A chance-constrained network DEA approach based on enhanced Russell-based directional distance measure to evaluate public sector performance: a case study of OECD countries.

Decision-making quality is a concern for the public sector because its decisions may involve more dimensions than those faced by the private sector. However, past studies on public sector efficiency have ignored the uncertainty of data estimation. This study addresses this shortcoming by proposing a chance-constrained network DEA approach based on an enhanced Russell-based directional distance measure that evaluates public sector performance. The proposed approach uses stochastic inputs and outputs to enhance decision-making quality and capacity in the public sector. The usefulness of this approach is demonstrated through an empirical case of the OECD. Our approach also provides practical suggestions for promoting a green economic transformation and serves as a reference for government policies. [ABSTRACT FROM AUTHOR]