DYNAMIC OPTIMIZATION APPLIED TO A CRIMINOLOGICAL MODEL FOR REDUCING THE SPREAD OF SOCIETAL CORRUPTION

Abstract

Corruption is rapidly affecting any country’s economic, democratic, financial, social, and political stability. It has been a consistent social phenomenon that happens in all civilizations. Only in the last 20 years has this phenomenon been given serious attention. It has different forms and different impacts on the economy as well as society as a whole. Economic growth is slowed by corruption, which also has a detrimental effect on business operations, employment, and investment. Additionally, it has a detrimental effect on tax revenues as well as the effectiveness of various financial aid programs. So, it is necessary to reduce this global problem. For this reason, we propose a nonlinear deterministic model for the transmission dynamics of societal corruption in terms of optimal control problem, using two time-dependent controls namely the efforts aimed at preventing corruption through the use of social networks, media, and social organizations; including a strong and effective anti-corruption policy, and also the attempt to encourage the punishment of corrupt people to analyze the model. The goal of this study is to reduce the problem of corruption. The results show that our proposed model can help to alleviate this social issue. Our findings also reveal that by using both control strategies instead of just one we get a more effective result. Overall, this research suggests that the impact of corruption can be reduced by implementing anti-corruption media and advertising campaigns, as well as exposing corrupted people to jail and punishing them.