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Cited by 96Open Source Software InnovationsDigital Platforms and EconomicsInnovation and Knowledge Management

Copy, transform, combine: Exploring the remix as a form of innovation

Open access
Flath, Christoph M., Friesike, Sascha, Wirth, Marco, Thiesse, Frédéric·2017·Journal of Information Technology
DOI 10.1057/s41265-017-0043-9
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Abstract

The reuse of existing knowledge is an indispensable part of the creation of novel ideas. In the creative domain knowledge reuse is a common practice known as “remixing”. With the emergence of open internet-based platforms in recent years, remixing has found its way from the world of music and art to the design of arbitrary physical goods. However, despite its obvious relevance for the number and quality of innovations on such platforms, little is known about the process of remixing and its contextual factors. This paper considers the example of Thingiverse, a platform for the 3D printing community that allows its users to create, share, and access a broad range of printable digital models. We present an explorative study of remixing activities that took place on the platform over the course of six years by using an extensive set of data on models and users. On the foundation of these empirically observed phenomena, we formulate a set of theoretical propositions and managerial implications regarding (1) the role of remixes in design communities, (2) the different patterns of remixing processes, (3) the platform features that facilitate remixes, and (4) the profile of the remixing platform's users.

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  • The literature on digital architecture is underpinned by the notion of massive recombination, which gives digital architecture substantial influence in shaping a new value landscape.

    “The idea of 'massive recombination' underpins the literature (cf.Flath et al. 2017), attributing to digital architecture much leverage in the formation of a new value landscape.”

    From Recombination in the open-ended value landscape of digital innovation (2018) · cites this paper as Flath et al. 2017

  • The research direction complements existing thinking on massive recombination and resource integration.

    “The research direction posed by this research commentary complements existing thinking on massive recombination (Flath et al. 2017;Yoo et al. 2010;Yoo et al. 2012) and resource integration (e.g.Lusch and Nambisan 2015).”

    From Recombination in the open-ended value landscape of digital innovation (2018) · cites this paper as Flath et al. 2017

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1 of the 137 references couldn’t be matched to a known paper.

Research works printed but not linked: 10

  1. Bastian, M., Heymann, S. and Jacomy, M. (2009). Gephi. An Open Source Software for Exploring and Manipulating Networks, in Proceedings of the 3rd AAAI International Conference on Weblogs and Social Media (San Jose, USA, 2009). California: AAAI.
  2. Birkinshaw, J., Bouquet, C. and Barsoux, J.-L. (2012). The 5 Myths of Innovation, MIT Sloan Management Review 52(2): 43-50.
  3. Hwang, E., Singh, P. and Argote, L. (2014) Jack of All, Master of Some: The Contingent Effect of Knowledge Breadth on Innovation, in Proceedings of the 35th International Conference on Information Systems (Auckland, New Zealand, 2014); Atlanta: AIS.
  4. Kane, G. and Ransbotham, S. (2012) Codification and Collaboration: Informa- tion Quality in Social Media, in Proceedings of the 33th International Conference on Information Systems (Orlando, USA, 2012); Atlanta: AIS.
  5. Kyriakou, H. and Nickerson, J.V. (2013). Idea inheritance, originality, and collective innovation, in 5th Workshop on Information on Networks (New York, USA, 2013).
  6. Lee, K.Y., Lee, M., Bassellier, G. and Faraj, S. (2010) The Impact of Emotional Expressions on Knowledge Creation in Online Communities, in Proceedings of the 31st International Conference on Information Systems (St. Louis, USA, 2010); Atlanta: AIS.
  7. Mitchell, B.T. and Subramani, M.R. (2010) Knowledge Repositories and Knowledgeable Action, in Proceedings of the 31st International Conference on Information Systems (St. Louis, USA, 2010); Atlanta: AIS.
  8. Tuite, K. and Smith, A.M. (2012) Emergent Remix Culture in an Anonymous Collaborative Art System, in Proceedings of the 8th AAAI Artificial Intelligence and Interactive Digital Entertainment Conference (Toronto, Canada, 2012); Palo Alto: AAAI, pp. 16-23.
  9. Usher, A.P. (2011). A History of Mechanical Inventions: Revised Edition, New York: Dover Publications.
  10. Yu, L.L. and Nickerson, J.V. (2011) Generating creative ideas through crowds: An experimental study of combination, in Proceedings of the 32nd International Conference on Information Systems (Shanghai, China, 2011); Atlanta: AIS.

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Authors
Flath, C. M., Friesike, S., Wirth, M., & Thiesse, F.
Affiliations
  • University of Würzburg (DE)
  • Alexander von Humboldt Institute for Internet and Society (DE)
Corresponding author
Thiesse, Frédéric
ORCID
Venue
Journal of Information Technology
Publisher
SAGE Publications
Published
2017-12
Volume
32
Issue
4
Pages
306-325
ISSN
  • 0268-3962 (ISSN-L)
  • 1466-4437
DOI
10.1057/s41265-017-0043-9
OpenAlex
W2747262803
Cited by
96
References
137
Citations by year
2026: 4 · 2025: 4 · 2024: 3 · 2023: 13 · 2022: 14 · 2021: 28 · 2020: 13 · 2019: 9 · 2018: 7 · 2017: 1
FWCI
9.84
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Information Technology (publishedVersion, cc-by)
  • Journal of the Association for Information Systems (submittedVersion)
  • VU Research Portal (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
Funders
Karlsruhe Institute of Technology
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Open Source Software Innovations
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
Keywords
remix, knowledge reuse, innovation, Thingiverse, 3D printing, design community, digital platforms, digital models, user behavior, platform characteristics, user profiles

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