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Evaluating Alternative DEA Models Used to Control for Non-Discretionary Inputs
Abstract
Evaluation of performance using DEA requires models consistent with the underlying technology. There have been a number of models proposed for analyzing performance in the presence of non-discretionary inputs. Banker and Morey (Operations Research 34 (1986) 513–521) provided the first DEA model to measure technical efficiency. Other single- and multiple-stage models that incorporate DEA have been developed. This paper discusses the various approaches and provides a simulation analysis to compare the relative performance of each.
... .. ( , ) x is a weak efficient solution of model (6), then the efficiency of all DMUs including DMUo after changes, that is ...
... We increase the first output of DMU4 to 14 and achieve its x using model (6). ...
... The results are shown in the third column ofTable 5. As it is shown, Libraries {1, 2, 5,6,9,15,17,19 and 23} are efficient. ...
Inverse DEA (InvDEA) models put one step forward, in contrast with the DEA models by estimating required input level for producing a perturbed output level with the current efficiency status. In many real world applications, decision-makers face non-discretionary factors which can be hardly controlled by the Decision Making Units (DMUs). However, these types of factor are not dealt in the inverse DEA problems. Thus, the current covers the research methodological gap of the literature by developing mathematical foundation of the InDEA models capable of dealing with non-discretionary factors. To do this end, an MOLP model along with its required constraints is developed to be linked with the developed models. A numerical example and a real-world case study are provided to illustrate the proposed models and demonstrate their applicability and validity for the real world problems.
... Cristina Polo would also like to acknowledge the support and funds provided by the Ramon Areces Foundation in Spain. to evaluate the performance of different alternatives (Ruggiero, 1996(Ruggiero, , 1998Yu, 1998;Syrjänen, 2004;Muñiz et al., 2006;Cordero et al., 2009;Estelle et al., 2010;Harrison et al., 2012). However, none of these studies include the conditional approach recently developed by Daraio and Simar (2005, 2007a,2007b. ...
... This suggests that many researchers have found it adequate for their particular contexts. Moreover, according to the results reported by Muñiz et al. (2006) or Harrison et al. (2012), the variable and the number of units is high. ...
... DEA, data envelopment analysis; FDH, free disposal hull. the number of observations (Muñiz et al., 2006;Cordero et al., 2009;Harrison et al., 2012). In addition, the rank correlation coefficient increases for all approaches with the number of observations. ...
The aim of this paper is to compare the performance of the conditional nonparametric approach with several traditional nonparametric methods to incorporate the effect of exogenous or environmental variables into the estimation of efficiency measures. To do this, we conduct a Monte Carlo experiment using a translog production function with one output, two discretionary inputs and two exogenous variables to generate simulated data. According to the values of different accuracy measures calculated to evaluate the performance of each method, the conditional data envelopment analysis clearly outperforms all the traditional alternatives.
... La definizione del contesto operativo è attuata tramite un indice aggregato che combina l'efficienza tecnica dei singoli comuni con le variabili relative al contesto ambientale. Formalmente tale esclusione può essere effettuata in vario modo (Muñiz et al., 2006(Muñiz et al., , pp. 1175 ma nella versione one-stage di Ruggiero (1996) il tutto si risolve, sotto l'ipotesi di RSV, nel problema di minimizzazione (eq. 8) con il vincolo su z che consente di escludere quelle unità che si collocano in un ambiente più favorevole. ...
... 2002;Ruggiero. 2004a;2004b;Muñiz et al., 2006). Per una trattazione completa si rimanda a Coelli et al. (1998, pp. ...
... I metodi proposti in letteratura consentono di operare sia con i punteggi di efficienza che con le slacks (Muñiz et al., 2006(Muñiz et al., , pp. 1175 ma in ogni caso sussistono delle controindicazioni legate principalmente al problema della dimensione dei vari cluster, curse dimensionality, poiché la numerosità dei cluster non solo è diversa ma talvolta può essere molto ridotta per 1e unità che si trovano nelle condizioni peggiori. I principali limiti che ne derivano sono: i) i punteggi di efficienza ottenuti sono distorti con un distorsione che è proporzionale al condizionamento dovuto alle variabili ambientali; ii) i punteggi di efficienza, essendo calcolati su sub-campioni diversi, non sono sempre direttamente confrontabili. ...
... To effectively deal with these factors, a radial DEA model in the presence of exogenous fixed inputs was proposed by Banker and Morey (1986). Based on their model, many versions of DEA models in the presence of exogenous fixed inputs have been introduced (Muñiz et al., 2006;Ruggiero, 1998;Saati et al., 2011;Syrjänen, 2004). These studies, however, were only introduced in the presence of exogenous fixed inputs. ...
... The first completed formula of a radial model in the case of exogenously fixed inputs was introduced by Banker and Morey (1986). The basic concepts of their model were later adopted by many efficiency studies that used a radial model in the presence of exogenous fixed inputs or outputs, such as Agasisti and Pohl (2012), Muñiz et al. (2006), Ruggiero (1996), Ruggiero (1998), Saati et al. (2011) andWorthington (1999). In contrast to the radial model, a nonradial SBM model in the presence of exogenous fixed inputs and outputs was proposed by Farzipoor Saen (2005). ...
Because port operations have rapidly been extending, air pollution resulted from ports has been increased and become a persistent concern for environmentalist and policy makers. The objective of this paper is to measure the environmental efficiency of ports in Korea. The main characteristic of the environmental efficiency assessment problem is that undesirable output of carbon dioxide ( CO2) emissions and exogenous fixed input of the terminal area of ports should concurrently be considered. By analysing the impacts of the exogenous fixed input and undesirable outputs on decision making units (DMUs) performance, a super efficiency slacks-based measure in data envelopment analysis (SE-SBM-DEA) approach is proposed. The proposed approach consists of two models: slacks-based measure (SBM) model and super efficiency SBM (SE-SBM) model. The models effectively discriminate between efficient and inefficient ports, and rank their efficiencies. To restrict any decreases or increases in the fixed input levels, the slacks of fixed inputs are removed from the target functions and their relevant constraints of the proposed approach. In addition, the undesirable outputs are formulated according to the weak disposability assumption, so that
they can only be reduced with the reduction of certain desirable outputs. Hence, its slack
should also be removed from the SBM and SE-SBM models. As a result, the scalar measures of the models only deal with the discretionary inputs and desirable outputs of a DMU being evaluated. We examine the applicability of the proposed approach, using real data, for 19 ports in Korea.
... These input or output factors are not influenced or cannot be changed by the organizations' discretion, judgment or preference. The non-discretionary factors in addition to discretionary factors should be considered in the performance evaluation process of a DMU to ensure fair comparisons ( Ebadi & Shahraki, 2010;Muñiz, Paradi, Ruggiero, & Yang, 2006;Ruggiero, 1998 ). The non-discretionary factors are also known as environmental factors or contextual variables in some studies, e.g., Amirteimoori, Maghbouli, and Kordrostami (2016), Banker and Morey (1986), Camanho, Portela, andVaz (2009), Cordero-Ferrera et al. (2008), Ruggiero (1996) . ...
... Additionally, the objective function should only deal with discretionary inputsoutputs since their levels are not subject to the control of a DMU's management. To incorporate these concepts into a DEA model, there have been many studies proposing the integration of the non-discretionary factors of inputs or outputs into the radial DEA models, e.g., Seiford (2009), Fried, Lovell, Schmidt, andYaisawarng (2002), Fried, Schmidt, and Yaisawarng (1999), Muñiz et al. (2006), Patel and Pande (2013), Ruggiero (1998) and Syrjänen (2004) . In the same context, Estelle, Johnson, and Ruggiero (2010) considered three-stage DEA models in the presence of non-discretionary inputs where the peformance of the models was compared using Monte Carlo analysis. ...
