Does E-government curb corruption? The moderating role of national culture: a machine learning approach

Purpose – The study aims to investigate the relationship between E-government and corruption. It also examines the moderator role of national culture through Hofstede's dimensions on the association between E-government and corruption. Design/methodology/approach – In addition to panel regression techniques, the authors use the random forest method to assess the order of importance of all significant variables in determining corruption. The sample of this study consists of 55 countries during 2008–2020 period. Findings – The results show that E-government is negatively correlated with corruption. The authors also find that both economic and cultural variables play an important role in determining corruption. However, religion has no impact on corruption. The results can potentially assist regulators and policy-makers when trying to control corruption as they should take into consideration the cultural background of citizens when making rules and procedures that aim at reducing corruption. Originality/value – The current study uses random forests model, which allows the regression of variables based on the construction of a multitude of decision trees. The main contribution of using this model compared to the other regression models used in prior studies is to extract the relative importance of each significant variable. More precisely, it evaluates the rank of importance for each significant variable that drives corruption rather than merely identifying variables that drive corruption regardless of their relative importance. Keywords Hofstede, E-government, Culture, Corruption