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There are still important theoretical and empirical gaps in understanding the role of best practices (BPs), such as quality management, lean and new product development, in generating firm's performance advantage and overcoming trade-offs across distinct performance dimensions. We examine these issues through the perspective of performance frontiers, integrating in novel ways the resource-based theory with the emergent practice-based view. Hypotheses on relationships between BPs, performance advantage, and trade-offs are developed and tested with stationary and longitudinal (recall) data from a global survey of manufacturing firms. We use data envelopment analysis, which overcomes limitations of mainstream methods based on central tendency. Our findings support the view that BPs may serve as a source of enduring competitive advantage, based on their ability to lead to a heterogeneous range of dominant and difficult-to-imitate competitive positions. The study provides new insights on contemporary debates about the role of BPs in generating performance advantage and how practitioners can sustain internal support and extract benefits from them. [ABSTRACT FROM AUTHOR]

The nonparametric estimator of the Extended Facet reference technology for the Constant Returns to Scale case has attracted some attention, because the associated production frontier by construction does only include strongly efficient faces of maximal dimension, or strongly efficient faces that are part of such strongly efficient faces of maximal dimension. The strongly efficient faces of maximal dimension are denoted Full Dimensional Efficient Facets (FDEFs). The identification of such strongly efficient facets is facilitated by removing all inefficient and all strongly efficient but not extreme efficient DMUs from the estimation procedure of the technology set. Any face that i) is passing through the origin and with (s + m − 1) linear independent extreme efficient observed DMUs positioned on it and ii) with a normal vector with strict positive (strict negative) output (input) components, is a FDEF, where s (m) is the number of outputs (inputs). It is, however, not correct that every face that satisfies only i) is a FDEF. We denote a face (a subface) that satisfies only condition i) but not condition ii) for an AP-face (an AP-subface). It is proved that a radial projection of any output input combination in the estimated EXFA technology set is positioned on the strongly efficient frontier if and only if i) no AP-(sub)faces exist, ii) a regulaty condition RC1 is satisfied and only dual multiplier constraints corresponding to extreme efficient DMUs are included in the estimation. A test for the fulfillment of the condition that no AP-(sub)faces exist is provided. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an optimization model to quantify the trade-off between resource capacity utilization and disposition time for the caseload of courts of justice. The optimization model takes into account the impact of an increase in demand that may arise when disposition time is reduced. We employ the model to measure the impact of various policy reform scenarios on the length of trials, both at the court and system level. We do so by taking into account the potential reallocation of resources, using the population of Italian courts of justice over the 2005–2012 period. Our results show that if all policy scenarios we discuss were to be implemented, the average length of trials for civil cases would be more than halved, from the current 15.5 months to about 7 months. Implementing best practices, the single most effective policy would be equivalent to a 25% increase in the number of judges (which would otherwise cost around 100 million euros per year). [ABSTRACT FROM AUTHOR]

Innovation is often seen as crucial for firm survival and as a way for firms to differentiate themselves from their rivals. However, innovation studies are vague about the actual importance of different innovation strategies. In this study, we distinguish between pure product, process, organizational, and marketing innovations and their combinations. We use a (balanced) panel data set with more than 15,000 firm-year observations for manufacturing firms to analyze the performance of firms with different innovation strategies. Additionally, we investigate from a societal perspective whether innovation facilitates less efficient firms to catch up, or whether firms already utilizing best practices are the main beneficiaries. Using Data Envelopment Analysis (DEA), we find the highest increase in firms' performance among the firms with innovation strategies that combine product innovation with other innovation types. This finding applies to both the short and the longer term. We also conclude that catch-up is strongest among the firms adopting pure process innovation, whereas the other innovation strategies are primarily associated with frontiers shifts. [ABSTRACT FROM AUTHOR]

Nonparametric methods have been commonly used to assess the performance of both private and public organizations. Among them, the most popular ones are envelopment estimators such as Free Disposal Hull (FDH) or Data Envelopment Analysis (DEA), which estimate the attainable sets and their efficient boundaries by enveloping the cloud of observed units in the appropriate input-output space. However, these nonparametric envelopment techniques do not provide estimates of marginal products and other coefficients of economic interest. This paper presents a new approach that provides local estimates of all the desired partial derivatives and economic coefficients, which complement and complete the analysis based on nonparametric envelopment estimators. We improve nonparametric estimators by estimating nonparametrically smoothed efficient boundaries and providing derivatives and other coefficients without having to assume any parametric structure for the frontier and the inefficiency distribution. Our approach offers several advantages, such as a flexible nonparametric adjustment of the efficient frontier based on local linear models; a general multivariate efficiency model based on directional distances where one can choose the desired benchmark direction; the possibility of assessing the impact of external-environmental variables; a bootstrap-based statistical inference for deriving confidence intervals on the estimated coefficients for nonparametric and robust frontier approximations; the possibility of including factors aggregating inputs or outputs and recovering the estimated coefficients in the original units. To demonstrate the usefulness of the proposed approach, we provide an illustration in the field of education, where economic coefficients are important but the parametric assumptions have been questioned. [ABSTRACT FROM AUTHOR]

