Reflections on the 2022 AMR Decade Award: Crowdsourcing as a Solution to Distant Search

众包 过程(计算) 盈利能力指数 外包 事前 数据科学 收入 众包软件开发 热情 业务 营销 知识管理 计算机科学 经济 万维网 心理学 财务 软件系统 宏观经济学 软件建设 操作系统 程序设计语言 社会心理学 软件
作者
Allan Afuah,Christopher L. Tucci
出处
期刊:Academy of Management Review [Academy of Management]
卷期号:48 (4): 597-610 被引量:5
标识
DOI:10.5465/amr.2023.0202
摘要

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.
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