Developing a Directed Graph Analysis Framework as a Method to Analyse and Present Complex Datasets: A Case Study in Tax Compliance

Abstract

Directed graphs are often used as graphical representations of interrelationships between entities. In many fields of research besides the STEM fields, datasets containing complex qualitative interrelationships are challenging to represent graphically in traditional line graphs, bar graphs, or pie charts. In addition, if quantitative data needs to be presented on top of the qualitative relationships, graphical representation becomes even more complex. As a result, datasets of this nature are often tabulated or presented in text since graphical representation is considered difficult or impractical. This paper presents a Directed Graph Analysis Framework that may be used to develop graphical illustrations of such complex datasets. A PhD study in employer tax compliance undertaken by the principal author is utilised as a case study in this paper (Van der Walt, Z., 2024). The framework is then used to develop a variable interrelationship and compliance decision flow diagram to present employer tax compliance decisions in graphical form. It is demonstrated that the method is suitable to produce a single graphical representation of a large number of variables and sub-variables, displaying the relevant qualitative and quantitative information in an easy-to-understand way. The proposed method may be applied to other fields of research where similarly complex datasets are presented.