identify enablers of agility and agile modeling strategy with neural network approach

the electronic industry suffers a rapid changing and highly rival environment. thus, firms have an essential need to strive for acquiring the competitive advantage. strategy organizational agility (soa) is a tool which enables to assist firms to attain the competitive advantage. therefore, this study benchmarks the core competencies from a case study within the supply chain network and establishes a set of attributes for augmenting soa. a novel multi-criteria decision-making structure is proposed to deal with the complex interrelationships among the aspects and attributes. radial basis function (rbf) neural network can use linear learning algorithm to complete the work formerly handled by nonlinear learning algorithm, and maintain the high precision of the nonlinear algorithm. however, the results of rbf would be slightly unsatisfactory when dealing with small sample which has higher feature dimension and fewer numbers. higher feature dimension will influence the design of neural network, and fewer numbers of samples will cause network training incomplete or over-fitted, both of which restrict the recognition precision of the neural network. the competence and accountability indicators can the continuously increasing level of agility to be effective. according to the analysis chart production and product design performance indicators alone cannot level a considerable amount of agility to change. but reducing the level of the index level of agility is reduced. flexibility indices speed and agility level changes can also affect the organization. but with increased levels of these two indicators increased agility rate change indicators will be more flexibility. the results showed that customer knowledge management impact on organizational agility and organizational effectiveness and customer knowledge management through organizational agility has significant positive impact on organizational effectiveness. finally, some practical suggestions, future research suggestions and research limitations are presented.