Reflections on the 2022 AMR Decade Award: Crowdsourcing as a Solution to Distant Search
回顾了众包研究十年进展，反思了原论文中市场与层级二分法及无事前合同市场的理论贡献，并提出了一个分析众包对寻求者盈利能力影响的框架，包含AI、众包流程、收入模型等新要素。
Since we wrote “Crowdsourcing as a solution to distant search” a decade ago, enthusiasm for crowdsourcing’s capacity to produce remarkable solutions to some problems has continued to grow, and profiting from crowdsourced solutions has become a strategic goal for more and more firms. Crowdsourcing research has progressed impressively, with more progress made in researching the phenomenon than in theorizing about it. We are deeply honored by the 2022 Decade Award. In this manuscript, we reflect on the factors that led to this progress in crowdsourcing research, and how the theoretical insights from our paper––e.g., markets in the hierarchies-markets dichotomy are made up of markets with ex ante contracts and crowdsourcing (markets with no ex ante contracts)––may have influenced that progress. Also, because profits have become the ultimate goal of a large number of the seekers of solutions through crowdsourcing, we present an outline of a framework for exploring the impact of crowdsourcing on a seeker’s profitability. The framework builds on insights from the paper and new constructs in crowdsourcing such as artificial intelligence (AI), the crowdsourcing process, revenue models, complementary assets, and organizing to minimize crowdsourcing disadvantages that we have added. We conclude with suggestions for future research.