Opening the 'black box' of efficiency measurement: input allocation in multi-output settings

We develop a new Data Envelopment Analysis (DEA)-based methodology for measuring the efficiency of Decision Making Units (DMUs) characterized by multiple inputs and multiple outputs. The distinguishing feature of our method is that it explicitly includes information about output-specific inputs and joint inputs in the efficiency evaluation. This contributes to opening the „black box? of efficiency measurement in two different ways. First, including information on the input allocation substantially increases the discriminatory power of the efficiency measurement. Second, it allows to decompose the efficiency value of a DMU into output-specific efficiency values which facilitates the identification of the outputs the manager should focus on to remedy the observed inefficiency. We demonstrate the usefulness and managerial implications of our methodology by means of a unique dataset collected from the Activity Based Costing (ABC) system of a large service company with 290 DMUs.

Islamic Bank Efficiency: A Comparative Study Between Indonesia and Pakistan

This study aims to compare the efficiency level of full-fledged Islamic banks in Indonesia and Pakistan during the period 2012–2016 using data envelopment analysis method based on assumption of CRS, VRS and also scale efficiency. In addition, this study also aims to look at the factors mostly affecting the level of efficiency of the variables studied by using the data panel regression method. This study used four samples of BUS in Indonesia and four samples of BUS in Pakistan in the first to fourth quarter of 2012–2016. Considering the result of research, full-fledged Islamic banks in Indonesia are more efficient than full-fledged Islamic banks in Pakistan according to the assumption of CRS, VRS and Scale, but there is no significant difference of efficiency value between full-fledged Islamic banks in Indonesia and those in Pakistan. In Indonesia, the banks with the efficiency value closest to optimum value are Bank Muamalat Indonesia, Bank Syariah Mandiri and Bank BRI Syariah based on the assumption of CRS, VRS and Scale at 99 percent point, while the one with lowest efficiency is Bank BNI Syariah with mean value below 99 percent. In Pakistan, on average, the bank with efficiency value closest to the optimum efficiency is Al-Baraka Bank based on the assumption of CRS, VRS and Scale at 99 percent, while the one with the lowest ones are the Bank Islami Pakistan Limited and Meezan Islamic Bank Value based on VRS assumption, with efficiency value below 99 percent. However, based on CRS and Scale assumptions, Dubai Islamic Bank Pakistan Limited gets the lowest efficiency value. All good variables from fixed assets, personal costs, deposits, financing and other income to financial investment both partially or simultaneously affect significantly the efficiency value. The variable with the greatest effect on efficiency value is deposits, followed with financing, based on the existing samples.   Keywords: data envelopment analysis (DEA), constant return to scale (CRS), variable return to scale (VRS), Scale, full-fledged Islamic ban

Disentangling Within- and Between-Country Efficiency Differences of Bank Branches

In this paper we propose a framework to assess the efficiency of bank branch networks operating in different financial environments. The framework can be used to disentangle within- from between-country performance differences. The framework is constructive in that it identifies operational aspects responsible for superior performance and suggests guidelines for branch improvement. We report results from three bank branch networks in the U.K., Greece and Cyprus, and demonstrate how branch networks can benefit from such international comparisons.Bank Branch Efficiency, International Benchmarks, Data Envelopment Analysis.

Efficiency, Profitability and Quality of Banking Services

This paper develops a general framework for combining strategic benchmarking with efficiency benchmarking of the services offered by bank branches. In particular, the service-profit chain is cast as a cascade of efficiency benchmarking models. Three models-based on Data Envelopment Analysis (DEA)-are developed in order to implement the framework in the practical setting of a bank's branches: an operational efficiency mode, a quality efficiency model and a profitability efficiency model. The use of the models is illustrated using data for the branches of a commercial Bank. Empirical results indicate that superior insights can be obtained by analyzing operations, service quality, and profitability simultaneously than the information obtained from benchmarking studies of these three dimensions separately. Some relations between operational efficiency and profitability, and between operational efficiency and service quality are investigated. This paper was presented at the Financial Institutions Center's conference on Performance of Financial Institutions, May 8-10, 1997.

Technical and scale efficiency in Zambia's agro-progressing industry: a firm level data envelope analysis of the 2011/2012 manufacturing census

The implementation of privatization and Structural Adjustment Programs in Zambia saw the contribution of manufacturing in GDP significantly reduce from 37.2 percent in 1992 to 8.2 percent in 2013. Efforts to revamp manufacturing have not delivered to expectations and the industrial base has continued to be smaller than it used to be in the 1970s and 1980s. This has raised serious questions about suitable industrialization policies not only for Zambia but for other African countries as well. This study examines the agro-processing industry with a view to establish whether it can drive the development of Zambia's manufacturing. We start by exploring the growth opportunities and highlighting the key sectors of comparative advantage. Thereafter, we apply the Data Envelopment Analysis algorithm to construct measures of technical and scale efficiency for a sample of 115 firms using the 2011/2012 Economic Census data. Finally, we examine the effect of firm attributes on the firm's technical and scale efficiency using the Tobit regression model. The results reveal that there are sufficient growth opportunities in Zambia's agro-processing industry, but the industry is highly inefficient. The average technical efficiency was 42.5 percent while scale efficiency was 81.7 percent. The study also shows that firm efficiency is affected by firm size, the size of the firm's market share, labour costs, and location of the firm

Optimal Capacity Utilization and Reallocation in a German Bank Branch Network: Exploring Some Strategic Scenarios

