Enhancing the Efficiency of the Benchmarking Learning Map Model: The Integrated Fra Perspective
AbstractFinancial Ratio Analysis (FRA) has been used for the evaluation of firm’s operating performance. However, these individual performance values calculated from FRA have their own different managerial deficiencies. The original Data Envelopment Analysis (DEA) may fill this gap and may be used to calculate efficiency values. This study integrates the DEA with Slacks-Based Measure Model (SBM) to enhance the evaluation efficiency of firms’ operating performance. The analysis used financial data of 46 textile firms (that trade in the Taiwan stock market) before the 2007 financial crisis. From this total, 8 textile firms were categorized as an efficient operating group and the other 38 firms were categorized inefficient. This study employed the slackbased measure and the analysis model as a benchmark management tool to offer some improvements for the inefficient firms.
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Bibliographic InfoArticle provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.
Volume (Year): (2012)
Issue (Month): 3 (September)
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financial ratio; performance evaluation; Slacks-Based Measure Model (SBM); benchmarking management; BCG matrix;
Find related papers by JEL classification:
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
- R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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