Mathematical Methods for Identification of Core Competitors: Based on Social Networks and Hierarchical Cluster Analysis

Author:

Wen Ming1,Li Mingxing2,Hu Cheng2,Hakro Saifullah3,Hussain Abid24ORCID,Heydari Mohammad5ORCID,Zadi Kashif Imran4,Arzo Shumaila6

Affiliation:

1. Jiangsu Intellectual Property Research Center, Jiangsu University, Zhenjiang 212013, China

2. School of Management, Jiangsu University, Zhenjiang 212013, China

3. Department of Management Sciences, University of Okara, Okara, Punjab, Pakistan

4. University of Management and Technology, Johar Town, Lahore 54782, Pakistan

5. Business College, Southwest University, Chongqing 400715, China

6. School of Public Affairs, Zijingang Campus, Zhejiang University, Hangzhou 310058, China

Abstract

Based on the introduction of complex social network theory and methods, this study reveals enterprises' patent layouts to help Chinese enterprises distinguish the core competitors. This study uses the social network analysis method and the system cluster analysis method to systematically analyze the macro technology development trend and competitors' micro technology innovation points. Based on the structure of enterprise resource investment, a two-dimensional matrix with the keyword “similarity-technological competition intensity” was constructed to accurately identify BYD's core technological competitors. In China, BYD company should regard GX company and ND company as core technology competitors, pay attention to the technology development direction and patent layout of YW company and HD company, and pay attention to the patent dynamics of GLM company and YQ company in specific technological innovation points.

Funder

Social Science Foundation of Jiangsu Province

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference21 articles.

1. Web footprints of firms: using online isomorphism for competitor identification;P. Gautam;Operations Research Management Science,2017

2. Discovering competitive intelligence by mining changes in patent trends;S. Meng-Jung;Expert Systems with Applications,2010

3. A uniqueness-driven similarity measure for automated competitor identification

4. Patent-based measurements on technological convergence and competitor identification: the case of semiconductor industry;Z. H. Song;European Journal of Business and Management,2016

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