This paper investigates the contribution of industrial robots to labor productivity growth and cross-country economic convergence in a sample of 19 developed and 16 emerging countries over the period 1999 to 2019. To answer our research questions, we extend the non-parametric production frontier framework by considering industrial robots as a separate production factor. We find a positive contribution of robotization to labor productivity growth for all countries in our sample. In the period after the financial crisis (2009 to 2019) the contribution of robot capital deepening to productivity growth gained in importance. Over the period 1999 to 2019 we find some evidence of i) unconditional β-convergence (countries with lower initial productivity levels grow faster), ii) a reduction in the dispersion of productivity levels across economies (σ-convergence) and iii) a depolarization (shift from bimodal to unimodal distribution) of the labor productivity distribution in our sample. Accumulation of 'traditional' physical capital is the main driver of β-convergence. Robot capital deepening significantly contributed to economic convergence and the depolarization of the labor productivity distribution, but its effect on the entire shift of the labor productivity distribution is modest and dominated by other drivers of productivity growth such as 'traditional' physical capital deepening and technological change. [ABSTRACT FROM AUTHOR]

This contribution focuses on extending the current state of the art in a central resource allocation planning model known under the name of the short-run Johansen industry model in three ways. First, we correct a long-standing issue of the correct choice of weight variables on the capacity distribution by guaranteeing that these weights determine production combinations that belong to the production technology on which the plant capacity estimates are based in the first place. Second, we exploit the gap between average practice and best practice models by introducing an efficiency improvement imperative that allows for partial technical inefficiency when planning. Third, instead of only considering output-oriented plant capacity, we allow for alternative plant capacity concepts. In particular, we introduce an input-oriented plant capacity concept, and an alternative attainable output-oriented plant capacity concept that corrects a major empirical issue in the traditional output-oriented plant capacity notion. These methodological refinements are illustrated with a data set on U.S. fishing vessels by developing a planning model to curb overfishing. [ABSTRACT FROM AUTHOR]

Congestion is a well-known economic phenomenon in which excessive inputs lead to a decrease in the maximum possible outputs. This study analyzes the relationship between congestion and overinvestment using a data envelopment analysis framework to reveal that some congestion can be eliminated by increasing inputs. The proposed approach classifies congestion into two categories, relative and absolute congestion, depending on the possibility of eliminating congestion by increasing inputs. Corresponding methods for identifying and measuring congestion are proposed and employed for empirical analyses examining China's papermaking and paper products industry. We find that most congestion in 2013–2016 is in the relative congestion and could be eliminated by increasing inputs. The primary causes of congestion are identified based on our analysis and corresponding policy suggestions are proposed for eliminating congestion. [ABSTRACT FROM AUTHOR]

This paper addresses the efficiency measurement of firms composed by multiple components, and assessed at different decision levels. In particular it develops models for three levels of decision/production: the subunit (production division/process), the DMU (firm) and the industry (system). For each level, inefficiency is measured using a directional distance function and the developed measures are contrasted with existing radial models. The paper also investigates how the efficiency scores computed at different levels are related to each other by proposing a decomposition into exhaustive and mutually exclusive components. The proposed method is illustrated using data on Portuguese hospitals. Since most of the topics addressed in this paper are related to more general network structures, avenues for future research are proposed and discussed. [ABSTRACT FROM AUTHOR]

In recent years, spatial dependence in production frontier models has attracted considerable research attention. This is explained, among other things, by the observation that in many economic sectors, decisions on taxes, expenditure, research and development, etc., are likely to be interconnected across production units. Consequently, the assumption that (benchmarked) production units operate in isolation from their peers may no longer be valid. In this article, we review and summarize this literature. First, we identify a set of analyses in the production frontier field that take into account spatial dependence based on a systematic search in the Web of Science and Scopus databases from 1975 to 2022, and provide global insights into this subfield. We find that this literature is relatively young: we trace the first contribution back to 2004 and, until 2011, the number of analyses per year remained relatively low (one per year at most). Second, we analyze identified articles in depth, classify them, and briefly outline avenues for future research. We hope that this will enable researchers to navigate this subfield and develop it further. We observe that the majority of these articles use parametric methods (e.g., stochastic frontier analysis) over nonparametric ones (e.g., data envelopment analysis). We also note that while in the nonparametric framework, the objective of the vast majority of contributions is to distinguish the intrinsic performance of productive units by the contribution of their territories, contributions in the parametric framework are more diverse. Highlights: We identify analyses in the frontier field that consider spatial dependence. We observe that this literature is relatively young but fast-growing. Most of these analyses use parametric methods over nonparametric ones. We classify the analyses and outline avenues for future research. This literature could benefit from putting identification issues at its center. [ABSTRACT FROM AUTHOR]

