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Bribery games on inter-dependent regular networks.

Prateek Verma1, Anjan K Nandi1, Supratim Sengupta1

  • 1Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, 741246, India.

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|February 17, 2017
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Summary
This summary is machine-generated.

Network structure significantly reduces bribery incidents between government servants and citizens. Optimal network connectivity promotes honest officials, highlighting the role of social networks in combating corruption.

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Area of Science:

  • Evolutionary Game Theory
  • Network Science
  • Public Administration

Background:

  • Corruption, specifically bribe demands by public officials (harassment bribes), is a pervasive issue globally.
  • Understanding the dynamics of corruption requires examining interactions within structured social systems.

Purpose of the Study:

  • To analyze how network structure influences the prevalence of corrupt strategies in interactions between public servants and citizens.
  • To investigate the impact of bribe demand levels and citizen complaint costs on corruption spread.
  • To determine the role of network connectivity in the success of honest versus corrupt strategies.

Main Methods:

  • Utilized evolutionary game theory modeling.
  • Simulated interactions within structured populations represented by interdependent networks.
  • Varied parameters such as bribe demand, cost of complaining, and network connectivity.

Main Results:

  • Network-structured populations showed a significant reduction in bribery compared to mixed populations.
  • An optimal range of connectivity within citizen and interaction networks was found to promote honest officials.
  • Network structure and connectivity play a crucial role in the dynamics of asymmetric games like bribery.

Conclusions:

  • Social network architecture is a key factor in mitigating corruption in public service delivery.
  • Strategic design of network connectivity can foster environments less conducive to corrupt practices.
  • Findings offer insights for policy interventions aimed at reducing corruption through structural changes.