An alternatve approach of super efficiency slack-based measure data envelopment analysis has been proposed to make the projection of an efficient decision making unit strongly-Pareto efficient. The approach however did not examine the simultaneous effect of non-discretionary factors and integer requirements on efficiency measures. To obtain more accurate efficiency measures, this paper proposes a two-stage approach of super efficiency slack-based measure in non-discretionary factors and mixed integer requirements. Both new factors and requirements were first integrated into the existing approach. The optimal solution of the proposed approach was then obtained by transforming its fractional form to a linear form. Thus, the scalar measures of the proposed approach can now deal directly with discretionary mixed integer input saving-output surplus and discretionary mixed integer input excess-output shortfall. The practicability of the proposed approach was tested using empirical data of Malaysian community colleges.
... These input or output factors are not influenced or cannot be changed by the organizations' discretion, judgment or preference. The non-discretionary factors in addition to discretionary factors should be considered in the performance evaluation process of a DMU to ensure fair comparisons ( Ebadi & Shahraki, 2010;Muñiz, Paradi, Ruggiero, & Yang, 2006;Ruggiero, 1998 ). The non-discretionary factors are also known as environmental factors or contextual variables in some studies, e.g., Amirteimoori, Maghbouli, and Kordrostami (2016), Banker and Morey (1986), Camanho, Portela, andVaz (2009), Cordero-Ferrera et al. (2008), Ruggiero (1996) . ...
... Additionally, the objective function should only deal with discretionary inputsoutputs since their levels are not subject to the control of a DMU's management. To incorporate these concepts into a DEA model, there have been many studies proposing the integration of the non-discretionary factors of inputs or outputs into the radial DEA models, e.g., Seiford (2009), Fried, Lovell, Schmidt, andYaisawarng (2002), Fried, Schmidt, and Yaisawarng (1999), Muñiz et al. (2006), Patel and Pande (2013), Ruggiero (1998) and Syrjänen (2004) . In the same context, Estelle, Johnson, and Ruggiero (2010) considered three-stage DEA models in the presence of non-discretionary inputs where the peformance of the models was compared using Monte Carlo analysis. ...
Conventional data envelopment analysis (DEA) models assume that all values of input and output variables are non-integers. However, in many situations of real life DEA application, some of the input and/or output variables are to be integers. The rounding process of the noninteger values to their nearest integers can cause inaccurate efficiency and performance measurement. Thus, it is important to develop a non-radial hybrid integer DEA model. Moreover, the projection of DEA model. Moreover, the projection of decision making units (DMUs) in the existing super efficiency slack based measure hybrid integer model may not be strongly Pareto-efficient. Thus, our hybrid integer DEA model is developed based on an alternative super efficiency slack based measure DEA model for ranking efficient and inefficient DMUs. The developed model can project efficient DMUs resulted from super efficiency strongly Pareto-efficient by identifying input excesses and output shortfalls of non-integer and integer slack variables. It then discriminates inefficient DMUs whose efficiency scores resulted from super efficiency slack based measure model equal to one. An application to measure the efficiency of 41 academic departments at National Cheng Kung University in Taiwan (NCKU) is used to test the applicability of developed models. The results showed that 51.20% of the departments (DMUs) were super efficiency. Moreover, the result also showed that most of the inefficient departments were caused by their input excesses of expenses and teaching space, and output shortfalls associating with publications and grants.
... Specifically, these advantages include offering better results and not requiring functional forms and/or ad hoc parametric values in any of the three stages necessary for the calculation of the efficiency stages. Thus, the model is coherent with the theoretical foundations of DEA (Muñiz, Paradi, Ruggiero, & Yang, 2006). Finally, the decision regarding the type of DEA model with contextual variables to be used was also based on the criteria of understability, applicability and acceptability, as suggested by Huguenin (2015). ...
... The previous program would be similar for Y r except for the total slack which would be: S T r + = (φo − 1) Y r + S r + . Now, the original values of the discretionary inputs and outputs are modified by the effect of the contextual inputs (Muñiz et al., 2006) as follows: ...
This study evaluates the technical efficiency of the learning-teaching process in higher education using a three-stage procedure that offers advances in comparison to previous studies and improves the quality of the results. First, it utilizes a multiple stage Data Envelopment Analysis (DEA) with contextual variables. Second, the levels of super efficiency are calculated in order to prioritize the efficiency units. And finally, through sensitivity analysis, the contribution of each key performance indicator (KPI) is established with respect to the efficiency levels without omission of variables. The analytical data was collected from a survey completed by 633 tourism students during the 2011/12, 2012/13 and 2013/14 academic course years. The results suggest that level of satisfaction with the course, diversity of materials and satisfaction with the teacher were the most important factors affecting teaching performance. Furthermore, the effect of the contextual variables was found to be significant.
... To address the above issues, there are two main types of approaches in past studies: one-stage approaches and multi-stage approaches [45]. One-stage approaches take uncontrollable factors into account when running a DEA model by refining the traditional DEA formula [47,48] or categorizing the uncontrollable factors of the DMU operation environment to compare the efficiency of DMUs in different environments [49,50]. Multistage approaches are carried out to explore the relevant effects by performing a regression analysis of uncontrollable factors based on the obtained DMU efficiency values [51][52][53]. ...
To figure out the primary factors that significantly impact the sustainability of highway routine maintenance management (HRMM), this paper examined 23 highway operating subsidiaries (evaluated decision-making units, DMUs) affiliated with Shaanxi Transportation Holding Group (STHG) in Shaanxi Province as an example. First, data envelopment analysis (DEA) was used to evaluate the performance of HRMM for each DMU. Subsequently, a truncated regression model was utilized to analyze the primary factors that impact the outcomes of HRMM. The conclusions indicated that except for the widely recognized input and output factors, there exist some uncontrollable factors that can affect HRMM efficiency, including the amount of natural dustfall, urbanization rate, tunnel length, and bridge length. These findings offer suggestions for STHG focusing on DMUs facing challenges with high dustfall and urbanization rate and long bridges and tunnels when allocating maintenance resources to improve HRMM efficiency and achieve sustainable highway maintenance management. Moreover, the methodology for analyzing uncontrollable factors can also serve as a valuable reference for other maintenance types or fields, contributing to the broader goal of promoting sustainability in transportation infrastructure development.
... Other variants of (1) and (2) are also considered in the literature [7,8,17,19,45]. In addition, more constraints or objectives can be added to (1) and (2) (e.g., to the weights [26,49] or objectives [41]). ...
A method has been proposed to select one of several project implementation variants in the context of sustainable project management. The method should be applied in the phase of the project definition. The projects are viewed across the entire lifecycle of the project and its product. In all the phases, the sustainability aspects should be addressed in a balanced way. The sustainability context implies that different stakeholders will have conflicting opinions on the weights of different variables. The proposed approach is based on network Data Envelopment Analysis that does not require the weights of individual variables as input. Consequently, the proposed method is the first approach allowing users to select a project implementation variant in the context of sustainability and the entire project and product lifecycle, without imposing the weights of individual variables. The proposal is designed for organisations using project sustainable management.
... Based on these studies, many DEA studies dealing with non-discretionary factors have been carried out. These include the studies introduced in Agasisti [48], Banker and Morey [32], Cook and Seiford [49], Muñiz et al. [50], Nigam et al. [51], Patel and Pande [52] and Ruggiero [53]. To evaluate suppliers with a non-discretionary situation of inputs and/or outputs of radial models, Farzipoor Saen [54], Noorizadeh et al. [55], and Noorizadeh et al. [56] introduced an integrated methodology using radial models with uncontrollable inputs and/or outputs. ...
