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Data-driven proactive contracting: a mathematical framework for enhancing strategic agility, risk management and value creation Cover

Data-driven proactive contracting: a mathematical framework for enhancing strategic agility, risk management and value creation

Open Access
|Apr 2025

Abstract

Traditional contracts assume that all future contingencies can be anticipated and explicitly addressed at the outset. However, due to uncertainty, information asymmetry and evolving business conditions, contracts inevitably leave gaps, limiting their ability to function as effective governance tools. While amendment clauses offer a means for adjustments, they fail to resolve complexities related to risk quantification, strategic flexibility and real-time adaptation. Grounded in proactive contracting, this paper presents a methodological framework that redefines contracts as dynamic, data-driven governance mechanisms. By integrating real-time data analytics, stochastic forecasting and multi-objective optimization, the framework enables contracts to anticipate risks, optimize trade-offs and continuously adjust to shifting market conditions. This research advances contract governance by demonstrating how adaptive contracts can move beyond static enforcement to actively support business resilience, sustainability and long-term value creation. By embedding structured adaptability, the study provides a transformative approach to ensuring that contracts remain strategically aligned, legally enforceable and responsive to uncertainty in modern business environments.

DOI: https://doi.org/10.2478/bjes-2025-0004 | Journal eISSN: 2674-4619 | Journal ISSN: 2674-4600
Language: English
Page range: 40 - 57
Published on: Apr 2, 2025
Published by: Tallinn University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2025 Mohammad Naji Shah Mohammadi, Azam Pirmoradian, Foad Shokrollahi, Peiman Pirmoradian, published by Tallinn University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.