Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Computer Information Systems

First Advisor

Arun Rai

Second Advisor

Yu-Kai Lin

Third Advisor

Likoebe Maruping

Fourth Advisor

Ling Xue

Fifth Advisor

Elena Karahanna


The proliferation of open-source software (OSS) projects makes it important to understand how to achieve innovation speed and novelty in this context. Although the prior OSS development literature has deciphered how OSS projects can use arm’s length mechanisms of digital platforms to self-organize, we lack parsimonious collective-level constructs to illuminate how collectives that achieve favorable innovation outcomes (i.e., high speed, high novelty, and both) organize differently from the others. To address this, we advance a collective attention view by conceptualizing: (1) attention partition, i.e., how collectives differentiate individuals’ primary foci of attention and (2) attention augmentation, i.e., how collectives integrate individuals’ secondary foci with others’ work. We further elaborate each of these constructs based on attention to issues or modules, rendering a novel perspective of collective attention.

Using data of 3,052 release cycles from 363 GitHub machine-learning projects, we conduct fuzzy-set qualitative comparative analyses to investigate how attention partition and attention augmentation by issues and by modules combine to impact innovation productivity of an OSS project in a release cycle. We find that a dual focus (attention partition and attention augmentation) of collective attention with a two-way (issue and module) orientation is a contingency-robust solution to achieve a singular goal of either high speed or high novelty. However, for achieving the dual goal of high speed and high novelty, additional contingencies, including a short release cycle with many developers working on a broad scope of innovative work, are needed. We also find that a one-way dual focus of collective attention can be sufficient to achieve a singular goal as the contingencies vary. Collectively, we contribute a novel dual focus perspective of collective attention for innovation productivity in open-source innovation.

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