In this paper, we model a performance measure of water utilities, considering an undesirable output: the amount of water lost within the network during distribution. We improve three methodological approaches in traditional production technology modeling with an undesirable output. We first adapt the model to the specificities of water production and distribution network. We then extend the analysis to include the economic objectives of three different stakeholders - a regulator that seeks to preserve this natural resource, the operator who wants to maximize his profit, and the consumer who seeks maximum consumption - in the context of a developing country with unfulfilled water demand. Finally, using our model, we estimate the economic value of lost water by its shadow marginal cost, which enables us to evaluate the cost of loss on the water grid in each of the scenarios. We then propose an empirical application for water production in Côte d'Ivoire. [ABSTRACT FROM AUTHOR]

A substantial part of production and trade now takes place through global value chains (GVC), making it an essential conduit of knowledge spillover and technology transfer. Yet, extant studies examining how countries become productively efficient and catch-up to the global efficiency frontier through international trade have ignored the possible role of GVC in fast-tracking this process. This paper provides the first empirical evidence that fills this knowledge gap. We propose a two-stage empirical strategy to this end. First, we use a data envelopment analysis (DEA) approach to compute a measure of productive efficiency—defined herewith as a country's relative productive efficiency to the global productive efficiency frontier. Second, we use the productive efficiency index as an outcome variable in a reduced-form equation that controls for GVC participation and its interaction with country characteristics that influence the gains from GVC participation. In addition to using the panel fixed effect method, we estimate the reduced-form equation with the difference-GMM to address endogeneity issues, and the Tobit and Fractional Response models to address the bounded nature of the productive efficiency index. We find strong evidence suggesting that GVC participation enables technology-lagging countries to become more productively efficient as well as catch-up to the global efficiency frontier. We also find that the productive efficiency and catch-up gains from GVC participation accrue more strongly to countries that have a high human capital stock, a well-functioning financial market, maintain stable macroeconomic conditions, and specialize in downstream activities in the value chain. [ABSTRACT FROM AUTHOR]

A simple yet easy to implement method is proposed to further improve the finite sample approximation of the recently developed central limit theorems for aggregates of envelopment estimators. Focusing on the simple mean efficiency, we propose using the bias-corrected individual efficiency estimate to improve the variance estimator. The extensive Monte-Carlo experiments confirm that, for relatively small sample sizes (≤100), with both low dimensions and especially for high dimensions, our new method combined with the data sharpening method generally provides better 'coverage' (of the true values by the estimated confidence intervals) than the previously developed approaches. [ABSTRACT FROM AUTHOR]

The question of how to properly model production systems with unintended outputs has proven both controversial and of particular interest to the productivity and efficiency community. The paper explains why some of the arguments put forward in these controversies are hardly convincing for industrial and other processes. Among other things, there is a lack of clear conceptual labelling of the different types of joint production, especially coupled production, which is the main source of undesirable and other unintended outputs, unless neglected. It is largely ignored that the desirability of such by-products may depend on the quantity produced. This is also true for reduction processes such as waste incineration or end-of-life vehicle dismantling, which in turn generate new unintended outputs. As a rule, industrial material and energy balances are modelled implicitly. Koopmans' activity analysis is the standard approach in modelling production systems with undesirable outputs in the literature of business economics on sustainable production and supply chain management. With data envelopment analysis (DEA), instead of entire production possibilities, it is sufficient to know only certain local properties in the relevant range of input and output quantities of the observed activities. This lowers the challenge to verify their empirical validity. [ABSTRACT FROM AUTHOR]

Frontier-based capacity utilization (CU) measures are the mainstream in CU evaluation of either firms or productive units in various fields. Traditional CU models have not developed a reasonable way to solve the incomparability problem, since efficiencies of the decision making units (DMUs) under a given production technology are not comparable to those of other DMUs under a different technology, which exists especially in data envelopment analysis (DEA) methods. To solve this problem, this paper proposes a systematic solution for the measurement of CU change over time, which reveals the variation of CU among different periods. To overcome the prevalent infeasibility problem since one or more DMUs cannot be projected onto the frontier in a certain direction, we further incorporate fixed-base global and overall techniques in redefining CU and CU change indices. To illustrate the effectiveness of our proposed models, we also employ a sample of Chinese universities to conduct the empirical analysis. [ABSTRACT FROM AUTHOR]

