Games Analysis and Simulation in Knowledge Sharing based on Knowledge Contribution Assessment and Utility among Organizational Employees
WU Ji-la
Abstract
WU Ji-la
Abstract
Companies are competing on knowledge as the source of innovation for competitive advantages. Knowledge sharing between employees can greatly enhance an organization's ability to innovate. Many knowledge sharing researches have focused on employee attitudes toward sharing knowledge with others,free riderproblems,and trust between employees,etc. However,little research about how knowledge assessment has contributed to knowledge sharing has been done.A model is established to describe game processing under management strategies,and analyze the existence of Nash equilibrium.We also propose that there will not be free riderphenomenon if the assessment of knowledge contribution is considered. Knowledge sharing activities are discussed according to an employee effect function.First,a knowledge sharing game model is established after considering the assessment of knowledge contribution. In addition,an employee utility function is analyzed based on two factors: knowledge devotion and obtaining. Based on the above analysis,we conclude that evaluation of employee knowledge contribution will change employee's free riderbehaviors of knowledge sharing.The second section discusses the relationship between employee utility function and knowledge sharing effect. Employees who devote more will contribute more if he or she obtains more knowledge from the knowledge sharing process. Simulation analysis shows the relationships among organizational knowledge sharing,organizational investment incentives,incentive levels,incentive differentiation,and individual effectiveness differences. When the absolute index values of two factors are almost equal,each individual will try to make contributions to the knowledge sharing process.In summary,knowledge sharing is affected by many factors,such as organizational incentives,individual characteristics,and so on. An organization needs to provide these factors to support its knowledge sharing activities.
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Companies are competing on knowledge as the source of innovation for competitive advantages. Knowledge sharing between employees can greatly enhance an organization's ability to innovate. Many knowledge sharing researches have focused on employee attitudes toward sharing knowledge with others,free riderproblems,and trust between employees,etc. However,little research about how knowledge assessment has contributed to knowledge sharing has been done.A model is established to describe game processing under management strategies,and analyze the existence of Nash equilibrium.We also propose that there will not be free riderphenomenon if the assessment of knowledge contribution is considered. Knowledge sharing activities are discussed according to an employee effect function.First,a knowledge sharing game model is established after considering the assessment of knowledge contribution. In addition,an employee utility function is analyzed based on two factors: knowledge devotion and obtaining. Based on the above analysis,we conclude that evaluation of employee knowledge contribution will change employee's free riderbehaviors of knowledge sharing.The second section discusses the relationship between employee utility function and knowledge sharing effect. Employees who devote more will contribute more if he or she obtains more knowledge from the knowledge sharing process. Simulation analysis shows the relationships among organizational knowledge sharing,organizational investment incentives,incentive levels,incentive differentiation,and individual effectiveness differences. When the absolute index values of two factors are almost equal,each individual will try to make contributions to the knowledge sharing process.In summary,knowledge sharing is affected by many factors,such as organizational incentives,individual characteristics,and so on. An organization needs to provide these factors to support its knowledge sharing activities.
Key concepts: Knowledge sharing, Knowledge management, Incentive, Knowledge value chain, Organizational learning, Function (biology), Knowledge worker, Process (computing)