Mette Asmild

Measuring overall efficiency and effectiveness using DEA

This paper presents a framework where data envelopment analysis (DEA) is used to measure overall efficiency and show how to apply this framework to assess effectiveness for more general behavioral goals. The relationships between various cone-ratio DEA models and models to measure overall efficiency are clarified. Specifically it is shown that as multiplier cones tighten, the cone-ratio DEA models converge to measures of overall efficiency. Furthermore, it is argued that multiplier cone and cone-ratio model selection must be consistent with the behavioral goals assigned or assumed for purposes of analysis. Consistent with this reasoning, two new models are introduced to measure effectiveness when value measures are represented by separable or linked cones, where the latter can be used to analyze profit-maximizing effectiveness.

Railway Reforms: Do They Influence Operating Efficiency?

This paper considers railway operations in 23 European countries during 1995-2001, where a series of reform initiatives were launched by the European Commission, and analyses whether these reform initiatives improved the operating efficiency of the railways. Efficiency is measured using Multi-directional Efficiency Analysis, which enables investigation of how railway reforms affect the inefficiencies of specific cost drivers. The main findings are that the reform initiatives generally improve operating efficiency but potentially differently for different cost drivers. Specifically, the paper provides clear empirical evidence that accounting separation is important for improving operating efficiency for both material and staff costs, whereas other reforms only influenced one of these factor.

Multi-directional efficiency analysis of efficiency patterns in Chinese banks 1997–2008

DEA-type efficiency studies are often used to investigate levels of efficiencies, differences in those levels between subgroups within a data set and possible determinants of such differences. In the current paper we show how differences in the efficiency patterns between different subgroups within a data set can be investigated using the more recent MEA methodology. We specifically look at the case of Joint Stock Banks and State Owned Banks in China and are able to empirically test hypotheses of whether there are differences not only in the levels but also in the patterns of inefficiencies between the two types of banks that is, which variables the inefficiencies are located on. We argue that certain differences are expected, based on differences in objectives and constraints in the two types of banks and find empirical support for most of those expected patterns.

Using Data Envelopment Analysis in Software Development Productivity Measurement

The ever-increasing size and complexity of software systems make the cost of developing and maintaining software important. Unfortunately, the process of software production has not been particularly well understood. This article helps clarify the relationship between postimplementation function points (FP) and the corresponding development effort for software development projects in a large Canadian bank. Knowledge of this relationship enables evaluations of the productivity of completed projects and, in particular, provides a predictive tool for future projects. The empirical analysis employs a combination of traditional regression models and Data Envelopment Analysis (DEA). The regression analyses show a log-linear relationship between project size and development effort, which is subsequently used in the DEA models. The DEA models identify best performers and use these as benchmarks, but are not limited to the constant returns to scale assumption of the regression analyses and are capable of including the delivery time as a nondiscretionary input. Finally, by including data from the International Software Benchmarking Standards Group (ISBSG) repository in the DEA models, the banks projects are benchmarked not only against its own best performers but also against what is globally feasible. Copyright

DEA based models for reallocations of police personnel

A difficult aspect of improving the efficiency of service organisations in the developed world is the need to lay-off experienced people, whose training had significant costs and where later replacements are both costly and time consuming. This paper shows a novel way to reallocate personnel resources between tasks within a specific unit as well as between similar units using a data envelopment analysis model set. As there are many different ways to reallocate people, we propose six different scenarios to provide for different circumstances or policy objectives that may exist in the organisations. The method is illustrated using police units in a major metropolitan area and the results herein illustrate how efficiency improvements can be made in the police units’ operations with very different impacts on the people involved for the various scenarios. This method saves resources and improves operating efficiency while allowing management to consider or compare the results following from different objectives. In some cases it may also preserve morale amongst the personnel, when the necessary productivity and efficiency improvements are made in ways that specifically aims at also minimising the impact on the personnel.

Banking efficiency analysis under corporate social responsibilities

This paper expands the banking efficiency literature by developing a banking intermediation model that captures both profit-maximising and corporate social responsibilities (CSRs) of banks. Using a dataset of 21 banks for each year 2006 to 2008, we evaluate the relative efficiency of Ghanaian banks using data envelopment analysis (DEA) thus contributing to the scanty research on African banks. We observe a significant difference between the DEA model that includes CSR and the other without CSR, an indication that the inclusion of CSR may be important for bank efficiency assessment. As a further analysis, we use a second stage OLS regression which confirms a positive relationship between CSR and profitability and efficiency indicators. The findings suggest that considering CSR in efficiency assessment of banks is not only important on conceptual grounds, but also indicates that banks that are socially responsible may have economic advantages.

Do efficiency scores depend on input mix? A statistical test and empirical illustration

In this paper we examine the possibility of using the standard Kruskal-Wallis (KW) rank test in order to evaluate whether the distribution of efficiency scores resulting from Data Envelopment Analysis (DEA) is independent of the input (or output) mix of the observations. Since the DEA frontier is estimated, many standard assumptions for evaluating the KW test statistic are violated. Therefore, we propose to explore its statistical properties by the use of simulation studies. The simulations are performed conditional on the observed input mixes. The method, unlike existing approaches in the literature, is also applicable when comparing distributions of efficiency scores in more than two groups and does not rely on bootstrapping of, or questionable distributional assumptions about, the efficiency scores. The approach is illustrated using an empirical case of demolition projects. Since the assumption of mix independence is rejected the implication is that it, for example, is impossible to determine whether machine intensive project are more or less efficient than labor intensive projects.

Frontier Differences and the Global Malmquist Index

This chapter reviews different ways of comparing the efficiency frontiers for subgroups within a data set, specifically program efficiency, the metatechnology (or technology gap) ratio and the global frontier difference index. The latter is subsequently used to define a global Malmquist index, as well as in an alternative decomposition of the traditional Malmquist index which also considers socalled favourability and favourability change components, indicating whether individual observations are located in favourable positions in the production space based on the extent of frontier shifts they observe. The various approaches are illustrated in an empirical case of Ghanaian banks.

Testing over-representation of observations in subsets of a DEA technology

This paper proposes a test for whether data are over-represented in a given production zone, i.e. a subset of a production possibility set which has been estimated using the non-parametric Data Envelopment Analysis (DEA) approach. A binomial test is used that relates the number of observations inside such a zone to a discrete probability weighted relative volume of that zone. A Monte Carlo simulation illustrates the performance of the proposed test statistic and provides good estimation of both facet probabilities and the assumed common inefficiency distribution in a three dimensional input space. Potential applications include tests for whether benchmark units dominate more (or less) observations than expected.

A Method for Comparison of Efficiency Scores: A Case Study of Danish Dairy Farms

This paper suggests the use of a particular parametric test when comparing the efficiency scores resulting from efficiency analysis. As an illustrative case Data Envelopment Analysis (DEA) is run on a set of Danish dairy farm data. Assuming that the efficiency scores resulting from DEA are right censored log-normally distributed, the influence of potential external factors affecting the efficiency can be investigated. It is found that efficiency increases with size and more surprisingly, that farms with jersey cows tend to be more efficient than non-jersey farms.