Transformation of wealth produced into quality of life: analysis of the social efficiency of nation-states with the DEA’s triple index approach

Although an essential condition for the occurrence of human development, economic growth is not always efficiently converted into quality of life by nation-states. Accordingly, the objective of this study is to measure the social efficiency—the ability of a nation-state to convert its produced wealth into quality of life—of a set of 101 countries. To achieve this goal, the Data Envelopment Analysis method was used in its standard, cross-multiplicative and inverted form, by means of a new approach called ‘triple index’. The main results indicated that the former Soviet republics and Eastern European countries stood out in terms of social efficiency. The developed countries, notwithstanding their high social indicators, did not excel in efficiency; however, the countries of south of Africa, despite having the worst social conditions, were also the most inefficient.     

A DEA methodology to evaluate the impact of information asymmetry on the efficiency of not-for-profit organizations with an application to higher education in Brazil

This paper presents a conceptual framework and an analytical DEA model for evaluating the impact of information asymmetry on organizational efficiency. The framework uses concepts from agency theory to estimate the extent of moral hazard by comparing the objectives of the principal to those of the agent. The framework and model are useful in the analysis of both for-profit and not-for-profit organizations because DEA is applicable whether or not inputs and/or outputs are subject to pricing mechanisms. An illustration focusing on the Brazilian not-for-profit federal university system finds that the agency problem indeed exists for a subset of those institutions, indicating the desirability of improved incentive and control mechanisms on the part of the principal.     

Ecological modernization in the electrical utility industry: An application of a bads–goods DEA model of ecological and technical efficiency

Newly-developed data envelopment analysis techniques permit simultaneous consideration of ‘good and bad’ outputs in evaluating efficiency. We use these techniques to determine joint ecological and technical efficiencies of the 437 largest fossil-fueled electricity-generating plants in the United States. Utilizing the EPA’s E-Grid and Clean Air Markets databases and drawing on ecological modernization theory we evaluate whether innovations in organizational practices and technological solutions help achieve joint technical and environmental performance efficiencies.     

Chapter 12 New uses of DEA and statistical regressions for efficiency evaluation and estimation — with an illustrative application to public secondary schools in Texas

This paper examines new combinations of Data Envelopment Analysis (DEA) and statistical approaches that can be used to evaluate efficiency within a multiple-input multiple-output framework. Using data on five outputs and eight inputs for 638 public secondary schools in Texas, unsatisfactory results are obtained initially from both Ordinary Least Squares (OLS) and Stochastic Frontier (SF) regressions run separately using one output variable at-a-time. Canonical correlation analysis is then used to aggregate the multiple outputs into a single aggregate output, after which separate regressions are estimated for the subsets of schools identified as efficient and inefficient by DEA. Satisfactory results are finally obtained by a joint use of DEA and statistical regressions in the following manner. DEA is first used to identify the subset of DEA-efficient schools. The entire collection of schools is then comprehended in a single regression with dummy variables used to distinguish between DEA-efficient and DEA-inefficient schools. The input coefficients are positive for the efficient schools and negative and statistically significant for the inefficient schools. These results are consistent with what might be expected from economic theory and are informative for educational policy uses. They also extend the treatments of production functions usually found in the econometrics literature to obtain one regression relation that can be used to evaluate both efficient and inefficient behavior.     

The effective application of a new approach to the generalized orienteering problem

The Orienteering Problem (OP) is an important problem in network optimization in which each city in a network is assigned a score and a maximum-score path from a designated start city to a designated end city is sought that is shorter than a pre-specified length limit. The Generalized Orienteering Problem (GOP) is a generalized version of the OP in which each city is assigned a number of scores for different attributes and the overall function to optimize is a function of these attribute scores. In this paper, the function used was a non-linear combination of attribute scores, making the problem difficult to solve. The GOP has a number of applications, largely in the field of routing. We designed a two-parameter iterative algorithm for the GOP, and computational experiments suggest that this algorithm performs as well as or better than other heuristics for the GOP in terms of solution quality while running faster. Further computational experiments suggest that our algorithm also outperforms the leading algorithm for solving the OP in terms of solution quality while maintaining a comparable solution speed.     

The application of spectral distribution of product of two random matrices in the factor analysis

In the factor analysis model with large cross-section and time-series dimensions,we pro- pose a new method to estimate the number of factors.Specially if the idiosyncratic terms satisfy a linear time series model,the estimators of the parameters can be obtained in the time series model. The theoretical properties of the estimators are also explored.A simulation study and an empirical analysis are conducted.     

