Abstract
Systemic corruption is a common term amongst scholars and practitioners, yet there is sparse conceptual agreement and substantive analysis within the discourse. Regardless of the current deficit, there is considerable pioneering space and advantages to contrast against the overwhelming emphasis on individuals.
This paper aims to broaden the conceptual scope of systemic corruption research through a pattern-to-process mixed-methods design. The design combines empirical data from the public procurement sector analyzing the spatiotemporal patterns of network behavior with a descriptive account of processes from in-depth interviews.
The empirical approach statistically distinguishes the performance differentials of public procurement awards amongst firms that exhibit the characteristics of political influence from those that do not. This paper operationalizes that political influence is corruption when a public official would not have made the same decision without the special consideration of political affiliation, contribution, or network connection.
After stripping away explanatory factors for firm competence, the data reveals that firms with influence characteristics win substantially more and more often performing similar work. The usage of geospatial cluster analysis, in conjunction with field interviews, reveals that influence networks forge preferential advantages through political officials and secure repeat wins by engaging with smaller government office sizes outside of densely populated regions.
The reoccurring patterns, independent of one specific time or place, suggests characteristics more suitable for the concept of systemic corruption. This framework will be of utility for policymakers to improve their vantage point perspective beyond case-by-case individual instances for sustainable intervention strategies.