Modified Goal Programming Approach for Improving the Discrimination Power and Weights Dispersion

Abstract Data envelopment analysis (DEA) is a technique based on linear programming (LP) to measure the relative efficiency of homogeneous units by considering inputs and outputs. The lack of discrimination among efficient decision making units (DMUs) and unrealistic inputoutputs weights have been known as the drawback of DEA. In this paper the new scheme based on a goal programming data envelopment analysis (GPDEA) are developed to moderate the homogeneity and reasonability of weights distribution by using of facet analysis On GPDEA (GPDEA-CCR and GPDEA-BCC) models. These modifications are done by considering the lower bounds for each individual inputs and outputs weights in standard CCR model and an upper bound just for free variable of standard BCC model. In the both of the cases the mentioned modification preserved the inputs and outputs weights from zero value. The modified GPDEA models also improve the discrimination power of DEA. The advantages of each modified GPDEA-CCR and GPDEA-BCC models are shown by some examples

Efficiency Analysis of Healthcare System in Lebanon Using Modified Data Envelopment Analysis

The inflow of refugees from Syria into Lebanon necessitates a robust and efficient healthcare system in Lebanon to withstand the growing demand for healthcare service. For this purpose, we evaluate the efficiency of healthcare system in Lebanon from 2000 through 2015 by applying a modified data envelopment analysis (DEA) model. We have selected four output variables: life expectancy at birth, maternal mortality ratio, infant mortality rate, and newly infected with HIV and two input variables: total health expenditure (% of GDP) and number of hospital beds. The findings of the paper show improvement in the efficiency of the healthcare system in Lebanon after the widespread of the health system reform in 2005. It also shows that reduction in health expenditure does not necessarily reduce efficiency if operational and technical aspect of the healthcare system is improved. The study infers that the healthcare system in Lebanon is capable of withstanding the increase in health demand provided further resources are made available and the existing technical and operational improvement are maintained

Egoists dilemma with fuzzy data

In this paper, we investigate the problems of consensus-making among individuals or organizations with multiple criteria for evaluating performance when the players are supposed to be egoistic and the score for each criterion for a player is supposed to be fuzzy number. We deal with problems with fuzzy parameters from the viewpoint of experts' imprecise or fuzzy understanding of the nature of parameters in a problem-formulation process. Egoistic means that each player sticks to his/her superiority regarding the criteria. The concept that is developed in optimization leads the problem to a dilemma called 'egoists dilemma'. We examine this dilemma using cooperative fuzzy game theory and propose a solution. The scheme developed in this paper can also be applied to attaining fair cost allocations as well as benefit-cost distributions for fuzzy data

Improving weak efficiency frontier in a variable returns to scale stochastic data envelopment analysis model

The conventional stochastic data envelopment analysis (SDEA) model suffers from biased efficiency scores for units located at the weak efficient frontier or compared to the weak frontier. This study modifies the weak efficient hyperplane(s) while maintaining the general production function by restricting the gradients of weak efficient hyperplanes in the original model using facet analysis. Empirical analysis on environmental efficiency of sustainable development goals validates the results of the modification. Results of the modified model compared to the conventional model show change in efficiency scores of weak efficient units and those compared to the weak part of the frontier while the efficiency scores of the strong efficient frontier remain the same. Furthermore, the proposed model shows greater discriminatory power compared to the conventional model, hence, providing a reliable benchmark and improvement strategy post efficiency analysis

Dual Efficiency and Productivity Analysis of Renewable Energy Alternatives of OECD Countries

This paper examines the dual efficiency of bioenergy, renewable hydro energy, solar energy, wind energy, and geothermal energy for selected OECD countries through an integrated model with energy, economic, environmental, and social dimensions. Two questions are explored: Which renewable energy alternative is more dual efficient and productive? Which renewable energy alternative is best for a particular country? Data envelopment analysis (DEA) is used for the efficiency evaluation, and the global Malmquist productivity index is applied for productivity analysis. Results indicate bioenergy as the most efficient renewable energy alternative with a 20% increase in average efficiency in 2016 compared to 2012. Renewable hydro energy, wind energy, and solar energy show a 17.5%, 16%, and 11% increase, respectively. The average efficiency growth across all renewable energy alternatives signifies major advancement. Country performance in renewable energy is non-monolithic; therefore, they should customize their renewable energy portfolio accordingly to their strengths to enhance renewable energy efficiency. Renewable hydro appears to have the most positive productivity change in 2016 compared to 2012, while solar energy regressed in productivity due to its scale inefficiency. All renewable energy alternatives have relatively equal average pure efficiency change. The positive trend in efficiency and productivity provides an incentive for policy makers to pursue further development of renewable energy technologies with a focus on improving scale efficiency

Estimating efficiency of Directive 2011/24/EU cross-border healthcare in member states

Aim: Directive 2011/24/EU on patients’ rights in cross-border healthcare facilitates EU citizens' access to and reimbursement for healthcare provided or prescribed in a member state other than the member state of affiliation. Materials &amp; methods: The efficiency of cross-border healthcare policy is evaluated using data envelopment analysis of relevant items in Eurobarometer Survey on Safety and Quality of Care and Patients’ Rights in the EU. Results: Our study shows policy inefficiency in 52% of the 25 EU member states included in the analysis. Addressing difficulties patients encounter while seeking reimbursement from their national health service or health insurer and reducing the number of adverse events patients experience when receiving healthcare improves policy efficiency. Conclusion: Our findings confirm that there is country-level variation in cross-border healthcare policy efficiency. </jats:p