On the efficiency of the WKB–Galerkin method in differential equations with variable coefficients

We have proposed an algorithm for the solution of inhomogeneous singular second-order differential equations with variable coefficients, based on a model of the hybrid WKB–Galerkin method. The efficiency of this approach is illustrated in the solution of an applied problem describing heat removal through a radiator of variable geometry. Translated from Matematychni Metody ta Fizyko-Mekhanichni Polya, Vol. 51, No. 1, pp. 82–87, January–March, 2008.     

The effects of exogenous variables in efficiency measurement—A monte carlo study

A Monte Carlo study is conducted to compare the stochastic frontier method and the data envelopment analysis (DEA) method in measuring efficiency in situations where firms are subject to the effects of factors which are beyond managerial control. In making efficiency measurements and comparisons, one must separate the effects of the environment (the exogenous factors) and the effects of the productive efficiency. There are two basic approaches to account for the effects of exogenous variables: (1) an one-step procedure which includes the exogenous variables directly in estimating the efficiency measures, and (2) a two-step procedure which first estimates the relative ‘gross’ efficiencies using inputs and outputs, then analyzes the effects of the exogenous variables on the ‘gross’ efficiency. The results show that the magnitude of exogenous variables does not appear to have any significant effect on the performance of the one-step stochastic frontier method as long as the exogenous variables are correctly identified and accounted for. However, the effects of exogenous variables are significant for the two-step approach, especially for the DEA methods.     

A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect

In observational cohort mortality studies with prolonged periods of exposure to the agent under study, it is not uncommon for risk factors for death to be determinants of subsequent exposure. For instance, in occupational mortality studies date of termination of employment is both a determinant of future exposure (since terminated individuals receive no further exposure) and an independent risk factor for death (since disabled individuals tend to leave employment). When current risk factor status determines subsequent exposure and is determined by previous exposure, standard analyses that estimate age-specific mortality rates as a function of cumulative exposure may underestimate the true effect of exposure on mortality whether or not one adjusts for the risk factor in the analysis. This observation raises the question, which if any population parameters can be given a causal interpretation in observational mortality studies?In answer, we offer a graphical approach to the identification and computation of causal parameters in mortality studies with sustained exposure periods. This approach is shown to be equivalent to an approach in which the observational study is identified with a hypothetical double-blind randomized trial in which data on each subject's assigned treatment protocol has been erased from the data file. Causal inferences can then be made by comparing mortality as a function of treatment protocol, since, in a double-blind randomized trial missing data on treatment protocol, the association of mortality with treatment protocol can still be estimated.We reanalyze the mortality experience of a cohort of arsenic-exposed copper smelter workers with our method and compare our results with those obtained using standard methods. We find an adverse effect of arsenic exposure on all-cause and lung cancer mortality which standard methods fail to detect.     

Applying a hybrid DEA model to evaluate the influence of marketing activities to operational efficiency on Taiwan’s international tourist hotels

This study uses the hybrid DEA model, in which the proportionate inputs are evaluated with a radial measure and the non-proportionate inputs are evaluated with a non-radial measure in order to evaluate the impact of marketing expense on the efficiency of Taiwan's international tourist hotels. We further introduce the hybrid DEA into the technology gap measurement to evaluate the technology gaps of marketing expense utilization between different operating types. The empirical results indicate that the inefficiency caused from excess marketing expense is the main reason for lower efficiency in many tourist hotels, especially to chain-operated hotels and hotels that cater to domestic clients. Through the hybrid technology gap measurement, we find that the utilization of marketing resources is more effective for independent, city type hotels, as well as those that cater to international clients.     

Cost allocation in the establishment of a collaborative transportation agreement—an application in the furniture industry

Transportation is an important part of the Canadian furniture industry supply chain. Even though there are often several manufacturers shipping in the same market region, coordination between two or more manufacturers is rare. Recently, important potential cost savings and delivery time reduction have been identified through transportation collaboration. In this paper we propose and test on a case study involving four furniture companies, a logistics scenario that allows transportation collaboration. Moreover, we address the key issue of cost savings sharing, especially when heterogeneous requirements by each collaborating company impact the cost-savings. To do so, we propose a new cost allocation method that is validated through a case study. Sensibility analysis and details about the actual outcome of the case study complete the discussion.     

