Researchers at Amirkabir University of Technology have introduced a new decision-making model to optimize the selection of knowledge-based products, responding to the growing importance of knowledge-driven organizations.
According to the university’s Public Relations Office, Dr. Mohsen Sadeghi Dastaki, a PhD graduate and lead researcher of the project titled “Presenting an Optimization Method under Uncertainty for New Product Selection with Emphasis on Knowledge Creation,” said that idea screening and product portfolio selection remain major challenges for large and knowledge-based organizations.
He explained that many existing methods focus mainly on cost and profitability, while overlooking how the required knowledge for product development is acquired and managed—an oversight that can lead to project failure. The proposed model addresses this gap by integrating knowledge management principles into the early stages of new product development.
The multi-stage model identifies and prioritizes knowledge gaps and then selects an optimal product portfolio using stochastic mathematical modeling. The model was tested in several organizations in Australia and delivered positive results.
Findings from the project have been published in reputable international journals. The research was supervised by Dr. Abbas Afrazeh and Dr. Masoud Mahootchi, faculty members of Amirkabir University of Technology.