Environmental Concerns in Water Pricing Policy: an Application of Data Envelopment Analysis (DEA)

25 p.

Uma metodologia para a análise do desempenho sustentável dos postos de revenda de combustível na cidade de Natal/RN, com o uso de data envelopment analysis-DEA

The increasing use of fossil fuels in line with cities demographic explosion carries out to huge environmental impact in society. For mitigate these social impacts, regulatory requirements have positively influenced the environmental consciousness of society, as well as, the strategic behavior of businesses. Along with this environmental awareness, the regulatory organs have conquered and formulated new laws to control potentially polluting activities, mostly in the gas stations sector. Seeking for increasing market competitiveness, this sector needs to quickly respond to internal and external pressures, adapting to the new standards required in a strategic way to get the Green Badge . Gas stations have incorporated new strategies to attract and retain new customers whom present increasingly social demand. In the social dimension, these projects help the local economy by generating jobs and income distribution. In this survey, the present research aims to align the social, economic and environmental dimensions to set the sustainable performance indicators at Gas Stations sector in the city of Natal/RN. The Sustainable Balanced Scorecard (SBSC) framework was create with a set of indicators for mapping the production process of gas stations. This mapping aimed at identifying operational inefficiencies through multidimensional indicators. To carry out this research, was developed a system for evaluating the sustainability performance with application of Data Envelopment Analysis (DEA) through a quantitative method approach to detect system s efficiency level. In order to understand the systemic complexity, sub organizational processes were analyzed by the technique Network Data Envelopment Analysis (NDEA) figuring their micro activities to identify and diagnose the real causes of overall inefficiency. The sample size comprised 33 Gas stations and the conceptual model included 15 indicators distributed in the three dimensions of sustainability: social, environmental and economic. These three dimensions were measured by means of classical models DEA-CCR input oriented. To unify performance score of individual dimensions, was designed a unique grouping index based upon two means: arithmetic and weighted. After this, another analysis was performed to measure the four perspectives of SBSC: learning and growth, internal processes, customers, and financial, unifying, by averaging the performance scores. NDEA results showed that no company was assessed with excellence in sustainability performance. Some NDEA higher efficiency Gas Stations proved to be inefficient under certain perspectives of SBSC. In the sequence, a comparative sustainable performance and assessment analyzes among the gas station was done, enabling entrepreneurs evaluate their performance in the market competitors. Diagnoses were also obtained to support the decision making of entrepreneurs in improving the management of organizational resources and promote guidelines the regulators. Finally, the average index of sustainable performance was 69.42%, representing the efforts of the environmental suitability of the Gas station. This results point out a significant awareness of this segment, but it still needs further action to enhance sustainability in the long term

Uma metodologia para a análise do desempenho sustentável dos postos de revenda de combustível na cidade de Natal/RN, com o uso de data envelopment analysis-DEA

The increasing use of fossil fuels in line with cities demographic explosion carries out to huge environmental impact in society. For mitigate these social impacts, regulatory requirements have positively influenced the environmental consciousness of society, as well as, the strategic behavior of businesses. Along with this environmental awareness, the regulatory organs have conquered and formulated new laws to control potentially polluting activities, mostly in the gas stations sector. Seeking for increasing market competitiveness, this sector needs to quickly respond to internal and external pressures, adapting to the new standards required in a strategic way to get the Green Badge . Gas stations have incorporated new strategies to attract and retain new customers whom present increasingly social demand. In the social dimension, these projects help the local economy by generating jobs and income distribution. In this survey, the present research aims to align the social, economic and environmental dimensions to set the sustainable performance indicators at Gas Stations sector in the city of Natal/RN. The Sustainable Balanced Scorecard (SBSC) framework was create with a set of indicators for mapping the production process of gas stations. This mapping aimed at identifying operational inefficiencies through multidimensional indicators. To carry out this research, was developed a system for evaluating the sustainability performance with application of Data Envelopment Analysis (DEA) through a quantitative method approach to detect system s efficiency level. In order to understand the systemic complexity, sub organizational processes were analyzed by the technique Network Data Envelopment Analysis (NDEA) figuring their micro activities to identify and diagnose the real causes of overall inefficiency. The sample size comprised 33 Gas stations and the conceptual model included 15 indicators distributed in the three dimensions of sustainability: social, environmental and economic. These three dimensions were measured by means of classical models DEA-CCR input oriented. To unify performance score of individual dimensions, was designed a unique grouping index based upon two means: arithmetic and weighted. After this, another analysis was performed to measure the four perspectives of SBSC: learning and growth, internal processes, customers, and financial, unifying, by averaging the performance scores. NDEA results showed that no company was assessed with excellence in sustainability performance. Some NDEA higher efficiency Gas Stations proved to be inefficient under certain perspectives of SBSC. In the sequence, a comparative sustainable performance and assessment analyzes among the gas station was done, enabling entrepreneurs evaluate their performance in the market competitors. Diagnoses were also obtained to support the decision making of entrepreneurs in improving the management of organizational resources and promote guidelines the regulators. Finally, the average index of sustainable performance was 69.42%, representing the efforts of the environmental suitability of the Gas station. This results point out a significant awareness of this segment, but it still needs further action to enhance sustainability in the long term

