This paper proposes a multi-criteria decision making (MCDM) model, namely, Weighted Product Evaluation Based on Distance from Average Solution (WPEDAS), to evaluate the financial performance of companies. The proposed WPEDAS model focuses on the weighted product approach, which is different from the existing Evaluation Based on Distance from Average Solution (EDAS) model that adopts a weighted sum approach based on distance from average solution. Besides that, we further enhance the model performance by developing a hybrid MCDM model. The proposed hybrid Weighted Aggregated Sum Product Evaluation Based on Distance from Average Solution (WASPEDAS) model is developed based on the weighted sum EDAS and the proposed WPEDAS. The proposed hybrid WASPEDAS model offers higher flexibility and robustness of customizing decision strategies based on the decision makers in solving MCDM problems. The proposed hybrid model is demonstrated using the financial ratios of companies in the Consumer Discretionary sector in the NASDAQ Exchange. The entropy weight method is integrated into the proposed models to determine the weights of decision criteria. Based on the results of sensitivity analyses, the proposed hybrid WASPEDAS model proves its reliability and robustness in performance evaluation. This implies that the proposed hybrid WASPEDAS model offers greater stability in ranking the companies, thus helping investors and fund managers in analyzing the companies during investment decision making. In addition, this study also provides guidance to the companies’ management teams in their strategic and tactical decision making to reduce volatility in driving the companies towards excellence.
Lam et al. (Wed,) studied this question.