Practice Frontier Research Articles

Direct mailing decisions based on the worst and best practice cross-efficiency evaluations

The problem argued in the literature of direct mailing decisions generally contains three parts: 1 forecasting customers' future purchase/non-purchase responses; 2 evaluating the effectiveness of various strategies for increasing customers purchase responses; 3 prioritising the customers in terms of their values. A significant body of the literature has been dedicated to the first two components, and in particular, to purchase/non-purchase prediction modelling. However, in the current paper, we do not address these two components, but rather we focus on the third component. To this end, data envelopment analysis DEA technique and particularly cross-efficiency formulation of the best practice frontier Charnes, Cooper and Rhodes CCR Charnes et al., 1978 BPF-CCR is used to determine those customers who should be put on the first priorities of marketing mailing list. In addition, the cross-efficiency formulation of worst practice frontier CCR WPF-CCR is developed to exclude the worst customers from mailing list and save the mailing expenses for the best practice ones. Using a numerical example, the application of the proposed model is demonstrated.

English

  This paper is a first attempt to examine efficiency in the Zimbabwean hospital sector using the non-parametric data envelopment analysis (DEA) methodology. The paper evaluates whether for-profit hospitals are significantly more efficient than non-profit hospitals in order to shed some light on the role of profit incentives as implied by the theory of property rights. DEA findings revealed that there was a marked deviation of efficiency scores from the best practice frontier with for-profit hospitals having the highest mean overall technical efficiency (OTE) score of 61.4%. The mean OTE scores for mission and public hospitals were 35% and 50.3% respectively. Evidence from the second stage, Tobit model suggested that while both for-profit hospitals and government hospitals were both important in influencing efficiency, for-profit hospitals had a higher marginal mean efficiency score than government hospitals.   Key words: Profit incentives, data envelopment analysis, allocative efficiency, overall technical efficiency, pure technical efficiency, scale efficiency, Censored Tobit model.

A DEA Approach to Performance-Based Budgeting of Formula One Constructors

This article assesses the relative efficiency of teams participating in Formula One (F1) World Constructors’ Championship. A nonparametric method based on data envelopment analysis (DEA) has been used. The aim is to measure each constructor’s performance, comparing its efficiency relative to all other competing constructors. The study uses financial and performance data to assess the proximity of the constructors to the best practices frontier. The analysis has been made considering the results of the 2003, 2006, 2008, 2010, and 2011 F1 seasons. In order to create a parsimonious DEA model, a variable screening method for dimensionality reduction is considered. The results indicate that, generally, a substantial reduction should be made to the constructors’ budget over the seasons in order to be efficient as compared to the identified benchmarks. In addition, scale efficiency reveals that most constructors operate below their most productive scale size.

Productivity Growth and Efficiency Measurements in Fuzzy Environments with an Application to Health Care

Health care organizations must continuously improve their productivity to sustain long-term growth and profitability. Sustainable productivity performance is mostly assumed to be a natural outcome of successful health care management. Data envelopment analysis (DEA) is a popular mathematical programming method for comparing the inputs and outputs of a set of homogenous decision making units (DMUs) by evaluating their relative efficiency. The Malmquist productivity index (MPI) is widely used for productivity analysis by relying on constructing a best practice frontier and calculating the relative performance of a DMU for different time periods. The conventional DEA requires accurate and crisp data to calculate the MPI. However, the real-world data are often imprecise and vague. In this study, the authors propose a novel productivity measurement approach in fuzzy environments with MPI. An application of the proposed approach in health care is presented to demonstrate the simplicity and efficacy of the procedures and algorithms in a hospital efficiency study conducted for a State Office of Inspector General in the United States.

