REFLECTIONS ON THE 2022 AMR DECADE AWARD: CROWDSOURCING AS A SOLUTION TO DISTANT SEARCH

• 成果类型: Article
• 署名作者: Afuah, Allan; Tucci, Christopher L.
• 署名单位: University of Michigan System; University of Michigan; Imperial College London
• 刊物名称: ACADEMY OF MANAGEMENT REVIEW
• ISSN/ISSBN: 0363-7425
• DOI: 10.5465/amr.2023.0202
• 发表日期: 2023
• 页码: 597-610
• 关键词: OPEN INNOVATION; artificial-intelligence; complementary assets; capabilities; performance; COMMUNICATION; governance; KNOWLEDGE; ideas; MODEL

摘要

Since we wrote Crowdsourcing as a solution to distant search a decade ago, enthusi-asm for crowdsourcing's capacity to produce remarkable solutions to some problems has continued to grow, and profiting from crowdsourced solutions has become a strate-gic 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 con-tracts)--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 disadvan-tages that we have added. We conclude with suggestions for future research.