Efficient Identification of Leading-Edge Expertise: Screening vs. Pyramiding

In order to find ideas for leading edge innovations, the lead user method recently gained much interest. A very important step in this method is the identification of lead users. Recently, there is a notable switch towards a technique we term "pyramiding". Instead of selecting the most appropriate users from a large but finite sample ("screening"), the pyramiding technique, a modified version of the snowball sampling method, relies on the fact that people with a strong interest in a topic or field tend to know people more expert than themselves: For example, good IT professionals tend to know the identity of IT people who are even more skilled than they are. In this article, we empirically compare the efficiency of both methods and identify the factors impacting the efficiency of the pyramiding method. For this we conduct a large scale experiment in which we simulate 292 pyramiding "chains". Findings have implications for managing efficient search for leading-edge expertise

[1]  M. Sherif,et al.  Book Reviews: The Psychology of Ego-Involvements: Social Attitudes & Identifications , 1947 .

[2]  Sharon L. Milgram,et al.  The Small World Problem , 1967 .

[3]  Stanley Milgram,et al.  An Experimental Study of the Small World Problem , 1969 .

[4]  E. von Hippel,et al.  Sources of Innovation , 2016 .

[5]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

[6]  S. Welch.  SAMPLING BY REFERRAL IN A DISPERSED POPULATION , 1975 .

[7]  J. Guiot.  A modification of Milgram's small world method , 1976 .

[8]  P. Biernacki,et al.  Snowball Sampling: Problems and Techniques of Chain Referral Sampling , 1981 .

[9]  Mark S. Granovetter.  T H E S T R E N G T H O F WEAK TIES: A NETWORK THEORY REVISITED , 1983 .

[10]  G. Laurent,et al.  Measuring Consumer Involvement Profiles , 1985 .

[11]  S. Sudman.  Efficient Screening Methods for the Sampling of Geographically Clustered Special Populations , 1985 .

[12]  Linda L. Price,et al.  The market maven: A diffuser of marketplace information. , 1987 .

[13]  Eric von Hippel.  Novel Product Concepts from Lead Users , 1988 .

[14]  Daniel A. Levinthal,et al.  ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION , 1990 .

[15]  M. Spreen.  Rare Populations, Hidden Populations, and Link-Tracing Designs: What and Why? , 1992 .

[16]  E. Hippel,et al.  FROM EXPERIENCE: Developing New Product Concepts Via the Lead User Method: A Case Study in a “Low-Tech” Field , 1992 .

[17]  C. Haythornthwaite.  Social network analysis: An approach and technique for the study of information exchange☆ , 1996 .

[18]  Gabriel Szulanski.  Exploring internal stickiness: Impediments to the transfer of best practice within the firm , 1996 .

[19]  Jo Reichertz,et al.  Qualitäten polizeilichen Handelns , 1996 .

[20]  Douglas D. Heckathorn,et al.  Respondent-driven sampling : A new approach to the study of hidden populations , 1997 .

[21]  Fiona Campbell.  Journalistic construction of news: information gathering , 1997 .

[22]  B. Uzzi,et al.  Social Structure and Competition in Interfirm Networks: The Paradox of Embeddedness , 1997 .

[23]  E. Hippel,et al.  Creating Breakthroughs at 3 M by , 1999 .

[24]  Morten T. Hansen,et al.  The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits , 1999 .

[25]  C. Lüthje.  Kundenorientierung im Innovationsprozess , 2000 .

[26]  Jon M. Kleinberg,et al.  Navigation in a small world , 2000, Nature.

[27]  R. Atkinson,et al.  Accessing Hidden and Hard-to-Reach Populations: Snowball Research Strategies , 2022 .

[28]  Erik L. Olson,et al.  Implementing the lead user method in a high technology firm: A longitudinal study of intentions versus actions , 2001 .

[29]  Gary L. Lilien,et al.  Performance Assessment of the Lead User Idea-Generation Process for New Product Development , 2002, Manag. Sci..

[30]  J. Kleinfeld,et al.  The small world problem , 2002 .

[31]  A. Krapp.  An educational-psychological theory of interest and its relation to SDT. , 2002 .

[32]  Douglas D. Heckathorn,et al.  Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hi , 2002 .

[33]  Joel A. C. Baum,et al.  MANAGEMENT CHALLENGES IN A NEW TIME , 2002 .

[34]  D. Watts,et al.  An Experimental Study of Search in Global Social Networks , 2003, Science.

[35]  Ray Reagans,et al.  Network Structure and Knowledge Transfer: The Effects of Cohesion and Range , 2003 .

[36]  K. Gwinner,et al.  WHAT MAKES MAVENS TICK? EXPLORING THE MOTIVES OF MARKET MAVENS INITIATION OF INFORMATION DIFFUSION , 2004 .

[37]  Han Zhu,et al.  Navigation in a small world with local information. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  S. Berg.  Snowball Sampling—I , 2006 .

[39]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.