Navigating Complexity in Information Systems and Analytics Through Innovative Research Methodologies

The latest complexities of Big Data and Gen-AI are posing novel difficulties to Information Systems (IS) and Analytics researchers. The conventional mono-methods are inadequate to address this complexity. This chapter argues for methodological pluralism and suggests a synthesized approach, a combination of Mixed-Methods Research (MMR) and Computational Social Science (CSS). The chapter is grounded in a pragmatic philosophy. This approach leverages the interpretive richness of qualitative methods, the scale of the quantitative analysis, as well as the strength of computational research methods. The chapter identifies the MMR designs and emerging types of computational data, and provides examples of their combination, such as computational ethnography. The synthesized approach enables a more holistic and robust understanding of complex socio-technical phenomena in informatics, providing a direction for rigorous and relevant research.