The drinking water and wastewater services often involve heterogenous production environments and considerable negative externalities such as greenhouse gas emissions. Conventional productivity measurements do not factor in either of these issues. This paper analyses the environmentally sensitive productivity change in the Australian drinking water sector whilst including greenhouse gas emissions and group heterogeneities simultaneously. It uses a smooth bootstrap metafrontier Malmquist-Luenberger production frontier framework to decompose the productivity change into efficiency change, best practice frontier change, and technical gap ratio change for 2006 to 2015 using utility-level data. The method circumvents the limitations of convexification strategy when determining the intertemporal and global directional distance functions. The findings indicate that the environmentally sensitive productivity of the Australian drinking water sector has improved for the overall study period but declined in the periods of 2006/07 to 2008/09, 2010/11 and 2012/13. The large utilities have made the most improvement in closing the gap between the within-group and global frontiers. [ABSTRACT FROM AUTHOR]

Understanding the drivers of productivity remains one of the most sought after phenomena in economics. The ability to create produce more from less resources is undoubtedly appealing. Using recently updated Penn World Table data, we investigate to what degree previous results using a popular productivity decomposition are maintained. We find that, contrary to conclusions from earlier work, technical efficiency (catching up) played a more pronounced role in the global increase in productivity over the 1965–1990 period. We also find a larger effect for technical change than earlier work and a far lesser role for capital deepening. This suite of results augurs the coming information age that placed less weight on physical capital to create and sustain wealth. Taken together our findings here suggest that as data collection, its quality and evaluation methods evolve, so too will our understanding of productivity dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we adapt the ZSG-DEA model to the case of a reverse output, whose larger (smaller) values reflect lower (higher) achievements. Then, we introduce the zero-sum reverse output redistribution strategies, state the resulting Target's Assessment Theorem for both the proportional and the equal expansion strategy, and confirm that the Benchmarks' Contribution Equality Theorem is also applicable to these cases. We also apply the ZSG-DEA model with a forward and a reverse output to estimate respectively teams' offensive and defensive efficiency in Greek premier soccer league. [ABSTRACT FROM AUTHOR]

Advanced efficiency measurement methods usually fall within Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA), or their derivatives. Although SFA has some theoretical advantages, it has been criticized for relying on arbitrary and potentially restrictive assumptions about model specification. One strand of the literature suggests the use of nonparametric SF models to cope with the issue. We follow an alternative path and demonstrate that it is possible to deal with specification uncertainty and potentially restrictive assumptions while maintaining the advantages of the parametric approach. First, we develop a flexible stochastic model based on generalized t and generalized beta of second kind distributions, which encompasses virtually all known parametric SFA specifications. Second, we apply Bayesian inference methods, which are less restrictive than those used so far, and propose feasible approximate alternatives based on maximum likelihood. Third, we pool results from alternative specifications using model averaging. Our focus is on the distributional assumptions regarding the compound error in SFA since this aspect has not been addressed so far in a satisfactory way. However, extensions to other elements of specification uncertainty, like the choice of the frontier functional form, are straightforward. Finally, we show simulations results and analyze two well-researched datasets, for which we obtain probabilistic (density) estimates of efficiency scores that take into account the estimation error and model uncertainty in a formally justified manner. [ABSTRACT FROM AUTHOR]

Using data from the Brazilian Higher Education Census and other public institutions, this study aims to obtain and compare efficiency scores from stochastic frontier analysis (SFA) and data envelopment analysis (DEA) models for 56 Brazilian federal universities for the period of 2010 to 2016. The output distance function includes financial and human resources as inputs, and teaching, research, patents and third mission activities as outputs. The research is innovative considering: (i) the estimation of SFA for Brazilian universities as whole institutions, (ii) its comparison with DEA; and (iii) the inclusion of patents and third mission variables. The findings suggest there is inefficiency in Brazilian higher education production, with a very small increase through time and with some influence from universities and environmental characteristics. Thus, consolidated traditional institutions with university hospitals tend to be more efficient than the younger ones. The values and the rank of the efficiencies are sensitive to the model/method employed, presenting highly significant although modest correlations. In general, the inclusion of third mission activities improves the efficiencies for both approaches, mainly for DEA. Hence, as advised in other international comparative analyses, caution is required when deriving management and policy recommendations from the analytical results. [ABSTRACT FROM AUTHOR]

Recently, the elasticity of response measures revealing the marginal characteristics of efficient frontiers have been developed and generalized for different types of DEA production technologies. In theory, the elasticity measures can be calculated for the units on the efficient frontier that satisfy a selective radial efficiency assumption. This corresponds to a subset of the evaluated units. In this research, we propose to extend the elasticity measurement to the entire production possibility set (technology) by stratifying the units to different levels of efficient frontiers. The stratification idea is inspired by the commonly known context-dependent DEA based on the exclusion of efficient units at each iteration and obtaining multiple levels of frontiers. We build the proposed methodology on the idea that a DEA technology theoretically consists of several frontiers and calculating elasticity measures on all frontiers may provide additional information on the returns-to-scale (RTS) characteristics of all the units whether they are on the first-level frontier or not. The proposed methodology is presented in an empirical application using the Farm Accountancy Data Network (FADN) data of the agricultural farms operating in the Aegean Region of Turkey. The results reveal that the proposed method enables us to obtain a wider perspective on the RTS characterizations of DEA production technologies. [ABSTRACT FROM AUTHOR]

