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

Mohammadi Mohammad Naji Shah (), Pirmoradian Azam (), Shokrollahi Foad () and Pirmoradian Peiman ()
Additional contact information
Mohammadi Mohammad Naji Shah: Department of Business Law, University of Vaasa, Wolffintie 32, Vaasa 65200, Finland
Pirmoradian Azam: NielsenIQ, Nielsen House, John Smith Drive, Oxford OX4 2WB, UK
Shokrollahi Foad: Department of Mathematical and Statistical Modelling, University of Vaasa, Wolffintie 32, Vaasa 65200, Finland
Pirmoradian Peiman: Pundit, Ltd., Grovelands Rd., Oxford OX3 8HZ, UK

TalTech Journal of European Studies, 2025, vol. 15, issue 1, 40-57

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.

Keywords: data-driven governance; multi-objective optimization; proactive contracting; risk management; strategic adaptability (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:bjeust:v:15:y:2025:i:1:p:40-57:n:1005

DOI: 10.2478/bjes-2025-0004

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