Matching Knowledge Suppliers and Demanders on a Digital Platform: A Novel Method

Abstract

More knowledge service providers are using digital platforms to provide services, which operate under a different set of operating rules than the traditional service model. This paper presents a novel method to match knowledge suppliers and demanders on a digital platform that considers the differences between the two service models. In addition, this paper proposes an innovative approach to assess the network value to the platform provider by fuzzy multi-attribute decision making. A case study is used to show that the novel method is valid and practical. The matching method proposed in this paper extends the application of the knowledge matching method and provides a theoretical basis to improve the efficiency and profits of knowledge service platforms.

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