Applications of efficiency and productivity analysis in which some inputs and outputs are given in the form of percentages, averages and other types of ratio measures are sufficiently common in the literature. In two recent papers, the authors developed the variable and constant returns-to-scale technologies with both volume and ratio types of inputs and outputs, referred to as the R-VRS and R-CRS technologies. These technologies are generally nonconvex and have a complex structure. In this paper we explore this in detail. We show that the R-VRS technology can be stated as the union of a finite number of specially constructed standard VRS technologies. Similarly, the R-CRS technology in which all ratio inputs and outputs are of the fixed type, which are typically used to represent environmental and quality factors, can be stated as the union of a finite number of partial polyhedral cones. We show that these results have important theoretical, including conceptual, implications. [ABSTRACT FROM AUTHOR]

This research defines the energy intensity target of the contemporaneous metafrontier and global metafrontier in order to assist decision-makers at identifying the efficient energy intensity target. We find that the sources of energy intensity improvement under the global metafrontier are due to three reasons: managerial inefficiency, technology gap inefficiency, and global technology gap inefficiency. In addition, the measurement of the energy intensity target also extends to that of energy productivity changes. The research applies data envelopment analysis (DEA) to empirically study Brazil, Russia, India, China, and South Africa (BRICS) and the Group of Seven (G7) countries and demonstrates that the BRICS group exhibits a larger scope for energy intensity improvement than the G7 group, but that both groups should still pay greater attention to energy technology promotion to improve energy intensity. A win–win strategy for the two groups to achieve this is by fully realizing energy technology transfer from high-tech to low-tech countries. [ABSTRACT FROM AUTHOR]

In this paper, we derive conditions under which merger between a number of firms within the same industry would induce a more cost efficient production of the aggregate output bundle, especially in the short-run, and show that potential cost economies from a merger can be attributed to three factors: convexity of the technology, sub-additivity of the ray short-run total cost curve, and a trade-off between reduction in the variable cost and increase in fixed cost arising from an aggregation of the fixed inputs of the merging units. We use this proposed analytical framework to evaluate the gains from various recent bank mergers in India. We employ the nonparametric method of Data Envelopment Analysis for retrospectively quantifying the potential gain from specific mergers and its components both in the short-run and in the long-run. [ABSTRACT FROM AUTHOR]

This article provides a generalization of the materials balance-based production model introduced by Coelli et al. (2007). Based on this, some new environmental efficiency (EE) measures are presented. The Coelli et al. (2007) EE measure and its extension by Rødseth (2016) produce biased efficiency estimates if the material flow coefficients (MFCs) are heterogeneous across decision-making units and non-discretionary. Furthermore, the Coelli et al. (2007) measure fails to reward emission reductions by emission control. To overcome these shortcomings, this paper proposes production models which allow for heterogeneous MFCs reflecting differences of external environmental factors or non-controllable heterogeneities in inputs and outputs, and which properly take into account emission abatement activities. Based on this, EE measures are provided and decomposed into (i) a part reflecting emission control efficiency (ECE), (ii) a part measuring material input efficiency (MIE), and (iii) a part reflecting the efficient allocation between material and non-material inputs (environmental allocative efficiency, EAE). The approach is illustrated by an empirical application to arable farming in Austria utilizing data from 90 farms for the year 2011. Soil erosion is considered an undesirable output and land a material input. The average EE, ECE, MIE, and EAE are 0.53, 0.96, 0.69, and 0.79, respectively. The results indicate that actual output can be potentially achieved with 47% less soil loss. Most of the potential to improve EE is due to differences in MIE and EAE. Removing inefficiencies in the implementation of existing, subsidized erosion controls allows soil loss to be reduced by 4%. [ABSTRACT FROM AUTHOR]

