Product Innovation Decision Support Based on On-line Patent Database

This research proposes a model of decision support in product innovation, especially during idea generation phase. The proposed model uses two types of knowledge: tacit knowledge which is gathered from expert opinions and explicit knowledge which is gathered from on-line patent database. Cathecin (green tea) is used for the case study in this research. The proposed model is based on combination of data mining model and Analytic Hierarchy Process (AHP). This model represents the data mining process from on-line patent database and then analyzes them as a resource for product innovation during product's idea generation. This process allows generating product mapping and technology mapping. After the patent analysis, some product and process alternatives can be generated. Selection process for the best alternative uses AHP model. The AHP model used in this research is modified from Chiu (2003) AHP model in patent valuation. This model supports to select the best alternative for catechin's product.