• Title of article

    A Game Theory Approach for Solving the Knowledge Sharing Problem in Supply Chain

  • Author/Authors

    Safari، H نويسنده Associated professor, Department of Industrial Management, University of Tehran, Tehran, Iran. , , Soufi ، M نويسنده Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran. ,

  • Issue Information
    فصلنامه با شماره پیاپی 13 سال 2014
  • Pages
    12
  • From page
    13
  • To page
    24
  • Abstract
    Knowledge management is the process of capturing, developing, sharing, and effectively using organizational knowledge as we known Knowledge management literature emphasizes the importance of knowledge as a valuable asset for SMEs. This paper highlights the efficient sharing of knowledge as a way of creating core competencies in the SMEs that are in civil construction activities. This perspective mainly focuses on the analysis of attributes that should provide the resources for generating a competitive advantage. We want to gain to two objectives, first examination of supplier’s perceived payoff of sharing knowledge is contingent on the knowledge sharing behavior of other suppliers and second objective is analyzing the perceived payoff of knowledge sharing and determine if it can be characterized by an archetypical game in the game theoretic model. An empirical study was conducted among nearly 72 suppliers in a local civil construction supply chain in north of Iran. The results indicated that the supplier’s perceived payoff sharing knowledge was contingent on the knowledge sharing behavior of other suppliers. In addition, the perceived payoff of knowledge sharing among them could be characterized by a multi-person assurance game. In conclusion, discusses some implication for managers who aim to effective knowledge sharing in their supply chain to acquire sustained competitive advantage.
  • Journal title
    International Journal of Applied Operational Research
  • Serial Year
    2014
  • Journal title
    International Journal of Applied Operational Research
  • Record number

    2385747