Computational Modeling of Business Ecosystem Dynamics

Rahul Basole, Dieter Armbruster, Nicholaus Cortez, Brandon Barnett, Farzin Guilak, Karl Kempf

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 56th Annual Hawaii International Conference on System Sciences, HICSS 2023
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages1334-1338
Number of pages5
ISBN (Electronic)9780998133164
StatePublished - 2023
Event56th Annual Hawaii International Conference on System Sciences, HICSS 2023 - Virtual, Online, United States
Duration: Jan 3 2023Jan 6 2023

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2023-January
ISSN (Print)1530-1605

Conference

Conference56th Annual Hawaii International Conference on System Sciences, HICSS 2023
Country/TerritoryUnited States
CityVirtual, Online
Period1/3/231/6/23

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'Computational Modeling of Business Ecosystem Dynamics'. Together they form a unique fingerprint.

Cite this