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    Kevin Boudreau and Andrei Hagiu. 2009. “Platform Rules: Multi-sided Platforms as Regulators.” In Platforms, Markets, and Innovation, edited by Annabelle Gawer. Northampton, MA: Edward Elgar Publishing, Inc. Publisher's VersionAbstract

    This paper provides a basic conceptual framework for interpreting non-price instruments used by multi-sided platforms (MSPs) by analogizing MSPs as "private regulators" who regulate access to and interactions around the platform. We present evidence on Facebook, TopCoder, Roppongi Hills and Harvard Business School to document the "regulatory" role played by MSPs. We find MSPs use nuanced combinations of legal, technological, informational and other instruments (including price-setting) to implement desired outcomes. Non-price instruments were very much at the core of MSP strategies.

    Kevin Boudreau. 2010. “Open Platform Strategies and Innovation: Granting Access vs. Devolving Control.” Management Science, 56, 10, Pp. 1849-1872. Publisher's VersionAbstract

    This paper studies two fundamentally distinct approaches to opening a technology platform and their different impacts on innovation. One approach is to grant access to a platform and thereby open up markets for complementary components around the platform. Another approach is to give up control over the platform itself. Using data on 21 handheld computing systems (1990–2004), I find that granting greater levels of access to independent hardware developer firms produces up to a fivefold acceleration in the rate of new handheld device development, depending on the precise degree of access and how this policy was implemented. Where operating system platform owners went further to give up control (beyond just granting access to their plat- forms) the incremental effect on new device development was still positive but an order of magnitude smaller. The evidence from the industry and theoretical arguments both suggest that distinct economic mechanisms were set in motion by these two approaches to opening.

    Kevin J. Boudreau, Nicola Lacetera, and Karim R. Lakhani. 2011. “Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis.” Management Science, 57, 5, Pp. 843-863. Publisher's VersionAbstract

    Contests are a historically important and increasingly popular mechanism for encouraging innovation. A central concern in designing innovation contests is how many competitors to admit. Using a unique data set of 9,661 software contests, we provide evidence of two coexisting and opposing forces that operate when the number of competitors increases. Greater rivalry reduces the incentives of all competitors in a contest to exert effort and make investments. At the same time, adding competitors increases the likelihood that at least one competitor will find an extreme-value solution. We show that the effort-reducing effect of greater rivalry dominates for less uncertain problems, whereas the effect on the extreme value prevails for more uncertain problems. Adding competitors thus systematically increases overall contest performance for high-uncertainty problems. We also find that higher uncertainty reduces the negative effect of added competitors on incentives. Thus, uncertainty and the nature of the problem should be explicitly considered in the design of innovation tournaments. We explore the implications of our findings for the theory and practice of innovation contests.

    Kevin J. Boudreau and Karim R. Lakhani. 2012. “The Confederacy of Heterogeneous Software Organizations and Heterogeneous Developers: Field Experimental Evidence on Sorting and Worker Effort.” In The Rate and Direction of Inventive Activity Revisited, edited by Scott Stern and Josh Lerner. Chicago, IL: University of Chicago Press. Publisher's VersionAbstract
    Confederacy_of_Heterogeneous_Software.pdf

    This chapter reports on an actual field experiment that tests for the influence of “sorting” on innovator effort. The focus is on the potential heterogeneity among innovators and whether they prefer a more cooperative versus competitive research environment. The focus of the field experiment is a real-world multiday software coding exercise in which participants are able to express a preference for being sorted into a cooperative or competitive environment—that is, incentives in the cooperative environment are team based, while those in the competitive environment are individualized and depend on relative performance. Half of the participants are indeed sorted on the basis of their preferences, while the other half are assigned to the two modes on a random basis.

    Kevin J. Boudreau. 2012. “Let a Thousand Flowers Bloom? An Early Look at Large Numbers of Software App Developers and Patterns of Innovation.” Organization Science, 23, 5, Pp. 1409-1427. Publisher's VersionAbstract

    In this paper, I study the effect of adding large numbers of producers of application software programs (“apps”) to leading handheld computer platforms, from 1999 to 2004. To isolate causal effects, I exploit changes in the software labor market. Consistent with past theory, I find a tight link between the number of producers on platform and the number of software varieties that were generated. The patterns indicate the link is closely related to the diversity and distinct specializations of producers. Also highlighting the role of heterogeneity and nonrandom entry and sorting, later cohorts generated less compelling software than earlier cohorts. Adding producers to a platform also shaped investment incentives in ways that were consistent with a tension between network effects and competitive crowding, alternately increasing or decreasing innovation incentives depending on whether apps were differentiated or close substitutes. The crowding of similar apps dominated in this case; the average effect of adding producers on innovation incentives was negative. Overall, adding large numbers of producers led innovation to become more dependent on population-level diversity, variation, and experimentation —while drawing less on the heroic efforts of any one individual innovator.

