Analysis of Motivational Theories in Crowdsourcing Using Long Tail Theory: A Systematic Literature Review

Q2 Decision Sciences International Journal of Crowd Science Pub Date : 2024-02-27 DOI:10.26599/IJCS.2023.9100010
Hasan Humayun;Mohammad Nauman Malik;Masitah Ghazali
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Abstract

Motivational theories have been extensively studied in a wide range of fields, such as medical sciences, business, management, physiology, sociology, and particularly in the natural sciences. These theories are regarded as crucial in motivating online workers to engage in crowdsourcing. Nevertheless, there is a dearth of research on an overarching review of these theories. We performed a systematic literature review of peer-reviewed published studies focusing on motivational theories to identify popular theories and risks associated with nascent theories presented over the last decade in crowdsourcing. Based on a review of 91 papers from the domain of the natural sciences, we identified 35 motivational theories. The long tail theory helped us to identify the contribution of major influencing theories in a crowdsourcing environment. The results justify the long tail theory based on the Pareto principle of 80/20, which underlines the 20% of the popular motivation theories, namely self-determination, expectancy-value, game, gamification, behavior change, and incentive theory, as a cause of 80%. Similarly, we discussed the risks associated with 10 theories presented over the long tail, which have a frequency equal to 2. Understanding the significant impact, approximately 80%, of widely recognized motivational theories and their role in risk identification is crucial. This understanding can assist researchers in optimizing their results by effectively integrating these theories.
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利用长尾理论分析众包中的动机理论:系统性文献综述
激励理论在医学、商业、管理学、生理学、社会学,特别是自然科学等众多领域都有广泛的研究。这些理论被认为是激励在线工作者参与众包的关键。然而,对这些理论进行全面回顾的研究却十分匮乏。我们对同行评审发表的研究进行了系统的文献综述,重点关注激励理论,以确定过去十年众包领域流行的理论以及与新兴理论相关的风险。根据对自然科学领域 91 篇论文的审查,我们确定了 35 种激励理论。长尾理论帮助我们确定了众包环境中主要影响理论的贡献。结果证明了基于帕累托 80/20 原则的长尾理论的正确性,该原则强调了 20% 的流行激励理论,即自我决定理论、期望值理论、游戏理论、游戏化理论、行为改变理论和激励理论,是造成 80% 的原因。同样,我们讨论了与长尾上呈现的 10 种理论相关的风险,这些理论的频率等于 2。了解广泛认可的动机理论的重大影响(约 80%)及其在风险识别中的作用至关重要。这种理解可以帮助研究人员通过有效整合这些理论来优化研究结果。
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来源期刊
International Journal of Crowd Science
International Journal of Crowd Science Decision Sciences-Decision Sciences (miscellaneous)
CiteScore
2.70
自引率
0.00%
发文量
20
审稿时长
24 weeks
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