A DNA Helix Analogy for Interdependent Mixed-Methods Research: Enabling Cross-Fertilizations and Interim Meta-Inferences

Abstract

Mixed methods enable a more integrated and insightful understanding of the phenomena we study, but are complex to plan, execute, and document. This applies to concurrent and fully integrated mixed methods research designs in particular, which remain underrepresented in information systems research. In this paper, we extend the prevailing templates for this type of research and propose a new conceptualization. We argue that different research strands (e.g., qualitative, quantitative, computationally intensive, or other) that unfold at the same time need not be independent. Rather, as they run concurrently, they can interact and inform each other through ongoing cross-fertilization. This offers the opportunity for enhanced validation and deeper research insights. We conceptualize how the interaction between the research strands may unfold and we propose a DNA helix analogy to enable and enhance the conceptualization of such interdependent mixed methods research. We further explain the mechanism through which the different research strands interact in an ongoing cross-fertilization, and how interim meta-inferences may be continuously and incrementally drawn, (re)shaping how each research strand evolves. The research process within this conceptualization is depicted in a flow diagram that can serve as a possible roadmap for this type of research. We also show how this process can be documented, contributing to more transparent accounts of how mixed methods research actually evolves. We refer to our research on cloud adoption as an example and further validate our proposed research design with interviews with junior and experienced researchers engaged in mixed methods research. We conclude with a set of principles to guide interdependent mixed methods research and present their practical implications.