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Developing Best Practices in Crowdsourcing

LISH researchers are conducting experiments into the optimal design parameters for crowdsourcing challenges and characterizing the best practices in crowdsourcing. For example, experiments are designed to help understand the role of non-cash awards, career signaling, and community prestige as drivers for participation and performance for data science challenges.

  • Social Comparison and Contests

    In this project, we study the effect of social comparison on inequality in contest environment. We hypothesize that the effects of social comparison on effort will differ for top-performers and bottom-performers in a way that inequality increases, where we consider inequality both in terms of the dispersion of outcomes... Read more about Social Comparison and Contests

  • Best Management Practices

    LISH is working to develop testable systems and methods to help open innovation (OI) practitioners explore techniques for best practices. To date, the lab has spent extensive time studying both contests and communities with profit companies, governments, academic research centers, and platforms. Research in these areas explore... Read more about Best Management Practices

  • Races vs. Tournaments

    Contests are frequently used to raise the workers’ productivity and innovation in business, government, and many other settings.  They can take many different formats or designs, but two seem prevalent:  the race and the tournament. Races set the incentives by rewarding the first person to meet a specified,... Read more about Races vs. Tournaments

  • Optimal Prize Structure

    One of the strongest design parameters for contests is the prize structure, i.e., the number and level of prizes. In developing best practices, we are working to provide guidance to practitioners to optimize the use of prize funds. Optimal selection of prizes is a complex task. For tasks with diminishing returns to effort (the 100th hour of work improves the output less than the 1st hour),... Read more about Optimal Prize Structure