Abstract
Under the “Internet+” environment, the R&D intensity of products and services has increased; hence, organizations need to improve their ability to integrate knowledge and technology resources. Knowledge gaps will arise when an organization’s knowledge reserves fail to meet the needs of innovation activities. This research established a network of complete knowledge topics under the “Internet+” environment based on the Word2Vec model. The word vectors and word frequencies of organizational reserve knowledge texts were analyzed to establish an organizational reserve knowledge topic network. The Term Frequency-Inverse Document Frequency algorithm was used to identify the demanded knowledge topic. The satisfaction capability of demanded knowledge in the reserve knowledge topic network was calculated via the eigenvector centrality and the fuzzy evaluation method. The corresponding strategies were then put forward to make up the knowledge gap. Finally, a case study was conducted and compared with SWOT (Strengths, Weaknesses, Opportunities, and Threats) and Venn diagram analysis on the economic and management college of a university in Beijing to verify the effectiveness of this method.
Highlights
The rapid development of the Internet presented by information technology has gradually integrated into the real economy and has become widely used in all walks of life
This paper focuses on research on the knowledge gap identification method in innovative organizations under the “Internet+” environment and builds a network of complete knowledge topics under the
“Internet+” environment based on the Word2Vec model
Summary
The rapid development of the Internet presented by information technology has gradually integrated into the real economy and has become widely used in all walks of life. According to the realistic requirement of collaborative innovation, important means to improve the competitiveness of organizations under the Internet+ environment are the rapid, objective, and quantitative analysis of the organization’s knowledge gaps, choosing effective remedies methods, and reducing the uncertainty of innovation activities. Chen et al identified the knowledge gap and proposed the strategies for studying the different types of gaps by matching and comparing the knowledge demand set and the stock knowledge set based on Venn diagram analysis. It provides a structured representation of the organization’s stock knowledge and demanded knowledge and quantitative suggestions on the strategies to fill the knowledge gap, which will become the basis for organizations to choose reasonable competition and cooperation strategies in the future. The fifth section compares the proposed method with the existing method, and the sixth section draws conclusions and makes improvements
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