TOWARDS A MULTIDIMENSIONAL PERSPECTIVE FOR DECISION OPTIMISATION: INTEGRATING SOCIAL, MATHEMATICAL, AND TECHNOLOGICAL DIMENSIONS
DOI:
https://doi.org/10.24193/subbnegotia.2026.2.01Keywords:
Artificial intelligence, decision-making, decision support, digitalisation, optimisation, machine learning, multidimensional, sustainabilityAbstract
Ineffective decision-making remains a persistent challenge for organisations operating in complex, uncertain, and data-intensive environments. This paper explores the interrelationships among decision-making, optimisation, and digitalisation, aiming to develop an integrated perspective on organisational decision support. A structured literature review is conducted, drawing on insights from operations research (OR), decision sciences, and digital transformation. The findings highlight that contextual and human factors shape decision-making, while optimisation provides the analytical structure required to address complex problems. Furthermore, digitalisation enhances these capabilities by enabling improved data integration, processing, and real-time analysis. While each domain contributes individually, their combined application enables more robust, adaptive, and data-driven decision processes. This paper proposes a multidimensional framework that conceptualises decision optimisation as a socio-technical process involving the interaction between human judgement, analytical modelling, and digital technologies. The study contributes to the literature by bridging traditionally fragmented research areas and providing a holistic foundation for more effective decision support systems. Practically, the findings emphasise the need for organisations to align optimisation methods, digital capabilities, and contextual considerations to improve decision quality, resilience, and long-term sustainability.
JEL Classification: C61, D83, M15, D81
Article History: Received: February 10, 2026; Reviewed: April 14, 2026; Accepted: May 29, 2026; Available online: June 30, 2026
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