Alleviating corruption: a data driven perspective

Overview

Corruption is cited as among the greatest challenges faced by government and citizenry the world over and threatens to undermine the very trust that is essential for a functioning democratic society. In order to earn and maintain public trust, governments at all levels must continuously strive to reduce corruption and uphold the highest levels of integrity.

Amidst the countless human interactions and electronic transactions that occur within the public service on a daily basis are a complex and ever-changing variety of operational access points and enabling factors that together give rise to unique, and often unseen opportunities for corruption. Embedding the necessary systems, processes and behaviours to identify and constrain corruption therefore requires conscious and sustained effort.

Research activities

The tasks include:

• a systematic literature review to collect, collate and synthesis high quality published material
• collection of primary data
• development of corruption patterns taxonomy using the relevant process analytics techniques.

Outcomes

This research project aims to alleviate corruption by:

• utilising data-driven analytical methods to identify patterns of corruption
• identifying the mechanisms that systematically support corrupt practices by conceptualizing corruption as an ecosystem
• discovering the unique properties and structures of corrupt processes using the theory of workarounds.

Skills and experience

• literature search
• academic writing
• ability to learn qualitative data analysis software (NVivo)
• process mining/data analytics skills
• time management.

Keywords

• corruption
• process analytics
• patterns

Contact

Contact the supervisor for more information.