Crowdsourcing to Develop Open-Access Learning Resources on Antimicrobial Resistance

ObjectivesAntimicrobial resistance (AMR) is a significant threat to global public health. Many medical curricula have limited clinical cases and materials focused on AMR. Enhanced AMR education and training are needed to support antimicrobial stewardship programmes. We used crowdsourcing methods to develop open-access, learner-centred AMR resources. Crowdsourcing is the process of having a large group, including experts and non-experts, solve a problem and then share solutions with the public.MethodsWe organised a global crowdsourcing contest soliciting AMR-related multiple-choice questions, infographics, and images. First, we convened a diverse steering committee group to finalise a call for entries. Second, we launched the contest and disseminated the call for entries using social media, blog posts, email, and an in-person event. Partner institutions included two digital healthcare platforms: Fig. 1® and Ding Xiang Yuan. Both organizations serve as online communities for healthcare specialists and professionals to report and comment on clinical information. At the end of the call, solicited entries were screened for eligibility and judged on merit and relevance to AMR learning and education. Exceptional entries were recognised, awarded prizes, and further reviewed for sharing with the public via open-access platforms.ResultsWe received 59 entries from nine countries. These included 54 multiple-choice questions, four infographics, and one image. Eligible entries (n = 56) were reviewed and assigned a score on a 1–10 scale. Eight entries received mean scores greater than 6.0 and were selected as finalists. The eight finalist entries consisted of three infographics and five multiple-choice questions. They were disseminated through open-access publications and online medical communities.ConclusionsWe demonstrate that crowdsourcing challenge contests can be used to identify infectious disease teaching materials. Medical educators and curriculum developers can adapt this method to solicit additional teaching content for medical students.

The Nonlinear Impact of Task Rewards and Duration on Solvers’ Participation Behavior: A Study on Online Crowdsourcing Platform

Crowdsourcing has attracted significant attention in the past decade because it has more competitive advantages than traditional methods for mobilizing distributed labor and utilizing innovation. Crowdsourcing contests are one of the most popular and effective crowdsourcing modes. Reasonable task rewards and duration are the key factors for seekers to attract solvers who can efficiently participate in the crowdsourcing contest task. Previous studies have mainly focused on task results to analyze solvers’ participation behavior in crowdsourcing contests, but have paid little attention to the task process, and there have been conflicting conclusions regarding the impact of task rewards and duration on solvers’ participation behavior and the performance of crowdsourcing contests. In view of this gap, this study collected 2706 logo design task data points from 2015–2017 on an online crowdsourcing platform and measured the performance of solvers’ participation behavior in two stages. The participation time was used to represent the performance of solvers’ participation behavior in the task process, while the number of submissions of solutions was used to represent the performance of participation behavior in the task result. The results show that task rewards and duration have an inverted U-shaped effect on the number of submissions, money rewards have a positive impact on participation time, and duration has an inverted U-shaped relationship with participation time. This study proposes the nonlinear effects of task rewards and duration on participation behavior and explains the reason for the conflicting results of previous studies. This paper also expands upon existing research by using solvers’ participation time in the task process to measure the performance of solvers’ participation behavior.

Crowdsourcing to identify social innovation initiatives in health in low- and middle-income countries

Background Crowdsourcing is a distributed problem-solving and production mechanism that leverages the collective intelligence of non-expert individuals and networked communities for specific goals. Social innovation (SI) initiatives aim to address health challenges in a sustainable manner, with a potential to strengthen health systems. They are developed by actors from different backgrounds and disciplines. This paper describes the application of crowdsourcing as a research method to explore SI initiatives in health. Methods The study explored crowdsourcing as a method to identify SI initiatives implemented in Africa, Asia and Latin America. While crowdsourcing has been used in high-income country settings, there is limited knowledge on its use, benefits and challenges in low- and middle-income country (LMIC) settings. From 2014 to 2018, six crowdsourcing contests were conducted at global, regional and national levels. Results A total of 305 eligible projects were identified; of these 38 SI initiatives in health were identified. We describe the process used to perform a crowdsourcing contest for SI, the outcome of the contests, and the challenges and opportunities when using this mechanism in LMICs. Conclusions We demonstrate that crowdsourcing is a participatory method, that is able to identify bottom-up or grassroots SI initiatives developed by non-traditional actors.

Joint vs. Separate Crowdsourcing Contests

In a crowdsourcing contest, innovation is outsourced by a firm to an open crowd that competes in generating innovative solutions. Given that the projects typically consist of multiple attributes, how should the firm optimally design a crowdsourcing contest for such a project? We consider two alternative mechanisms. One is a joint contest, where the best solution is chosen from the joint solutions across attributes submitted by all contestants. The other is multiple separate parallel subcontests, with each dedicated to one attribute of the project. It is intuitive that the separate contest has the advantage of potentially creating a “cooperative” final solution contributed by different contestants. However, somewhat surprisingly, we show that the separate contest may reduce the incentive for the crowd to exert effort, resulting in the joint contest becoming the optimal scheme. The comparison of the expected best performances in the two contests depends on the project’s characteristics. For example, if contestants’ performances have a sufficiently high (respectively, low) level of randomness, the separate (respectively, joint) contest is optimal. If the number of contestants is large (respectively, small) enough, the separate (respectively, joint) contest is optimal. Moreover, we find that when the prize is endogenized, the optimal amount of the prize in the joint contest is no less than that in the separate contest. Finally, we extend the model to account for contestants with heterogeneous types. This paper was accepted by Gad Allon, operations management.

How to Bid Success in Crowdsourcing Contest? ― Evidence from the Translation Tasks of Tripadvisor

Material incentive is the main motivation for solvers to attend crowdsourcing tasks. So raising the bidding success rate is benefit to inspire the solvers attendance’ and increase the answering quality. This paper analyzes the effect of participation experience, task-fit capability, participation strategy and task attribute on the solvers bidding success by the solvers attending the series tasks of Tripadvisor. The results show that: 1) Participation times enrich the participation experiences and promote the bidding success, while bidding success times and last performances lower the bidding success because of the cognitive fixation; 2) The chance of bidding success will be increase when the solver own high task-fit capability; 3) The relationship between task submit sequence and bidding success is the type of reverse U shape, and the optimal submit sequence rate on the top of the reverse U shape; 4) Higher task difficulty lower bidding success, while higher task density easier bidding success.

How to enhance solvers’ continuance intention in crowdsourcing contest

Purpose The purpose of this paper is to explore the underlying mechanisms through which interactivity and fairness perception impart influence on solvers’ continuance intention in crowdsourcing contest settings. Design/methodology/approach On basis of self-determination theory and social exchange theory, this study focuses on the mediating roles of motivation and platform trust to explain the underlying influence processes of interactivity and fairness perception on continuance intention. A sample of 306 solvers was obtained from an online crowdsourcing platform through two separated surveys. The hypotheses were tested using the partial least squares method and bias-corrected bootstrapping method. Findings The empirical results indicate that motivation and platform trust together fully mediate the effect of interactivity on continuance intention, and the effect of fairness perception on continuance intention is also fully mediated by motivation and platform trust. While motivation is found to have a stronger mediating effect than platform trust does. Originality/value This study contributes to the crowdsourcing research by figuring out the pathway through which interactivity and fairness perception influence solvers’ continuance intention.