Efficiency frontier on Japanese banking system

Since the emergence of the efficiency frontier techniques, a series of comparisons between the methods that led to the resultant efficiency has been presented. In this paper, data from 99 Japanese banks are used in order to prove the applicability of efficiency frontier analysis on the East-Asian financial system and to reveal the differences between inter and intra-regional banks, showing the effect of the present financial crisis on the efficiency of the studied banks. DEA and FDH are used to determine the technical and scale efficiency of the analyzed banks and also it compares fully efficient banks by ranking them through the super-efficiency notion.This work was co-financed from the European Social Fund through the Sectoral Operational Programme Human Resources Development 2007–2013, project number POSDRU 159/1.5/S/134197 “Performance and excellence in doctoral and postdoctoral research in Romanian economics science domain”

Canonical correlation analysis and DEA for azorean agriculture efficiency

In this paper we will document the application of canonical correlation analysis to variable aggregation using the correlations of the original variables with the canonical variates. A case study, about farms in Terceira Island, with a small data set is presented. In this data set of 30 farms we intend to use 17 input variables and 2 output variables to measure DEA efficiency. Without any data reduction procedure several problems known as “curse of dimensionality” are expected. With the data reduction procedures suggested it was possible to conclude quite acceptable and domain consistent conclusions.N/

The technical efficiency of Public Libraries in the Czech Republic

The purpose of this article is to define and evaluate the development of the aggregated technical efficiency of public libraries in the Czech Republic from 1993 to 2014. To simulate technical efficiency, the Data Envelopment Analysis Model (The BCC model) was chosen. To evaluate the production units (the unit of the Czech Republic from 1993 to 2014 and its production is given by the sum of real homogenous units, i.e. the public libraries operating in a given area and in a given time), two input variables (the recalculated number of employees and the library collection) and two output variables (the number of registered readers and the number of loans) were analysed. Two basic models were simulated – the M1 model oriented to inputs and the M2 model oriented to outputs. Correlation between the input and output variables was researched using Pearson’s coefficient. Within the range of the M1 and M2 basic models, partial models were simulated. All of the basic and partial models identically showed eight efficient periods of public libraries in the Czech Republic (1995, 1997, 1999–2000, 2002–2005). Public libraries were, according to the chosen variables, inefficient in the remaining 16 observed years

Azorean agriculture efficiency by PAR

The producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimizing their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study, and, at the same time, to the need of timely and inexpensive information. The “Productivity Analysis with R” (PAR) framework establishes a user-friendly data envelopment analysis environment with special emphasis on variable selection and aggregation, and summarization and interpretation of the results. The starting point is the following R packages: DEA (Diaz-Martinez and Fernandez-Menendez, 2008) and FEAR (Wilson, 2007). The DEA package performs some models of Data Envelopment Analysis presented in (Cooper et al., 2007). FEAR is a software package for computing nonparametric efficiency estimates and testing hypotheses in frontier models. FEAR implements the bootstrap methods described in (Simar and Wilson, 2000). PAR is a software framework using a portfolio of models for efficiency estimation and providing also results explanation functionality. PAR framework has been developed to distinguish between efficient and inefficient observations and to explicitly advise the producers about possibilities for production optimization. PER framework offers several R functions for a reasonable interpretation of the data analysis results and text presentation of the obtained information. The output of an efficiency study with PAR software is self- explanatory. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores (Mendes et al., 2009). All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of “good” practices and cluster of “less good” practices. This makes PAR appropriate to support public policies in agriculture sector in Azores.N/

Multi-level DEA Approach in Research Evaluation

It is well known that the discrimination power of DEA models will be diminishing if too many inputs or outputs are used. It is a dilemma if the decision makers want to select comprehensive indicators to present a relatively holistic evaluation using DEA. In this work we show that by utilizing hierarchical structures of input-output data DEA can handle quite large numbers of inputs and outputs. We present two approaches in a pilot evaluation of 15 institutes for basic research in Chinese Academy of Sciences using DEA models

Measuring Eco-efficiency of Production: A Frontier Approach

Eco-efficiency of production is an important concept both from the viewpoint of society and business community; but as yet, there is no unambiguous way to its measurement. The purpose of this paper is to present a general measurement framework based on production theory and the activity analysis approach. Although we exploit the existing methods and techniques, our approach diverges essentially from the usual treatments of the environmental performance of firms in the productive efficiency analysis. The main difference between our approach and the earlier studies is that we build on the definition of eco-efficiency as the ratio of economic value added to the environmental damage index. Related to this orientation, we also approach eco-efficiency from a more aggregate perspective. Our general framework is illustrated by an empirical application to the evaluation of eco-efficiency of road transportation in Finland.Eco-efficiency, Environmental Pressures, Aggregation, Benefit of the Doubt Weighting, Distance Function, Activity Analysis, Data Envelopment Analysis, Road transportation

Incorporating Undesirable Outputs into Malmquist TFP Index: Environmental Performance Growth of Chinese Coal-Fired Power Plants

In this article we examine the effects of undesirable outputs on the Malmquist TFP indices. Our empirical work uses an unbalanced panel which covers 796 utility and non-utility coal-fired power plants in China during 1996-2002. In order to meet the requirement of a balanced panel for calculating the Malmquist indices, an innovative fake unit approach has been introduced. Our final results show that (1) the growth of the Chinese electricity heavily depends upon an increase of resource input; and (2) huge potential remains with regards to the efficiency improvement and emissions control in Chinese coal-fired power plants

Analyzing Product Efficiency – A Customer-Oriented Approach

The purpose of this study is to provide a broader, economic perspective on customer value management. By developing an efficiency-based concept of customer value we aim at contributing to the presently underrepresented research field of marketing economics. The customer value concept is utilized to assess product performance and eventually to determine the competitive market structure and the product-market boundaries. Our analytical approach to product-market structuring based on customer value is developed within a microeconomic framework. We measure customer value as the product efficiency viewed from the customer’s perspective, i.e., as a ratio of outputs (e.g., resale value, reliability, safety, comfort) that customers obtain from a product relative to inputs (price, running costs) that customers have to deliver in exchange. The efficiency value derived can be understood as the return on the customer’s investment. Products offering a maximum customer value relative to all other alternatives in the market are characterized as efficient. Different efficient products may create value in different ways using different strategies (output-input- combinations). Each efficient product can be viewed as a benchmark for a distinct sub-market. Jointly, these products form the efficient frontier, which serves as a reference function for the inefficient products. Thus, we define customer value of alternative products as a relative concept. Market partitioning is achieved endogenously by clustering products in one segment that are benchmarked by the same efficient peer(s). This ensures that only products with a similar output-input structure are partitioned into the same sub-market. As a result, a sub-market consists of highly substitutable products. In addition, value-creating strategies (i.e., indications of how to vary inputs and outputs) to improve product performance in order to offer maximum customer value are provided. The impact of each performance parameter on customer value is determined, identifying the value drivers among them. This methodological framework is applied to data of the 1996 German Automobile Club (ADAC) survey.Customer Value, Data Envelopment Analysis (DEA), Efficiency Analysis, Market Partitioning, Product-Market Structuring