Disentangling the collective motivations for user innovation in a 3D printing community

Michael A. Stanko and B.J. Allen

Technovation, 2022, vol. 111, issue C

Abstract: Online innovation communities encourage innovators to build upon others' prior work (i.e., remixing). This generative user innovation necessitates new theorization to better understand the interplay between characteristics of the source innovation and the community's collective motivation. Motivation is a heightened concern in online communities where contributors often select which problems warrant their effort. Two studies improve our understanding of how the community's motivations compel remixing and impact two aspects of the depth of these remixes (improvement and differentness). First, hypotheses regarding the community's collective remix response are developed and tested. After this, an exploratory (fsQCA) study seeks out configurations of these motivations that consistently result in improved and different remixes. Using data from thingiverse.com, we show that established motivations for user innovation (enjoyment, learning, use-value) motivate remixing, but learning and use-value's effects are moderated by source innovation quality. Learning and use-value are only impactful for high quality source objects. We also demonstrate that originality of the source object has an inverted-U relationship with remixing; innovations need to be novel, but not drastically different from expectations to generate a remix response from the community.

Keywords: User innovation; motivation; 3D printing; online communities; Digital remixing (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166497221001681
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:111:y:2022:i:c:s0166497221001681

DOI: 10.1016/j.technovation.2021.102387

Access Statistics for this article

Technovation is currently edited by Jonathan Linton

More articles in Technovation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().