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Luiz Fernando de Lyra Novaes's Lab
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Featured research (3)
Goal: This article presents a PMM - Performance Measurement and Management system which analyzes 72 regional managerial offices (RMO) found on the database of a banking institution. Each of the offices has a portfolio of investments in real estates in Brazil financed by the Banking Institution. The PMM gives diagnosis of the performance of each of these offices through a data mining procedure from the years 2015 to 2017 and suggest on how the worst performing offices can replicate the best performing ones.
Design / Methodology / Approach: The PMM was designed to estimate an efficient model by Data Envelopment Analysis (DEA). Ranks the efficiency of the RMOs and provides managerial solutions with the background information upon which to base decisions.
Practical implications: The design of PMM has the ability to enable the institution of processing a more flexible and dynamic performance management. The practical implications achieved are reported in systematic analysis approach that testify the quality and effectiveness of this PMM modeling in conclusion section at table 8.
Results: The proposed PMM is a new approach paradigm to institution, in the way to set the best results on account of resources available. The current method used per the Institution sets effectiveness targets without accounting the resources spent.
Limitations of the investigation: The restrictions in time and resources did not make possible compare the current organizational method with the proposed PMM. A main question was not answered if the effectiveness RMOs are efficient too, or, vice-versa.
Originality / method value: This article is innovative as it introduces the ability to perform simulations in the DEA environment, principally because its possibility to rearrange the modeling from the evolution of institution performance. Also, the corporate aspect of adopting a universalized methodology for evaluating efficiency.
Objective: This article innovates when we incorporate the statistical analysis to the method of Double-Perspective Data Envelopment Analysis (DP-DEA), with the objective of obtaining an estimate of greater accuracy and reliability according to the assumptions of the Best Unbiased Estimator (BUE).
Design / Research Method: Double Perspective Data Envelopment Analysis (DP-DEA) is an extension to Classical Data Envelopment Analysis (DEA) for estimating efficiency, asset values, indicators, and other attributes from two perspectives, achieving a common result is the main objective. This article innovates in DEA methodology, in two aspects: 1. To demonstrate the ability of the DP-DEA to perform at intervals the estimation of values from a random sample; 2. Through the statistical analysis, making estimates of central tendency according to the assumptions of the Best Unbiased Estimator (BUE – Best Unbiased Estimator).
Conclusions / findings: The practical procedures performed step by step through DP-DEA according to the assumptions of the BUE, presented in its main findings and conclusions are: 1. Incorporation of statistical analysis to the DP-DEA method, which assumes assumptions of properties of the Best Estimator Non-biased; 2. Within the scope of the DEA, it presents an innovative capacity to make estimates from random samples, and; 3. At the end of the article, by simulation, able to validate modeling through the variation of property characteristics, demonstrating that the estimation of the corresponding values is consistent according to the market’s expectations.
Originality / value of the method: This article opens new avenues to be explored by the DEA community. Firstly, as a tool for valuing assets, according to the Comparative Market Data Method. In Brazil, DP-DEA has been approved by the Brazilian Association of Technical Standards for this purpose. Another innovation is to evaluate performance which results from common gain according to two perspectives, which interact in the process or procedure under analysis.
Objective: This article innovates when we incorporate the statistical analysis to the method of Double-Perspective Data Envelopment Analysis (DP-DEA), with the objective of obtaining an estimate of greater accuracy and reliability according to the assumptions of the Best Unbiased Estimator (BUE). Design / Research Method: Double Perspective Data Envelopment Analysis (DP-DEA) is an extension to Classical Data Envelopment Analysis (DEA) for estimating efficiency, asset values, indicators, and other attributes from two perspectives, achieving a common result is the main objective. This article innovates in DEA methodology, in two aspects: 1. To demonstrate the ability of the DP-DEA to perform at intervals the estimation of values from a random sample; 2. Through the statistical analysis, making estimates of central tendency according to the assumptions of the Best Unbiased Estimator (BUE – Best Unbiased Estimator). Conclusions / findings: The practical procedures performed step by step through DP-DEA according to the assumptions of the BUE, presented in its main findings and conclusions are: 1. Incorporation of statistical analysis to the DP-DEA method, which assumes assumptions of properties of the Best Estimator Non-biased; 2. Within the scope of the DEA, it presents an innovative capacity to make estimates from random samples, and; 3. At the end of the article, by simulation, able to validate modeling through the variation of property characteristics, demonstrating that the estimation of the corresponding values is consistent according to the market’s expectations. Originality / value of the method: This article opens new avenues to be explored by the DEA community. Firstly, as a tool for valuing assets, according to the Comparative Market Data Method. In Brazil, DP-DEA has been approved by the Brazilian Association of Technical Standards for this purpose. Another innovation is to evaluate performance which results from common gain according to two perspectives, which interact in the process or procedure under analysis.