| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 496102 | Applied Soft Computing | 2013 | 13 Pages |
Creativity is a promoting factor in organizations. Having employees in structured and organized configurations in a creative manner, helps in improving the productivity. We investigate different structural aspects of teams’ network organization and the creativity within a knowledge development program (KDP). The proposed methodology being equipped with a heuristic clustering technique, classifies the employees with respect to creativity parameters and configures a creativity matrix. Applying the creativity matrix, clustering is performed via mathematical programming. For large problems, a genetic algorithm (GA) is developed to solve the mathematical model. We also employ the Taguchi method to evaluate the effects of different operators and parameters on the performance of GA. A case study conducted in Mazandaran Gas Company in Iran illustrates the applicability and effectiveness of the proposed methodology.
Graphical abstractWe investigate different structural aspects of teams’ network organization and the creativity within a knowledge development program (KDP). First, a pilot group of employees in an organization is selected. This group is evaluated through creativity parameters using a questionnaire. Considering the questionnaires’ data, a creativity matrix is configured by a binary scoring. Applying the creativity matrix, clustering is performed via mathematical programming. For large problems, a genetic algorithm (GA) is developed to solve the mathematical model. The pilot group is divided into a number of research teams. The research subjects are submitted to the teams. This procedure is repeated dynamically for different time periods. A case study is conducted in Mazandaran Gas Company to illustrate the applicability and effectiveness of the proposed methodology.Figure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Considering the questionnaires’ data, a creativity matrix is configured by a binary scoring. ► Applying the creativity matrix, clustering is performed via mathematical programming. ► For large problems, a genetic algorithm (GA) is developed to solve the mathematical model. ► A case study is conducted in Mazandaran Gas Company to illustrate the applicability and effectiveness of the proposed methodology.