About the stability of the inverse problem in 1-D wave equations—application to the interpretation of seismic profiles

This paper is devoted to the study of the following inverse problem: Given the 1-D wave equation: (1) $$\begin{gathered} \rho (z)\frac{{\partial ^2 y}}{{\partial t^2 }} - \frac{\partial }{{\partial z}}\left( {\mu (z)\frac{{\partial y}}{{\partial z}}} \right) = 0 z > 0,t > 0 \hfill \\ + boundary excitation at z = 0 + zero initial conditons \hfill \\ \end{gathered} $$ how to determine the parameter functions (ρ(z),μ(z)) from the only boundary measurementY(t) ofy(z, t)/z=0. This inverse problem is motivated by the reflection seismic exploration techniques, and is known to be very unstable. We first recall in §1 how to constructequivalence classes σ(x) of couples (ρ(z),ρ(z)) that areundistinguishable from the givenboundary measurements Y(t). Then we give in §2 existence theorems of the solutiony of the state equations (1), and study the mappingσ→Y: We define on the set of equivalence classes Σ={σ(x)|σ _min ?σ(x) ? σ _max for a.e.x} (σ _min andσ _max a priori given) a distanced which is weak enough to make Σ compact, but strong enough to ensure the (lipschitz) continuity of the mappingσ→Y. This ensures the existence of a solution to the inverse problem set as an optimization problem on Σ. The fact that this distanced is much weaker than the usualL ² norm explains the tendency to unstability reported by many authors. In §3, the case of piecewise constant parameter is carefully studied in view of the numerical applications, and a theorem of stability of the inverse problem is given. In §4, numerical results on simulated but realistic datas (300 unknown values forσ) are given for the interpretation of seismic profiles with the above method.     

Modeling the interaction of an electromagnetic field with a two-dimensional surface in the framework of symanzik’s approach

Symanzik’s approach to the construction of models for the interaction between quantum fields and macroobjects allows finding the general form of the action functional with a Chern-Simons potential up to an arbitrary dimensionless constant; it is used to describe the interaction of a material surface with the electromagnetic field. We discuss results obtained in static models of such a type. We also consider a simple dynamic model of the interaction of a massless scalar field with moving planes.     

Technology selection: application of the PROMETHEE in determining preferences—a real case of nanotechnology in Iran

PROMETHEE (Preference Ranking Organization METHod for Enrichment) is a family of outranking methods. In this paper, we explore its application to technology selection by first providing a generic comparison of PROMETHEE with other ranking methods. We start our investigation by comparing the strengths and weaknesses of PROMETHEE to prevalently used methods in technology selection, such as Analytic Hierarchical Process (AHP), technology selection framework and Fuzzy Analytic Hierarchical Process (FAHP with Fuzzy Delphi). We then explain how PROMETHEE can be applied to a particular technology selection application by detailing the steps for selecting among various nanotechnology application fields. Lastly, we compare PROMETHEE to other methods in this context and explain the advantages and constraints of its use.     

The markov property of the filter in the finitely additive white noise approach to nonlinear filtering †

It is shown that the nonlinear filter is a measure-valued Markov process on a finitely additive probability space.     

Efficient application of nonlinear stationary operators in adaptive wavelet methods—the isotropic case

This paper deals with the efficient application of nonlinear operators in wavelet coordinates using a representation based on local polynomials. In the framework of adaptive wavelet methods for solving, e.g., PDEs or eigenvalue problems, one has to apply the operator to a vector on a target wavelet index set. The central task is to apply the operator as fast as possible in order to obtain an efficient overall scheme. This work presents a new approach of dealing with this problem. The basic ideas together with an implementation for a specific PDE on an L-shaped domain were presented firstly in [38]. Considering the approximation of a function based on wavelets consisting of piecewise polynomials, e.g., spline wavelets, one can represent each wavelet using local polynomials on cells of the underlying domain. Because of the multilevel structure of the wavelet spaces, the generated polynomial usually consists of many overlapping pieces living on different spatial levels. Since nonlinear operators, by definition, cannot generally be applied to a linear decomposition exactly, a locally unique representation is sought. The application of the operator to these polynomials now has a simple structure due to the locality of the polynomials and many operators can be applied exactly to the local polynomials. From these results, the values of the target wavelet index set can be reconstructed. It is shown that all these steps can be applied in optimal linear complexity. The purpose of the presented paper is to provide a self-consistent development of this operator application independent of the particular PDE, operator, underlying domain, types of wavelets, or space dimension, thereby extending and modifying the previous ideas from [38].     

The Minimum FIll—in for the Corona of Two Graphs

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The complexity of nonlinear dynamic economic systems—the Kaldorian model with bond finance of the government

We are concerned with the existence of limit cycles in the macroeconomic model of the bond finance recently developed by Asada. It is shown that small shifts of the policy may result in structural changes when the system is at a critical state. The Hopf bifurcation theorem is applied to identify cycles.