P2P Human-Resource Sharing and Its Redistribution Strategy of Stable Coin

  • Miki Saito Advanced Institute of Industrial Technology
  • Hisashi Hayashi Advanced Institute of Industrial Technology
Keywords: human-resource allocation, sharing economy, human-resource sharing, automated negotiation, peer-to-peer (P2P), multi-agent simulation, agent-based modeling


Workloads fluctuate in many small and medium-sized enterprises (SMEs). Managing human resources in these fluctuating conditions is difficult for many companies. During busy periods, workers struggle to complete all their work; however, during idle periods, they may not have sufficient work. The following are the two aims of this study: first to propose a new peer-to-peer (P2P) human-resource-sharing platform to balance the work hours of employees, and second to propose new reallocation strategies of stable coins called share P (sharing point). The first aim enables companies that are experiencing idle periods to offer their employees to other companies that are busy, by using an automated-negotiation technology. The second aim eliminates the share P bias that prevents smooth circulation of both share P and employees within the platform. The effectiveness of the new platform and new allocation strategy will be evaluated and verified via multi-agent simulation. Our simulation results show that idle/busy periods decrease approximately from one-third to one-half by using our P2P human-resource-sharing methods of employees. They can be further reduced to less than from one-fifth to one-seventh by using our new redistribution strategies of share P.


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