Abstract
Multivariate Exponential Weighted Moving Average (MEWMA) control chart is a popular statistical tool for monitoring multivariate process over time. However, this chart is sensitive to the presence of outliers arising from the use of classical mean vector and covariance matrix in estimating the MEWMA statistic. These classical estimators are known to be sensitive to the outliers. To address this problem, robust MEWMA control charts based on modified one-step M-estimator (MOM) and Winsorized modified one-step M-estimator (WM) are proposed. Their performance is then compared with the standard MEWMA control chart in various situations. The findings revealed that the proposed robust MEWMA control charts are more effective in controlling false alarm rates especially for large sample sizes and high percentage of outliers.
Highlights
The vast number of corporate scandals, such as Enron, Tyco and HealthSouth, have caused large scale of workers retrenchment, huge investment losses to the shareholders and have encouraged massive white collar crimes that led to enormous record-breaking bankruptcy filings (Solomon, 2010)
The results show that 72% of the samples apply non duality role for their Chairman, which indicate only 28% of the companies are served by the same person as for the Chairman and Chief Executive Officer (CEO)
This is in line with requirement of MCCG that requires the positions of Chairman and CEO should be held by different individuals, and the Chairman must be a non-executive member of the board
Summary
The vast number of corporate scandals, such as Enron, Tyco and HealthSouth, have caused large scale of workers retrenchment, huge investment losses to the shareholders and have encouraged massive white collar crimes that led to enormous record-breaking bankruptcy filings (Solomon, 2010). In such chaos business situations, engaging corporate governance mechanisms is of importance as a well-governed corporate governance is said to be associated with better firm performance Core et al (1999).
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