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International Journal of Crowd Science 2021, 5(3): 239-256 https://doi.org/10.1108/IJCS-04-2021-0015
Case study | Open Access | Issue | Published: 03 October 2021

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

Show Author's Information Octavio González Aguilar( )
Felizmente Verde, Tepic, Mexico
Keywords:
Crowdsourcing, Crowd science, Citizen science, Crowdsourced research, Theory building, Theorizing
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González Aguilar O. Crowd modelling: aggregating non-expert views as a method for theorizing. International Journal of Crowd Science, 2021, 5(3): 239-256. https://doi.org/10.1108/IJCS-04-2021-0015
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Abstract Full text About this article
Purpose

This 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/approach

This 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.

Findings

This document answers to what extent the crowd-based method produces similar results to theories tested and published by experts.

Research limitations/implications

From 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 implications

This paper exemplifies how to obtain an expert-level research model by aggregating the views of non-experts.

Social implications

This study is particularly important for institutions with limited access to costly databases, labs and researchers.

Originality/value

Previous 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.


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Abstract
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About this article

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

Show Author's information Octavio González Aguilar( )
Felizmente Verde, Tepic, Mexico

Abstract

Purpose

This 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/approach

This 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.

Findings

This document answers to what extent the crowd-based method produces similar results to theories tested and published by experts.

Research limitations/implications

From 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 implications

This paper exemplifies how to obtain an expert-level research model by aggregating the views of non-experts.

Social implications

This study is particularly important for institutions with limited access to costly databases, labs and researchers.

Originality/value

Previous 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: Crowdsourcing, Crowd science, Citizen science, Crowdsourced research, Theory building, Theorizing

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Publication history
Copyright
Acknowledgements
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Publication history

Received: 17 April 2021
Revised: 29 July 2021
Accepted: 31 July 2021
Published: 03 October 2021
Issue date: November 2021

Copyright

© The author(s)

Acknowledgements

Acknowledgements

The author want to thank Professor Christian Wagner for all the meaningful guidance and advice. The author also want to thank Professor Carlos Jimenez for providing the space and access to participants during the data collection.

Rights and permissions

Octavio González Aguilar. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

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