Remeasuring the HDI by Data Envelopement Analysis

The measurement of human development has a potentially strong impact on how the development gap is viewed and on the formulation of new policies. Therefore correct and fair measurement is of great importance. In this paper, we develop an algorithm to compute comprehensive differentiation rules suitable for measuring human development. We used models from Data Envelopment Analysis (DEA) literature to compare performance in a multiple output setting. The models were evaluated by empirically re-estimating the human development index (HDI). The most notable advantages of DEA models are that they endogenously construct a non-linearly arranged set of best practice countries and the weights of each indicator entering the HDI is endogenously determined based on an optimization calculus. These weights are allowed to vary thereby accounting for cross-sectional heterogeneity. While country clusters are identified by their similarity, some interesting outliers can also be singled out using DEA. Such outliers are either best practice frontier countries or countries that are locked in underdevelopment trap.

EFFICIENCY OF NON-LIFE INSURANCE IN INDONESIA

It is a fact that financial institutions among Asian countries, especially Indonesia, have been dominated by commercial banks. In addition, an insurance market share is only 10 percent of the financial market. Yet, the insurance industry is an important partner for the banking industry. This function is to guarantee the risk of banks in distributing credit and supporting the national economy through the community's fund. This paper evaluates the relative efficiency of 23 Non Life Insurance companies in Indonesia, using Data Envelopment Analysis (DEA) model. DEA is a management evaluation tool that assists in identifying the most efficient and inefficient decision-making units (DMUs) in the best practice frontier. Empirical results show that bigger insurance companies are found to be more efficient than smaller firms. Moreover, companies with captive market and the company's group with non-captive market have relatively the same result. These findings are new empirical contributions to efficiency literature of the insurance industry. The paper also provides policy implications for the Indonesian insurance sector.

Technical Progress and Regress in Norwegian Salmon Farming: A Malmquist Index Approach

Abstract In this study we measure change in total factor productivity for production of Atlantic salmon in Norway from 2001 to 2008. The Malmquist Productivity Index (MPI) is used. Our results demonstrate that total factor productivity change measured by MPI increased from 2001 to 2005, but thereafter regressed. This is due to a regress in the technical change component of the MPI. The efficiency change component is as strong as before. We interpret this result as an indication that the industry has reached a level of technological sophistication from where it is difficult to make substantial progress. For an individual producer it may still be possible to improve efficiency by catching up relative to the best practice frontier. When this possibility is exhausted, the total factor productivity change for the industry may come to a halt. JEL Classification Codes: Q22, O33, D24, C43.

Autres séances

The lack of access to water and sanitation services (WSS) of a considerable share of the world population has been challenging the international community for decades. The proposal of the Millennium Development Goals and, later on, the Sustainable Development Goals (SDGs) by the United Nations (UN) intended to act as a blueprint to achieve a more equitable future for all and, in the case of WSS, “Ensure the availability and sustainable management of water and sanitation for all” (SDG 6). However, the current global pandemic further emphasised the importance of WSS, given the increasing asymmetries faced by billions worldwide, and the gaps between high-income and low- and middle-income nations. For this reason, understanding whether low- and middle-income countries have been approximating towards or deviating from the SDG 6 is crucial to derive and communicate key information for the sake of improved public governance and political decision-making. In this paper, we extend a state-of-the-art methodology based on data envelopment analysis for assessing the convergence of the low- and middle-income UN Member States regarding the SDG 6 between 2016 and 2017. We find that, on average, not only did the Member States converge by decreasing the performance spread and the gap between the best and worst practice frontiers, but also the Level of water stress: freshwater withdrawal as a proportion of available freshwater resources was the indicator in which the majority exhibited the worst performances. In the end, we derive possible policy implications, which, as our results show, are aligned with the recent UN reports on the subject.

