TY - GEN
T1 - Computational Modeling of Business Ecosystem Dynamics
AU - Basole, Rahul
AU - Armbruster, Dieter
AU - Cortez, Nicholaus
AU - Barnett, Brandon
AU - Guilak, Farzin
AU - Kempf, Karl
N1 - Publisher Copyright:
© 2023 IEEE Computer Society. All rights reserved.
PY - 2023
Y1 - 2023
N2 - This paper presents a multi-method approach for computational modeling of complex business ecosystem dynamics that enables strategic decision support. Our computational model is informed by theories of business strategy, organizational ecology, and interfirm networks, and uses real-world data mined from public and proprietary sources. Using a complex system and network analytic lens, our model provides insights into how the interconnected nature of actors, capabilities, and interfirm behaviors (mergers, acquisitions, and collaborations) can lead to different ecosystem characteristics. We discuss results and extensions of this work.
AB - This paper presents a multi-method approach for computational modeling of complex business ecosystem dynamics that enables strategic decision support. Our computational model is informed by theories of business strategy, organizational ecology, and interfirm networks, and uses real-world data mined from public and proprietary sources. Using a complex system and network analytic lens, our model provides insights into how the interconnected nature of actors, capabilities, and interfirm behaviors (mergers, acquisitions, and collaborations) can lead to different ecosystem characteristics. We discuss results and extensions of this work.
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M3 - Conference contribution
AN - SCOPUS:85152128066
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 1334
EP - 1338
BT - Proceedings of the 56th Annual Hawaii International Conference on System Sciences, HICSS 2023
A2 - Bui, Tung X.
PB - IEEE Computer Society
T2 - 56th Annual Hawaii International Conference on System Sciences, HICSS 2023
Y2 - 3 January 2023 through 6 January 2023
ER -