A spatiotemporal Data Envelopment Analysis (S-T DEA) approach:the need to assess evolving units

One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.

Input-orientated data envelopment analysis framework for measuring and decomposing economic, environmental and ecological efficiency : an application to OECD agriculture

This paper presents an input-orientated data envelopment analysis (DEA) framework which allows the measurement and decomposition of economic, environmental and ecological efficiency levels in agricultural production across different countries. Economic, environmental and ecological optimisations search for optimal input combinations that minimise total costs, total amount of nutrients, and total amount of cumulative exergy contained in inputs respectively. The application of the framework to an agricultural dataset of 30 OECD countries revealed that (i) there was significant scope to make their agricultural production systemsmore environmentally and ecologically sustainable; (ii) the improvement in the environmental and ecological sustainability could be achieved by being more technically efficient and, even more significantly, by changing the input combinations; (iii) the rankings of sustainability varied significantly across OECD countries within frontier-based environmental and ecological efficiency measures and between frontier-based measures and indicators.

Fuzzy data envelopment analysis for performance evaluation of an irrigation system

Sixteen irrigation subsystems of the Mahi Bajaj Sagar Project, Rajasthan, India, are evaluated and selection of the most suitable/best is made using data envelopment analysis (DEA) in both deterministic and fuzzy environments. Seven performance-related indicators, namely, land development works (LDW), timely supply of inputs (TSI), conjunctive use of water resources (CUW), participation of farmers (PF), environmental conservation (EC), economic impact (EI) and crop productivity (CPR) are considered. Of the seven, LDW, TSI, CUW, PF and EC are considered inputs, whereas CPR and EI are considered outputs for DEA modelling purposes. Spearman rank correlation coefficient values are also computed for various scenarios. It is concluded that DEA in both deterministic and fuzzy environments is useful for the present problem. However, the outcome of fuzzy DEA may be explored for further analysis due to its simple, effective data and discrimination handling procedure. It is inferred that the present study can be explored for similar situations with suitable modifications.

Efficiency assessment of electricity power generation on Ireland’s Single Electricity Market by Data Envelopment Analysis

The efficiency of generation plants is an important measure for evaluating the operating performance. The objective of this paper is to evaluate electricity power generation by conducting an All-Island-Generator-Efficiency-Study (AIGES) for the Republic of Ireland and Northern Ireland by utilising a Data Envelopment Analysis (DEA) approach. An operational performance efficiency index is defined and pursued for the year 2008. The economic activities of electricity generation units/plants examined in this paper are characterized by numerous input and output indicators. Constant returns to scale (CRS) and variable returns to scale (VRS) type DEA models are employed in the analysis. Also a slacks based analysis indicates the level of inefficiency for each variable examined. The findings from this study provide a general ranking and evaluation but also facilitate various interesting efficiency comparisons between generators by fuel type.

