Abstract
Although entrepreneurships is recognized as a complex field, existing research does not pay enough attention to capturing the essence of its complexity. I argue that mixed methods designs offer a solid foundation for bridging this gap. To build my argument, I review the key assumptions and dimensions that make entrepreneurship a complex scientific field, discuss the structure of complexity and compare and contrast different research paradigms in terms of their ability to capture complexity. I will then show that mixed methods designs based on the pragmatic paradigm are philosophically better suited than mono-method designs to capture complex phenomena in entrepreneurship. The paper concludes with an integrative framework to guide research and practice along this direction and discusses the implications of this view for studying complexity in entrepreneurship.
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Notes
- 1.
I thank an anonymous reviewer for this point.
- 2.
Interest in studying systems is not new. The holism-reductionism view emerged after WWII which was then completed by Cybernetics and the general system theory (GST). Cybernetics is the study of closed linear feedback loops between a system and the environment [see for example Ashby, R. (1956). An introduction to cybernetics. London, United Kingdom: Chapman and Hall] and general system theory is a more complete theory of general systems such as open, close, simple and relatively complex systems in which the linearity assumption between feedback loops and the environments is relaxed [see for example von Bertalanffy, L. (1968). General system Theory: Foundations, development, applications. New York, NY: George Braziller]. Ecology theory also addresses the conflict between holism and reductionism by looking at hierarchies in systems but is limited only to middle-number systems those in which component are too many to represent individually and too few to capture statistically in causal models [see Malansona, G. P. (1999). Considering complexity. Annals of the Association of American Geographers, 89(4), 746–753]. So complexity theory represents the most appropriate lens to look at complex systems. Another interesting point is the main difference between normal science (Descartesean scientific method), complexity theory and chaos theory. Normal science explains how complex effects can be understood from simple laws by breaking systems into components and examines them independently using competing theories and add them together in linear fashions to get to the system behavior. Chaos theory, however, stresses the importance of nonlinear relationships and explains how simple laws can have complicated, unpredictable and radically big consequences for the system and the environment. Finally, Complexity theory also subscribes to the nonlinearity of cause and affects and describes how complex causes can produce simple effects.
- 3.
I thank an anonymous reviewer for this point.
- 4.
Design paradigm is also used in the design of mixed methods research but it is not a philosophical paradigm. Other philosophical paradigms that enable mixed methods research include emancipatory paradigm and critical realism [see Venkatesh, Brown, and Bala (2013), for a review]. We focus on pragmatism because it has been argued to be the dominant and main paradigm for mixed methods research (Creswell, 2007).
- 5.
I thank an anonymous reviewer for this point.
- 6.
I thank an anonymous reviewer for suggesting to add this section.
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Najmaei, A. (2016). Using Mixed-Methods Designs to Capture the Essence of Complexity in the Entrepreneurship Research: An Introductory Essay and a Research Agenda. In: Berger, E., Kuckertz, A. (eds) Complexity in Entrepreneurship, Innovation and Technology Research. FGF Studies in Small Business and Entrepreneurship. Springer, Cham. https://doi.org/10.1007/978-3-319-27108-8_2
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