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Pyramiding: Efficient search for rare subjects

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  • von Hippel, Eric
  • Franke, Nikolaus
  • Prügl, Reinhard
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    Abstract

    The need to economically identify rare subjects within large, poorly mapped search spaces is a frequently encountered problem for social scientists and managers. It is notoriously difficult, for example, to identify "the best new CEO for our company," or the "best three lead users to participate in our product development project." Mass screening of entire populations or samples becomes steadily more expensive as the number of acceptable solutions within the search space becomes rarer. The search strategy of "pyramiding" is a potential solution to this problem under many conditions. Pyramiding is a search process based upon the idea that people with a strong interest in a topic or field tend to know people more expert than themselves. In this paper we report upon four experiments empirically exploring the efficiency of pyramiding searches relative to mass screening. We find that pyramiding on average identified the most expert individual in a group on a specific topic with only 28.4% of the group interviewed - a great efficiency gain relative to mass screening. Further, pyramiding identified one of the top 3 experts in a population after interviewing only 15.9% of the group on average. We discuss conditions under which the pyramiding search method is likely to be efficient relative to screening.

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    Bibliographic Info

    Article provided by Elsevier in its journal Research Policy.

    Volume (Year): 38 (2009)
    Issue (Month): 9 (November)
    Pages: 1397-1406

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    Handle: RePEc:eee:respol:v:38:y:2009:i:9:p:1397-1406

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    Web page: http://www.elsevier.com/locate/respol

    Related research

    Keywords: Sequential search Research method Lead user innovation Serial experimentation Network theory;

    References

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    1. Thomke, Stefan & von Hippel, Eric & Franke, Roland, 1998. "Modes of experimentation: an innovation process--and competitive--variable," Research Policy, Elsevier, vol. 27(3), pages 315-332, July.
    2. Ray Reagans & Linda Argote & Daria Brooks, 2005. "Individual Experience and Experience Working Together: Predicting Learning Rates from Knowing Who Knows What and Knowing How to Work Together," Management Science, INFORMS, vol. 51(6), pages 869-881, June.
    3. Yuqing Ren & Kathleen M. Carley & Linda Argote, 2006. "The Contingent Effects of Transactive Memory: When Is It More Beneficial to Know What Others Know?," Management Science, INFORMS, vol. 52(5), pages 671-682, May.
    4. Stephen P. Borgatti & Rob Cross, 2003. "A Relational View of Information Seeking and Learning in Social Networks," Management Science, INFORMS, vol. 49(4), pages 432-445, April.
    5. Gary L. Lilien & Pamela D. Morrison & Kathleen Searls & Mary Sonnack & Eric von Hippel, 2002. "Performance Assessment of the Lead User Idea-Generation Process for New Product Development," Management Science, INFORMS, vol. 48(8), pages 1042-1059, August.
    6. Christoph H. Loch & Christian Terwiesch & Stefan Thomke, 2001. "Parallel and Sequential Testing of Design Alternatives," Management Science, INFORMS, vol. 47(5), pages 663-678, May.
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    Cited by:
    1. Lehnen, Jens & Ehls, Daniel & Herstatt, Cornelius, 2014. "Implementation of lead users into management practice: A literature review of publications in business press," Working Papers 78, Hamburg University of Technology (TUHH), Institute for Technology and Innovation Management.
    2. Isabelle Salle & Pascal Seppecher, 2013. "Social Learning about Consumption," GREDEG Working Papers 2013-18, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), University of Nice Sophia Antipolis, revised Sep 2013.
    3. Linda Hamdi-Kidar & Cyrielle Vellera, 2012. "What drives lead users to become users entrepreneurs ? an exploratory study of motivations," Post-Print halshs-00851319, HAL.

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