Content Factor Analysis of Crowd Workers' Satisfaction
Andrey Barashev, Guoxin Li · 2019
Our study uses semi-structured interviews and Two-factor theory in order to examine drivers influencing task solvers' feeling of satisfaction on the crowdsourcing platform. Satisfaction could effectively motivate workers to exert higher effort and performance thus leading to better working results. Current study results proved that we can delineate platform features that would be attributed to the theoretically proposed content factors of recognition, achievement, responsibility, advancement, personal growth in competence, challenging work, opportunity to do something meaningful, involvement in decision making, and sense of importance to the organization. Besides, this study shows that recognition, personal growth in competence, achievement, and advancement are indeed of the most important for the workers. Hence, improving the above-said features is a good way for an increase in workers' level of satisfaction. A clear understanding of what influence workers could help work providers and platform managers to implement new features and rules so as to facilitate higher satisfaction.