Crowd modelling: aggregating non-expert views as a method for theorizing

Abstract

PurposeThis paper aims to introduce a crowd-based method for theorizing. The purpose is not to achieve a scientific theory. On the contrary, the purpose is to achieve a model that may challenge current scientific theories or lead research in new phenomena.Design/methodology/approachThis paper describes a case study of theorizing by using a crowd-based method. The first section of the paper introduces what do the authors know about crowdsourcing, crowd science and the aggregation of non-expert views. The second section details the case study. The third section analyses the aggregation. Finally, the fourth section elaborates the conclusions, limitations and future research.FindingsThis document answers to what extent the crowd-based method produces similar results to theories tested and published by experts.Research limitations/implicationsFrom a theoretical perspective, this study provides evidence to support the research agenda associated with crowd science. The main limitation of this study is that the crowded research models and the expert research models are compared in terms of the graph. Nevertheless, some academics may argue that theory building is about an academic heritage.Practical implicationsThis paper exemplifies how to obtain an expert-level research model by aggregating the views of non-experts.Social implicationsThis study is particularly important for institutions with limited access to costly databases, labs and researchers.Originality/valuePrevious research suggested that a collective of individuals may help to conduct all the stages of a research endeavour. Nevertheless, a formal method for theorizing based on the aggregation of non-expert views does not exist. This paper provides the method and evidence of its practical implications.

Keywords

• crowdsourced research
• crowdsourcing
• crowd science
• theory building
• theorizing
• citizen science