Title: Coping with complexity in scientific research by combining systems, qualitative and quantitative approaches

Abstract

The traditional method of science is reductionist in essence. Reductionism imposes severe limits in dealing with the complexity that is proper to some areas of research. To cope with complexity in research, it may be wise to combine different approaches, including systems approaches, qualitative methods and quantitative methods. Systems approaches can help researchers to cope with structural, behavioral or evolutionary complexity. They allow researchers to develop theoretical frameworks to comprise a broad perspective of a research problem. Theories are systems themselves. A system is a set of elements that interact with each other to meet some declared purpose. Analogously, a theory is a set of constructs related to each other by propositions. Qualitative methods can help a researcher to gather rich data to support the process of building a theoretical model and to ground theory on data. Quantitative methods contribute the rhetorical power of numbers. Multivariate data analysis methods, for instance, can help researchers to organize big data to support the process of theory building. Researchers can also apply quantitative methods to test and validate theory, by verifying key features of a systemic theoretical model. Methods must be however consistently combined, based on a solid epistemological approach. This requires a deep understanding of each method and the conditions under which the application of each method is valid, to not violate these conditions as methods are put together. Some articles illustrate how systems, quantitative and qualitative approaches can be combined to deal with complex research subjects such as the diagnosis of the situation of micro, small and medium enterprises in a city, the analysis of outcomes of sustainable development goals in countries, and sustainable competitive advantage in very dynamic markets.