Integrating artificial neural networks with rule-based expert systems
Decision Support Systems - Special issue on neural networks for decision support
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Credit risk assessment with a multistage neural network ensemble learning approach
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy neural based importance-performance analysis for determining critical service attributes
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Innovation management is the practice of managing new ideas and insights into business environment so as to increase market competitiveness. Therefore, it is vital to address the critical determinants of effective innovation management within an organizational context, hence called organizational innovation. Based on some existing frameworks of managing organizational innovation, several key determinants can be identified. Using industrial survey data, we then proposed and used a neural network-based approach to quantify the connectivity between each of these determinants and organizational innovation. First, the modeling accuracy of our proposed method was examined and benchmarked with multiple linear regression and non-linear least square fitting methods. Next, the relative importance among various key determinants toward organizational innovation can be computed using our method. We then compared the results with the qualitative judgment of field experts and professionals using the analytical hierarchy process. Based on the comparison outcomes, our proposed method is proved to be reasonably useful and practical in capturing the comparative influence among determinants toward organizational innovation.