Supply chain management (SCM) has been received much attention from academics and corporates. Effective and sustainable SCM require proper efficiency evaluation of suppliers. Such evaluation can be performed using data envelopment analysis (DEA). Classical DEA models presume all inputs and outputs are under the control of suppliers’ management, as well as the models cannot provide a complete ranking of efficient and inefficient suppliers. However, in SCM and other real-managerial problems, some inputs and/or outputs may be uncontrollable (outside management control). Thus, this paper proposes a super efficiency of slacks-based measure (SE-SBM) approach that can handle uncontrollable factors. The proposed approach can distinguish between efficient and inefficient suppliers and identify their rankings. The discriminating power of the proposed approach is due to it concurrently deals with input excesses and output shortfalls to improve inefficient suppliers, as well as input savings and output surpluses of efficient suppliers to maintain their efficient status.
... The idea of non-discretionary factors in DEA was proposed by Charnes and Cooper (1984). Muñiz et al. (2006) introduced a DEA model to check the non-discretionary data. Azizi and Ganjeh Ajirlu (2011) proposed a pair of DEA models to measure the efficiency of the DMUs with non-discretionary factors and imprecise data. ...
The transport industry is one of the main contributors to environmental pollution. Sustainable supply chain management (SSCM) is an essential subject in the transportation industry. Today, one of the important goals of organizations is to evaluate the sustainability of supply chain (SC) because assessing the efficiency of SCs helps organizations to enhance their awareness of performance and develop managerial strategies. Data envelopment analysis (DEA) is a common technique to assess the sustainability. The objective of this paper is to propose a Malmquist productivity index (MPI) based on network data envelopment analysis (NDEA) model in the presence of integer data, undesirable outputs, and non-discretionary inputs. The NDEA models deal with the internal structure of decision making units (DMUs). The MPI reflects the productivity change over time. The proposed model can fully rank DMUs. To prove the applicability of the proposed model, the sustainability of intercity passenger transportation is evaluated.
... Also, Banker and Morey (1996) expanded the first model for evaluating DEA efficiency with exogenously fixed inputs and outputs in forms like "age of store" in an analysis of a network of fast-food restaurants. Several other research with this thought-provoking approach are explained in Ray (1991), Golany and Roll (1993), Ruggiero (2004Ruggiero ( , 1998, Yu (1998), Muniz et al. (2006), Camanho et al. (2009), Jahanshahloo et al. (2010, Patel and Pande (2012), Syrjanen (2004), Amirteimoori et al. (2014), Shih et al. (2016) and Galagedera (2019). Moreover, there were few studies that dealt with the effect of exogenous environmental factors on forest resources. ...
Purpose
This paper aims to apply a new approach for resource sharing and efficiency estimation of subunits in the presence of non-discretionary factors and partial impacts among inputs and outputs in the data envelopment analysis (DEA) framework.
Design/methodology/approach
First, inspired by the Imanirad et al. ’s model (2013), the authors consider that each decision-making unit (DMU) may consist of several subunits, that each of which can be affected by non-discretionary inputs. After that, the Banker and Morey’s model (1996) is used for modeling non-discretionary factors. For measuring performance of several subunits, which can be considered as DMUs, the aggregate efficiency is suggested. At last, the overall efficiency is computed and compared with each other.
Findings
One of the important features of proposed model is that each output in this model applies discretionary input according to its need; therefore, the result of this study will make it easier for the managers to make better decisions. Also, it indicates that significant predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the influence of non-discretionary input. Therefore, the proposed model provides a more reasonable and encompassing measure of performance in participating non-discretionary and discretionary inputs to better efficiency. An application of the proposed model for gaining efficiency of 17 road patrols is provided.
Research limitations/implications
More non-discretionary and discretionary inputs can be taken into consideration for a better analysis. This study provides us with a framework for performance measures along with useful managerial insights. Focusing upon the right scope of operations may help out the management in improving their overall efficiency and performance. In the recent highway maintenance management systems, the environmental differences exist among patrols and other geotechnical services under the climate diverse. Further, in some cases, there might exist more than one non-discretionary factor that can have different effects on the subunits’ performance.
Practical implications
The purpose of this paper was to measure the performance of a set of the roadway maintenance crews and to analyze the impact of non-discretionary inputs on the efficiency of the roadway maintenance. The application of the proposed model, on the one hand, showed that each output in this model uses discretionary input according to its requirement, and on the other hand, the result showed that meaningful predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the impact of non-discretionary input.
Originality/value
Providing information on resource sharing by taking into account non-discretionary factors for each subunit can help managers to make better decisions to increase the efficiency.
... Non-discretionary factors in DEA are particularly useful where business owners cannot directly control some inputs and/or outputs. Again, the consideration of non-discretionary factors in robust DEA in this paper makes it the first of its kind and adds to the literature studies on the topic for the traditional DEA models (see for e.g., Banker and Morey, 1986;Muñiz et al., 2006;Huguenin 2015;Taleb et al., 2018) and imprecise DEA models (e.g. Fried et al., 2002;Farzipoor Saen, 2009;Saati et al., 2011;Azizi and Ajirlu, 2011;Zerafat Angiz and Mustafa, 2013;Toloo et al. 2018Toloo et al. , 2021. ...
Traditionally, data envelopment analysis (DEA) evaluates the performance of decision-making units (DMUs) with the most favorable weights on the best practice frontier. In this regard, less emphasis is placed on non-performing or distressed DMUs. To identify the worst performers in risk-taking industries, the worst-practice frontier (WPF) DEA model has been proposed. However, the model does not assume evaluation in the condition that the environment is uncertain. In this paper, we examine the WPF-DEA from basics and further propose novel robust WPF-DEA models in the presence of interval data uncertainty and non-discretionary factors. The proposed approach is based on robust optimization where uncertain input and output data are constrained in an uncertainty set. We first discuss the applicability of worst-practice DEA models to a broad range of application domains and then consider the selection of worst-performing suppliers in supply chain decision analysis where some factors are unknown and not under varied discretion of management. Using the Monte-Carlo simulation, we compute the conformity of rankings in the interval efficiency as well as determine the price of robustness for selecting the worst-performing suppliers.
... • Extended WDEA (EWDEA): Developing WDEA approach for dynamic efficiency measurement of DMUs in the presence of special data and factors such as negative data, integer data, undesirable factor, dual-role factor, and non-discretionary factor (for details, see Portela et al., 2004;Cook et al., 2006;Muñiz et al., 2006;Kuosmanen & Matin, 2009;Halkos & Petrou, 2019). Finally, the most valuable suggestion for future studies would be to apply existing or extended WDEA approaches in real-world problems and applications. ...
Window Data Envelopment Analysis (WDEA) is a popular, effective, and applicable methods for dynamic performance assessment of peer decision making units (DMUs). WDEA is a non-parametric panel method that operates based on the principle of moving averages and establishes efficiency measures by treating each DMU in different periods as a separate DMU. By applying the WDEA approach, a decision-maker (DM) can measure the efficiency of different DMUs in different periods through a sequence of overlapping windows. Also, WDEA can increase the discrimination power by increasing the number of DMUs when a limited number of DMUs is available. Given the advantages of the WDEA approach and its applications in real-world problems, this paper surveys and analyses 387 WDEA papers published from 1985 to 2020. The paper also recommends some suggestions, guidelines, and opportunities for future research. Notably, the findings show the applicability and efficacy of WDEA in the literature.
... We use Ruggiero's 3-stage method (Ruggiero 1998) to incorporate multiple risk factors into one risk variable (4a), as it performed best in virtually all scenarios, being the only model robust to sample size and the number of nondiscretionary variables (Muñiz et al. 2006). The original DEA model without the risk factors (4a) is solved and the second-stage regression on the risk factors is performed. ...
