Abstract

This chapter advocates a mixed methods research strategy for the types of problem generally investigated by complexity science research. Indeed complexity science thinking underpins mixed methods research through embracing different types of data found in real-world problems. The need for multiple perspectives, philosophically and theoretically, and new stances to solving paradigmatic dilemmas, are highlighted. Alternative frameworks are compared to assist in alignment with research questions and research purpose as well as recognizing practical influences on research design choice. Numerous mixed methods research designs demonstrating the integration of mixed methods are reviewed, as are techniques for integrating the data between traditional methods. Data collection and data analysis techniques are considered from a mixed methods perspective. The benefits and challenges of mixed methods research are discussed. Overall, mixed methods research has critical mass but continues to evolve and become ever more relevant to address complex systems problems.