The paper deals with the technical efficiency evaluation under the fixed proportion technologies (FPTs) assumption where nonsubstitutable inputs and outputs are present. The recent research has shown that the conventional data envelopment analysis (DEA) models used for FPTs are biased, and when inputs and outputs are not substituted for either technological or other reasons, the models that account for nonsubstitutability need to be employed. This paper discusses a technical efficiency decomposition under FPTs and proposes two new models for quantification of contribution of various sources to overall inefficiency. The first model, called the calculation-based model, is a purely parametric model for efficiency decomposition, whereas the second model, called the adjusted CCR model, is a combination of parametric and nonparametric DEA approach. Using the models presented in the paper, the overall efficiency measure is decomposed into three main components: Farrell efficiency component, input mix efficiency component and output mix efficiency component. The selected estimators, some of them newly developed, are compared with the true efficiency levels via Monte Carlo simulations to measure the accuracy of the models. The results demonstrate that the proposed models provide sufficiently reliable results and in terms of overall efficiency are comparable with existing models for measuring efficiency in FTP conditions. [ABSTRACT FROM AUTHOR]

In this paper, we propose a flexible two-stage data envelopment analysis (DEA) approach to evaluate the bank performance. Specifically, instead of fixing the role of the deposits in an ex-ante manner, the proposed approach regards deposits as a flexible measure in which it can play different roles for different banks under evaluation. Further, the traditional two-stage approach that regards deposits as an intermediate measure can be a special case of our proposed approach. Additionally, a potential Pareto efficiency improvement for multiple perspectives is identified, which can mitigate discontentment arisen from those fixed-role strategies. The applicability and superiority of the proposed approach is illustrated by assessing the performance of Chinese listed banks over the period from 2014 to 2018. The empirical results demonstrate consistent evidence that the inefficiency of the banking system in China is mainly sourced from the value-added stage. However, different banks may prefer to clarify different roles for the deposits, demonstrating the importance of employing the proposed flexible approach. [ABSTRACT FROM AUTHOR]

Benchmarking farms, in order to advise farmers to cure inefficiency, may be biased if heterogeneity is not accounted for. Technological variability in agriculture indeed happens, but productive efficiency analysis with frontier methods usually assumes homogeneity. Heterogeneity influences investment motives and production strategies, but is not always clear-cut, for example, when gradation in external inputs use occurs. Unfortunately, these indistinct (no clear-cut) differences in technologies are very common within farming communities, but have often been ignored by the advisors focusing on the discrete ones such as organic versus conventional farming. This paper explores indistinct heterogeneity in efficiency analysis, aiming at identifying peers/reference farms while reflecting on their significance for benchmarking. The gradual differentiation between low and high input dairy farms in Flanders is used as a case, based on a five-year balanced panel data for 58 farms. A data envelopment analysis (DEA) version of the meta-frontier approach is used to account for heterogeneity. The research revealed that, although stemming from a continuous distribution, low and high input farming can be considered as different strategies but none can be said to be superior to the other. Coupling the efficiency scores with peer information allows distinguishing good and bad performing efficient farms within each strategy, and thus improves benchmarking using frontier analysis. [ABSTRACT FROM AUTHOR]

Conventional models of data envelopment analysis (DEA) are based on the constant and variable returns-to-scale production technologies. Any optimal input and output weights of the multiplier DEA models based on these technologies are interpreted as being the most favorable for the decision making unit (DMU) under the assessment when the latter is benchmarked against the set of all observed DMUs. In this paper we consider a very large class of DEA models based on arbitrary polyhedral technologies, which includes almost all known convex DEA models. We highlight the fact that the conventional interpretation of the optimal input and output weights in such models is generally incorrect, which raises a question about the meaning of multiplier models. We address this question and prove that the optimal solutions of such models show the DMU under the assessment in the best light in comparison to the entire technology, but not necessarily in comparison to the set of observed DMUs. This result allows a clear and meaningful interpretation of the optimal solutions of multiplier models, including known models with a complex constraint structure whose interpretation has been problematic and left unaddressed in the existing literature. [ABSTRACT FROM AUTHOR]

This paper is concerned with the identification of the closest strong efficient target of a Decision Making Unit (DMU) in the Free Disposal Hull (FDH) technology in Data Envelopment Analysis (DEA). The paper uses the geometrical properties of the FDH Production Possibility Set (PPS) to design and test an enumeration algorithm to obtain the minimum distance from a DMU to the strong efficient frontier of the PPS, corresponding to each of the various returns to scale assumptions. The proposed method solves some simple optimization problems whose optimal solutions are obtained by calculating a limited number of ratios. Then, an attempt will be made to mitigate the problem of the lack of unit and translation invariance of the selected distances by considering weighted norms. Finally, the applicability of the presented method is illustrated by a numerical example using real data. [ABSTRACT FROM AUTHOR]