... Over the years, a number of DEA models with non-discretionary factors have been developed by researchers (Banker and Morey, 1986;Golany and Roll, 1993;Yang and Paradi, 2006); however, Banker and Morey (1986) is the most frequently used model in literature (Muñiz et al., 2006). The main benefit of Banker and Morey (1986) model is its computational advantages and its ability to include non-discretionary and discretionary variables simultaneously in the same DEA model, but either an input or output which is suitable for the current study (as consultation time is the only non-discretionary output). ...
Purpose
The aim of this research study is to develop a queue assessment model to evaluate the inflow of walk-in outpatients in a busy public hospital of an emerging economy, in the absence of appointment systems, and construct a dynamic framework dedicated towards the practical implementation of the proposed model, for continuous monitoring of the queue system.
Design/methodology/approach
The current study utilizes data envelopment analysis (DEA) to develop a combined queuing–DEA model as applied to evaluate the wait times of patients, within different stages of the outpatients' department at the Combined Military Hospital (CMH) in Lahore, Pakistan, over a period of seven weeks (23rd April to 28th May 2014). The number of doctors/personnel and consultation time were considered as outputs, where consultation time was the non-discretionary output. The two inputs were wait time and length of queue. Additionally, VBA programming in Excel has been utilized to develop the dynamic framework for continuous queue monitoring.
Findings
The inadequate availability of personnel was observed as the critical issue for long wait times, along with overcrowding and variable arrival pattern of walk-in patients. The DEA model displayed the “required” number of personnel, corresponding to different wait times, indicating queue build-up.
Originality/value
The current study develops a queue evaluation model for a busy outpatients' department in a public hospital, where “all” patients are walk-in and no appointment systems. This model provides vital information in the form of “required” number of personnel which allows the administrators to control the queue pre-emptively minimizing wait times, with optimal yet dynamic staff allocation. Additionally, the dynamic framework specifically targets practical implementation in resource-poor public hospitals of emerging economies for continuous queue monitoring.
... Zind k ≤ Zind 0 ). We refer the interested reader to Ruggiero (1998) for more details and to Estelle et al. (2010); Muñiz et al. (2006) for simulation analysis of different methods to incorporate environmental variables. ...
This paper uses Data Envelopment Analysis (DEA) to evaluate how the technical efficiency of forest harvesting operations is influenced by terrain conditions and forest attributes, in addition to exploring the existence of other influencing factors. To this end, 643 shift-level observations of harvesting operations on 253 distinct harvested sites were used. The aim of this study is to highlight the harvester’s ability to maximize the outputs, represented by the number of assortments for various tree species, given inputs such as harvest volume, harvest time for various tree species, and distance traveled by the harvester. Operational environment variables such as harvest, or decision-making unit (DMU) size, shape, and terrain characteristics were included. We found large variations in efficiency scores, and that inefficient harvest operations could theoretically be improved by reducing input by up to ca. 80%. A second stage regression estimation was applied to identify which factors significantly affected inefficiency. It was found that the inefficiency decreases with increasing stem-volume for pine and broadleaves, increasing stand density, and increasing share of pulpwood and non-marketable timber, while it increases with the number of logs produced per tree (in broadleaves). Inefficiency increases also with an increasing ratio of actual travel distance to minimal travel distance. The study shows how adopting DEA methods in forest operations might be used in combining efficiency analysis and environmental factors, by identifying and measuring inefficiency due to, for example, difficult terrain.
... Banker and Morey [1] provided the first DEA model to include non-discretionary variables for measuring technical efficiency. Muniz et al. [15] reviewed various non-discretionary approaches and compared their performance by simulation analysis. Taleb et al. [17] proposed a two-stage approach of super efficiency slack-based measure in nondiscretionary factors and mixed integer requirements. ...
... For instance, in order to deal with uncontrollable variables in DEA and to create a fair level of comparison for the DMUs, Banker and Morey (1986) introduced a modification to the traditional DEA formulations. Formulation (4) demonstrates the input-oriented dual BCC model for the DMU under investigation (i.e., DMU 0 ) with additional constraints to account for uncontrollable variables [35,36]: ...
With many lives lost every year in crashes, highway traffic safety is a major concern. With 93% of crashes being contributed to by roadway users’ poor behaviors, one of the most effective ways to improve highway traffic safety is to improve the performance of organizations enforcing traffic laws to change those poor behaviors. This research introduces a framework that makes it possible to benchmark the efficiency performance within the highway patrol. Data envelopment analysis (DEA), a mathematical methodology based on the concepts of optimization and linear programming, was used to develop that framework to measure the efficiency performance of a highway patrol’s divisions. Such framework is used to measure and compare the efficiency performance of 17 divisions of the Wyoming Highway Patrol to allow internal benchmarking and thus to improve the overall organizational performance. The concepts discussed in this paper can be implemented by highway patrol agencies for internal and external efficiency benchmarking. Although DEA has been utilized for organizational performance evaluation in multiple sectors, literature review to date has not identified any study that has specifically utilized DEA in the context of highway traffic safety from the highway patrol’s perspective. As such, this study is original and timely.
... A further modification in the form of a three-stage model was also proposed by Ruggiero (1998). Comparisons and simulation studies by Muñiz et al. (2006) show that in the case where there are just one non-discretionary variable and one or multiple discretionary variables, the one-stage model gives satisfactory results. Threestage model is more appropriate when multiple nondiscretionary inputs are present. ...
The paper provides a complete and reliable ranking to the states of India in the renewable energy generation arena. The methodology adopted in the article rests on Data Envelopment Analysis (DEA). One of the recently developed super-efficiency DEA formulations is integrated with a procedure to allow for non-discretionary input variables. The integration may fail to be feasible in certain cases. To deal with infeasibility, a heuristics is proposed. Using a simulation, it is demonstrated that the approach yields complete and fairly reliable rankings in the vast majority of the cases. Tamil Nadu appears as the leader followed by Haryana and Uttar Pradesh. Madhya Pradesh, Rajasthan and Andhra Pradesh are the laggards. Rankings will be useful for policy-makers in identifying the leaders and the laggards in the renewable energy sector, and hence, for fine tuning the policies to promote better renewable energy deployment. Rankings will also be helpful for investors in the sector by providing them with a simple tool to identify lucrative investment options. The approach is fairly generalizable to many other practical cases.
... model (Yang and Paradi 2003)), because its result is not sensitive to changes in the number of variables or units, although the other mentioned models are based on a priori assumption in their technology set (Muñiz et al. 2006). Therefore, based on these points, the applied ND-DEA model using the correlation factor ␦(z) has higher discriminating power than the traditional BCC-DEA model and hence provides strong impetus for applying the ND-DEA approach to distinguish between the inefficient and efficient units when ND factors exist. ...
In this study, we develop a marginal chance-constrained data envelopment analysis (DEA) model in the presence of nondiscretionary inputs and hybrid outputs for the first time. We call it a stochastic nondiscretionary DEA model (SND-DEA), and it is developed to measure and compare the relative efficiency of forest management units under different environmental management systems. Furthermore, we apply an output-oriented DEA technology to both deterministic and stochastic scenarios. The required data are collected from 24 forest management plans (as decision-making units) and included four inputs and an equal amount of outputs. The findings of this practical research show that the modified SND-DEA model in different probability levels gives us apparently different results compared with the output from pure deterministic models. However, when we calculate the correlation measures, the probability levels give us a strong positive correlation between stochastic and deterministic models. Therefore, approximately 40% of the forest management plans based on the applied SND-DEA model should substantially increase their average efficiency score. As the major conclusion, our developed SND-DEA model is a suitable improvement over previous developed models to discriminate the efficiency and (or) inefficiency of decision-making units to hedge against risk and uncertainty in this type of forest management problem.
