How to Motivate Experts to Contribute
Getting experts to contribute to open content, such as Wikipedia, is not an easy task as experts often have high demands on their time. But one way to increase expert contributions is to understand what motivates them to contribute, a University of Michigan study shows.
The study, led by U-M behavioral and experimental economist Yan Chen, finds that an accurate match between a task and an expert's expertise can significantly increase the quality and length of expert contributions. Chen and colleagues observed a lack of expert participation in Wikipedia writing and editing, resulting in inaccuracies, incompleteness and outdated information across many Wikipedia articles. Given Wikipedia's status as one of the top five most visited websites in the English-speaking world and its role as a primary knowledge source for the general public, enhancing the quality of its content has become imperative, Chen says.
"Sometimes patients even bring flawed Wikipedia articles as reference to discuss their treatment with doctors," said Chen, the Daniel Kahneman Collegiate Professor of Information at U-M's School of Information and a research professor at the Institute for Social Research.
To figure out how to motivate experts, Chen and co-authors Iman YeckeZaare of the Massachusetts Institute of Technology, Ark Fangzhou Zhang of Google, Rosta Farzan of the University of Pittsburgh and Robert Kraut of Carnegie Mellon University conducted a large-scale field experiment by sending out emails to about 4,000 academic economists, asking them to comment on articles on Wikipedia.
The study, published this month in Management Science, explored the effectiveness of different incentives in motivating experts' participation, including social impact, public recognition and the quality of match between expert skills and Wikipedia articles. The researchers found that a general ask received a positive response rate of 45%. However, when experts were informed that articles they were asked to comment on might include their own publication in the references, indicating a high-quality match, there was a 6-percentage-point increase in positive responses.
Interestingly, telling them that their contributions would influence more readers (social impact) or that their contributions would be publicly recognized (public recognition) had no influence on their response rates, the researchers say.
Furthermore, the study revealed that a more accurate actual match between an expert's expertise and a Wikipedia article not only increases the quality but also the length of the expert's contribution. Several reasons may account for this phenomenon. First, more expertise in an area reduces the cost of contribution. Secondly, experts are more inclined to enjoy reading and commenting on articles in their areas of expertise. Thirdly, experts are more likely to believe that topics they consider important should be presented accurately to the general public. Lastly, experts are likely to derive intrinsic pleasure from a feeling of competency, leading to more substantial and insightful comments within their area of expertise.
Beyond match quality, two significant factors influencing both the quality and length of an expert's contribution are expert reputation and the length of the Wikipedia article. The reputation of the expert and the length of Wikipedia article directly correlate with the quality and length of the contribution: lower reputation and a shorter Wikipedia article tend to result in shorter and less substantial contributions.
However, among these factors, accurate matching between expertise and the task is the most significant predictor of both contribution length and quality, Chen and colleagues say.
This finding extends beyond contributions to digital public goods and can be applied to other types of volunteer activities where expertise matters. For instance, recruiting corporate executives to give students career advice, seeking mentors for startup entrepreneurs, finding lawyers to offer legal consultations to low-income individuals, or asking employees to contribute to corporate initiatives beyond their typical roles and responsibilities.
"Given the significant contributions made by volunteers in many aspects of our lives, understanding how to motivate expert volunteers to participate is crucial," Chen said.