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The Contribution of Different Online Communities in Open Innovation Projects

The Contribution of Different Online Communities in Open Innovation Projects. Michael A. Zeng Helmut-Schmidt-University Hamburg Institute of Technology and Innovation Management Prof. Dr. Hans Koller. Agenda. Research Questions Empirical Field Method Findings Future Research.

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The Contribution of Different Online Communities in Open Innovation Projects

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  1. The Contribution of Different Online Communities in Open Innovation Projects Michael A. Zeng Helmut-Schmidt-University Hamburg Institute of Technology and Innovation Management Prof. Dr. Hans Koller

  2. Agenda • Research Questions • Empirical Field • Method • Findings • Future Research

  3. Motivation

  4. Research Questions How do brand communities and innovation communities differ? How could they be used best in new product development processes? Innovation community Brand community ? ? ? Idea generation Screening Development Testing Launch

  5. Empirical Field Innovation community Brand community powered by

  6. Method: Sample

  7. Method: Research design

  8. Findings Brand loyalty Innovation community on crowdsourcing platform • Brand community • on social network Innovative members Idea generation Screening Development Testing Launch Idea generation Screening Development Testing Launch Open innovation process Marketing effect • Would be best to bring the potential of both communities together in a harmonized form

  9. Future Research • Does this harmonized strategy work with a larger sample? And how? • What about other fields? More complex products or processes? • Brand communities with stronger social relations than among Facebook fans?

  10. Thank you! Questions? Contact Michael Zeng Helmut-Schmidt-University/ University of the Federal Armed Forces Hamburg Institute of Technology and Innovation Management Holstenhofweg 85 22043 Hamburg Germany +49 40 6541 3735 michael.zeng@hsu-hh.de

  11. BACKUP

  12. Findings Brand loyalty Innovation community on crowdsourcing platform • Brand community • on social network Innovative members Idea generation Screening Development Testing Launch Idea generation Screening Development Testing Launch Open innovation process Marketing effect • Would be best to bring the potential of both communities together in a harmonized form

  13. Characteristics of a BC on FB According to Loewenfeld (2006): • Non-geographical • Based on interests • offline and/or online • Admirer of the brand • Interaction • Sense of community/ corporate feeling • Connection of values and needs

  14. Example

  15. Example

  16. References • Chesbrough, H. W. (2006). Open Business Models: How to Thrive in the New Innovation Landscape. Boston, MA: Harvard Business School Press. • Füller, J., Matzler, K., & Hoppe, M. (2008). Brand community members as a source of innovation. Journal of Product Innovation Management, 25(6), 608–619. • Janzik, L., & Raasch, C. (2011). Online communities in mature markets: Why join, why innovate, why share? International Journal of Innovation Management, 15(04), 797–836. • Mayring, P. (2010). Qualitative Inhaltsanalyse: Grundlagen und Techniken (11th ed.). Weinheim: Beltz. • Kim, A. J. (2000). Community Building on the Web: Includes Index. Berkeley, CA: Peachpit Press. • Möslein, K. M., Reichwald, R., & Kölling, M. (2011). Open innovation in der Dienstleistungsgestaltung. WSI Mitteilungen, 64(9), 484–490. • Muniz Jr., A.M., and O’Guinn, T.C. (2001). Brand Community. Journal of Consumer Research. 27, 4, 412–432. • Ollila, S., & Elmquist, M. (2011). Managing open innovation: Exploring challenges at the interfaces of an open innovation arena. Creativity and Innovation Management, 20(4), 273–283. • Shani, A. B., Sena, J. A., & Olin, T. (2003). Knowledge management and new product development: A study of two companies. European Journal of Innovation Management, 6(3), 137–149. • Schau, H. J., Muniz Jr., A. M., & Arnould, E. J. (2009). How Brand Community Practices Create Value. Journal of Marketing(73)5, 30-51. • Schroll, A., & Römer, S. (2011). Open Innovation heute: Instrumente und Erfolgsfaktoren. Zeitschrift für Information Management und Consulting, 26(1), 58–64.

  17. Theoretical Background: Online Communities • Online communities: • Individuals with same interests or common goals • Discussion via an Internet platform, especially Web 2.0 (Janzik, Raasch 2011; Kim 2000) • Innovation communities: • Include Lead User characteristics and innovative skills • Ideas are collaboratively developed and discussed (Janzik, Raasch 2011; Shani, Sena, Olin 2003) • Brand communities: • Strong connection to the brand and/or the product • Can be used as innovation sources (Schau, Muniz, Arnould 2009; Janzik, Raasch 2011; Muniz, O’Guinn 2001; Füller, Matzler, Hoppe 2008)

  18. Theoretical Background: Online Community Platforms • Third party platforms: • Innovation intermediary • Helps other companies to implement open innovation into their business • Two-sided market between innovator and inventor (Schroll, Römer2011, Chesbrough 2006; Möslein, Reichwald, Kölling 2011; Ollila, Elmquist 2011) • Social media • Low-cost possibility to connect with users • Critical mass cannot always be reached (Schroll, Römer2011) • Self-designed platform • Better to control • Community is smaller (Schroll, Römer 2011)

  19. Method and Data: Interview Procedure • Informed via email about the research project • 5 interviews personally at the company • 5 telephone interviews • Interview guideline ensured that the obtained data was comparable • Rather guided conversations, open-ended, and held in German • Tape-recorded • Conducted between August and September 2012 • The length of an interview ranged between ten minutes and one hour with an average duration of forty minutes • Audio files were transcribed with the software F5 • Topics of the interview guideline: • Experiences with open innovationand unserAller • Comparison with their brand community • Influence of open innovation on their product development process

  20. Method and Data: Evaluation Procedure • Evaluated with a self-developed category system, based on Mayring’s (2010) qualitative content analysis • Inductive and deductive category generation • Five categories: • Open innovation in general • Social media/ unserAller • Impact of customer integration • Growth • Future • Interviews were coded with the software MaxQDA • Inter-rater reliability with an arithmetic mean of 88.75 %

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