    Karim R. Lakhani, Hila Lifshitz-Assaf, and Michael L. Tushman. 2013. “Open Innovation and Organizational Boundaries: Task Decomposition, Knowledge Distribution and the Locus of Innovation.” In Handbook of Economic Organization: Integrating Economic and Organizational Theory, edited by Anna Grandori, Pp. 355-382. Edward Elgar Publishing, Inc. Publisher's VersionAbstract
    Open_Innovation_and_Organizational_Boundaries.pdf

    This chapter contrasts traditional, organization- centered models of innovation with more recent work on open innovation. These fundamentally different and inconsistent innovation logics are associated with contrasting organizational boundaries and organizational designs. We suggest that when critical tasks can be modularized and when problem- solving knowledge is widely distributed and available, open innovation complements traditional innovation logics. We induce these ideas from the literature and with extended examples from Apple, the National Aeronautics and Astronomical Agency (NASA) and LEGO. We suggest that task decomposition and problem- solving knowledge distribution are not deterministic but are strategic choices. If dynamic capabilities are associated with innovation streams, and if different innovation types are rooted in contrasting innovation logics, there are important implications for firm boundaries, design and identity.

    Kevin J. Boudreau and Karim R. Lakhani. 2013. “Using the Crowd as an Innovation Partner.” Harvard Business Review 91 (4), Pp. 61-69. Publisher's VersionAbstract

    From Apple to Merck to Wikipedia, more and more organizations are turning to crowds for help in solving their most vexing innovation and research questions, but managers remain understandably cautious. It seems risky and even unnatural to push problems out to vast groups of strangers distributed around the world, particularly for companies built on a history of internal innovation. How can intellectual property be protected? How can a crowdsourced solution be integrated into corporate operations? What about the costs? These concerns are all reasonable, the authors write, but excluding crowdsourcing from the corporate innovation tool kit means losing an opportunity. After a decade of study, they have identified when crowds tend to outperform internal organizations (or not). They outline four ways to tap into crowd-powered problem solving — contests, collaborative communities, complementors, and labor markets — and offer a system for picking the best one in a given situation. Contests, for example, are suited to highly challenging technical, analytical, and scientific problems; design problems; and creative or aesthetic projects. They are akin to running a series of independent experiments that generate multiple solutions—and if those solutions cluster at some extreme, a company can gain insight into where a problem’s “technical frontier” lies. (Internal R&D may generate far less information.)

    Andrew King and Karim R. Lakhani. 2013. “Using Open Innovation to Identify the Best Ideas.” MIT Sloan Management Review 55 (1). Publisher's VersionAbstract

    As innovation becomes more democratic, many of the best ideas for new products and services no longer originate in well-financed corporate and government laboratories. Instead, they come from almost anywhere and anyone.1 How can companies tap into this distributed knowledge and these diverse skills? Increasingly, organizations are considering using an open-innovation process, but many are finding that making open innovation work can be more complicated than it looks. PepsiCo, the food and beverage giant, for example, created controversy in 2011 when an open-sourced entry into its Super Bowl ad contest that was posted online featured Doritos tortilla chips being used in place of sacramental wafers during Holy Communion. Similarly, Kraft Foods Australia ran into challenges when it launched a new Vegemite-based cheese snack in conjunction with a public naming contest. The name Kraft initially chose from the submissions, iSnack 2.0, encountered widespread ridicule, and Kraft abandoned it. (The company instead asked consumers to choose among six other names. The company ultimately picked the most popular choice among those six, Vegemite Cheesybite.) Reports of such problems have fed uncertainty among managers about how and when to open their innovation processes. Managers tell us that they need a means of categorizing different types of open innovation and a list of key success factors and common problems for each type. Over the last decade, we have worked to create such a guide by studying and researching the emergence of open-innovation systems in numerous sectors of the economy, by working closely with many organizations that have launched open-innovation programs and by running our own experiments.2 This research has allowed us to gain a unique perspective on the opportunities and problems of implementing open-innovation programs. (See “About the Research.”) In every organization and industry, executives were faced with the same decisions. Specifically, they had to determine (1) whether to open the idea-generation process; (2) whether to open the idea-selection process; or (3) whether to open both. These choices led to a number of managerial challenges, and the practices the companies implemented were a major factor in whether the innovation efforts succeeded or failed.

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