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Social network analysis comprises a powerful set of techniques for quantifying, differentiating, and interpreting social interactions or relational data in general. This provides a means of interrogating assumptions of independent yet homogeneous actions and pay-offs in economic processes, a particular interest of heterodox approaches to economics. Contemporary applications include modelling opinion leadership among consumers, search and matching in labour markets, collaboration in research and development, patterns of innovation diffusion among firms, and global commodity chains. This chapter introduces the central concepts and methods of social network analysis, including data collection and interpretation considerations and a brief discussion of specialized software in the field. Each is illustrated with an economic application, either a heterodox example or with a discussion of its heterodox implications.

Where economics is dominated by a monolithic methodology of axiomatic theorizing and econometric analysis of secondary datasets, multiple and mixed methods research offers a much and richer toolkit to examine economic problems from a variety of perspectives with custom methods suited for the particular task. Rather than limiting analysis to the application of approved methods to an approved dataset, with little consideration of its content, a multiple or mixed method approach inherently interrogates choices and limitations of data and methods from the outset. This chapter aims to equip readers with a grounding in the principles of multiple and mixed methods research and to consider benefits and limitations of triangulation of methods, issues in research design, choices of methods and their integration, and issues of validity and ethics.