... Those alternative methods produce divergent results with empirical data (see Muñiz 2002;Yang and Pollitt 2009) and results derived from some previous works comparing their performance using simulated data (e.g., Yu 1998;Ruggiero 1998;Muñiz et al. 2006;Cordero et al. 2009;Estelle et al. 2010;Harrison et al. 2012) are inconclusive. Thus, researchers have not yet agreed on identifying a preferred option for empirical problems (Cordero et al. 2008). ...
The treatment of the contextual variables (Z) has been one of the most controversial topics in the literature on efficiency measurement. Over the last three decades of research, different methods have been developed to incorporate the effect of such variables in the estimation of efficiency measures. However, it is unclear which alternative provides more accurate estimations. The aim of this work is to assess the performance of two recently developed estimators, namely the nonparametric conditional DEA method (Daraio and Simar in J Prod Anal 24(1):93–121, 2005; J Prod Anal 28:13–32, 2007a) and the StoNEZD (Stochastic Non-Smooth Envelopment of Z-variables Data) approach (Johnson and Kuosmanen in J Prod Anal 36(2):219–230, 2011). To do this, we conduct a Monte Carlo experiment using three different data generation processes to test how each model performs under different circumstances. Our results show that the StoNEZD approach outperforms conditional DEA in all the evaluated scenarios.
... Additionally, Portela and Camanho (2010) and Portela et al. (2013) employ DEA to compute student and school value added. Several papers in the literature have applied second-stage DEA models (e.g., Ray, 1991;Afonso and Aubyn, 2006;Muñiz et al., 2006;Cordero-Ferrera et al., 2010;Miningou and Vierstraete, 2013;Masci et al., 2017). Another recent research strand applies more robust DEA models such as the conditional model (Haelermans and Ruggiero, 2013), the application of assurance region models with DEA (e.g., Halkos et al., 2015) or non-radial DEA models (e.g. ...
The economic crisis forced politicians to make public finances sustainable. The education sector was one of the most adversely affected by control of public expenditure. This paper analyzes the drivers causing productivity changes of especially vulnerable public schools during the crisis. We use the Hicks-Moorsteen index, which is a seldom applied methodology that leads to feasible results under variable returns to scale. To illustrate the benefits of this index, we use a sample of 298 Catalan public primary schools between 2009 (when budgetary constraints started) and 2014. The results reveal that during the crisis schools improved their total factor productivity by raising academic achievement despite cutbacks in resources. We also found that there was a strong convergence pattern during the financial crisis, driven by the catch-up process of some schools. The
findings have important policy implications, suggesting that a monitoring system should be set up for use by policy makers.
... For instance, in some recent studies, researchers figured out that the efficiency scores of the models with further number of discretionary input variables are greater than or equal to the efficiency scores calculated with less number of discretionary input variables (Zahidul Islam et al. 2011;Pande & Patel 2012). Furthermore, to demonstrate the high discriminating power of this approach, Muñiz et al. (2006) evaluated alternative DEA models used to control Narmash district 2 1 ---23 ...
The purpose of this paper is to measure the relative performance of forest management units, and to analyze the impact of the external non-discretionary (ND) factors on these units’ technical efficiency. Toward this end, data envelopment analysis (DEA) technique in variable returns to scale environment with both discretionary and ND factors has been used. The required data are collected from 24 Iranian forest management units (as decision-making units (DMUs)) and included four inputs and two outputs. The ND factors are first ignored and it is shown that most of the forest management units are operating at high efficiency levels. Then the variable “area” is considered as the exogenously fixed (or the external ND) input in a modified ND model because it is outside of the forest manager’s control. The results indicate that the number of efficient units and the average technical efficiency score are reduced to 12 (approximately 50%) and 0.85, respectively. The forest management units should therefore increase their average efficiency score by 0.15 to move onto the new efficient frontier which is made by applying this strict criterion. As a consequence, it is recommended to apply the ND models for controlling the exogenously fixed factors and carrying out a correct and accurate evaluation, because the traditional DEA approaches may overestimate the efficiency of DMUs.
... (Cazals et al. 2002;B din et al. 2012) 11 . To this regard, several comparisons between the proposed models have been done, by using either empirical (Cordero-Ferrera et al. 2008;Huguenin, 2015) or simulated data (Ruggiero, 1998;Syrjänen, 2004;Muñiz et al., 2006;Cordero-Ferrera et al. 2009;Harrison et al.2012). However, there is no agreement on which is the best model to deal with environmental factors. ...
... These contributions have been developed in many directions. For example, to deal with the selection of appropriate inputs and outputs to include in DEA specifications ( Cook, Tone, & Zhu, 2014;Nataraja & Johnson, 2011;Smith,1997 ), to deal with the inclusion of non-discretionary inputs ( Banker & Morey, 1986;Cordero et al. 2008;Muñiz, Paradi, Ruggiero, & Yang, 2006;Ruggiero, 1996 ), to deal with fuzzy data ( Hatami-Marbini, Emrouznejad, & Tavana, 2011;Liu and Chuang, 2009;Liu, 2011 ), to improve DEA estimations under the presence of noise ( Gstach, 1998;Ruggiero, 20 06;Simar, 20 07 ), or to deal with complex input and output structures ( Jianfeng, 2015;Lotfi, Noora, Jahanshahloo, & Reshadi, 2011;Wang & Chin, 2010;Yu & Shi, 2014 ;), among others. ...
... Since DEA first emerged, its applications to the field of efficiency in education have grown steadily [41]. Many papers in the literature have applied DEA to assess efficiency in education (e.g., [12,23,13,14,103,97,71,100,89,91,1,48,92,110,95,105,96], among others). This line of research is based on empirical studies designed to estimate the magnitude of the impact of schools' results promoted by internal inputs and environmental factors [109]. ...
Centralized resource allocation requires planning how to implement changes in order to adapt resources to the allocated budget without losing outputs. This paper presents an alternative model to reallocate human resources in a public education network based on the so-called centralized data envelopment analysis. This stream has received less attention in the efficiency literature and evaluates the overall efficiency of a set of decision making units controlled by a central authority. In this study, an extended centralized data envelopment analysis dealing with non-transferable inputs and environmental factors is proposed to assess the global efficiency of a centralized education network. We then design an iterative procedure capable of reallocating resources without jeopardizing the level of efficiency. The proposed model is applied in a real case of public schools from Catalonia (north-east Spain). The results indicate the network could be improved to optimally redistribute educational resources without falls in the level of aggregated outputs. The study also provides useful information for accountability and decision making when implementing improvement programs in public schools.
... Concerning the non-discretionary external factors that affect the production process, also known as environmental variables, (see for instance Fried [16,17]), Daraio and Simar [18,19], Muniz [20], Gomes et al. [21], Lima et al. [22] among others. ...
Data Envelopment Analysis is a non-parametrical approach for efficiency evaluation of so-called DMUs (Decision Making Units) and takes into account multiple inputs and outputs. For each inefficient DMU, a target is provided which is constituted by the inputs or outputs levels that are to be attained for the inefficient DMU to become efficient. However, multiobjective models, known as MORO (Multiobjective Model for Ratio Optimization) provide a set of targets for inefficient DMU, which provides alternatives among which the decision-maker can choose. In this paper, we proposed an extension of the MORO models to take into account non-discretionary variables, i.e., variables that cannot be controlled. We present a numerical example to illustrate the proposed multiobjective model. We also discuss the characteristics of this model, as well as the advantages of offering a set of targets for the inefficient DMUs when there are non-discretionary variables in the data set.
