Value ontology-based multi-aspect intellectual asset valuation method for decision-making support in k-commerce

Advent of the innovation economy has ushered in knowledge as the most valuable corporate asset and a major impetus of product and service creativity. Knowledge commerce (k-commerce) refers to the real-time marketing and delivery of organizational knowledge via the Internet to enable knowledge to be transferred from owners to consumers legally and rapidly. In k-commerce, however, buyer cannot acquire complete product knowledge and can only rely on a limited description of product specifications and fragmented knowledge summary to make purchasing decisions. Consequently, a relatively objective method must be developed for automated knowledge valuation to provide a valuable reference for buyers and sellers, as well as ensure a functioning knowledge market. This study first analyzes the scenario for knowledge valuation activities in k-commerce to identify knowledge services in different knowledge-commercialized phases. A knowledge valuation factor model is then developed that comprises five aspects: knowledge inventor capability, knowledge supplier reputation, knowledge innovative degree, knowledge complexity and knowledge marketable value. To evaluate the market value of knowledge efficiently, a knowledge value ontology (KVO) is constructed based on historical product transaction records to offer the latest value and market status of similar knowledge. Based on factors in the knowledge valuation factor model, finally this study develops a multi-aspect knowledge valuation method including four evaluation sub-methods, capable of estimating the market value of knowledge products from different aspects. The proposed method allows for more rational and accurate decision making for the seller's pricing or the buyer's product selection, thereby encouraging market transactions by reducing information asymmetry and risks while enhancing fairness during a transaction. (C) 2010 Elsevier Ltd. All rights reserved.