Measuring sustainable capacity utilization in OECD economies: A new DEA framework with undesirable outputs under chance constraints

Examining the sustainable capacity utilization (SCU) of various systems is crucial for effective planning and decision-making. However, many studies face challenges when it comes to assessing capacity utilization due to the presence of random variables and undesirable outputs. In this research, we propose using chance-constrained data envelopment analysis (CCDEA) methods that take into account both managerial and natural disposability to evaluate the SCU of entities with random fixed and variable inputs. Specifically, we introduce non-radial directional distance function (DDF) models that incorporate random measures to provide estimates of input- and output-oriented random SCU metrics in the short term. These innovative techniques are then applied to analyze the SCU of OECD countries, considering both managerial and natural disposability factors. Our findings reveal that uncertainty and risk levels significantly influence the performance outcomes and ratios of the SCU that we calculate. This highlights the importance of accounting for these factors in capacity utilization assessments, ultimately contributing to more informed planning and strategic insights.