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Due to the challenges of implementing environmental responsibility, sustainable development is often criticized for its promise to "square the circle". This paper incorporates sociological theories into operational research to enhance our understanding of the issue. It proposes a framework for evaluating eco-efficiency that captures the decision-making process from a macro perspective rather than focusing on a single technique or employing a multimethodology. By utilizing 272 Chinese cities as case studies, the evaluation process is effectively implemented. From three perspectives - region, city size, and policy - we draw some interesting conclusions. Finally, a vision for future research is presented in the concluding section. • This study incorporates sociological theories into operational research to enhance the understanding of eco-efficiency evaluations. • By utilizing 272 Chinese cities as case studies, we implement a comprehensive and effective evaluation process. • We propose a visionary framework and four potential directions for further exploration. [ABSTRACT FROM AUTHOR]

We undertake a systematic comparison of existing models measuring and decomposing the economic efficiency of organizations. For this purpose we introduce the package BenchmarkingEconomicEfficiency.jl for the open-source Julia language including a set of functions to be used by scholars and professionals working in the fields of economics, management science, engineering, and operations research. Using mathematical programming methods known as Data Envelopment Analysis, the software develops code to decompose economic efficiency considering alternative definitions: profit, profitability, cost and revenue. Economic efficiency can be decomposed, multiplicative or additively, into a technical (productive) efficiency term and a residual term representing allocative (or price) efficiency. We include traditional decompositions like the radial efficiency measures associated with the input (cost) and output (revenue) approaches, as well as new ones corresponding to the Russell measures, the directional distance function, DDF (including novel extensions like the reverse DDF, modified DDF, or generalizations based on Hölder norms), the generalized distance function, and additive measures like the slack based measure, their weighted variants, etc. Moreover, regardless the underlying economic efficiency model, many of these technical inefficiency measures are available for calculation in a computer software for the first time. This article details the theoretical methods and the empirical implementation of the functions, comparing the obtained results using a common dataset on Taiwanese Banks. • We present an open-source Julia package for measuring economic efficiency. • Economic efficiency is decomposed into technical and allocative efficiencies. • Each economic efficiency model is decomposed with different technical measures. • We consider Farrell's measures, Russell, weighted additive, directional functions, etc. • We discuss the pros and cons of each decompositions based on desirable properties. [ABSTRACT FROM AUTHOR]

Research on productive efficiency at the firm level has developed as an important and active strand of research the last decades, both within operations research, management science and economics. Two apparently different definitions of efficiency are examined, but it is shown that when both estimation methods are based on solving linear programming problems the definitions of efficiency are identical. The purpose of the paper is to give the basic ideas of efficiency analyses using DEA as a tool for researchers not so familiar with efficiency analysis and DEA. The concept of shadow prices is given special attention. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic required managerial and structural changes inside hospitals to address new admission demands, frequently reducing their care capacity for other diseases. In this regard, this study aims to support the recovery of hospital productivity in the post-pandemic context. The major challenge will be to make use of all the resources the institution has obtained (equipment, beds, temporarily hired human resources) and to increase production to meet the existing repressed demand. To support evidence-based decision-making at a major university hospital in Rio de Janeiro, hospital managers and operations research analysts designed an approach based on multiple methodologies. Besides multimethodology, one important novelty of this study is the application of a productivity frontier function to future scenario planning through the quantitative DEA methodology. Concept maps were used to structure the problem and emphasize stakeholders' perspectives. In sequence, data envelopment analysis (DEA) was applied, as it combines benchmarking best practices and assigns weights to inputs and outputs. To guarantee that the efficiency measurement considers all inputs and outputs before any inclusion of expert judgment, the scope was redirected to full dimensional efficient facet, if any, or to maximum efficient faces. The results indicate that production scenarios proposed by stakeholders based on the Ministry of Health parameters overestimate the viable production framework and that the scenario that maintains temporary human resource contracts is more compatible with quality in health provision, teaching, and research. These findings will serve as a basis for decision-making by the governmental agency that provided temporary contracts. The present methodology can be applied in different settings and scales. • Coronavirus pandemic demanded hospital structural and human resource changes. • Planning post-pandemic hospital production requires multimethodological approach. • Concept maps facilitate integration between hospital stakeholders and OR analysts. • DEA and GP adjust scenarios towards a feasible and efficient production framework. • Full Dimension Efficient Faces consider positive weights for all model's variables. [ABSTRACT FROM AUTHOR]

Abstract: In this note we show, by means of several examples, that a directional distance function model cannot be matched with an additive model. Specifically, we show the difference between the directional slacks-based measure and the corresponding directional distance function. [Copyright &y& Elsevier]