Research and development (R&D) consortia are specialized strategic alliances that shape the direction and scope of firm innovation activities. Little research exists on the performance consequences of participating in R&D consortia. We study the effect of patent pools, a unique form of R&D consortia, on firm performance in innovation. While prior research on alliances generally implies that patent pools enhance firm innovation, our study finds the opposite. Analyzing data on systemic innovation in the global optical disc industry, we find that patent pool formation substantially and significantly decreases both the quantity and quality of patents subsequently generated by licensors and licensees relative to the patenting activity of nonparticipants. Our empirical findings suggest that patent pools actually inhibit, rather than enhance, systemic innovation by participating firms.

Knowledge production and scientific discourse are observable in published scholarly texts. Citations capture knowledge consumption and impact. Drawing from the sociology of science, our theoretical framework posits scientific communities as thought collectives with distinctive thought styles that embed a hidden topic structure and rhetorical signals into a journal’s published articles. We hypothesize and uncover how an article’s topic attributes (structure, focus, and newness) and rhetorical attributes (inclusiveness, exclusiveness, tentativeness, and certainty) are related to future knowledge consumption. We empirically test our ideas by applying text mining algorithms to model topics and extract rhetorical signals from 1,646 strategy articles composed of nearly 18 million words generating 172,237 citations over 35 years. We find that strategy articles’ hidden topic structure explains 14% of variance in scientific impact. We also show that topic focus and topic newness each independently, directly, and significantly increase impact. As for newness, the first two articles published on a new topic each generate a citation premium >100%, which is higher within the focal thought collective than outside. Importantly, we find that the citation premium of newness increases with greater topic focus (which attracts attention) and greater inflow of prior intracollective knowledge (which enhances absorption). Impact also increases when authors present new topics using a rhetorical style that is more tentative than certain. Overall, our findings demonstrate that topic and rhetorical attributes, as constitutive elements of scientific content, are independently and interdependently related to the consumption of strategy articles across thought collectives in management research.

The substantial volume, continued growth, and resulting complexity of the scientific literature not only increases the need for systematic, replicable, and rigorous literature reviews, but also highlights the natural limits of human researchers’ information processing capabilities. In search of a solution to this dilemma, computational techniques are beginning to support human researchers in synthesizing large bodies of literature. However, actionable methodological guidance on how to design, conduct, and document such computationally augmented literature reviews is lacking to date. We respond by introducing and defining computational literature reviews (CLRs) as a new review method and put forward a six-step roadmap, covering the CLR process from identifying the review objectives to selecting algorithms and reporting findings. We make the CLR method accessible to novice and expert users alike by identifying critical design decisions and typical challenges for each step and provide practical guidelines for tailoring the CLR method to four conceptual review goals. As such, we present CLRs as a literature review method where the choice, design, and implementation of a CLR are guided by specific review objectives, methodological capabilities, and resource constraints of the human researcher.

How does language friction affect alliance formation? Language friction is a form of cultural friction arising from structural differences in the respective languages used by potential partners to reason and solve problems together. A little language friction may prompt partners to rethink solutions, thereby enhancing collaboration, but excessive friction may impede collaboration. We develop a Language Friction Index (LFI) to quantify relative differences in linguistic structure for any language pair. Utilizing a unique data set of semiconductor design activities (1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001), our empirical analysis finds an inverted U-shaped relationship between partners' LFI and the likelihood of cross-border research and development (R&D) alliance formation. This relationship is further moderated by prior ties and technological distance. Our findings have several important implications, including: (1) language differences are a measurable and discernible source of cultural friction; (2) the effects of language friction are economically significant and strategically consequential; (3) certain aspects of language friction occur independent of language proficiency and persist despite the use of lingua franca to reduce language barriers; (4) linguistic diversity is an indirect marker of cognitive diversity, which is useful in boosting creativity, especially in first-time collaborations; (5) beyond R&D alliances, language friction may also influence other types of strategic interactions and organizational processes.

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