MEASURING EFFICIENCY IN TRANSPORT: THE STATE OF THE ART OF APPLYING DATA ENVELOPMENT ANALYSIS / TRANSPORTO EFEKTYVUMO NUSTATYMAS: NAUJAUSI DUOMENYS ATLIEKANT PAVIRŠINĘ DUOMENŲ ANALIZĘ / ОПРЕДЕЛЕНИЕ ЭФФЕКТИВНОСТИ ТРАНСПОРТА: НОВЫЕ ДАННЫЕ ПРИ ВЫПОЛНЕНИИ АНАЛИЗА СРЕДЫ ФУНКЦИОНИРОВАНИЯ

Data Envelopment Analysis (DEA) is a non-parametric linear programming method used for determining the efficiency of a set of companies as compared to the best practice frontier. It can be employed to analyze private, public or non-profit organizations. The application of the method in the transport sector is wide-spread, especially in the evaluation of airports, ports, railways and urban transport companies. The present paper is aimed at giving a review of how DEA is applied in the transport sector with a special emphasis on the inputs and outputs selected in the DEA models employed in different fields. For this reason, the author has compiled data from 69 DEA applications found or reported in literature, investigated their characteristics and the field of applying them along with the inputs and outputs used. Santrauka Paviršinė duomenų analizė (Data Envelopment Analysis, DEA)—neparametrinis linijinio programavimo metodas, taikomas siekiant nustatyti įmonių grupės efektyvumą, lyginant jį su geriausiais praktiniais laimėjimais. Jis gali būti įgyvendinamas vertinant privačių, valstybinių ir ne pelno siekiančių organizacijų veiklą. Šis metodas plačiai paplitęs transporto sektoriuje, ypač vertinant oro uostų, geležinkelių ir viešojo transporto organizacijas. Straipsnyje nagrinėjama, kaip DEA metodas taikomas transporto sektoriuje, ir pabrėžiamos įdėtos pastangos bei pasiekti rezultatai, naudojant DEA modelius skirtingose srityse. Surinkti duomenys iš DEA modelių ir išnagrinėtos jų charakteristikos. Резюме Анализ среды функционирования (Data Envelopment Analysis – DEA) – это метод сравнительного анализа деятельности различных сложных экономических и социальных систем. Метод анализа среды функционирования охватывает гораздо более широкий спектр понятий и возможностей, чем просто вычисление и анализ эффективности сложных объектов. Метод имеет глубокую связь с математической экономикой, системным анализом, многокритериальной оптимизацией, он позволяет строить многомерное экономическое пространство, находить оптимальные пути развития в нем, вычислять важнейшие количественные и качественные характеристики поведения объектов, моделировать различные ситуации. Этот метод может быть использован при оценке деятельности частных и государственных предприятий и организаций. Метод также применяется в транспортной сфере для оценки деятельности аэропортов, предприятий железнодорожного и общественного транспорта. В статье исследуется применение метода анализа среды функционирования в транспортной сфере. Анализируются данные, характеристики и результаты различных исследований с применением метода анализа среды функционирования.

Productivity growth and biased technological change in hydroelectric dams

This paper analyses productivity growth and the nature of technical change in a sample of Portuguese hydroelectric generating plants over the period 2001 to 2008. In a first step, we employ the Luenberger productivity indicator to estimate and decompose productivity change. A Malmquist productivity index is also used for a comparative purpose. The results paint a picture of mixed productivity performance in the Portuguese energy sector. The first decomposition underlines that, in average, the productivity variation is explained by the technological change. Then, in a second step, we analyse the nature of this technical change by using the recent concept of parallel neutrality (Briec et al., 2006). We observe a global shift in the best practice frontier as well as in the evidence of input bias in technical change.

Agricultural efficiency under resource scarcity in Uzbekistan: A Data Envelopment Analysis

Water scarcity and land degradation increases led to a sharp rise in input resource’s costs. These developments make it increasingly difficult for agricultural farms to produce according to the demand for food and other commodities, especially owing a rapid population growth. The present study aims to focus on scarce resource use in the agricultural production of the Zarafshan valley by means of the efficiency analysis. A DEA model is estimated to investigate the farm level efficiency levels with respect to the use of the limited resources available to the farmers. By the application of linear programming methods a ‘best practice frontier is estimated’, classifying farms on the frontier as efficient and others as inefficient with respect to different scales. Technical and allocative efficiencies are calculated relative to the frontier. Results shows input resources are not used efficiently and a great majority of farms could effectively reduce considerable amounts of input use by still producing the same output.

