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.

在线创新社区鼓励创新者在他人先前工作的基础上再接再厉（即重新混合）。这种生成性用户创新需要新的理论来更好地理解源创新特征与社区集体动机之间的相互作用。在在线社区中，动机是一个高度关注的问题，贡献者通常会选择哪些问题值得他们努力。两项研究提高了我们对社区动机如何迫使重新混音和影响这些混音深度的两个方面（改进和差异）的理解。首先，开发和测试关于社区集体混音反应的假设。在此之后，一项探索性 (fsQCA) 研究寻找这些动机的配置，这些配置始终会导致改进和不同的混音。使用来自 thingiverse.com 的数据，我们表明用户创新（享受、学习、使用价值）的既定动机会激发再混合，但学习和使用价值的影响受源创新质量的影响。学习和使用价值只对高质量的源对象有影响。我们还证明了源对象的原创性与重新混合具有倒 U 关系；创新必须是新颖的，但不能与期望产生太大的不同，以产生社区的混音反应。我们还证明了源对象的原创性与重新混合具有倒 U 关系；创新必须是新颖的，但不能与期望产生太大的不同，以产生社区的混音反应。我们还证明了源对象的原创性与重新混合具有倒 U 关系；创新必须是新颖的，但不能与期望产生太大的不同，以产生社区的混音反应。