Stochastic Data Envelopment Analysis (DEA) For Measuring Efficiency And Productivity Of Commercial Banks In Malaysia
| dc.contributor.author | Deng, Qiang | |
| dc.date.accessioned | 2017-10-20T07:16:21Z | |
| dc.date.available | 2017-10-20T07:16:21Z | |
| dc.date.issued | 2014 | |
| dc.description.abstract | The banking sector plays an important role in the development of the country’s economy. The banking industry in Malaysia has experienced major consolidation and restructuring over the past decade. This has attracted a sizeable attention in measuring banks’ performance. Past researches have largely considered banking data as deterministic and only covered limited duration and banks. These limitations affect the accuracy of the overall evaluation of banks’ performances and consequently the suitability of decisions and policies made. Thus, the objective of this study is to examine more accurately the banks’ performance in Malaysia in the stochastic environment. In this study, the efficiency and productivity of banks’ performance are investigated. The Data Collection Budget Allocation (DCBA) model is introduced and developed to optimize the accuracy in measuring the efficiency and productivity growth. This model is capable of effectively allocating the computational budget for Monte Carlo simulation to predict a more accurate performance with stochastic data. Data from 34 banks for the period 1998-2012 were collected and analyzed. The findings show that the DCBA model can effectively optimize the accuracy of the performance. The results of the analysis reveal that on the average, banks’ efficiency has improved 29% and total factor productivity growth improved 3.9% for the period 2001-2010. The findings indicate that Malaysia has developed a high performance banking system and the performance gap between the local banks and foreign banks was gradually reduced. This study also provides recommendations to practitioners on ways to improve the banks’ performance. Lastly, this study has provided a more accurate method to measure banks’ performance in the stochastic environment. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/5026 | |
| dc.language.iso | en | en_US |
| dc.publisher | Universiti Sains Malaysia | en_US |
| dc.subject | Data Envelopment Analysis | en_US |
| dc.subject | The Data Collection Budget Allocation | en_US |
| dc.title | Stochastic Data Envelopment Analysis (DEA) For Measuring Efficiency And Productivity Of Commercial Banks In Malaysia | en_US |
| dc.type | Thesis | en_US |
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