Efficiency Assessment in the Swedish Forest Industry Using Data Envelopment Analysis

Data Envelopment Analysis (DEA) is a widely used non-parametric method for evaluating the relative efficiency of decision-making units (DMUs). This study applies DEA to assess the efficiency of SCA Forest Company, one of Europe’s largest privately held forest estates, located in Sweden. The analysis utilizes both the CCR (Charnes, Cooper, and Rhodes) and BCC (Banker, Charnes, and Cooper) models to account for both desirable and undesirable outputs over a 30-year period. Significant variations in efficiency scores were observed across different scenarios using the CCR model, whereas the BCC model exhibited minimal differences among the DMUs. To enhance the precision of the assessment, the Andersen-Petersen (AP) super-efficiency model was employed, identifying several highly efficient DMUs, particularly DMU 1 and DMU 6, which demonstrated superior efficiency. The statistical significance of these findings was validated using the Wilcoxon signed-rank test, revealing significant differences in efficiency scores under the BCC model across scenarios. However, no such differences were found under the CCR model. This study provides valuable benchmarks for operational improvements within SCA and other similar sectors, offering insights into strategies for better resource allocation and performance enhancement.