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Crowdsourcing Business Model Innovation
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Author: Florian Waldner, U. of Vienna
Author: Marion Kristin Poetz, Copenhagen Business School
Author: Marcel Bogers, U. of Copenhagen
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Successfully adapting existing business models or developing new ones significantly influences a firm’s ability to generate profits and develop competitive advantages. However, business model innovation is perceived as a complex, risky and uncertain process and its success strongly depends on whether or not the firm is capable of understanding and addressing their customers’ needs. We conduct a quantitative exploratory case study to investigate how crowdsourcing-based search approaches among user communities can contribute to developing business model innovation. Drawing on data from a crowdsourcing initiative designed to develop ideas for new business models in the podcast industry, we provide first exploratory insights into the value of crowdsourcing for innovating a firm’s way of creating, delivering and capturing value, and discuss characteristics of crowd-contributors that influence the quantity and quality of the outcomes. Our findings indicate that crowd contributions go beyond suggesting new value propositions, they also comprise novel and useful ideas for innovating a firm’s approach to value delivery and value capture. These findings, which are quite counterintuitive from the perspective of classic strategy making literature, suggest that, at least under certain conditions, crowdsourcing might constitute a promising method to alleviate the process of successful business model innovation.
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Search Terms: Open innovation | Ideation | User communities
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Paper is No Longer Available Online: Please contact the author(s).
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Entrepreneurial Intent and Commercialization ofApplications on a Technology Platform
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Author: Morten H. J. Fenger, Aarhus U.
Author: Lars Frederiksen, Aarhus U.
Author: Hans Jørn Juhl, Aarhus U.
Author: Joachim Scholderer, Aarhus U.
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Third-party providers as entrepreneurs boost technology platforms. Yet, despite increasing interest in technological platforms, existing research offers little predictive insight into how firms can identify individuals who are likely to become entrepreneurs. We take the strategic perspective of a platform owning company, asking how to pinpoint those individuals who transition into entrepreneurship in the near future. We base our analysis on automatically registered behavioral data, such as the complete sales history of all applications related to a technological platform, and the complete history of communications in communities related to the platform. We employ logistic regression models to predict: (a) the transition from registered platform user to third-party developer (i.e. entrepreneurial intent) and (b) the launch of a first platform application (i.e. commercialization). We control for individuals’ social network positions, their communication behaviors, exposure to input from other entrepreneurs (i.e social contagion), and their early adoption and lead- user traits. We show that even after inclusion of these controls volume-wise “bulk” consumption still adds significantly to the predictional power on each step towards entrepreneurship. The impact of simple measures for bulk consumption on entrepreneurship is often ignored in the entrepreneurship literature. Our study contributes to the strategic management literature on the dynamics of innovation on technological platforms, by explicitly linking the production and consumption sides of two-sided markets. It also adds to the entrepreneurship literature by showing how the entrepreneurial process manifests itself in the context of technological platforms.
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Search Terms: Platforms | Entrepreneurship | Applications
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Paper is No Longer Available Online: Please contact the author(s).
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The influence of network positions on user innovation communities
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Author: Wonho Lee, Korea Advanced Institute of Science and Technology (KAIST)
Author: Youngbae Kim, Korea Advanced Institute of Science and Technology (KAIST)
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User innovators join communities of interest in search of support for their unmet needs, however only a handful of scholars explored how different network relationships alter an individual¡¯s innovative performance. This study explores network positional (degree centrality and betweenness centrality) influence on innovative performance, and furthermore investigates the influences of social network on originality of the innovation. Unique data set was created to explore these relationships. 594,236 interaction data between 3,489 community members of XDA developer¡¯s community was collected. According to the findings, both network positions hold a boundary condition in optimum number of relationships that are beneficial for innovative performance. Where beyond a certain boundary, innovative performance saturates. The main result of this study is that innovative outcomes vary in originality (e.g. sources used in the development process). In relation to the innovator¡¯s social network position, individuals that occupy a higher between centrality position are more likely to innovate by using peer developed innovations as a source, whereas individuals that possess higher degree centrality are likely to innovate with and without peer developed innovation sources. Major implication of this study is that network positional influences innovative performance with an inverted u-shape relationship where beyond certain boundaries the innovative performance saturates. Furthermore, individuals with high betweenness centrality are more likely to innovate with multiple sources compared to individuals that possess high degree centrality.
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Search Terms: User innovation | Social network position | Communities
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Paper is No Longer Available Online: Please contact the author(s).
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The Distance Dilemma: Effects of Knowledge Distance on Solvers' Adoption of Broadcasted R&D Problems
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Author: Christoph Ihl, Hamburg U. of Technology
Author: Robin Kleer, RWTH Aachen U.
Author: Jan Willem Reerink, Hamburg U. of Technology
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Open innovation is exemplified in crowdsourcing platforms that allow firms to broadcast R&D problems, which they are unable to solve by their own means, to a wide range of potential solvers. A few studies so far indicate that especially solvers from distant fields have higher chances to make the winning contributions in crowdsourcing contests. It is not fully understood, however, what generally attracts potential solvers to crowdsourcing in the first place and how solvers’ knowledge distance towards the broadcasted innovation problem in particular affect their initial interest and adoption. To investigate this question, we situate our study in the field of nanoscience and technology. By the means of topic modeling with over 900.000 scientific papers and 35 real requests for proposals (RfPs), we are able to locate solvers and problems within a knowledge space and measure the distance between them. In a field experiment, we invite scientists to inspect randomly assigned RfPs of high and low distance. In a subsequent discrete choice analysis, we measure their willingness to engage in solving the assigned R&D problem conditional on contractual arrangements. Our findings lend support to the conjecture that knowledge distance reduces scientists’ attention paid towards broadcasted innovation problems and their willingness to solve them. Contractual arrangements can only partially mitigate this effect. Solvers that are more closely linked to the problem are also more responsive to contract attributes. More distant solvers can best be incentivized by higher award money and by the right to license the invention also to third parties. Overall, we shed light on managing an important trade-off in innovation crowdsourcing: while more distant solvers could make valuable contributions, they are more difficult to contract.
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Search Terms: Innovation contests | broadcast search | cognitive distance
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Paper is No Longer Available Online: Please contact the author(s).
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