Journal of CENTRUM Cathedra

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Subject: search.filters.subject.Data envelopment analysis

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    Competitiveness Among Higher Education Institutions: A Two-Stage Cobb-Douglas Model for Efficiency Measurement of Schools of Business
    (Pontificia Universidad Católica del Perú. CENTRUM, 2014) Avilés-Sacoto, Sonia Valeria; Cook, W. D.; Güemes-Castorena, David
    In this paper, we present a methodology for evaluating competing organizations in order to identify best practices among those organizations. We focus attention specifically on competitiveness in the context of a set of business schools for the purpose of identifying those that appear to be most efficient relative to their peers. One of the most widely recognized efficiency measurement methodologies is data envelopment analysis (DEA). DEA literature has witnessed the expansion of the original concept to encompass a wide range of theoretical and applied research areas, with one such area being network DEA, with two-stage DEA in particular. This latter concept and its extensions to multi-stage situations have been particularly influential in such settings as supply chain management. In the conventional two-stage serial model, it is assumed that in each stage efficiency will be defined by the standard ratio of weighted outputs to inputs or inputs to outputs. This depends on whether an input or output orientation is chosen. In terms of the model used, we develop a two-stage approach where at each stage we define efficiency in terms of a Cobb-Douglas function. This serves two important purposes. First, the data in this particular setting appears in the form of percentages or ratings. Therefore, a geometric mean which the Cobb-Douglas function is based on might be deemed as more appropriate than the arithmetic mean concept at the center of the conventional model. Second, unlike some of the previous models that define the aggregate efficiency of the process as the simple product of the scores for the two stages, the Cobb-Douglas structure permits one to define aggregate efficiency as a weighted product of those scores. This permits one to place greater emphasis on one stage versus the other. This allows for a sensitivity analysis on the effect of the “stage weights” on the aggregate score and on the individual scores that make up that aggregate.
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    Monitoring Public Company Rankings for Investment Decisions: Are They Undervalued or Overvalued?
    (Pontificia Universidad Católica del Perú. CENTRUM, 2013) Wu, Wei-Wen; Lan, Lawrence; Lee, Yu-Ting
    This study proposes a novel framework to monitor the rankings of public companies that are released periodically by worldwide business organizations. With different ranking rationales and diverse indicators, the released reports may not be comparable or suited to investment objectives. Therefore, this study introduces the DuPont model to derive well-recognized common investment indicators and then employs the data envelopment analysis (DEA) ranking method and the grey entropy (GE) ranking method to re-rank the listed companies. Both DEA and GE re-rankings are compared with the released rankings to generate a map of the DEA-gap versus the GE-gap to advise stock investors of undervalued or overvalued companies. As a demonstration, the proposed framework is applied to the case of Taiwan Info Tech 100 released by Business Next. It is thought that continual monitoring of public company rankings may promote business opportunities in the long run; hence, application of the proposed framework to develop favorable business models is further addressed in this study.
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    Evaluating the Efficiency of Turkish Banks: A Risk and Profitability Approach
    (Pontificia Universidad Católica del Perú. CENTRUM, 2013) Eken, Mehmet Hasan; Kale, Süleyman
    Conventional performance indicators, especially after recent financial restructuring initiatives, are criticized more than ever for not associating performance and risk. The purpose of this study is to benchmark performance of banks in comparison to risk-taking preferences, under different models with data envelopment analysis, to evaluate whether risks are reasonably priced. Comparing a bank’s risk efficiency with its competitors may provide additional insights to regulatory and supervisory authorities together with bank management. The results indicate that profitability of banks is not necessarily parallel with their risk-taking preferences. Banks with low risk efficiency should revise their business style for potential improvements.
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    Benchmarking Peruvian Banks using Data Envelopment Analysis
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Charles, Vincent; Kumar, Mukesh; Zegarra, Luis Felipe; Avolio, Beatrice
    Despite the growing literature on bank efficiency worldwide over the last decade, researchers have neglected the Peruvian banking sector. In this paper, the technique of data envelopment analysis (DEA) is used to investigate the efficiency of Peruvian banks for the period 2000 to 2009 to benchmark currently existing banks based on their super-efficiency scores over time. Further, an in-depth analysis of currently existing banks for the period 2008 to 2009 is conducted to check the robustness of DEA efficiency scores and the potential improvement of inputs and outputs for inefficient banks, indicating by how much and in what areas inefficient banks need to improve in order to be efficient. Our finding shows an increasing trend in technical efficiency during the period 2000 to 2009 which gives an indication of an affirmative effect of the reform process in the Peruvian banking sector. On average, the multinational banks are performing better than are domestic banks throughout the period except in 2007, during which a sharp decline in efficiency performance for both the groups was apparent, possibly a result of global financial turmoil. The application of jackknifing analysis with appropriate statistical tools shows the DEA efficiency scores are robust. Among the 14 currently existing banks, Banco Ripley and Banco Santander Peru were the best performers, whereas Banco Azteca was the worst performer, followed by Interbank and Banco de Comercio. Furthermore our findings suggest that inefficient banks require more rigorous policies with respect to the allocation of funds for additional loans as well as other earnings assets. In this way, presently inefficient banks may approach the efficiencies of the best practice banks.
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    Natural Resources Exchange Traded Funds: Performance Appraisal using DEA Modeling
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Tsolas, I. E.
    The purpose of this paper is to evaluate the performance of a sample of natural resources exchange traded funds (ETFs) by applying a two-stage procedure. In the first stage, the generalized proportional distance function (GPDF) in the data envelopment analysis (DEA) context is used for the first time to measure the relative efficiency of sectoral ETFs. In the second stage, a Tobit model is employed to identify the drivers of performance. The results indicate there is scope for efficiency improvement for about half or more of the sample funds depending on the variables used in the assessments, and fund performance can be explained by fund persistence and the beta coefficient.