Quite a few studies have considered efficiency at the bank branch level by comparing mostly a single branch network, while an abundance of studies have focused on comparing banking institutions. However, to the best of our knowledge no study has ever assessed performance at the level of the branch bank network by looking for ways to reallocate resources such that overall performance improves. Here, we introduce the Johansen-Färe measure of plant capacity of the firm into a multi-output, frontier-based version of the short-run Johansen industry model. The first stage capacity model carefully checks for the impact of the convexity assumption on the estimated capacity utilization results. Policy scenarios considered for the short-run Johansen industry model vary in terms of their tolerance with respect to existing bank branch inefficiencies, the formulation of closure policies, the reallocation of labor in terms of integer units, etc. The application to a network of 142 bank branches of a German savings bank in the year 1998 measures their efficiency and capacity utilization and demonstrate that by this industry model approach one can improve the performance of the whole branch network.Bank Branch Network, Efficiency, Capacity, Reallocation

EFFICIENCY PERFORMANCE ANALYSIS OF PANIN DUBAI SYARIAH BANK IN COLLECTING AND DISTRIBUTING THIRD PARTY FUNDS BEFORE AND AFTER MERGER

In this study, the researcher would make Panin Dubai Syariah Bank was the object of research on Islamic banks that carry out mergers and acquisitions. This research by using quarterly financial reports to determine the level of efficiency of the Panin Dubai Syariah Bank to be analyzed using the Data Envelopment Analysis (DEA) method. The researcher was used the annual report to find out the extent the Panin Dubai Syariah Bank carries out its Shariah values and objectives to be analyzed based on the Maqashid Index Sharia. The frontier approach can be divided into parametric approaches and non-parametric approaches. The parametric  approach  takes  measurements  using  stochastic  econometrics  and  seeks  to  eliminate interference from the effects of inefficiency. While the non-parametric approach with linear programs ( non-parametric linear programming approach ) performs non-parametric measurements using an approach is not stochastic and tends to combine the interference into inefficiency. This is based on the discovery and observation of the population and evaluates efficiency relative to the units observed. In the non- parametric method, the approaches that can be used are Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). The results of the measurement of Bank Panin Dubai Syariah using DEA indicate that the decision to merge carried out by Panin Syariah Bank with Dubai Islamic Bank was the right decision because, with the merger, Panin Dubai Syariah Bank could produce almost perfect efficiency value of 99% in the year 2015. With doing the merger, Bank Panin Dubai Syariah can minimize the inefficiencies that occur in the input variable so that it can maximize the efficiency that occurs in the output variabl

Relative efficiency in the branch network of a Greek bank : a quantitative analysis

Measuring and evaluating the efficient use of resources of Bank branches plays a decisive role in a Bank’s strategic planning. Usually, efficiency is measured by using accounting ratios, such as labor productivity, capital productivity, return on assets etc. When these ratios are properly used, they provide significant information regarding the effective operation of the branch, and contribute in carrying out intrabank comparisons and comparisons over a period of time. However, by using such ratios, an important part of the branch operation remains uncovered: the measurement of the effective use of the resources. New mathematical programming models that are related with the degree at which each branch makes use of its resources, are applied to deal with the weaknesses of such ratios. This study discuss the limitations of using accounting ratio analysis for assessing performance and, presents and interprets the results from the application of mathematical programming models in a sample of branches of a Greek Bank.peer-reviewe

A generalized fuzzy Multiple-Layer NDEA: An application to performance-based budgeting

Network data envelopment analysis (NDEA) is capable of considering operations and interdependence of a system’s component processes to measure efficiencies. There are numerous performance evaluation applications in which some indicators have hierarchical structures with a considerable number of sub-indicators. This problem of ignoring the hierarchical structure of indicators weakens the discrimination power of NDEA models and may result in inaccurate efficiency scores. In this paper we propose a generalized fuzzy Multiple-Layer NDEA (GFML-NDEA) model and GFML-NDEA-based composite indicators (GFML-NDEA-CI) to incorporate the hierarchical structures of indicators in the ambit of the particular two-stage NDEA models. To demonstrate the usefulness of the GFMLNDEA-CI model proposed, its application was tested by evaluating the efficiency of the performance-based budgeting (PBB) system in 14 governmental agencies in Iran. The comparative analysis results obtained from the GFML-NDEA-CI (multi-layer) model with those from the single-layer fuzzy NDEA-CI model indicate that the number of efficient decision-making units (DMUs) in the one-layer model is eight, whereas it is solely one DMU in the multi-layer model. The discrimination power of the multi-layer model proposed is significantly increased by observing that standard deviation of efficiency scores are increased by 41%, 61%, and 84% for possibility levels 0, 0.5, and 1, respectively. This is obtained while reducing information entropy, thus suggesting that the proposed model yields more reliable scores

Envelopment methodology to measure and compare subcontractor productivity at the firm level

This paper describes a conceptual approach to measure and compare productivity of resource utilization at the firm level, adapting a set of techniques known as Data Envelopment Analysis (DEA). Within this approach, the paper addresses the issues of multiple inputs and multiple outputs of a construction firm, level of detail for data collection, and the required transformations to correct for differences among projects. In particular, we focus on the resource management of subcontractors. Subcontractors manage multiple, concurrent projects and must allocate limited resources across these projects. Interaction between projects and resource allocation creates non-linear effects, and therefore the productivity of the firm is not simply the productivity of its projects. The proposed measurement methodology will allow assessment of the impact of different management policies (including many of those proposed by lean construction researchers) on firm performance. It is hoped that this novel approach to productivity measurement will help subcontractors identify efficient practices and superior management policies, and will promote adoption of these policies.<br /