Amol M. Joshi, Ph.D.
Joshi, A. M. and Lahiri, N. (2014), Language friction and partner selection in cross-border R&D alliance formation, Journal of International Business Studies. doi:10.1057/jibs.2014.56
(An earlier version of this paper was Runner-Up for the 2012 Academy of International Business (AIB) Conference Best Paper Prize)
ABSTRACT: 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 (1988–2001), 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.
Joshi, A. M. and Nerkar, A. (2011), When do strategic alliances inhibit innovation by firms? Evidence from patent pools in the global optical disc industry, Strategic Management Journal, 32: 1139–1160. doi: 10.1002/smj.929
(Nominated for the 2012 European Business School Best Paper Award in Innovation Management)
ABSTRACT: 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.
Joshi, A. (2013), “Innovation Policy," In D. J. Teece and M. A. Augier (eds.), The Palgrave Encyclopedia of Strategic Management. Hampshire: Palgrave Macmillan
ABSTRACT: Innovation policy refers to the collection of laws, standards, regulations, incentives and programmes that governments (at the supranational, national, regional and local levels) utilize to promote the development of new inventions including products, services, technologies, systems and infrastructure. Innovation policy encompasses initiatives in commerce, education, trade, finance and immigration to spur economic growth by increasing productivity, competitiveness and social welfare. This entry outlines the concept of innovation policy in the domain of strategic management. First, an overview of the history, goals and underlying principles of innovation policy is presented. Next, the primary functions and possible means of implementing innovation policy are described with an emphasis on theoretical foundations. Finally, the evaluation of innovation policy outcomes, including the intended and unintended consequences of policy changes, are briefly discussed.
Dissertation (Kenan-Flagler Business School, University of North Carolina at Chapel Hill)
TITLE: "Entrepreneurial Discovery and Information Complexity in Knowledge-Intensive Industries,"(2011)
COMMITTEE: Atul Nerkar (chair), Howard Aldrich, Rich Bettis, Christopher Bingham, Dean Shepherd (external)
ACKNOWLEDGEMENT: This research is funded in part by a Kauffman Foundation Dissertation Fellowship Grant.
AWARDS: Finalist for the Academy of Management Wiley-Blackwell Award for Outstanding Dissertation Research in Business Policy and Strategy (2012) and the INFORMS Organization Science Dissertation Proposal Competition (2010).
ABSTRACT: I investigate how the inherent complexity of the information associated with a newly introduced product affects the likelihood that the product is subsequently replicated, imitated, or both. Using information theory, I introduce a model and methods for quantifying the complexity of any product that is representable as an algorithm. I apply this methodology to construct and analyze a historical dataset of 91 digital signal processing firms and 853 product introductions (1974-2009). The empirical results support previously untested predictions from earlier simulation studies. The generalized model is extensible to many knowledge-intensive industries and has important implications for researchers, managers, and policymakers.
M.S. Thesis (Thayer School of Engineering, Dartmouth College)
Joshi, A. M. (1997). A Video Streaming Performance Model and Content Sourcing Algorithm for Optimizing the Quality of Service of a Multimedia Server: Dartmouth College.
ADVISOR: Charles Hutchinson, Dean Emeritus, Thayer School of Engineering
ACKNOWLEDGEMENT: Funded by Defense Advanced Research Projects Agency (DARPA) and National Science Foundation (NSF) Grant #CCS600658001C to Dartmouth College, “Digital Library for Networked, Dual-Use Education and Training”