Avaliação de desempenho dos municípios portugueses pelo método data envelopment analysis

Dissertação de mest., Economia Regional e Desenvolvimento Local, Faculdade de Economia, Univ. do Algarve, 2011

Manutenção preventiva ou manutenção corretiva em linhas aéreas de média tensão? Utilização do data envelopment analysis como auxiliar de gestão dos ativos técnicos de manutenção

O uso de Data Envelopment Analysis (DEA) no setor de distribuição de energia elétrica tem dado origem à publicação de vários artigos científicos. No geral, estes artigos focam-se na comparação da eficiência das empresas de distribuição de eletricidade. Na generalidade dos artigos, o tratamento da informação tem sido predominantemente descritivo e classificatório, sem focar no processo de transformação. Em contraste, o trabalho que se apresenta aqui pretende mostrar as potencialidades do DEA na análise de variáveis do processo de transformação e procura explorar o seu potencial para a identificação dos programas e intervenções que contribuem para a melhoria efetiva no processo de distribuição de eletricidade. É nossa convicção que as avaliações de natureza formativa, com fins de aprendizagem, são mais eficazes do que os estudos sumativos porque contribuem para uma melhor compreensão das estruturas e processos, sendo portanto mais adequadas para contribuir para a melhoria do desempenho. Neste trabalho, apresenta-se uma questão importante no contexto da análise DEA: a de investigar, se as diferenças de eficiência são devidas a um programa específico de gestão ou às características de conceção. Para o efeito, o estudo recorre a dois métodos diferentes para realizar este tipo de análise. Em primeiro lugar, aplicamos a estatística de rank de Mann-Whitney aos scores do DEA, a fim de avaliar a significância estatística das diferenças observadas entre um programa de tratamento e o programa de controlo. Em segundo lugar, procedemos a uma análise dinâmica com o Índice de Produtividade de Malmquist, a fim de estudar o impacto da introdução de uma nova tecnologia num grupo de unidades. O estudo de caso desenvolvido centra-se na avaliação do desempenho de linhas de média tensão afetas a uma das regiões de serviço de uma empresa de distribuição de energia elétrica, regulada pelo Sistema Público de Distribuição de Energia em Portugal (ERSE). Os resultados do estudo de caso mostram que a aplicação do DEA tem um grande potencial para contribuir para a melhoria dos processos e deve ser explorado noutros contextos.

O uso do data envelopment analysis para avaliação e melhoria de desempenho no setor bancário: estudo de caso

O presente estudo aborda o uso do Data Envelopment Analysis (DEA) para avaliar e melhorar o desempenho no setor bancário. Consiste num estudo de caso aplicado a um dos maiores bancos portugueses. O seu objetivo, é avaliar a eficiência relativa das 333 agências bancárias que formam um dos dois departamentos comerciais do banco. Pretende-se identificar boas práticas e verificar a sua aplicabilidade nas unidades menos eficientes por forma a contribuir para a melhoria do desempenho global da instituição. Ao mesmo tempo, comparam-se os resultados de eficiência obtidos com o desempenho das unidades de negócio no cumprimento dos seus objetivos comerciais. Procura-se, assim, analisar a eventual existência de correlação entre eficiência e eficácia, ou seja, se as agências bancárias mais eficientes são também as mais eficazes. Para o efeito, é construído um modelo DEA que, considera em simultâneo, vários inputs e outputs. No modelo, as variáveis de input agregam os custos das unidades de negócio e as variáveis de output, os seus principais proveitos e alguns dos aspetos estratégicos que o banco pretende maximizar. Os resultados obtidos, identificam não só as agências bancárias menos eficientes, como assinalam aquelas que sendo semelhantes e eficientes, lhes podem servir de referência para a melhoria do seu desempenho. Tendo em conta, o caráter formativo que se pretende para o estudo, e de modo a facilitar a aceitação pelos decisores, procura-se verificar a exequibilidade das propostas apresentadas. O documento conclui pela existência, nas unidades de negócio analisadas, de uma correlação positiva fraca entre eficiência e eficácia, ainda assim estatisticamente significante. Por último, assinala a importância da metodologia DEA, enquanto medida de complementaridade de outras técnicas de controlo de gestão, em particular nas organizações que adotam a gestão por objetivos.