... Ella consiste en la evaluación de un modelo FDH tradicional, de manera repetida para distintos subconjuntos de observaciones de igual tamaño.La cuantificación del impacto de variables no controlables por los gestores (en cuya definición englobamos tanto los inputs no controlables como las variables ambientales) sobre la medición de la eficiencia es rica en propuestas metodológicas para su tratamiento, no existiendo consenso entre los investigadores en cuanto a cuál de las distintas posibilidades utilizadas es la literatura es la más adecuada. Una revisión de algunas estas metodologías se encuentra enMuñiz (2002),Cordero et al. (2005), o enMuñiz et al. (2006) Diferentes autores han realizado aplicaciones al sector educativo considerando las variables de entorno:Ray (1991),Ruggiero et al. (1995),Kirjavainen y Loikkanent (1998),Giménez et al. (2007) o Silva Portela y Thanassoulis (2001) pero de nuevo sin mostrar consenso acerca de la alternativa más adecuada.En este trabajo se ha optado para medir de la eficiencia técnica bajo la influencia de variables de entorno por la propuestaLozano-Vivas et al. (2002) y en Lozano-Vivas et al.(2001). Se trata de un método simple basado en un única etapa que previamente fue utilizado también en el contexto de sistemas educativos porGiménez et al. (2007). ...
This article quantifies the requirements of management improvement and resource endowments that Chilean schools need to achieve optimal levels of performance, combining the literatures on efficiency and productivity, school effectiveness and the theory on resources and capabilities. The study shows that the improvement in outcomes, due to an increase in the endowments of resources, is higher than the improvements of results in academic achievement, which can be attained due to efficiency gains. Specifically, the increase in resource endowments in the medium term should be, on average, larger in infrastructure and equipment, obtaining better results when focusing in those schools in a more unfavorable environment.
... In any realistic situation, however, there may be ''exogenously fixed'' (nondiscretionary) factors that are beyond the control of a DMU's management and also need to be considered (Lotfi and Jahanshahloo 2007;Ebadi and Shahraki 2010). Banker and Morey (1986) developed the first model for evaluating DEA efficiency with ''exogenously fixed'' inputs and outputs in forms like ''age of store'' in the analysis of a fast food restaurants network (Ray 1991;Roggiero 1998;Muniz et al. 2006). ...
This paper reports the use of data envelopment analysis (DEA) and a distance friction minimization (DFM) approach with fixed factors presented by Suzuki and Nijkamp (A stepwise efficiency improvement DEA model for airport operations with fixed production factors. Paper presented at the ERSA Congress. http:// ideas. repec. org/ p/ wiw/ wiwrsa/ ersa11p1065. html #biblio. Accessed 18 April 2013, 2011) to assess the levels of match between expected demand for the next 25 years and infrastructure expansion investments announced by Infraero (the Brazilian Airport Authority) for the Rio de Janeiro International Airport (also known as “Galeão”). The main advantage of using the DFM approach with fixed factors lies in the fact that, to achieve maximum performance for inefficient units (away from the efficiency frontier), there is no need to linearly improve all input variables, as for most real situations, this assumption could be very difficult for management to implement and control. Additionally, this method enables the development of models with production factors that for some reason cannot be changed or adjusted by management. Based on the data regarding the planned infrastructure expansion explicit in the concession agreement for the Rio de Janeiro International Airport (established when the airport was recently privatized), the results of this study confirm those of some previous studies that had already suggested (but did not objectively measure the shortfall considering efficiency issues) a possible capacity shortfall in the medium and long run for the Rio de Janeiro International Airport.
... For instance, snowfall or weather forecast in measuring the efficiency of maintenance units, the population of the area in measuring the efficiency of a library and age of store in the branch performance of a restaurant chain are not controllable by the user, but they are a part of the production process which needs to be considered. The first DEA model for measuring the efficiency with ND inputs was presented by Banker and Morey [5] and extended by Ruggiero [6], Syrjänen [7] and Muniz et al. [8] among others. In this study, we propose an enhanced Russell measure of efficiency in the presence of ND factors (ERM ND ). ...
Standard data envelopment analysis (DEA) models suppose that all inputs and outputs can be varied at the discretion of management of each decision making unit (DMU). In some situations, DMUs can have non-discretionary inputs or outputs that are beyond the control of decision maker, which also need to be considered. This paper proposes an enhanced Russell measure (ERM) model in the presence of non-discretionary factors. The new model is compared with the well-known radial DEA model proposed by Banker and Morey [5]. An empirical data set is used to illustrate the model.
... Among the various ways to incorporate environmental variables into the DEA framework, we use Ruggiero's 3-stage method [124] to consolidate multiple risk factors into one risk variable (4a), as it performed best in virtually all scenarios, being the only model robust to sample size and the number of nondiscretionary variables [125], when compared to the other common methods such as Ray (1991) [126], Muñiz (2002) [127] and Banker and Morey [128]. The original DEA model without the risk factors (4a) is solved and the second-stage regression on the risk factors is performed. ...
This paper measures the multi-stage technical efficiency of healthcare systems, the impact of environmental variables, and the expenditure levels across OECD countries between 2000 and 2011, based on a 12 year, 34 country panel data. We adopt an output-oriented DEA (Data Envelopment Analysis) methodology to obtain the technical efficiencies in production and provision. We find 3.05% overall inefficiency across OECD countries, which translates into a loss of 1.38 years of life expectancy at birth and additional 0.75 infant deaths per 1000 live births. There are further outcome losses, however, from environmental variables (0.54%), and inadequate healthcare spending (1.94%), almost doubling the total OECD outcome loss to 5.65%, or 2.4 years of life expectancy and 1.5 infant deaths per 1000 live births.
The inefficiency is split 21%-79% between production and provision. While provision is generally the main source of inefficiency, other countries like the US, suffer heavily from production inefficiency (61%). Although most countries are inefficient in one way or another, the type of inefficiencies they suffer and the solutions to those issues as well as the policy implications might be very different.
The DEA methodology concerns the efficiency measurement of production systems that apply multiple inputs to produce multiple outputs. Under normal conditions, it is desirable to have less input consumed and more output produced, because this leads to higher efficiencies. With regard to inefficient DMUs, improvement targets can be obtained to make them more efficient. However, there are cases in which the decision maker has no control over the input and output factors, in that the amounts of some factors cannot be adjusted at the discretion of the decision maker. The conventional DEA models introduced in the preceding chapters are either unable to handle or will produce misleading results for these cases. This chapter discusses two of the cases, non-discretionary and undesirable factors.
Subject. Increasing the productivity of each academic staff member is an important condition for the achievement of high indicators by the university. The modern system of the effective contract in Russian higher education institutions provides great growth opportunities which need to be identified by analysts. Appropriate analysis methods are needed to secure a rational use of these opportunities. Objectives. Our goal was to find the best option for using the non-parametric method of Data Envelopment Analysis to solve the task related to the assessment of the productivity of each academic staff member at a middle-size university. Methodology. We used single-stage DEA models with constant and variable returns to scale, including non-discretionary outputs. The choice of a specific model was based on both quantitative and content interpretation of the obtained results. Results. It was established that R.D. Banker and R.C. Morey’s model can properly measure the productivity of academic staff and provide the university management with valuable information which can be used to efficiently manage the productivity of the employees. We identified the most probable difficulties regarding the application of similar models to a large sample of employees under real conditions. We obtained data on the productivity distribution and the dependence of productivity on occupation, which require further analysis. Conclusions. The basic single-stage DEA models are sufficient to measure the productivity of employees if non-discretionary outputs are carefully introduced and the solution's sustainability is controlled. However, the features characteristic of all DEA models cannot be ignored: they set achievable goals to improve the existing results, however they do not search new opportunities; they inform that the goals are achieved but not how significant the achieved results are for the university.