Traditional radial DEA models treat DMUs as black boxes, whose internal structures are ignored, and measure input and output changes proportionally. On the other hand, network DEA models consider the internal structure of a DMU as a network system where sub-processes are connected by intermediate products aside from consuming main inputs and producing final outputs. The interest in network DEA has increased over the years producing different types of formulations including the network slacks-based measure DEA (NSBM). NSBM is a non-radial network approach suitable for measuring efficiencies when inputs and outputs may change non-proportionally. However, NSBM models and some of its recent developments failed to adhere to three important efficiency measurement issues: (a) able to properly define overall and divisional efficiencies, (b) able to identify Pareto-Koopmans efficiency status, and (c) able to show equivalence of primal (multiplier) and dual (envelopment) forms of the network DEA model. This study addressed these issues based on the NSBM approach and compared the results of the proposed network SBM model with other existing models in the literature. A numerical study on 10 electric power companies further illustrated the use and significance of the proposed network SBM model in efficiency measurement. [ABSTRACT FROM AUTHOR]

Gross domestic product (GDP) has come under criticism as the only objective that countries should pursue for societal well-being. In this paper we apply an innovative Data Envelopment Analysis (DEA) approach for including two other pillars including an environmental dimension, reduction of carbon dioxide (CO2) emissions and social efforts for employment, health and education. By linking together three DEA models, we model a global technology that combines the objectives of the three pillars. Finally, by weighting each of them by different schemes, we illustrate the practicality of our approach to analyze policy trade-offs among economic, environmental, and social objectives. [ABSTRACT FROM AUTHOR]

Health care systems face resource scarcity that may jeopardise their financial sustainability as well as the quality of delivered health care. In view of that, the association between technical efficiency, access, and quality of services should be investigated, despite some past attempts that led to mixed, unclear, and perhaps biased results. We use a dataset composed of financial resources, hospital services, appropriateness and timeliness of care, patients' clinical safety, access to health care services, demographics, and epidemiology variables to study the aforementioned link regarding the Portuguese public hospitals (operating between 2013 and 2016). Quality and access data are aggregated into three main composite indicators, through Grey Relational Analysis (GRA). Bias- and environmentally corrected efficiency scores are estimated via bootstrap-based directional Data Envelopment Analysis. A double bootstrap algorithm is employed, using GRA-based quality indicators as predictors of technical efficiency. Evidence suggests that (1) Portuguese public hospitals exhibit low performance in terms of quality, while the different indicators present considerable correlation among them and with hospital size and patients' complexity characteristics; (2) patients' clinical safety, appropriateness and timeliness, as well as access to health care services are consistent and significant predictors of technical efficiency; and (3) the association between efficiency, quality, and access depends on the interaction between appropriateness, timeliness, and access. Therefore, quality and access can be improved with no efficiency sacrifice and vice versa. Highlights: We investigate the relationship between efficiency, quality and access in hospitals We use the Gray Relational Analysis to merge and simplify social performance data We use Data Envelopment Analysis to assess efficiency of public hospitals We use the double bootstrap for multiple regression (explanatory) analysis Efficiency, quality, and access to healthcare services evolve in the same sense. [ABSTRACT FROM AUTHOR]

Education is considered an important factor of economic growth, employment and social inclusion. However, the economic crisis has put the need to achieve educational goals in the most efficient way ever more to the fore. The main objective of this paper is to assess the spending efficiency of European compulsory educational systems, creating a ranking of countries based on the efficiency scores of their systems using a number of standard variables from the literature. To this end, we also present a methodological innovation that combines Data Envelopment Analysis (DEA) with discrete Multiple Criteria Evaluation (MCE), two methods that we consider complementary if used for providing a performance analysis. Moreover, both methods identify a set of common variables which are associated with higher levels of efficiency in educational systems (e.g. some characteristics of teachers, the stock of adults' human capital and lower expenditures per student). The results show that findings using DEA are largely confirmed by MCE. [ABSTRACT FROM AUTHOR]

Providing secure and affordable drinking water and sewerage services is the primary mandate of the urban water industry. Water businesses must balance their service obligations and the quality of service delivered in order to maximize customer value. Being a monopoly industry, the urban water sector's service levels and associated prices are not driven by competitive market pressures but through the regulatory processes. However, improving service quality often comes at a cost and yardstick regulation requires the evaluation and benchmarking of service quality within an economic efficiency framework. This paper uses a bootstrap Data Envelopment Analysis model to evaluate the service quality performance of the Australian urban water sector from 2009-2010 to 2015-2016. Specifically, the paper models the lack of service quality as undesirable outputs of water production. It estimates the Malmquist-Luenberger productivity index and its efficiency change and technical change components for 50 integrated water and sewerage utilities in Australia. Findings indicate that, overall, the sector's quality-adjusted productivity has improved after a marked decline in 2010/2011. A comparison of the service quality productivity results with the conventional productivity measure revealed that the conventional analysis tends to underestimate the productivity growth. The paper concludes that benchmarking service quality helps the urban water sector to move from compliance-based regulation to best-practice regulation. [ABSTRACT FROM AUTHOR]

