Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Genetic algorithm solution for a risk-based partner selection problem in a virtual enterprise
Computers and Operations Research
Evolving Neural Networks for Pharmaceutical Research
ICHIT '06 Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01
A fuzzy approach to value and culture assessment and an application
International Journal of Approximate Reasoning
Engineering Drug Design Using a Multi-Input Multi-Output Neuro-Fuzzy System
SYNASC '06 Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
Is there a need for fuzzy logic?
Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems
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Many organizations attempt to form strategic networked enterprises, yet such strategies are difficult to implement because they are as likely to fail as to succeed. This failure is due to intangible differences and mismatches between partners in tacit knowledge TK. Despite the various proposed partnership assessment models/tools in the literature, an immediate need exists for a new approach to measure the mismatch in TK across different organizations. This is due to the complex, vague, and uncertain nature of TK attributes. Hence, an instrument for measuring vagueness imprecise, such as fuzzy linguistic variables, is needed. In this study, the author applies a neuro-fuzzy approach to assess TK fitness in networked enterprises. The results show how differences in TK between partners affect the networked enterprise's performance. Furthermore, the assessment approach reveals the most significant values to adopt and the irrelevant values that must be abandoned to smooth the partnership formation. The proposed model can prevent unexpected conflicts between partners if managed properly.