The main purpose of this study is to provide an efficient system in order to evaluate the value chain of research and development (R&D) projects for complex products and systems (CoPS) with the ability to consider the network structure of projects value chain and data uncertainty. In addition, another goal of this research is to present a new approach for assessing and ranking of R&D projects to select and construct a desirable and optimal portfolio among the options and projects ahead under various constraints including budget, time, manpower. resources, and equipment. It is important to note that in many R&D projects, due to the novelty and innovative nature of the projects, as well as the lack of required information and records, the existence of data uncertainty is inevitable. Therefore, in order to achieve the above goals, two new approaches including fuzzy network data envelopment analysis (FNDEA) based on possibilistic programming and scenario-based robust data envelopment analysis (SBRDEA) have been proposed. Finally, both approaches have been implemented using data related to R&D projects for CoPS. The analysis of the results indicates the effectiveness and capability of the research proposed approaches.
Many firms are involved in rebuilding a region’s critical infrastructure after a disaster. One question that follows is how efficient were firms in delivering restoration services? The evaluation approach proposed in this paper builds off Reilly et al. (Reliability Engineering & System Safety 152: 197–204, 2016) by considering disaster severity to assess efficiency. We expand on the approach by adjusting limitations on the upper bound of efficiency. This paper similarly provides an application to recent post-hurricane restoration activities across different electric power companies in the states and territories of the United States.
Data envelopment analysis (DEA) has been widely applied to empirically measure the technical efficiency of a set of schools for benchmarking their performance. However, the endogeneity issue in the production of education, that plays a central role in education economics, has received minor attention in the DEA literature. Under a DEA framework, endogeneity arises when at least one input is correlated with the efficiency term. Cordero, et al. (2015) highlighted that DEA performs well under negative and moderate positive endogeneity. However, when an input is highly and positively correlated with the efficiency term, DEA estimates are misleading. The aim of this work is to propose a new test, based on defining a grid of input flexible transformations, for detecting the presence of positive endogeneity in inputs. To show the potential ability of this test, we run a Monte Carlo analysis evaluating the performance of the new approach in finite samples. The results show that this test outperforms alternative statistical procedures for detecting positive high correlations between inputs and the efficiency term. Finally, to illustrate our theoretical findings, we perform an empirical application on the education sector.
In this paper, we discuss a number of key methodological and data issues presented to researchers in determining base funding requirements for Australian schools. In particular, we outline the commonly used ‘reference school’‐ based approach to determining a benchmark level of school effectiveness and efficiency, and discuss some of its limitations. In contrast to this method, we present a new approach to estimating base funding requirements that, aided by the use of more granular data, provides a more robust approach to understanding and measuring school effectiveness and efficiency.
This paper measures the multi-stage technical efficiency of healthcare systems across OECD Countries between 2000 and 2011, based on a 34 country panel data set, taking into account the impact of environmental variables and health expenditure levels. We measure technical efficiencies in a two-stage process—the production of health services and the subsequent provision of health outcomes—using output-oriented Data Envelopment Analysis (DEA). An overall inefficiency of 3.05% across OECD countries translates into an average loss of 1.38 years of life expectancy at birth and an additional 0.75 infant deaths per 1000 live births, exacerbated by environmental variables and inadequate healthcare spending, almost doubling the total OECD outcome loss to 5.65%, or 2.4 years of life expectancy and 1.5 infant deaths per 1000 live births. Measured inefficiency is split 21%/79% between production and provision. The type of inefficiencies exhibited, the solutions to these, and the resulting policy implications vary greatly.
This paper studies the efficiently use of resources to generate income and reduce inequality, considering non-controllable variables, in the 32 states of Mexico during the 1990-2010 period. To define efficiency, we use the Data Envelopment Analysis (DEA), considering as a bad output the poverty of capacities and as a uncontrollable variable, the average level of schooling of the population aged 15 or older. The results shows that only Baja California Sur, Campeche and the Federal District were efficient in generating income and reducing inequality.
El documento aborda el estudio del uso eficiente de los recursos para generar ingreso y reducir la inequidad, considerando variables no controlables, en las 32 entidades de México, durante el período 1990-2010. Para determinar la eficiencia, se utilizó el Análisis de la Envolvente de Datos (DEA), considerando como bad output a la pobreza de capacidades, y como variable no controlable, el grado promedio de escolarización de la población de 15 y más años. Los resultados muestran que sólo Baja California Sur, Campeche y el Distrito Federal fueron eficientes en la generación de ingreso y en la reducción de inequidad.
This paper studies the efficiently use of resources to generate income and reduce inequality, considering non-controllable variables in the 32 states of Mexico during the 1990-2010 period. To define efficiency, we use the Data Envelopment Analysis (DEA), considering as a bad output the poverty of capacities and as a uncontrollable variable the average level of schooling of the population aged 15 or older. The results shows that only Baja California Sur, Campeche and the Federal District were efficient in generating income and reducing inequality.
In this study we examine the determinants of efficiency in Tax administration entities across 49 countries, using data extracted from OECD Tax administration database. Methodologically, we use a two-stage nonparametric frontier analysis. In the first stage efficiency is measured through Data Envelopment Analysis (DEA) approach. Then, truncated regression estimation with double-bootstrap Algorithm 2 (Simar & Wilson, 2007) is performed to test the significance of country-level determinants i.e. macro institutional variables. Specifically, we account for the model uncertainty through Bayesian Model Averaging (BMA) technique. We find that institutional factors are statistically significant in explaining the efficiency of Tax administration entities across countries.
Keywords: Tax administration, efficiency analysis, two-stage DEA, Bayesian Model Averaging (BMA), institutional factors.
Spanish Abstract: El analisis de eficiencia de los centros escolares constituye un tema de interes actual. El numero de publicaciones en este campo de investigacion se ha incrementado en los ultimos anos, al intentar explicar que ciertas caracteristicas del centro y del entorno influyen en los resultados de los alumnos. A la luz de la Teoria de la Produccion y la Post-New Public Management, el objetivo del trabajo es la evaluacion y rediseno, a traves de tecnicas frontera, de una muestra de centros de la red educativa publica de Catalunya. Los resultados obtenidos determinaran las acciones necesarias que permitan optimizar la red y redistribuir de forma optima los recursos educativos. Por otro lado, aportaran informacion util que ayude a la toma de decisiones por parte de las Administraciones Publicas y a la puesta en marcha de programas de mejora en los centros docentes. English Abstract: The analysis of efficiency of schools is a subject of current interest. The number of publications in this field of research has increased in recent years, trying to explain certain features of the center and the environment influence student outcomes. In light of the Theory of Production and Post-New Public Management, the aim of this work is the evaluation and redesign, through technical frontier, a sample of schools of public education network of Catalunya. The results determine the necessary actions to optimize the network and optimally redistribute educational resources. On the other hand, will provide useful information to assist decision-making by the government and the implementation of improvement programs in schools.
Data Envelopment Analysis (DEA) has been used to measure the productive efficiency of decision making units (DMUs) with multiple input and output. However, in real life, the ways to improve efficiency of DMUs is impractical because some of the inputs or outputs are uncontrollable. Thereby, using the non-controllable input output oriented model (NCNI-O), duality formulation and vector average input/output, this research is an attempt to improve the efficiency score and derive the input-output target strategy and at the same time to prove that the uncontrollable input cannot be reduce but the value should be fixed. At the end of this work, it has been proving that the objectives to maintain input and increase output or maintain output and reduce input were successfully achieved. It is also discovered the new input-output target and the results obtained indicate that the impact of uncontrollable variables is relatively significant.
The DEA methodology concerns the efficiency measurement of production systems that apply multiple inputs to produce multiple outputs. Under normal conditions, it is desirable to have less input consumed and more output produced, because this leads to higher efficiencies. With regard to inefficient DMUs, improvement targets can be obtained to make them more efficient. However, there are cases in which the decision maker has no control over the input and output factors, in that the amounts of some factors cannot be adjusted at the discretion of the decision maker. The conventional DEA models introduced in the preceding chapters are either unable to handle or will produce misleading results for these cases. This chapter discusses two of the cases, non-discretionary and undesirable factors.
