(2017) The open innovation research landscape: established perspectives and emerging themes across different levels of analysis, Industry and Innovation, 24:1, 8-40, DOI: 10.1080/13662716.2016.1240068 To link to this article: https://doi.org/10. 1080/13662716.2016.1240068 Published online: 07 Nov 2016.Submit your article to this journal This paper provides an overview of the main perspectives and themes emerging in research on open innovation (OI). The paper is the result of a collaborative process among several OI scholarshaving a common basis in the recurrent Professional Development Workshop on 'Researching Open Innovation' at the Annual Meeting of the Academy of Management. In this paper, we present opportunities for future research on OI, organised at different levels of analysis. We discuss some of the contingencies at these different levels, and argue that future research needs to study OI -originally an organisationallevel phenomenon -across multiple levels of analysis. integrative framework allows comparing, contrasting and integrating various perspectives at different levels of analysis, further theorising will be needed to advance OI research. On this basis, we propose some new research categories as well as questions for future research -particularly those that span across research domains that have so far developed in isolation.

Research has shown that many innovations originate not in the manufacturer but the user domain. Internet-based toolkits for idea competitions (TIC) are a novel way for manufacturers to access innovative ideas and solutions from users. Idea competitions build on the nature of competition as a means to encourage users to participate at an open innovation process, to inspire their creativity, and to increase the quality of the submissions. When the contest ends, submissions are evaluated by an expert panel. Users whose submissions score highest receive an award from the manufacturer, which is often granted in exchange for the right to exploit the solution in its domain. Following the idea of evolutionary prototyping, we developed a TIC in cooperation with a manufacturer of sports goods. The TIC was launched as a pilot in one of the company's markets. Submissions were evaluated using the consensual assessment technique. The evaluation of this study provides suggestions for further research, but also implications for managers willing to explore TIC in their organization.

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This study analyzes the value created by so-called ''toolkits for user innovation and design,'' a new method of integrating customers into new product development and design. Toolkits allow customers to create their own product, which in turn is produced by the manufacturer. In the present study, questions asked were (1) if customers actually make use of the solution space offered by toolkits, and, if so, (2) how much value the self-design actually creates. In this study, a relatively simple, design-focused toolkit was used for a set of four experiments with a total of 717 participants, 267 of whom actually created their own watches. The heterogeneity of the resulting design solutions was calculated using the entropy concept, and willingness to pay (WTP) was measured by the contingent valuation method and Vickrey auctions. Entropy coefficients showed that self-designed watches vary quite widely. On the other hand, significant patterns still are visible despite this high level of entropy, meaning that customer preferences are highly heterogeneous and diverse in style but not completely random. It also was found that consumers are willing to pay a considerable price premium. Their WTP for a self-designed watch exceeds the WTP for standard watches by far, even for the best-selling standard watches of the same technical quality. On average, a 100% value increment was found for watches designed by users with the help of the toolkit. Taken together, these findings suggest that the toolkit's ability to allow customers to customize products to suit their individual preferences creates value for them in a business-to-consumer (B2C) setting even when only a simple toolkit is employed. Alternative explanations, implications, and necessary future research are discussed.

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