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Determining what constitutes a causal relationship between two or more concepts, and how to infer causation, are fundamental concepts in statistics and all the sciences. Causation becomes especially difficult in the social sciences where there is a myriad of different factors that are not always easily observed or measured that directly or indirectly influence the dynamic relationships between independent variables and dependent variables. This paper proposes a procedure for helping researchers explicitly understand what their underlying assumptions are, what kind of data and methodology are needed to understand a given relationship, and how to develop explicit assumptions with clear alternatives, such that researchers can then apply a process of probabilistic elimination. The procedure borrows from Pearl&rsquo ; s concept of &ldquo ; causal diagrams&rdquo ; and concept mapping to create a repeatable, step-by-step process for systematically researching complex relationships and, more generally, complex systems. The significance of this methodology is that it can help researchers determine what is more probably accurate and what is less probably accurate in a comprehensive fashion for complex phenomena. This can help resolve many of our current and future political and policy debates by eliminating that which has no evidence in support of it, and that which has evidence against it, from the pool of what can be permitted in research and debates. By defining and streamlining a process for inferring truth in a way that is graspable by human cognition, we can begin to have more productive and effective discussions around political and policy questions.

In this paper we present the results of our analyses of the existing literature on the sharing economy. It is important to understand the nature of the sharing economy, because its impacts on the larger economy, society, and governance are extensive and potentially deep and long lasting. Analyses of the 610 articles published between 2006 and 2018 show that there was a rapid increase in publications starting in 2014. Researchers in business, economics, technology, and environmental sciences were interested the most in the topic. There were relatively fewer publications in political science, public administration, and political science. Uber and Airbnb were the most studied platforms. The United States, China, and United Kingdom were the most commonly studied countries. A majority of the literature was a-theoretical. A majority of authors applied some empirical (qualitative and quantitative) research methods.