Getting experts to contribute to open content like Wikipedia is challenging, as their time is often in high demand. However, a study from the University of Michigan shows that understanding what motivates experts can increase their contributions.
The study finds that a good match between a task and an expert’s expertise significantly improves the quality and length of their contributions.
Lack of participation
The researchers noted a lack of expert participation in writing and editing Wikipedia articles, leading to inaccuracies, incomplete information, and outdated content. With Wikipedia being one of the most visited websites and a primary knowledge source, improving its content quality is crucial.
“Patients sometimes bring flawed Wikipedia articles to discuss treatments with their doctors,” the authors explain.
To understand how to motivate experts, researchers conducted a large-scale experiment by emailing around 4,000 academic economists, asking them to review Wikipedia articles.
A range of incentives
The study tested various incentives for motivating expert participation, such as social impact, public recognition, and matching expert skills with specific Wikipedia articles.
A general request for contributions received a 45% positive response rate. When experts were informed that articles might reference their own publications, indicating a high-quality match, the positive response rate increased by 6 percentage points.
Interestingly, incentives like social impact and public recognition did not affect response rates, the researchers found.
A good match
Moreover, an accurate match between an expert’s expertise and a Wikipedia article not only increased the quality but also the length of their contributions.
Several factors explain this phenomenon. First, greater expertise reduces the effort required to contribute. Second, experts enjoy engaging with content in their field. Third, they believe in the importance of accurate information for the public. Lastly, experts derive intrinsic satisfaction from contributing competently to their area of expertise.
Beyond match quality, two other factors—expert reputation and article length—also influence contribution quality and length. Experts with lower reputations and shorter Wikipedia articles tend to produce shorter, less substantial contributions.
However, the most significant predictor of contribution length and quality is the match between expertise and the task.
This finding applies beyond digital public goods to other volunteer activities requiring expertise. For example, recruiting corporate executives to advise students, finding mentors for entrepreneurs, seeking lawyers to provide legal aid to low-income individuals, or asking employees to contribute to corporate projects beyond their usual roles.
“Given the vital role of volunteers in many areas, understanding how to motivate expert volunteers is essential,” the authors conclude.
