Article Abstract:
Different methodologies for statistical process control are provided and compared in terms of their data correlation performance. The correlation of the different statistical process control charts is based on an autoregressive moving average (ARMA) model. Comparisons of the Shewhart chart and the Exponentially Weighted Moving Average (EWMA) chart to the Special-Cause Control (SCC) chart and the Common-Cause Control (CCC) chart show that traditional charts such as the Shewhart chart are not entirely robust to shifts in process randomness. The EWMA chart is highly suitable for detecting slight deviations, as well as large deviations for data correlation with negative autoregressive parameters and positive moving average parameters. The SCC and CCC is most effective for shifts that occur over a wide range of ARMA (1,1) parameters.
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Article Abstract:
A strategic management model is suggested which provides another possibility to the goals of maximizing growth in earnings per share or return on equity. The model asserts that a company's stock price is significantly and positively connected with research and development, capital expenditure, and dividend levels. A 303-firm sample for 1975-1982 is used to test empirically the suggested model. Research results indicate that empirical results support the model's assertions.
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Article Abstract:
The financial literature generally supports the hypothesis that businesses simultaneously calculate their research and development (R & D), dividend, new debt, and investment policies. R & D determinants, investment, dividend, and financing decisions of 140 companies are econometrically estimated for the period between 1978 and 1982. Management develops insights into the interactions of pursuing R & D outlays, offering dividends, and undertaking investments.
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