Crowdsourcing is a particular form of open innovation (OI) that aims to boost idea-generation in innovation processes. The underlying rationale is that the collective intelligence of a large number of contributors outside the firm's boundaries increases the likelihood of achieving ‘extreme outcomes’, i.e., high quality ideas with exceptional business potential. Due to the idiosyncrasies that differentiate crowdsourcing from other forms of OI, the findings from prior research on the performance implications of OI cannot be directly extended to crowdsourcing. Similarly, the findings on the effect of internal R&D on firm performance cannot be directly applied to crowdsourcing due to the greater uncertainty in dealing with a crowd of unknown individuals outside the organization whose ideas have to be evaluated and ultimately processed internally. Thus, while crowdsourcing research has recently burgeoned, it is ambiguous as to whether and when crowdsourcing is beneficial for firms. In fact, the overall effect of crowdsourcing on a firm's future profits has not been thoroughly investigated. To fill this gap, we conducted an event study analyzing stock market reactions to crowdsourcing announcements, a forward-looking market-based measure able to isolate the effect of crowdsourcing on a firm's future profits, which we refer to as firm stock market performance. Drawing on the resource-based view, we argue that an external crowd can become a valuable resource if the firm is able to extract value from it. Our findings show that two key contingency factors, i.e., brand value and investment opportunities, determine the boundary conditions that enable firms to extract value from the crowd, resulting in a positive stock market reaction to the announcement of a crowdsourcing campaign. In addition to advancing scholarly knowledge on crowdsourcing, our results provide practitioners with relevant indications for profitable crowdsourcing campaigns.

When does crowdsourcing benefit firm stock market performance?

Cappa F.;
2019-01-01

Abstract

Crowdsourcing is a particular form of open innovation (OI) that aims to boost idea-generation in innovation processes. The underlying rationale is that the collective intelligence of a large number of contributors outside the firm's boundaries increases the likelihood of achieving ‘extreme outcomes’, i.e., high quality ideas with exceptional business potential. Due to the idiosyncrasies that differentiate crowdsourcing from other forms of OI, the findings from prior research on the performance implications of OI cannot be directly extended to crowdsourcing. Similarly, the findings on the effect of internal R&D on firm performance cannot be directly applied to crowdsourcing due to the greater uncertainty in dealing with a crowd of unknown individuals outside the organization whose ideas have to be evaluated and ultimately processed internally. Thus, while crowdsourcing research has recently burgeoned, it is ambiguous as to whether and when crowdsourcing is beneficial for firms. In fact, the overall effect of crowdsourcing on a firm's future profits has not been thoroughly investigated. To fill this gap, we conducted an event study analyzing stock market reactions to crowdsourcing announcements, a forward-looking market-based measure able to isolate the effect of crowdsourcing on a firm's future profits, which we refer to as firm stock market performance. Drawing on the resource-based view, we argue that an external crowd can become a valuable resource if the firm is able to extract value from it. Our findings show that two key contingency factors, i.e., brand value and investment opportunities, determine the boundary conditions that enable firms to extract value from the crowd, resulting in a positive stock market reaction to the announcement of a crowdsourcing campaign. In addition to advancing scholarly knowledge on crowdsourcing, our results provide practitioners with relevant indications for profitable crowdsourcing campaigns.
2019
Brand value
Crowdsourcing
Investment opportunities
Open innovation
R&D
Stock market performance
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/67245
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