An AI-Enhanced Framework for Corporate Strategy on Ecosystems' Creation

In an era where interconnectedness and collaboration define corporate strategy, the effective management of ecosystems has emerged as a critical driver of competitive advantage. This research presents the conceptual development of a multi-objective optimization framework for corporate ecosystem creation enhanced by artificial intelligence (AI). The framework progresses through three key phases. First, it establishes a foundational approach that integrates strategic dimensions (desirability, feasibility, and sustainability) into traditional portfolio optimization, moving beyond the sole focus on financial risk-return. Second, it extends this foundation by introducing an AI-optimization hybrid model that predicts and incorporates synergies generated by interdependent projects, using machine learning techniques and rigorous optimization tools. This integrated approach aims to provide CEOs with new strategic tools to align ecosystems while balancing financial performance and broader sustainability goals. By combining precision and adaptability, this research proposes a robust methodology for decision-making in complex, dynamic corporate ecosystems. Future work will focus on empirical validation through real-world case studies, the incorporation of temporal dynamics of synergies, and the enhancement of model interpretability to foster greater executive trust in AI-driven insights.

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Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1109/ice/itmc65658.2025.11106671
Primary Topic
Complex Systems and Decision Making
Type
article
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article

An AI-Enhanced Framework for Corporate Strategy on Ecosystems' Creation

Patricia Rodriguez-Garcia, David López-López
Complex Systems and Decision Making
article

An AI-Enhanced Framework for Corporate Strategy on Ecosystems' Creation

Patricia Rodriguez-Garcia, David López-López
article en

Abstract

In an era where interconnectedness and collaboration define corporate strategy, the effective management of ecosystems has emerged as a critical driver of competitive advantage. This research presents the conceptual development of a multi-objective optimization framework for corporate ecosystem creation enhanced by artificial intelligence (AI). The framework progresses through three key phases. First, it establishes a foundational approach that integrates strategic dimensions (desirability, feasibility, and sustainability) into traditional portfolio optimization, moving beyond the sole focus on financial risk-return. Second, it extends this foundation by introducing an AI-optimization hybrid model that predicts and incorporates synergies generated by interdependent projects, using machine learning techniques and rigorous optimization tools. This integrated approach aims to provide CEOs with new strategic tools to align ecosystems while balancing financial performance and broader sustainability goals. By combining precision and adaptability, this research proposes a robust methodology for decision-making in complex, dynamic corporate ecosystems. Future work will focus on empirical validation through real-world case studies, the incorporation of temporal dynamics of synergies, and the enhancement of model interpretability to foster greater executive trust in AI-driven insights.

Universitat Oberta de Catalunya (ES), EAE Business School (ES)
Life in Land
Openalex Percentile: Top 76%
Complex Systems and Decision Making
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