The proposed method of Stochastic Non-smooth Envelopment of Data (StoNED) for measuring efficiency has to date mainly found application in the analysis of production systems which have exactly one output. Therefore, the objective of this paper is to examine the applicability of StoNED when a ray production function models a production technology with multi-dimensional input and output. In addition to a general analysis of properties required by a ray production function for StoNED to be applicable, we conduct a Monte Carlo simulation in order to evaluate the quality of the frontier and efficiencies estimated by StoNED. The results are compared with those derived via Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We show that StoNED provides competitive estimates in regard to other methods and especially in regard to the real functional form and efficiency. [ABSTRACT FROM AUTHOR]

Directional Distance Function (DDF) is an approach often used in data envelopment analysis (DEA) due to its clear interpretation and to the flexibility provided by the possibility of choosing the projection direction towards the efficient frontier. In this paper two new DDF approaches are considered. The first one uses an exogenous directional vector and a multi-stage methodology that at each step uses the projection along the input and output dimensions of the directional vector that can be improved. This lexicographic DDF approach also computes a directional efficiency score and a directional inefficiency indicator for each input and output variable. The second approach is a non-linear optimization model that endogenously determines the directional vector so that the smallest improvement required to reach the efficient frontier is computed. [ABSTRACT FROM AUTHOR]

Linking the theoretical predictions of the research on lending relationships with those of the literature on managerial incentives, we investigate whether the duration of credit relationships impacts on SMEs’ technical efficiency. Our hypothesis is that the balance between costs and benefits of enduring banking relationships might have heterogeneous effects on managers’ incentives depending on the level of firms’ indebtedness. Using a large sample of European SMEs, observed in the period 2001-2008, and adopting both parametric and non-parametric measures of efficiency, we find that the positive impact of longer lending relationships on efficiency decreases as indebtedness increases, suggesting that moral hazard problems may endanger firms’ technical efficiency. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic multidirectional inefficiency analysis approach within the context of Data Envelopment Analysis to measuring input- and investment-specific managerial and program inefficiency for groups of firms characterized by different technologies. Dynamic managerial inefficiency refers to the distance to the firms’ group-specific dynamic frontier of best practices, and dynamic program inefficiency measures the difference between the group-specific dynamic frontier and the pooled dynamic frontier. The empirical application focuses on panel data of large meat processing firms in Eastern, Western and Southern Europe over the period 2005–2012. The results show that Eastern European firms have the highest dynamic managerial inefficiency for all inputs, but have the smallest values for dynamic program inefficiency. Western European firms perform worst in terms of program inefficiency for all inputs, while Southern European firms are the best with regard to dynamic managerial inefficiency. The results also reveal that regardless the dynamic inefficiency dimension considered, investments is the most inefficient input, followed by labor, and materials. [ABSTRACT FROM AUTHOR]

Over the years following Debreu’s (1951) seminal formulation of a “coefficient of resource utilization”, a large number of indexes of technological inefficiency have been specified and a spate of papers has examined the properties satisfied by these indexes. This paper approaches the subject more synthetically, presenting generic results on classes of indexes and their properties. In particular, we consider a broad class of indexes containing almost all known indexes and a partition of this class into two subsets, slacks-based indexes and path-based indexes. Slacks-based indexes are expressed in terms of additive or multiplicative slacks for all inputs and outputs, and particular indexes are generated by specifying the form of aggregation over the coordinate-wise slacks. Path-based indexes are expressed in terms of a common contraction/expansion factor, and particular indexes are generated by specifying the form of the path to the frontier of the technology. Owing to an impossibility result in one of our earlier papers, we know that the set of all inefficiency indexes can be partitioned into three subsets: those that satisfy continuity (in quantities and technologies) and violate indication (equal to some specified value if and only if the quantity vector is efficient), those that satisfy indication and violate continuity, and those that satisfy neither. We prove two generic theorems establishing the equivalence of these two partitions: all slacks-based indexes satisfy indication and hence violate continuity, and all path-based indexes satisfy continuity and hence violate indication. We also discuss the few indexes that do not belong to either of these two sets. Our hope is that these results will help guide decisions about specification of the form of efficiency indexes used in empirical analysis. [ABSTRACT FROM AUTHOR]

This research contributes to the ongoing debate about differences in teachers’ performance. We introduce a new methodology that combines production frontier and impact evaluation insights that allows using DEA as an identification strategy of a treatment with high and low quality teachers within schools to assess their performance. We use a unique database of primary schools in Spain that, for every school, supplies information on two classrooms at 4th grade where students and teachers were randomly assigned into the two classrooms. We find considerable differences in teachers’ efficiency across schools with significant effects on students’ achievement. In line with previous findings, we find that neither teacher experience nor academic training explains teachers’ efficiency. Conversely, being a female teacher, having worked five or more years in the same school or having smaller class sizes positively affects the performance of teachers. [ABSTRACT FROM AUTHOR]