Incorporating undesirable outputs into the best and worst practice DEA models for customers scoring

Determining the profitability of customers and ranking them is an issue that has been frequently studied in the past decades. To differentiate marketing activities towards the profitable segments of customers from the non-profitable ones, it is necessary to separate customers into different categories (Jonker et al., 2004). To this end, in this paper, data envelopment analysis (DEA), as a multiple criteria decision making tool is used to evaluate customers and classify them as good and bad customers. Particularly, the objective of this paper is to use the best practice frontier (BPF) DEA in the presence of undesirable outputs to recognise good customers. As well, the worst practice frontier (WPF) DEA in the presence of undesirable outputs is developed to find bad customers and save the marketing expenses for the best practice ones. A case study demonstrates the use of the proposed models.

DEA-based hypothesis tests for comparing two groups of decision making units

In this paper, we develop five statistical tests to compare the efficiencies of different groups of DMUs. We consider a data generating process (DGP) that models the deviation of the output from the best practice frontier as the sum of two components, a one-sided inefficiency term and a two-sided random noise term. We use simulation to evaluate the performance of the five tests against the Banker tests ( Banker, 1993) that were designed for DGPs containing a single one-sided error term. It is found that while the Banker tests are very effective when efficiency dominates noise, the tests developed in this paper perform better than the Banker tests when noise levels are significant.

DEA models for identifying sensitive performance measures in container port evaluation

In the container port performance evaluation, the heterogeneity of input or output measures often exist owing to non-controllable external factors such as geographical location, regional economy, political systems and so on. Therefore, it becomes imperative to investigate the individual input or output measures so as to identify their specific impact on the efficiency of a port. In addition, the purpose of performance evaluation cannot be a mere exercise of candidate ranking. The purpose of this article is to study ways of retaining efficiency and improving on inefficiency. The article utilizes the conventional Data Envelopment Analysis model to test the sensitivity of the individual input and output of a decision-making unit (DMU). For an efficient DMU, we measure how much an input can be increased, or an output decreased, without changing its efficiency status. For an inefficient DMU, we measure how much an input should be decreased, or an output increased, to make it achieve the best practice frontier. The new approaches are applied to the efficiency analysis of 77 global container ports. The results indicate that the number of berths and the capital deployed are the most sensitive measures impacting performance of most container ports. The analysis also reveals that container ports located in different continents behave differently.

Efficiency of the health extension programme in Tigray, Ethiopia: a data envelopment analysis

BackgroundSince 2004, the government of Ethiopia has made a bold decision to strengthen and expand its primary health care system by launching the Health Extension Program (HEP). While the scaling up of the HEP is necessary to achieve the aim of universal access to primary health care, close attention should be paid to the performance of the program. Using a data envelopment analysis this study aimed at (i) to estimate the technical efficiency of a sample of health posts in rural Tigray, ii) to identify those factors which might be explaining the efficiency results.MethodsEfficiency was measured using a data envelopment analysis model. A Tobit model was performed to identify factors associated with efficiency. Seven rural districts (out of 35) were purposely chosen. Input/output information was collected from the database of the Tigray Health Bureau during July 2007-June 2008. Information was also collected on environmental factors that might influence the efficiency outcomes through a structured questionnaire from the correspondent district health officers.ResultsAnalysis was based on data from 60 health posts. The mean scores for technical and scale efficiency were 0.57 (SD = 0.32) and 0.95 (SD = 0.11) respectively. Out of the 60 health posts, 15 (25.0%) were found to be technically efficient constituting the best practice frontier. Thirty eight (63.3%) were operating at their most productive scale size. In the regression analysis, none of the variables was significantly associated with the efficiency outcome.ConclusionThere is a need to review the management of the health information system in the region. The findings have also revealed that only a quarter of the health posts are working efficiently and pointed the need for improvement. A closer monitoring of the health extension programme is required in order to achieve the best possible performance.

