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A Mathematical Model For Optimal Corporate Alliances: Evidence From Japan

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  • Satoshi Tomita
  • Yoshiyasu Takefuji

Abstract

In this paper, we are proposing a new mathematical model for choosing business partners in corporate alliances. We have used the real corporate data of 152 Japanese companies graded on eight characteristics. These characteristics include sales force, technical ability, capital resources, human resources, production capacity and other items that represent management resources. These characteristics can be described using a one-dimensional matrix. The subtraction of two such one-dimensional matrices results in a bipolar vector shows the relationship of the corporate alliance between two companies. The strength of a mutually complementary relationship is mathematically represented as the distance from the maximum point. The proposed model was implemented in the Python programming language. We have analyzed 152 Japanese companies and the computed results of the mutually complementary strength coefficient. Based on this, we have verified the functionality of the model. By using the proposed model, we can determine which candidate(s) from multiple potential companies form the best-suited alliance.

Suggested Citation

  • Satoshi Tomita & Yoshiyasu Takefuji, 2016. "A Mathematical Model For Optimal Corporate Alliances: Evidence From Japan," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 9(1), pages 63-80.
    • Handle: RePEc:ibf:ijmmre:v:9:y:2016:i:1:p:63-80
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    More about this item

    Keywords

    Mathematical Model; Corporate Alliance; Mutually Complementary Relationship; Management Resources; Python Programming Language; Japanese Companies;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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