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Top1. Introduction
In 2005, Jeff Howe and Mark Robinson, editors at Wired, coined the term ‘crowdsourcing’ to denote the practice by which an organisation or individual broadcasts a request to the public, soliciting contributions from volunteers in the form of an open call (Howe, 2006). Nowadays, organisations need to be dynamic, agile and focused on coping with the ever-changing environment such as COVID-19 (Piscini, Hyman, & Henry, 2016). In this regard, organisations are leveraging crowds' wisdom to perform various Human Intelligence Tasks (HITs), such as submitting novel ideas about new products/services and providing market feedback on existing products/services. Specifically, crowdsourcing allows organisations to expand their business without hiring dedicated staff to perform routine tasks. The varieties of crowdsourcing applications include crowdfunding (e.g., Kiva.org), competition-based crowdsourcing, knowledge sharing (e.g., Wikipedia), innovation communities (e.g., Dell’s IdeaStorm), and compensation-based crowdsourcing (e.g., Amazon’s Mechanical Turk, oDesk, and Rent-a-coder). This trend would be a stepping stone for building the next area of computing (Cook, et al. 2020).
In the past decade, crowdsourcing activity has grown dramatically and evolved noticeably in the forms of micro work (Howe, 2008; Deng et al., 2016). A compensation-based micro-task crowdsourcing (MCS) splits the problem into much smaller tasks that multiple crowd workers address independently in return for a reward. The unique low cost, low entry barrier and crowd wisdom leveraging MCS characteristics help companies equip themselves with new competencies (Maiolini & Naggi, 2011). A World Bank report estimated that Amazon’s Mechanical Turk (MTurk), the world’s largest compensation-based micro-task crowdsourcing, has about 500,000 registered crowd workers (Turkers) worldwide (Kuek et al., 2016). MTurk.com offers crowd workers who want to utilise their own skills and earn money by searching for interesting tasks for completion. However, if crowd workers do not believe that they can provide solutions and earn the money they deserve, they would not consider participating in an MCS platform.
Most crowd workers consider MCS as offering insecure jobs (Ross et. al., 2010) because the pay varies according to the task complexity, and the earnings are not stable. Moreover, some crowd workers may not claim payments because requesters may give micro-tasks to thousands of crowd workers and have the discretion to reject work from the crowd workers who deliver low-quality or incorrect work. Requesters often reserve the right to refuse payment even when completed work meets the requirements. As a consequence, crowd workers face inequality for distributive fairness (Deng et al., 2016). Research shows that crowd workers allocate an average of 23.2% of their capacity on tasks without payment (Berg, 2016). Due to MCS platforms' nature, namely, the lack of in-person interaction, crowd workers may refuse to participate if they perceive the payout from the system is unfair because no personnel are assigned to handle or settle any disputes.
The crowd workers who are rejected for their submitted work may leave crowdsourcing platforms entirely (Franke, Keinz, & Klausberger, 2013). While initial participation is an important first step toward realising MCS success, a platform’s eventual success and long-term viability depend on participants’ continued participation rather than their first-time use. Especially when most participants are part-timers to MCS platforms at all times, turnover is a major challenge. As such, understanding of participation motivation and continued participation intention is crucial to many MCS platforms' success. For example, Taskcn.com had over 2.8 million registered crowd workers in 2010, but fewer than a mere 10% of them (0.24 million) were paid more than once regardless of the number of completed tasks (Sun et al., 2012). In addition to the monetary incentive, factors such as work schedule flexibility, the autonomy to choose the tasks in which one is interested, and job satisfaction may promote continued participation (Taylor & Joshi, 2018).