A multi-subsystem fuzzy DEA model with its application in mutual funds management companies’ competence evaluation

Abstract This paper proposes a multi-subsystem fuzzy data envelopment analysis (MFDEA) model to evaluate mutual funds management companies’ core competence which is apparently characterized with both qualitative factors and quantitative factors. As the first attempt of core competence analysis of mutual funds management companies in a financial market, we evaluate how close the mutual funds management companies are to the best practices frontier, and analyze how they should manage their funds. An empirical study of 32 mutual funds management companies in China leads to a meaningful analysis and some management insights. The approach can also be applied to many other hard assessment and evaluation problems.

Evaluation of Potential of Innovations: A DEA-Based Application to U.S. Photovoltaic Industry

We present a model-based approach for evaluating the potential of innovations occurring in various stages of the industry value chain. The realization of the innovation's potential is conceptualized as the ability of the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">de</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">novo</i> firm to achieve the maximum possible efficiency in translating inputs into cost-reducing output. We apply recent developments from data envelopment analysis to measure the innovation's potential in terms of its relative efficiency with respect to a best practices frontier. We then present a conceptual framework to classify and identify the determinants related to technological and organizational variables in realizing the potential of innovations. Finally, we demonstrate the application of this model-based approach to conduct analysis of the potential of innovations in the U.S. photovoltaic and related systems manufacturing industry.

Productivity and efficiency change and shareholder value: evidence from the Spanish banking sector

Productivity change and shareholder value have been analysed in the banking sector in the last few years, although it should be noted that these two important aspects have been studied separately. In this regard, the main contribution of our study is to link these two lines of research by verifying whether those banks characterized by higher levels of efficiency and productivity change have a higher shareholder value. To measure changes in efficiency and productivity we use the Malmquist nonparametric technique, which is calculated from Data Envelopment Analysis (DEA) linear programming approach. The Malmquist total factor productivity index enables separation of the ‘catching up’ effect, i.e. changes over time in technical efficiency, from ‘technological change’, i.e. the shift of best practice frontier over time due to technological progress. Our results for a sample of listed Spanish banks in the period 2000 to 2004 confirm that those banks with higher efficiency and productivity changes have a higher shareholder value, even after controlling for the impact of traditional measures of performance, such as return on assets.

Productivity effects of environmental performance: evidence from TFP analysis on marketing cooperatives

The object of the present article is to offer a decomposition of productivity indices incorporating environmental changes. The model followed is an input oriented approach related to undesirable output (environmental performance attribute) in horticultural marketing cooperatives. This study is motivated by both the lack of analysis of environmental performance's effects on agribusiness productivity and the relevance of cooperative firms in the European agricultural model for attaining sustainability. For this purpose, bootstrapped envelopment analysis is applied and the best practice frontier obtained corresponds to decision making units showing the best environmental behaviour. The Malmquist total factor productivity (TFP) is decomposed into technological change, efficiency and environmental change. In the second stage, the correlations of these changes with other management variables of cooperatives are analysed. The indicators obtained, on one hand, advice about the nonseparable distance function estimations when the environmental factor is introduced. On the other hand, the results display a relevant increase in efficiency and environmental components for the period under study showing a high influence from labour qualification, environmental effort and spillover effect in the sector.

The Costs of Youth Exclusion in the Middle East

This paper explores the costs associated with youth exclusion in the Middle East by providing estimates of the economic costs to society related to youth unemployment, youth joblessness, school dropouts, adolescent pregnancy, and youth migration. The paper provides country-specific estimates of the costs of youth exclusion by using the human capital approach to valuing economic costs. In addition, the paper develops a new empirical methodology that benchmarks the costs of youth exclusion in Middle Eastern countries against a common hypothetical international best-practice in which the overall costs of youth exclusion are comparable across countries. Results show that youth exclusion poses major economic costs to Middle Eastern societies, reaching in 2006 as high as US$53 billion in Egypt and about US$1.5 billion in Jordan. Moreover, Middle Eastern countries are among the group furthest away from the best practice frontier as it relates to reducing youth exclusion, and their performance has deteriorated in recent years. Middle Eastern countries could decrease youth exclusion by at least 60 percent if they were to use their available resources more efficiently.