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Understanding Business Ecosystem Dynamics: A Data-Driven Approach

Understanding Business Ecosystem Dynamics: A Data-Driven Approach Understanding Business Ecosystem Dynamics: A Data-Driven Approach RAHUL C. BASOLE, Georgia Institute of Technology MARTHA G. RUSSELL, Stanford University ¨ JUKKA HUHTAMAKI, Tampere University of Technology NEIL RUBENS, University of Electro-Communications KAISA STILL, VTT Technical Centre of Finland HYUNWOO PARK, Georgia Institute of Technology Business ecosystems consist of a heterogeneous and continuously evolving set of entities that are interconnected through a complex, global network of relationships. However, there is no well-established methodology to study the dynamics of this network. Traditional approaches have primarily utilized a single source of data of relatively established firms; however, these approaches ignore the vast number of relevant activities that often occur at the individual and entrepreneurial levels. We argue that a data-driven visualization approach, using both institutionally and socially curated datasets, can provide important complementary, triangulated explanatory insights into the dynamics of interorganizational networks in general and business ecosystems in particular. We develop novel visualization layouts to help decision makers systemically identify and compare ecosystems. Using traditionally disconnected data sources on deals and alliance relationships (DARs), executive and funding relationships (EFRs), and public opinion and discourse (POD), we empirically illustrate our data-driven method of data triangulation and visualization techniques through three cases in http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Management Information Systems (TMIS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2015 by ACM Inc.
ISSN
2158-656X
DOI
10.1145/2724730
Publisher site
See Article on Publisher Site

Abstract

Understanding Business Ecosystem Dynamics: A Data-Driven Approach RAHUL C. BASOLE, Georgia Institute of Technology MARTHA G. RUSSELL, Stanford University ¨ JUKKA HUHTAMAKI, Tampere University of Technology NEIL RUBENS, University of Electro-Communications KAISA STILL, VTT Technical Centre of Finland HYUNWOO PARK, Georgia Institute of Technology Business ecosystems consist of a heterogeneous and continuously evolving set of entities that are interconnected through a complex, global network of relationships. However, there is no well-established methodology to study the dynamics of this network. Traditional approaches have primarily utilized a single source of data of relatively established firms; however, these approaches ignore the vast number of relevant activities that often occur at the individual and entrepreneurial levels. We argue that a data-driven visualization approach, using both institutionally and socially curated datasets, can provide important complementary, triangulated explanatory insights into the dynamics of interorganizational networks in general and business ecosystems in particular. We develop novel visualization layouts to help decision makers systemically identify and compare ecosystems. Using traditionally disconnected data sources on deals and alliance relationships (DARs), executive and funding relationships (EFRs), and public opinion and discourse (POD), we empirically illustrate our data-driven method of data triangulation and visualization techniques through three cases in

Journal

ACM Transactions on Management Information Systems (TMIS)Association for Computing Machinery

Published: Jun 2, 2015

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