^ Patent Cooperative Patterns and Development Trends of Chinese Construction Enterprises: A Network Analysis | Structurae
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Patent Cooperative Patterns and Development Trends of Chinese Construction Enterprises: A Network Analysis

Author(s):




Medium: journal article
Language(s): Latvian
Published in: Journal of Civil Engineering and Management, , n. 3, v. 25
Page(s): 228-240
DOI: 10.3846/jcem.2019.8137
Abstract:

Despite the rapid development of Chinese construction industry, there has been little research effort directed towards exploring patent cooperative patterns and evolution trends of construction enterprises, especially from the perspective of the patent development network. This paper extracts implicit collaborative information and introduces Social Network Analysis (SNA) method to conduct the patentometric analysis based on patent data from the “Top 500 Chinese Construction Enterprises” sourced from PatSnap database. The enterprise-enterprise networks and enterprise-university networks are analyzed quantitatively. The results reveal that: 1) there is a rising trend in the number of patents and patentees; 2) state-owned enterprises play a dominant role in patent development; 3) most of patents are classified as International Patent Classification E04G21; 4) the cooperative relationships are mainly within enterprises and their subsidiaries; 5) when enterprises choose to cooperate with universities, in addition to professional qualification, geographical factors should also be considered. Finally, the development and patent evolution trends are discussed. Some useful suggestions are proposed. The contribution lies in: (a) providing a visualization of the implicit collaboration information of patents in Chinese construction enterprises; (b) revealing cooperative patterns of construction enterprises on patents; and (c) providing enterprises some useful suggestions for patent cooperation.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3846/jcem.2019.8137.
  • About this
    data sheet
  • Reference-ID
    10354171
  • Published on:
    13/08/2019
  • Last updated on:
    13/08/2019