Identifying the Core Competitive Intelligence Based on Enterprise Strategic Factors

doi:10.1007/s12204-015-1598-7

Abstract

Abstract: Competitive intelligence (CI) is a key factor in helping business leaders gain and maintain competitive advantages. The emergence of big data and Web 2.0 has created new opportunities and more challenges for enterprises to effectively obtain CI. This paper attempts to explore a CI identification method based on strategic factors (SF). By filtering process before CI collection, the core CI, closely related to critical success factors and crisis inducement factors, are identified reliably and efficiently. Based on knowledge element model and multiattribute fusion method, emphasis is placed on the construction of a criterion function by which the SF thesaurus in achieving CI objectives is established. The advantages of this method lie not only in the capability of mining the core CI from massive data, but also in the foundation of efficient CI storage and analysis. This paper is of significance to make a thorough inquiry on CI obtaining and fusing methods of CI system in era of big data. Experiment results verified the feasibility and validity of this study.

Key words: competitive intelligence identification| strategic factors| knowledge fusion| big data

摘要： Competitive intelligence (CI) is a key factor in helping business leaders gain and maintain competitive advantages. The emergence of big data and Web 2.0 has created new opportunities and more challenges for enterprises to effectively obtain CI. This paper attempts to explore a CI identification method based on strategic factors (SF). By filtering process before CI collection, the core CI, closely related to critical success factors and crisis inducement factors, are identified reliably and efficiently. Based on knowledge element model and multiattribute fusion method, emphasis is placed on the construction of a criterion function by which the SF thesaurus in achieving CI objectives is established. The advantages of this method lie not only in the capability of mining the core CI from massive data, but also in the foundation of efficient CI storage and analysis. This paper is of significance to make a thorough inquiry on CI obtaining and fusing methods of CI system in era of big data. Experiment results verified the feasibility and validity of this study.

关键词: competitive intelligence identification| strategic factors| knowledge fusion| big data

CLC Number:

N 99

SUN Lin1,2* (孙琳), WANG Yan-zhang1 (王延章). Identifying the Core Competitive Intelligence Based on Enterprise Strategic Factors[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(1): 118-123.

References 19

[1]	Chen H C, Chau M, Zeng D. CI Spider: A tool for competitive intelligence on the web [J]. Decision Support System, 2002, 34(1): 1-17.
[2]	Biran D, Zack M H, Briotta R J. Competitive intelligence and information quality: A game-theoretic perspective [J]. Journal of Data and Information Quality,2013, 4(3): 1-20.
[3]	Vedder R G, Vanecek M T, Guynes C S, et al. CEO and CIO perspectives on competitive intelligence [J]. Communications of the ACM, 1999, 42(8): 108-116.
[4]	Huang Xiao-bin, Zhong Hui-xin. Build enterprise competitive intelligence system model based on big data [J]. Journal of Intelligence, 2013, 32(3): 37-43(in Chinese).
[5]	Mody A. Learning through alliances [J]. Journal of Economic Behavior and Organization, 1993, 20(2):151-170.
[6]	Colakoglua T. The problematic of competitive intelligence:How to evaluate & develop competitive intelligence?[J]. Procedia Social and Behavioral Sciences,2011, 24: 1615-1623.
[7]	Rockart J. Chief executives define their own data needs [J]. Harvard Business Review, 1979, 57(2): 81-93.
[8]	Munro M C, Wheeler B R. Planning, critical success factors, and management’s information requirement[J]. MIS Quarterly, 1980, 4(4): 27-38.
[9]	Pearson C M, Clair J A. Reframing crisis management [J]. Academy of Management Review, 1998,23(1): 59-76.
[10]	Shrivastava P, Mitroff R. Strategic management of corporate crises [J]. Columbia Joumal of World Business,1987, 22(1): 5-11.
[11]	Wang W S, Belardo S. The role of knowledge management in achieving effective crisis management: A case study [J]. Journal of Information Science, 2009,35(6): 635-659.
[12]	Marshall B, Chen H, Madhusudan T. Matching knowledge elements in concept maps using a similarity flooding algorithm [J]. Decision Support Systems,2006, 42(3): 1290-1306.
[13]	Wang Yan-zhang. Knowledge and representation of model management [J]. Journal of Systems Engineering,2011, 26(6): 850-856 (in Chinese).
[14]	Dempster A. Upper and lower probabilities induced by multivalued mapping [J]. Annals of Mathematical Statistics AMS, 1967, 38(2): 325-339.
[15]	Shafer G. A mathematical theory of evidence [M].New Jersey, USA: Princeton University Press, 1976.
[16]	Manyika J, Chui M, Brown B, et al. Big data: The next frontier for innovation, competition, and productivity [M]. New York, USA: McKinsey Global Institute,2011.
[17]	Sauter V L, Free D. Competitive intelligence systems:Qualitative DSS for strategic decision making [J]. The Data Base for Advances in Information Systems,2005, 36(2): 43-57.
[18]	Tang Tao-zhi. The analytical method of SWOT for competitive intelligence and competitive strategy choice [J]. Journal of Information, 2002(3): 36-37 (in Chinese).
[19]	Wang Zhi-jin, Ge Lin-lin. Comparison between SWOT model and BCG matrix in competitive intelligence [J]. Library and Information, 2013(3): 87-93(in Chinese).