Technical efficiency of production in agricultural research: a case study.

We define and model research production at Embrapa, the major Brazilian institution responsible for applied agricultural research in the country. The main theoretical framework we use is data envelopment analysis. We explore the ecoomic interpretation of these models to assess cost and technical efficiencies for the production of agricultural research in Brazil. Efficiency results are then compared with alternative measures defined via a stochastic frontier

The role of multiplier bounds in fuzzy data envelopment analysis

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The non-Archimedean epsilon ε is commonly considered as a lower bound for the dual input weights and output weights in multiplier data envelopment analysis (DEA) models. The amount of ε can be effectively used to differentiate between strongly and weakly efficient decision making units (DMUs). The problem of weak dominance particularly occurs when the reference set is fully or partially defined in terms of fuzzy numbers. In this paper, we propose a new four-step fuzzy DEA method to re-shape weakly efficient frontiers along with revisiting the efficiency score of DMUs in terms of perturbing the weakly efficient frontier. This approach eliminates the non-zero slacks in fuzzy DEA while keeping the strongly efficient frontiers unaltered. In comparing our proposed algorithm to an existing method in the recent literature we show three important flaws in their approach that our method addresses. Finally, we present a numerical example in banking with a combination of crisp and fuzzy data to illustrate the efficacy and advantages of the proposed approach

Pay for performance in health care: a new best practice tariff-based tool using a log-linear piecewise frontier function and a dual–primal approach for unique solutions

Health care systems worldwide have faced a problem of resources scarcity that, in turn, should be allocated to the health care providers according to the corresponding population needs. Such an allocation should be as much as effective and efficient as possible to guarantee the sustainability of those systems. One alternative to reach that goal is through (prospective) payments due to the providers for their clinical procedures. The way that such payments are computed is frequently unknown and arguably far from being optimal. For instance, in Portugal, public hospitals are clustered based on criteria related to size, consumed resources, and volume of medical acts, and payments associated with the inpatient services are equal to the smallest unitary cost within each cluster. First, there is no reason to impose a single benchmark for each inefficient hospital. Second, this approach disregards dimen sions like quality (and access) and the environment, which are paramount for fair comparisons and benchmarking exercises. This paper proposes an innovative tool to achieve best-practices tariff. This tool merges both quality and financial sustain ability concepts, attributing a hospital-specific tariff that can be different from hospital to hospital. That payment results from the combination of costs related to a set of potential benchmarks, keeping quality as high as possible and higher than a user-predefined threshold, and being able to generate considerable cost savings. To obtain those coefficients we propose and detail a log-linear piecewise frontier function as well as a dual–primal approach for unique solutions.info:eu-repo/semantics/publishedVersio

Embrapa's evaluation and awards system: selected papers.

This paper presents basic conceptsw and operational aspects of Performance Evaluation system and Premiums fos outstanding resuilts irnplemented by Embrapa in 1996. This system aims to increase performance of research units, research teams and employess in gerenal, rewarding the more productive members of the institution. This system procedure for research units; e) team and individual empoyee evaluation; and, d) team and individual reward procedure. O presente trabalho apresenta conceitos e aspectos operacionais do Sistema de Avaliação e Premiação por Resultados da Embrapa, implantado em 1996. O sistema objetiva elevar o desempenho das unidades de pesquisa, das equipes e empregados da Empresa e recompensar os mais produtivos. O sistema e constituido por 4 componentes: a) avaliação de unidades; b) premiação de unidades; c) Avaliação de equipes e empregados; e d) premiação de equipes e empregados

Robust optimization in data envelopment analysis: extended theory and applications.

Performance evaluation of decision-making units (DMUs) via the data envelopment analysis (DEA) is confronted with multi-conflicting objectives, complex alternatives and significant uncertainties. Visualizing the risk of uncertainties in the data used in the evaluation process is crucial to understanding the need for cutting edge solution techniques to organizational decisions. A greater management concern is to have techniques and practical models that can evaluate their operations and make decisions that are not only optimal but also consistent with the changing environment. Motivated by the myriad need to mitigate the risk of uncertainties in performance evaluations, this thesis focuses on finding robust and flexible evaluation strategies to the ranking and classification of DMUs. It studies performance measurement with the DEA tool and addresses the uncertainties in data via the robust optimization technique. The thesis develops new models in robust data envelopment analysis with applications to management science, which are pursued in four research thrust. In the first thrust, a robust counterpart optimization with nonnegative decision variables is proposed which is then used to formulate new budget of uncertainty-based robust DEA models. The proposed model is shown to save the computational cost for robust optimization solutions to operations research problems involving only positive decision variables. The second research thrust studies the duality relations of models within the worst-case and best-case approach in the input \u2013 output orientation framework. A key contribution is the design of a classification scheme that utilizes the conservativeness and the risk preference of the decision maker. In the third thrust, a new robust DEA model based on ellipsoidal uncertainty sets is proposed which is further extended to the additive model and compared with imprecise additive models. The final thrust study the modelling techniques including goal programming, robust optimization and data envelopment to a transportation problem where the concern is on the efficiency of the transport network, uncertainties in the demand and supply of goods and a compromising solution to multiple conflicting objectives of the decision maker. Several numerical examples and real-world applications are made to explore and demonstrate the applicability of the developed models and their essence to management decisions. Applications such as the robust evaluation of banking efficiency in Europe and in particular Germany and Italy are made. Considering the proposed models and their applications, efficiency analysis explored in this research will correspond to the practical framework of industrial and organizational decision making and will further advance the course of robust management decisions