Identifying Patterns of Idea Diffusion in Innovator Networks

The diffusion of innovative ideas throughout a social network of innovators depends crucially on how people are connected and influence each other, and particularly on the advocacy of influential individuals. We contend that existing conceptualizations of innovation diffusion and peer influence do not suffice to capture the multi-faceted nature of idea diffusion. To address this challenge, we adopt concepts from both innovation management and social network analysis to identify patterns of idea diffusion. Using topology analysis and percolation analysis, we examine the impact of peer influence on the percolation of idea-related artifacts. We demonstrate the applicability of our approach using the preliminary results of our study with one of Switzerland’s major independent banking software providers. The outcome will not only have valuable contributions to the studies of innovation management and social network analysis, but also make a methodological contribution by introducing the examination of artifact percolation to study idea diffusion.

[1]  Marcel Ausloos,et al.  Knowledge epidemics and population dynamics models for describing idea diffusion , 2012, ArXiv.

[2]  Martin Wiener,et al.  Challenges and Dilemmas in Open Innovation: Ambidexterity as Management Approach , 2013, Wirtschaftsinformatik.

[3]  Lada A. Adamic,et al.  The role of social networks in information diffusion , 2012, WWW.

[4]  Jon M. Kleinberg,et al.  The structure of information pathways in a social communication network , 2008, KDD.

[5]  J. Kleinberg,et al.  Networks, Crowds, and Markets , 2010 .

[6]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[7]  Jens J. Krüger,et al.  The Performance of Gatekeepers in Innovator Networks , 2011 .

[8]  Youngjin Yoo,et al.  Generative Diffusion of Innovations: An Organizational Genetics Approach , 2012, ICIS.

[9]  A. Rapoport.  Spread of information through a population with socio-structural bias: I. Assumption of transitivity , 1953 .

[10]  J. Leon Zhao,et al.  Discovering Determinants of Project Participation in an Open Source Social Network , 2009, ICIS.

[11]  Kathryn Graziano.  The innovator's dilemma: When new technologies cause great firms to fail , 1998 .

[12]  Jean-Pierre Eckmann,et al.  Entropy of dialogues creates coherent structures in e-mail traffic. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[13]  A. Bullinger,et al.  Integrating Inside and Outside Innovators: A Sociotechnical Systems Perspective , 2009 .

[14]  Eileen A. Hogan.  The Attention Economy: Understanding the New Currency of Business , 2001 .

[15]  Jari Saramäki,et al.  Small But Slow World: How Network Topology and Burstiness Slow Down Spreading , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[17]  Jan Marco Leimeister,et al.  Patients as Innovators – The Development of Innovative Ideas with the Ideenschmiede , 2013, Wirtschaftsinformatik.

[18]  Kevin C. Desouza.  Intrapreneurship: Managing Ideas Within Your Organization , 2011 .

[19]  Thomas W. Valente,et al.  Opinion Leadership and Social Contagion in New Product Diffusion , 2011, Mark. Sci..

[20]  Lada A. Adamic,et al.  How to search a social network , 2005, Soc. Networks.

[21]  Anatol Rapoport,et al.  Spread of information through a population with socio-structural bias: III. Suggested experimental procedures , 1954 .

[22]  Arun Sundararajan,et al.  Information in Digital, Economic and Social Networks , 2012 .

[23]  Eric Partridge,et al.  Origins : an etymological dictionary of modern English , 1966 .

[24]  Scott A. Golder,et al.  Blogging at work and the corporate attention economy , 2009, CHI.

[25]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[26]  J. Marshall.  Open Innovation: The New Imperative for Creating and Profiting from Technology , 2004 .

[27]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[28]  Arun Sundararajan,et al.  Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks , 2009, Proceedings of the National Academy of Sciences.

[29]  Uwe Cantner,et al.  Innovator networks and regional knowledge base , 2008 .

[30]  Sinan Aral,et al.  What Would Ashton Do--and Does It Matter? , 2013 .

[31]  G. Zipf,et al.  The Psycho-Biology of Language , 1936 .

[32]  R. Merton.  The Matthew Effect in Science , 1968, Science.

[33]  B. Dousset.  Innovation and network structural dynamics: Study of the alliance network of a major sector of the biotechnology industry , 2005 .

[34]  Ilkka Tuomi,et al.  Networks of Innovation , 2002 .

[35]  Dylan Walker,et al.  Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks , 2010, ICIS.

[36]  Sinan Aral,et al.  Identifying Social Influence: A Comment on Opinion Leadership and Social Contagion in New Product Diffusion , 2010, Mark. Sci..

[37]  M. Newman,et al.  Mixing patterns in networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  Sinan Aral,et al.  Identifying Influential and Susceptible Members of Social Networks , 2012, Science.

[39]  H. Chesbrough,et al.  Open Innovation: A New Paradigm for Understanding Industrial Innovation , 2006 .

[40]  J. West,et al.  Open innovation : researching a new paradigm , 2008 .