4 edition of Two stage evaluation of bank branch efficiency using data envelopment analysis found in the catalog.
Two stage evaluation of bank branch efficiency using data envelopment analysis
Stephen J. Rouatt
Thesis (M.A.Sc.) -- University of Toronto, 2003.
|Series||Canadian theses = -- Thèses canadiennes|
|The Physical Object|
|Pagination||2 microfiches : negative.|
Coprigt P- E- Binus Business Review, 8(2), August , DOI: /bbr.v8i The Evaluation of Bank Efficiency in Post Merger Stage in Banking Industry Rahmat Siauwijaya. Identifying the efficiency levels is a major concern in efficiency analysis. We examined several efficiency measures in Bangladeshi commercial banks during the period and detect the difference in efficiency measurement excluding state-owned and then Islamic banks using a data envelopment analysis (DEA).
Amongst the frontier efficiency analyses identified in the literature, Data Envelopment Analysis (DEA) was found to be one of the leading approaches. DEA has been successfully applied in many bank branch performance evaluations using traditional intermediation, profitability and production approaches. This handbook serves as a complement to the Handbook on Data Envelopment Analysis (eds, W.W. Cooper, L.M. Seiford and J, Zhu, , Springer) in an effort to extend the frontier of DEA research. It provides a comprehensive source for the state-of-the art DEA modeling on .
The main reason of cost inefficiency is the excess of clients' deposits in the banks' balance sheet. In the second stage, I use the panel data analysis and estimate the determinants of cost efficiency in the two countries. I choose 8 bank-specific and macroeconomic factors that influence cost efficiency. The early literature on bank efficiency has focused mainly on total productivity  and bank branch efficiency [8, 9].Recent studies have trended towards the relationship between bank efficiency and risk management [10–13].The results in these articles demonstrate that the incorporation of financial risk variables (e.g., NPLs or risky assets) into the analysis of efficiency estimation and.
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Two-stage evaluation of bank branch efficiency using data envelopment analysis. a two-stage Data Envelopment Analysis approach is developed for simultaneously benchmarking the performance of operating units along different dimensions (for line managers) and a modified Slacks-Based Measure model is applied for the first time to aggregate the Cited by: There are two key motivations for this paper: (1) the need to respond to the often observed rejections of efficiency studies' results by management as they claim that a single-perspective evaluation cannot fully reflect the operating units' multi-function nature; and (2) a detailed bank branch performance assessment that is acceptable to both line managers and senior executives is still needed.
Two-stage evaluation of bank branch efficiency using data envelopment analysis Article in Omega 39(1) January with Reads How we measure 'reads'.
Two-stage evaluation of bank branch efﬁciency using data envelopment analysis Joseph C. Paradia, Stephen Rouattb, Haiyan Zhua a Centre for Management of Technology and Entrepreneurship, University of Toronto, College Street, Toronto, Ontario, Canada L5J 2S6 b McKinsey & Company, London, UK article info Article history: Received 11 August Two-stage evaluation of bank branch efficiency using data envelopment analysis Omega, Vol.
39, No. 1 A Comparative Study on Performance Measurement of Decision-Making Units: A Case Study in Iranian Tejarat BanksCited by: "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol.
39(1), pagesJanuary. Schaffnit, Claire & Rosen, Dan & Paradi, Joseph C., " Best practice analysis of bank branches: An application of DEA in a large Canadian bank," European Journal of Operational Research, Elsevier, vol.
Journal of Banking and Finance 9 () North-Holland BANK BRANCH OPERATING EFFICIENCY Evaluation with Data Envelopment Analysis H. David SHERMAN Massachusetts Institute of Technology, Cambridge, MAUSA Franklin GOLD PRIME Computer Inc., Natick, MA O, USA Received Marchfinal version received October Measuring and evaluating the operating efficiency of bank.
This paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance.,Different statistical and data mining techniques are used to second-stage DEA for bank performance as a part of an attempt to produce a powerful model for bank performance with effective predictive ability.
Measuring Bank Branch Performance Using Data Envelopment Analysis (DEA): The Case of Turkish Bank Branches African Journal of Business Management, 5(3), – DOI: /AJBM Data Envelopment Analysis (DEA) is a better way to et al.  investigated the use of quantitative variable in bank branch evaluation using DEA.
Paradi and Schaffnit  obtain a different aspect of efficiency measures. The most important two approaches are the production approach and. This study employed the CCR model of Data Envelopment Analysis (DEA) and the slack variable analysis to evaluate the operating efficiency of the domestic banks in Taiwan from to Bank branch operating efficiency: evaluation with data envelopment analysis Pages Download PDF.
Authors: Roozbeh Talebi Zarinkamar, Akbar Alam-Tabriz. Keywords: Banking industry, Data envelopment analysis, DEA, Efficiency. Camanho, A.S. and Dyson, R.G. (), “Efficiency, size, benchmarks and targets for bank branches: an application of data envelopment analysis”, Journal of the Operational Research Soci – Google Scholar.
A Two-Stage DEA Model for Efficiency Evaluation of a Mobile Operator’s Branch Network (#1) and Output (#1) of Bank Branches and their Relative Efficiency (Output-Oriented) Table 1–2a Input (#1) and Outputs (#2) of Bank Branches and their The book, entitled Data Envelopment Analysis.
Including customer satisfaction measures in bank branch performance assessment Abstract This study reports a method for integrating customer satisfaction data into a DEA (Data Envelopment Analysis) model for exploring bank branch efficiency. It is confirmed that inclusion of an unadjusted customer satisfaction score.
This paper presents a new approach for quantifying a bank's managerial efficiency, using a data-envelopment-analysis model that combines multiple inputs and outputs to compute a scalar measure of efficiency and quality.
An analysis of banks over a five-year period shows significant differences in management-quality scores between surviving. This approach further develops the work on efficiency evaluation and on estimation of efficient production frontiers known as data envelopment analysis (DEA).
We also employ the model to provide efficient input and output targets for DMU managers in a way that specifically accounts for the fixed nature of some of the inputs or outputs.
universal agreement on the specification of bank efficiency and the challenge still remains in selecting the most suitable methodology for this task. At least two different approaches are commonly used: Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). Data Envelopment Analysis (DEA) First type of DEA was proposed by.
Bank branch operating efficiency: Evaluation with Data Envelopment Analysis. Measuring and evaluating the operating efficiency of bank branches requires analytic techniques that provide insights beyond those available from accounting ratio analysis.
Data envelopment analysis Introduction. Data envelopment analysis (DEA), occasionally called frontier analysis, was first put forward by Charnes, Cooper and Rhodes in It is a performance measurement technique which, as we shall see, can be used for evaluating the relative efficiency of decision-making units (DMU's) in organisations.
Here. Measuring Bank Branch Performance in Pakistan: Data Envelopment Analysis (DEA).alternative forms of financial analysis. This paper describes a particular methodology called Data Envelopment Analysis (DEA), that has been usedpreviously to analyze the relative effi-cienciesof industrial firms, universities, hospitals, military operations, baseball players and, more recently, commercial banks.2 The use of flEA is.On a bank branch level, constant returns to scales are preferred, because they are more in line with the experience of the bank branch managers (Athanassopoulos et al., ).
The mathematical formulation of the CCR models is described in the Appendix. Efficiency benchmarking of bank branches using DEA: a literature review.