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Understanding business ecosystem dynamics: A data-driven approach

Tutkimustuotosvertaisarvioitu

Standard

Understanding business ecosystem dynamics : A data-driven approach. / Basole, Rahul C.; Russell, Martha G.; Huhtamäki, Jukka; Rubens, Neil; Still, Kaisa; Park, Hyunwoo.

julkaisussa: ACM Transactions on Management Information Systems, Vuosikerta 6, Nro 2, 6, 01.05.2015.

Tutkimustuotosvertaisarvioitu

Harvard

Basole, RC, Russell, MG, Huhtamäki, J, Rubens, N, Still, K & Park, H 2015, 'Understanding business ecosystem dynamics: A data-driven approach', ACM Transactions on Management Information Systems, Vuosikerta. 6, Nro 2, 6. https://doi.org/10.1145/2724730

APA

Basole, R. C., Russell, M. G., Huhtamäki, J., Rubens, N., Still, K., & Park, H. (2015). Understanding business ecosystem dynamics: A data-driven approach. ACM Transactions on Management Information Systems, 6(2), [6]. https://doi.org/10.1145/2724730

Vancouver

Basole RC, Russell MG, Huhtamäki J, Rubens N, Still K, Park H. Understanding business ecosystem dynamics: A data-driven approach. ACM Transactions on Management Information Systems. 2015 touko 1;6(2). 6. https://doi.org/10.1145/2724730

Author

Basole, Rahul C. ; Russell, Martha G. ; Huhtamäki, Jukka ; Rubens, Neil ; Still, Kaisa ; Park, Hyunwoo. / Understanding business ecosystem dynamics : A data-driven approach. Julkaisussa: ACM Transactions on Management Information Systems. 2015 ; Vuosikerta 6, Nro 2.

Bibtex - Lataa

@article{944e096933db4577983634f205d8b2ba,
title = "Understanding business ecosystem dynamics: A data-driven approach",
abstract = "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 the mobile industry Google's acquisition of Motorola Mobility, the coopetitive relation between Apple and Samsung, and the strategic partnership between Nokia and Microsoft. The article concludes with implications and future research opportunities.",
keywords = "Business ecosystem, Data triangulation, Information visualization, Interorganizational networks",
author = "Basole, {Rahul C.} and Russell, {Martha G.} and Jukka Huhtam{\"a}ki and Neil Rubens and Kaisa Still and Hyunwoo Park",
year = "2015",
month = "5",
day = "1",
doi = "10.1145/2724730",
language = "English",
volume = "6",
journal = "ACM Transactions on Management Information Systems",
issn = "2158-656X",
publisher = "Association for Computing Machinery",
number = "2",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Understanding business ecosystem dynamics

T2 - A data-driven approach

AU - Basole, Rahul C.

AU - Russell, Martha G.

AU - Huhtamäki, Jukka

AU - Rubens, Neil

AU - Still, Kaisa

AU - Park, Hyunwoo

PY - 2015/5/1

Y1 - 2015/5/1

N2 - 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 the mobile industry Google's acquisition of Motorola Mobility, the coopetitive relation between Apple and Samsung, and the strategic partnership between Nokia and Microsoft. The article concludes with implications and future research opportunities.

AB - 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 the mobile industry Google's acquisition of Motorola Mobility, the coopetitive relation between Apple and Samsung, and the strategic partnership between Nokia and Microsoft. The article concludes with implications and future research opportunities.

KW - Business ecosystem

KW - Data triangulation

KW - Information visualization

KW - Interorganizational networks

UR - http://www.scopus.com/inward/record.url?scp=84937791797&partnerID=8YFLogxK

U2 - 10.1145/2724730

DO - 10.1145/2724730

M3 - Article

VL - 6

JO - ACM Transactions on Management Information Systems

JF - ACM Transactions on Management Information Systems

SN - 2158-656X

IS - 2

M1 - 6

ER -