Using data envelopment analysis to assess the efficiency of social security systems: the case of income protection in old age

As the number of pensioners in Europe rises relative to the number of people in employment, the gap between the contributions and the benefit levels increases, and consequently ensuring adequate pensions on a sustainable basis has become a major challenge. This study aims to explore the potential of using the Data Envelopment Analysis (DEA) technique in order to access the efficiency of the income protection in old age, one of the most important branches of Social Security. To this effect, we collected data from the 27 European Union Member States regarding this branch. Our results show important differences among the Member States and stress the importance of identifying best practices to achieve more adequate, sustainable and modernised pension systems. Our results also highlight the importance of using DEA as a decision support tool for policy makers.

Avaliação da efetidade dos países da OCDE no tratamento do cancro: uma aplicação do data envelopment analysis

Dissertação de Mestrado, Gestão de Unidades de Saúde, Faculdade de Economia, Universidade do Algarve, 2015

Análise exploratória do nível de eficiência dos hospitais portugueses através do Data Envelopment Analysis

Dissertação de mestrado, Contabilidade, Faculdade de Economia, Universidade do Algarve, 2014

Evaluating the efficiencies of university faculties : adjusted data envelopment analysis

Efficiency measurement is at the heart of most management accounting functions. Data envelopment analysis (DEA) is a linear programming technique used to measure relative efficiency of organisational units referred in DEA literature as decision making units (DMUs). Universities are complex organisations involving multiple inputs and outputs (Abbott & Doucouliagos, 2008). There is no agreement in identifying and measuring the inputs and outputs of higher education institutes (Avkiran, 2001). Hence, accurate efficiency measurement in such complex institutes needs rigorous research.

Prior DEA studies have investigated the application of the technique at university (Avkiran, 2001; Abbott & Doucouliagos, 2003; Abbott & Doucouliagos, 2008) or department/school (Beasley, 1990; Sinuany-Stern, Mehrez & Barboy, 1994) levels. The organisational unit that has control and hence the responsibility over inputs and outputs is the most appropriate decision making unit (DMU) for DEA to provide useful managerial information. In the current study, DEA has been applied at faculty level for two reasons. First, in the case university, as with most other universities, inputs and outputs are more accurately identified with faculties than departments/schools. Second, efficiency results at university level are highly aggregated and do not provide detail managerial information.

Prior DEA time series studies have used input and output cost and income data without adjusting for changes in time value of money. This study examines the effects of adjusting financial data for changes in dollar values without proportional changes in the quantity of the inputs and the outputs. The study is carried out mainly from management accounting perspective. It is mainly focused on the use of the DEA efficiency information for managerial decision purposes. It is not intended to contribute to the theoretical development of the linear programming model. It takes the view that one does not need to be a mechanic to be a good car driver.

The results suggest that adjusting financial input and output data in time series analysis change efficiency values, rankings, reference set as well as projection amounts. The findings also suggest that the case University could have saved close to $10 million per year if all faculties had operated efficiently. However, it is also recognised that quantitative performance measures have their own limitations and should be used cautiously.

Factors affecting the technical efficiency of production of the Brazilian banking system : a comparison of four statistical models in the context of data envelopment analysis

This paper uses an output oriented Data Envelopment Analysis (DEA) measure of technical efficiency to assess the technical efficiencies of the Brazilian banking system. Four approaches to estimation are compared in order to assess the significance of factors affecting inefficiency. These are nonparametric Analysis of Covariance, maximum likelihood using a family of exponential distributions, maximum likelihood using a family of truncated normal distributions, and the normal Tobit model. The sole focus of the paper is on a combined measure of output and the data analyzed refers to the year 2001. The factors of interest in the analysis and likely to affect efficiency are bank nature (multiple and commercial), bank type (credit, business, bursary and retail), bank size (large, medium, small and micro), bank control (private and public), bank origin (domestic and foreign), and non-performing loans. The latter is a measure of bank risk. All quantitative variables, including non-performing loans, are measured on a per employee basis. The best fits to the data are provided by the exponential family and the nonparametric Analysis of Covariance. The significance of a factor however varies according to the model fit although it can be said that there is some agreements between the best models. A highly significant association in all models fitted is observed only for nonperforming loans. The nonparametric Analysis of Covariance is more consistent with the inefficiency median responses observed for the qualitative factors. The findings of the analysis reinforce the significant association of the level of bank inefficiency, measured by DEA residuals, with the risk of bank failure.