The innovative performance evaluation model of grey factor analysis: A case study of listed biotechnology corporations in Taiwan

Decision-making is often characterized by complex and multiple criteria. Traditional multivariate statistical analysis used as a model for multiple criteria performance evaluation is often constrained by many underlying hypotheses and is probably hindered by insufficient amounts of sample data. Grey theory is a systematic analysis methodology that is specifically developed to rectify the above disadvantages. In addition to the revision of the calculation of absolute degree of grey incidence (ADGI), this study attempts to combine the advantages of grey theory and factor analysis and establish a grey factor analysis (GFA) performance evaluation model by means of an ADGI matrix, which replaces the correlation matrix. Hence, this model will not only be expected to find the principal common factors that affect performance, but can be expected to evaluate the overall performance of all the identity under evaluation. Furthermore, since the biotechnology industry is deemed as a major industry to be developed, this study will test the GFA performance evaluation model with listed biotechnology corporations in Taiwan. The result will be expected to indicate the adaptability of the GFA model, and how the model will also be able to offer a computationally easy and rapid ascertainable result method for multi-criteria decision-making (MCDM) models.