This dissertation aims to measure the impact of technical change on OECD Healthcare in a multi-stage framework and identify the different sources of outcome losses to allow for comprehensive policy implications within a diverse dataset including countries from a large variety of development levels facing different healthcare issues. We adopt an output-oriented DEA (Data Envelopment Analysis) methodology to obtain the technical efficiencies in production and provision. Data used in this study is mainly obtained from the Organization for Economic Cooperation and Development (OECD) Health Data 2013 and consists of 34 OECD countries and 12 years between 2000 and 2011.
Post-hurricane restoration of electric power is attracting increasing scrutiny as customers’ tolerance for even short power interruptions decreases. At the peak, 8.5 million customers were without power after Hurricane Sandy and over 1 million customers were without power more than a week after the storm made landfall. Currently, restoration processes are typically evaluated on a case-by-case basis by a regional public service commission or similar body and lack systematic comparisons to other restoration experiences. This paper introduces a framework using data envelopment analysis to help evaluate post-hurricane restorations through comparison with the experiences of other companies in similar storms. The method accounts for the variable severity of the hurricanes themselves, so that companies are not penalized for outages that are long only because the hurricane that caused them was particularly severe. The analysis is illustrated through an application comparing 27 recent post-hurricane restoration experiences across 13 different electric power companies in the United States. The results of the study show some consistency in performance among individual utilities after the hurricanes they experience. The method could be applied to other types of infrastructure systems and other extreme events as well.
Eficiencia y Calidad de la Atención Primaria
en Extremadura proporciona al lector una investigación
cuyo principal objetivo es evaluar
el servicio de Atención Primaria de Salud en la
Comunidad Autónoma de Extremadura. El proceso
de evaluación se realiza en términos de la
eficiencia económica de sus centros de salud y
de la calidad percibida por sus usuarios. El análisis
de estas dos dimensiones ofrece una visión
global del sector, atendiendo tanto al lado de la
oferta como al de la demanda de los servicios
sanitarios inherentes a este escalón de la Sanidad
pública.
Igualmente, este estudio pone a disposición
del administrador público y del investigador
toda una batería de análisis metodológicos, indicadores
técnicos y resultados empíricos que
pueden resultar de gran utilidad para la toma de
decisiones y la mejora competitiva en el ámbito
de la Atención Primaria de Salud tanto a nivel
regional como nacional e internacional.
A tales efectos, el equipo investigador responsable
de la elaboración de este trabajo presenta
un carácter marcadamente multidisciplinar, reuniendo
a especialistas en un conjunto de áreas
relacionadas con el objeto del estudio como lo
son las áreas de Fundamentos del Análisis Económico,
Economía Aplicada, Comercialización
de Mercados, Métodos Cuantitativos, Organización
de Empresas o Economía de la Salud.
This paper briefly traces the evolution of DEA from the initial publication by Chames, Cooper and Rhodes (1978) to the current state-of-the-art (SOA). The state of development of DEA is characterized at four points in time to provide a perspective in both directions—past and future. An evolution map is provided which illustrates DEA growth during the twenty year period, the timing of the major events, and the interconnections and influences between topics. An extensive DEA bibliography is provided.
We evaluate, by means of mathematical programming formulations, the relative technical and scale efficiencies of decision making units (DMUs) when some of the inputs or outputs are exogenously fixed and beyond the discretionary control of DMU managers. This approach further develops the work on efficiency evaluation and on estimation of efficient production frontiers known as data envelopment analysis (DEA). We also employ the model to provide efficient input and output targets for DMU managers in a way that specifically accounts for the fixed nature of some of the inputs or outputs. We illustrate the approach, using real data, for a network of fast food restaurants.
In management contexts, mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best. In this capacity, mathematical programming serves as a planning aid to management. Data Envelopment Analysis reverses this role and employs mathematical programming to obtain ex post facto evaluations of the relative efficiency of management accomplishments, however they may have been planned or executed. Mathematical programming is thereby extended for use as a tool for control and evaluation of past accomplishments as well as a tool to aid in planning future activities. The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs. A separation into technical and scale efficiencies is accomplished by the methods developed in this paper without altering the latter conditions for use of DEA directly on observational data. Technical inefficiencies are identified with failures to achieve best possible output levels and/or usage of excessive amounts of inputs. Methods for identifying and correcting the magnitudes of these inefficiencies, as supplied in prior work, are illustrated. In the present paper, a new separate variable is introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decreasing returns to scale (in multiple input and multiple output situations). The results are discussed and related not only to classical (single output) economics but also to more modern versions of economics which are identified with "contestable market theories."
This study combines Data Envelopment Analysis (DEA) with regression modelling to estimate relative efficiency in the public school districts of Connecticut. Factors affecting achievements are classified as school inputs and other socio-economic factors. DEA is performed with the school inputs only. Efficiency measures obtained from DEA are subsequently related to the socio-economic factors in a regression model with a one-sided disturbance term. The findings suggest that while productivity of school inputs varies considerably across districts this can be ascribed to a large extent to differences in the socio-economic background of the communities served. Variation in managerial efficiency is much less than what is implied by the DEA results.
The technique for efficiency measurement known as Data Envelopment Analysis (DEA) has been extended to allow non-discretionary inputs that affect production. Several methods exist for measuring efficiency while controlling for these fixed factors of production. This paper reviews these approaches, providing a discussion of strengths and weaknesses and highlighting potential limitations. In addition, a new approach is developed that overcomes existing weaknesses. To facilitate comparison, an analysis using simulated data is performed. The results show that the new approach improves existing models and performs relatively well.
A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs. A scalar measure of the efficiency of each participating unit is thereby provided, along with methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs. Equivalences are established to ordinary linear programming models for effecting computations. The duals to these linear programming models provide a new way for estimating extremal relations from observational data. Connections between engineering and economic approaches to efficiency are delineated along with new interpretations and ways of using them in evaluating and controlling managerial behavior in public programs.
Existing measures of technical inefficiency obtained through linear programming models in the public sector do not properly control for environmental variables that affect production. It will be shown that the consequences of not controlling for these fixed factors are biased estimates of technical efficiency. This paper extends the mathematical programming approach to frontier estimation known as Data Envelopment Analysis to allow for environmental variables. This modified model will be then contrasted with the existing model that purportedly controls for exogeneous factors to measure public sector efficiency with simulated data. The results provide evidence that the existing Data Envelopment Analysis model will overestimate the level of technical inefficiency and that the modified model developed in this paper does a better job controlling for exogenous factors. The modified model is also applied to analyze the technical efficiency of school districts.
In this paper, we highlight the importance of appropriately dealing with non-controllable inputs in technical efficiency evaluations by using DEA. In order to do this, the two most important options that exclusively use DEA methodology for the incorporation of these variables – the one-stage model by Banker and Morey [Operations Research 34(4) (1986a) 513] and the three-stage method developed by Fried and Lovell [Searching the Zeds, Working paper presented at II Georgia Productivity Workshop, 1996] – are compared both methodologically and empirically. At the same time, we propose a modification to the latter model which allows us to improve its results and interpretation. The education sector has been selected for the empirical application, the reason being that it has the desirable feature that, in the productive process, the students' socio-economic and family status (a non-controllable input) has a direct influence on the school results.The results obtained show the superiority of the multi-stage approach. It is argued that the model developed by Banker and Morey does not deal appropriately with inefficient units, as producer's behaviour in this model does not reflect the objective situation faced by such DMUs.
Benchmarking competitive banking units using ‘Handicapped’ DEA
- Z Yang
- J C Paradi
Yang Z, Paradi JC. Benchmarking competitive banking units using 'Handicapped' DEA. Omega, 2003, submitted for
publication.