Crowdsourcing: a systematic review of the literature using text mining
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 9 October 2020
Issue publication date: 27 October 2020
Abstract
Purpose
This study is a systematic literature review of crowdsourcing that aims to present the research evidence so far regarding the extent to which it can contribute to organisational performance and produce innovations and provide insights on how organisations can operationalise it successfully.
Design/methodology/approach
The systematic literature review revolved around a text mining methodology analysing 106 papers.
Findings
The themes identified are performance, innovation, operational aspects and motivations. The review revealed a few potential directions for future research in each of the themes considered.
Practical implications
This study helps researchers to consider the recent themes on crowdsourcing and identify potential areas for research. At the same time, it provides practitioners with an understanding of the usefulness and process of crowdsourcing and insights on what the critical elements are in order to organise a successful crowdsourcing project.
Originality/value
This study employed quantitative content analysis in order to identify the main research themes with higher reliability and validity. It is also the first review on crowdsourcing that incorporates the relevant literature on crowdfunding as a value-creation tool.
Keywords
Acknowledgements
The authors gratefully acknowledge Research Office and The Hong Kong Polytechnic University under a project account code RUNZ for supporting this research.
Citation
Pavlidou, I., Papagiannidis, S. and Tsui, E. (2020), "Crowdsourcing: a systematic review of the literature using text mining", Industrial Management & Data Systems, Vol. 120 No. 11, pp. 2041-2065. https://doi.org/10.1108/IMDS-08-2020-0474
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited