摘要
大数据下竞争对手识别模式发生了显著转变,催生了新型竞争对手识别研究范式。本文以该新范式为导向,借鉴企业生态位理论与互联网下的顾客价值理论,对传统经典陈明哲竞争分析框架进行拓展,提出了基于大数据下的市场共通性和资源能力优势度的竞争对手识别指标体系框架。该框架整合了行业与市场双元视角下的财务、专利、产品、客户等多方跨域信息源,使用模糊C均值聚类构建模型,并以新能源汽车行业为例开展仿真实验研究。结果表明,基于跨域多源信息融合的模型可有效提高竞争对手识别的准确性和全面性。
There have been significant changes in the pattern of competitor identification under the big data environment,engendering a new research paradigm of competitor identification.Guided by the new paradigm,this article modifies the traditional classic competitive analysis framework of Chen Ming-Jer,and then presents a new competitor identification index system framework consisting of market commonality and resource capability advantage,using the theory of corporate niche,the view of resources and ability,and the theory of customer value.The framework integrates cross-domain and multi-source information sources such as finance,patents,products,and customers from the perspective of the industry and market.Subsequently,the competitor identification model is built based on the fuzzy C-means clustering algorithm,and the new energy automobile industry is taken as an example to carry out simulation experiments.The results show that the model can effectively improve the accuracy and comprehensiveness of competitor identification.
作者
宋新平
陈梦梦
吕国栋
申彦
Song Xinping;Chen Mengmeng;Lyu Guodong;Shen Yan(School of Management,Jiangsu University,Zhenjiang 212013)
出处
《情报学报》
CSCD
北大核心
2023年第2期176-188,共13页
Journal of the China Society for Scientific and Technical Information
基金
国家社会科学基金项目“总体国家安全观视域下基于大数据的企业竞争情报感知能力提升研究”(21BTQ070)
国家自然科学基金项目“Web 2.0下全员有效参与竞争情报的行为形成机理及治理策略研究”(71573107)。
关键词
大数据
竞争对手
多源信息融合
综合视角
模糊C均值聚类
big data
competitors
multi-source information fusion
comprehensive perspective
fuzzy C-means clustering
