A DNA Helix Analogy for Interdependent Mixed-Methods Research: Enabling Cross-Fertilizations and Interim Meta-Inferences
Journal
Journal of the Association for Information Systems
Date Issued
December 10, 2024
DOI
10.17705/1jais.00902
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.
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.
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