|
|
|
| A Research on Competitor Identification Model Based on Cross-domain and Multi-source Information Fusion in the Context of Big Data |
| Song Xinping, Chen Mengmeng, Lyu Guodong, Shen Yan |
| School of Management, Jiangsu University, Zhenjiang 212013 |
|
|
|
|
Abstract 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.
|
|
Received: 16 December 2021
|
|
|
|
1 陈国青, 曾大军, 卫强, 等. 大数据环境下的决策范式转变与使能创新[J]. 管理世界, 2020, 36(2): 95-105, 220.
2 Halkos G E, Tzeremes N G. Industry performance evaluation with the use of financial ratios: an application of bootstrapped DEA[J]. Expert Systems with Applications, 2012, 39(5): 5872-5880.
3 Teker S, Teker D, Güner A. Financial performance of top 20 airlines[J]. Procedia - Social and Behavioral Sciences, 2016, 235: 603-610.
4 Yoon J, Park H, Kim K. Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis[J]. Scientometrics, 2013, 94(1): 313-331.
5 Niemann H, Moehrle M G, Frischkorn J. Use of a new patent text-mining and visualization method for identifying patenting patterns over time: concept, method and test application[J]. Technological Forecasting and Social Change, 2017, 115: 210-220.
6 施国良, 魏志皓, 周晓帆. 基于URL共现研究的竞争对手分析与识别——以携程旅行网为例[J]. 情报杂志, 2015, 34(9): 30-34.
7 唐晓波, 雍菲. 基于聚类分析的企业竞争对手社会网络分析[J]. 图书情报工作, 2012, 56(4): 75-79.
8 戴泽钒, 朱奕帆, 许鑫. 基于用户重合度的竞争对手识别方法[J]. 情报理论与实践, 2018, 41(9): 57-62.
9 Sayil E M, Akyol A, Golbasi Simsek G. An integrative approach to relationship marketing, customer value, and customer outcomes in the retail banking industry: a customer-based perspective from Turkey[J]. The Service Industries Journal, 2019, 39(5/6): 420-461.
10 李伟华, 郑彦宁. 企业竞争对手识别方法研究进展[J]. 情报理论与实践, 2015, 38(9): 126-129.
11 He W, Wu H, Yan G J, et al. A novel social media competitive analytics framework with sentiment benchmarks[J]. Information & Management, 2015, 52(7): 801-812.
12 Liu Y, Jiang C Q, Zhao H M. Assessing product competitive advantages from the perspective of customers by mining user-generated content on social media[J]. Decision Support Systems, 2019, 123: 113079.
13 周知. 基于微博用户共同关注的竞争对手识别策略研究[J]. 情报探索, 2014(10): 46-49.
14 Chen M J. Competitor analysis and interfirm rivalry: toward a theoretical integration[J]. Academy of Management Review, 1996, 21(1): 100-134.
15 Peteraf M A, Bergen M E. Scanning dynamic competitive landscapes: a market-based and resource-based framework[J]. Strategic Management Journal, 2003, 24(10): 1027-1041.
16 Peng Y S, Liang I C. A dynamic framework for competitor identification: a neglecting role of dominant design[J]. Journal of Business Research, 2016, 69(5): 1898-1903.
17 肖璐, 陈果, 刘继云. 基于情感分析的企业产品级竞争对手识别研究——以用户评论为数据源[J]. 图书情报工作, 2016, 60(1): 83-90, 97.
18 史敏, 罗建, 蔡丽君. 基于专利说明书语义分析的潜在竞争对手识别研究[J]. 情报学报, 2020, 39(11): 1171-1181.
19 王剑华, 马军伟. 企业竞争态势分析: 基于自我定位与公众认知的二维框架[J]. 情报杂志, 2017, 36(9): 58-63, 92.
20 宋新平, 陈梦梦, 申彦, 等. 大数据下基于多源信息融合的企业竞争对手评价模型研究[J]. 情报理论与实践, 2020, 43(2): 61-65, 60.
21 刘志辉, 李辉, 李文绚, 等. 基于多维框架的企业竞争威胁测度方法研究[J]. 情报学报, 2017, 36(7): 654-662.
22 林莉, 马江璐, 李靖华. 制造服务化市场的多主体竞争分析——基于服务市场共同度和服务能力等价性视角[J]. 科技管理研究, 2020, 40(9): 187-195.
23 许鑫, 朱奕帆, 姚占雷. 数据驱动的企业多层竞争网络构建与态势分析[J]. 情报学报, 2018, 37(8): 836-844.
24 陈梦梦. 大数据驱动的竞争对手识别与竞争态势评估研究——基于新能源汽车行业[D]. 镇江: 江苏大学, 2021.
25 Kim Y, Dwivedi R, Zhang J, et al. Competitive intelligence in social media Twitter: iPhone 6 vs. Galaxy S5[J]. Online Information Review, 2016, 40(1): 42-61.
26 黄晓斌, 张明鑫. 融合多源数据的企业竞争对手画像构建[J]. 现代情报, 2020, 40(11): 13-21, 33.
27 郑荣, 杨竞雄, 张薇, 等. 多源数据驱动的产业竞争情报智慧服务研究[J]. 情报学报, 2020, 39(12): 1295-1304.
28 王基建, 勾丽. 基于市场共通性的企业并购市场风险研究[J]. 科学学与科学技术管理, 2003, 24(10): 101-104.
29 Hannan M T, Freeman J. The population ecology of organizations[J]. American Journal of Sociology, 1977, 82(5): 929-964.
30 Zauner A, Koller M, Hatak I. Customer perceived value—Conceptualization and avenues for future research[J]. Cogent Psychology, 2015, 2(1): 1061782.
31 陈娅玲. “互联网+”企业竞争战略研究[D]. 南宁: 广西大学, 2016.
32 Blazquez D, Domenech J. Big Data sources and methods for social and economic analyses[J]. Technological Forecasting and Social Change, 2018, 130: 99-113.
33 梁帅, 李海波, 陈娜. 世界新能源汽车专利主体的竞争态势研究[J]. 科技管理研究, 2015, 35(4): 116-121.
34 Lee H G, Clark T H. Impacts of the electronic marketplace on transaction cost and market structure[J]. International Journal of Electronic Commerce, 1996, 1(1): 127-149.
35 胡涛, 王栋, 孙曜, 等. 基于改进CRITIC-LRA和灰色逼近理想解排序法的空战威胁评估[J]. 兵工学报, 2020, 41(12): 2561-2569.
36 张立军, 张潇. 基于改进CRITIC法的加权聚类方法[J]. 统计与决策, 2015(22): 65-68.
37 路燕, 于晓东. 基于改进k-means算法的企业竞争情报研究——以社会网络分析为方法[J]. 情报科学, 2017, 35(12): 81-85.
38 高云龙, 王志豪, 潘金艳, 等. 基于自适应松弛的鲁棒模糊C均值聚类算法[J]. 电子与信息学报, 2020, 42(7): 1774-1781.
39 翟丽丽, 张影, 王京. 基于广度优先搜索的变异加权模糊C-均值聚类算法[J]. 统计与决策, 2016(15): 9-14.
40 Li Y, Yu F S. A new validity function for fuzzy clustering[C]// Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing. IEEE, 2009: 462-465. |
|
|
|
