Strategies of Integration in Mixed Methods Research: Insights Using Relational Algorithms

The challenge of integration, namely, the bridging across different intellectual paradigms to combine empirical insights into a coherent and plausible explanation, is endemic to mixed methods research. In this article, we address this challenge in two ways: first, by drawing attention to the role that theoretical integration plays in mixed methods research as a complement to empirical integration and second, by broadening the repertoire of strategies for enhancing the interplay of theoretical and empirical elements in a mixed methods study. We use the technique of relational algorithms, a linguistic exercise designed to produce novel relations between pairs of things by experimenting with different words that can connect theory and empirics. We propose that connector words (e.g., along, near, within) can forge linkages between quantitative and qualitative methods that extend the simple coupling implied by and. We advance five strategies of integration, two that are commonly used in management researchconjoined and sequentialand three high-potential but relatively underused strategiessimultaneous, full-cycle, and mono-logic. We illustrate each of these with examples from the management and organizational literature.