The Impacts of Payment Policy on Performance of Human Resource Market System: Agent-Based Modeling and Simulation of Growth-Oriented Firms

Author:

Yang Jian1,Dong Jichang123,Song Qi1ORCID,Otmakhova Yulia S.4ORCID,He Zhou123ORCID

Affiliation:

1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China

2. MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation, University of Chinese Academy of Sciences, Beijing 100190, China

3. Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China

4. Central Economic and Mathematics Institute, Russian Academy of Sciences, 117418 Moscow, Russia

Abstract

The impact of human resource management (HRM) on corporate growth is a crucial research topic, especially for growth-oriented firms. This paper aims to study how different payment policies (such as recruitment and dismissal strategies and payment plans) affect the human resource market system. Based on the HRM characteristics of growth-oriented firms, we develop an agent-based model to simulate the decision-making and interaction behaviors of firms and workers. The system performance is measured by six indicators: the average profit, the profit Gini coefficient, the average output of firms, the average payment, the payment Gini coefficient, and the employment rate of workers. According to the simulation results and statistical analysis, the recruitment plan is the only key factor that significantly impacts all performance indicators other than the employment rate, and companies should pay extra attention to such plans. This study also finds that the changing worker’s payment gap is influenced by industry growth and their abilities, and that the payment cap policy has a positive impact on the development of growth-oriented firms in the startup stage.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Youth Innovation Promotion Association CAS

Ministry of Science and Higher Education of the Russian Federation

MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation at UCAS

Weiqiao Guoke Joint Laboratory at UCAS

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software

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