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• Working Paper | HBS Working Paper Series | 2013

  Hidden Structure: Using Network Methods to Map System Architecture

  Carliss Y. Baldwin, Alan MacCormack and John Rusnak

  In this paper, we describe an operational methodology for characterizing the architecture of technical systems and demonstrate its application to a large sample of software releases. Our methodology is based upon network graphs and allows us to identify and define three fundamental architectural patterns, which we call core-periphery, multi-core, and hierarchical. We apply our methodology to a sample of 1,286 software releases from 17 applications and find that 70% to 80% of these systems possess a core-periphery architecture under our classification scheme. This type of architecture is characterized by having a single dominant cyclic group (the Core) that is large relative to other cyclic groups and above a threshold with respect to system size. We find that the size of the Core varies widely, even for systems that perform the same function. These differences appear to be associated with different models of development—open, distributed organizations tend to develop systems with smaller Cores, while closed collocated organizations tend to develop systems with larger Cores. Our findings represent a first step in establishing some "stylized facts" about the fine-grained structure of large, real-world technical systems.

  Citation:

  Baldwin, Carliss Y., Alan MacCormack, and John Rusnak. "Hidden Structure: Using Network Methods to Map System Architecture." Harvard Business School Working Paper, No. 13–093, May 2013.

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• Case | HBS Case Collection | 2013

  Barnes & Noble: Managing the E-Book Revolution

  Alan MacCormack, Brian Kimball Dunn and Chris F. Kemerer

  The case describes competition in the market for E-Books, and Barnes & Noble's Strategy in this industry. As a traditional retailer, B&N was challenged by the introduction of digital technologies that allow books to be published, distributed and sold to consumers electronically. New competitors like Amazon and Apple attacked the traditional industry structure, creating many uncertainties over the long term viability of traditional retailers. Amid this uncertainty, B&N must decide how to compete, in terms of both devices that can read E-Books, as well as standards for their distribution. Should they create a separate digital business, centered around their "Nook" E-Book reader, or maintain an integrated strategy? And how should they think about the fragmented standards for distributing E-Books? The case allows students to probe the dynamics of platform based industries, as well as what happens in traditional industries when attacked by new competitors adopting new digital technologies. It is developed using public source material.

  Keywords: innovation; product development; technology strategy; platform competition; Standards; disruptive innovation; Innovation Strategy; Technology; Product Development; Technology Platform; Standards; Disruptive Innovation; Retail Industry; Publishing Industry; North America;

  Citation:

  MacCormack, Alan, Brian Kimball Dunn, and Chris F. Kemerer. "Barnes & Noble: Managing the E-Book Revolution." Harvard Business School Case 613-073, March 2013.

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• Article | Nature Biotechnology | February, 2013

  Prize-based Contests Can Provide Solutions to Computational Biology Problems

  Karim R. Lakhani, Kevin Boudreau, Eva C. Guinan, Carliss Y. Baldwin, Alan MacCormack, Eric Lonstein, Mike Lydon and Ramy A Arnaout

  Advances in biotechnology have fueled the generation of unprecedented quantities of data across the life sciences. However, finding analysts who can address such "big data" problems effectively has become a significant research bottleneck. Historically, prize-based contests have had striking success in attracting unconventional individuals who can overcome difficult challenges. To determine whether this approach could solve a real big-data biologic algorithm problem, we used a complex immunogenomics problem as the basis for a two-week online contest broadcast to participants outside academia and biomedical disciplines. Participants in our contest produced over 600 submissions containing 89 novel computational approaches to the problem. Thirty submissions exceeded the benchmark performance of the U.S. National Institutes of Health's MegaBLAST. The best achieved both greater accuracy and speed (1,000 times greater). Here we show the potential of using online prize-based contests to access individuals without domain-specific backgrounds to address big-data challenges in the life sciences.

  Citation:

  Lakhani, Karim R., Kevin Boudreau, Eva C. Guinan, Carliss Y. Baldwin, Alan MacCormack, Eric Lonstein, Mike Lydon, and Ramy A Arnaout. "Prize-based Contests Can Provide Solutions to Computational Biology Problems." Nature Biotechnology 31, no. 2 (February, 2013): 108–111.

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