareto analysis, modelling and induction. The statistical methods used were descriptive statistics and rank correlation. By using these methods and by combining them, a new model for forest estates ranking was created. Different input data and variables that refer to economic and natural indicators were used for ranking, all in accordance with the values for areas for which the ranking was carried out. Results: The main results are used for defining and proposal of the new model for forests estates ranking, i.e. the MRG Model. This model includes the following steps: (1) Survey, (2) Selection and scoring of specific variables, (3) Determining the intervals for specific variables, (4) Ranking of forest estates, and (5) Validation and rank correlation. This paper presented the algorithm of implementation of specific steps within the MRG Model, together with all activities that need to be implemented in order to perform forest estates ranking. It is necessary to emphasize that forest estates ranking was performed in accordance with the following three ranks: (1) for all analyzed variables, (2) for economic variables, and (3) for natural variables. Additionally, three modules for the calculation of scores for individual forest estates are the result of this research. Conclusions: The MRG Model is based on FE ranking according to deviation from the average value of the selected variables. The quality of the model lies in the fact that it is relatively simple (there are no complex statistical or other methods, necessary data can be collected easily), and that it can be applied again for similar surveys. Implementation of the MRG Model involves 5 basic steps with 7 phases to be performed in the order specified in this paper. The selection of variables which will be part of the MRG Model is crucial. The survey sample must include representatives that are directly or indirectly involved in the forestry sector. Although it might seem that all selected variables are significant, it is always necessary to give each variable the importance in accordance with the survey results. It is necessary to validate the defined model, data and final ranks on a pilot sample. Since there are three ranks, it is necessary to consider their mutual correlation, by performing statistical analysis rank correlation.