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Understanding and Leveraging Crowd Development in Crowdsourcing

abstract: Although many examples have demonstrated the great potential of a human crowd as an alternative supplier in creative problem-solving, empirical evidence shows that the performance of a crowd varies greatly even under similar situations. This phenomenon is defined as the performance variation puzzle in crowdsourcing. Cases suggest that crowd development influences crowd performance, but little research in crowdsourcing literature has examined the issue of crowd development.

This dissertation studies how crowd development impacts crowd performance in crowdsourcing. It first develops a double-funnel framework on crowd development. Based on structural thinking and four crowd development examples, this conceptual framework elaborates different steps of crowd development in crowdsourcing. By doing so, this dissertation partitions a crowd development process into two sub-processes that map out two empirical studies.

The first study examines the relationships between elements of event design and crowd emergence and the mechanisms underlying these relationships. This study takes a strong inference approach and tests whether tournament theory is more applicable than diffusion theory in explaining the relationships between elements of event design and crowd emergence in crowdsourcing. Results show that that neither diffusion theory nor tournament theory fully explains these relationships. This dissertation proposes a contatition (i.e., contagious competition) perspective that incorporates both elements of these two theories to get a full understanding of crowd emergence in crowdsourcing.

The second empirical study draws from innovation search literature and tournament theory to address the performance variation puzzle through analyzing crowd attributes. Results show that neither innovation search perspective nor tournament theory fully explains the relationships between crowd attributes and crowd performance. Based on the research findings, this dissertation discovers a competition-search mechanism beneath the variation of crowd performance in crowdsourcing.

This dissertation makes a few significant contributions. It maps out an emergent process for the first time in supply chain literature, discovers the mechanisms underlying the performance implication of a crowd-development process, and answers a research call on crowd engagement and utilization. Managerial implications for crowd management are also discussed. / Dissertation/Thesis / Doctoral Dissertation Business Administration 2017

Identiferoai:union.ndltd.org:asu.edu/item:45033
Date January 2017
ContributorsLiu, Zhongzhi (Author), Kull, Thomas (Advisor), Dooley, Kevin (Committee member), Oke, Adegoke (Committee member), Arizona State University (Publisher)
Source SetsArizona State University
LanguageEnglish
Detected LanguageEnglish
TypeDoctoral Dissertation
Format240 pages
Rightshttp://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved

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