Understanding and managing complexity through Bayesian network approach: the case of bribery in business transactions

Abstract

Managing complex business problems requires decision makers to take a systemic perspective and utilize tools that can generate knowledge from the interdependencies of the system’s complex properties. As such, the current research focuses on an important yet ambiguous business problem–bribery. Using the Global Competitiveness Index data provided by the World Economic Forum, the authors constructed and analysed a Bayesian network to delineate a ‘system’ of bribery in business transactions. In this context, they first determined the factors related to bribery activities and then developed a structural model (the Bayesian network). Through scenario and sensitivity analyses performed over the constructed model, the authors identified the factors that have the greatest impact on bribery activities. They further analysed the resulting model based on the countries’ stage of economic development in order to provide the manager and policy maker with a more informative diagnostic tool to understand and deal with bribery activities locally and globally.