ADAPTIVE MANAGEMENT SYSTEMS FOR ENHANCING PRODUCTION ENTERPRISE EFFICIENCY
DOI:
https://doi.org/10.26437/ajar.v11i1.865Keywords:
Adaptive management. bayesian analysis. behavioural economics. cognitive biases. management of assetAbstract
Purpose: The study aims to investigate adaptive management systems for enhancing production enterprise efficiency.
Design/Methodology/Approach: The research employed analytical-bibliographic methods and economic-statistical methods for processing statistical data to study the scientific literature on adaptive management and analyse and process data related to the research topic.
Research Limitation: Although the analysed adaptive management models provide valuable information on adjusting production, their application may be limited to manufacturing enterprises, and therefore, they do not cover other economic or service-oriented industries. Given this, the study's main limitation is its focus on the regional context, particularly Ukraine's industrial sector.
Findings: The study results have identified the main critical theoretical aspects of applying adaptive management models and revealed the practical characteristics of different models developed by scientists. The study examined the conceptual basis of adaptive management, investigated the integration of innovative strategies that are key to ensuring the flexibility and sustainability of manufacturing enterprises, and analysed the interrelationships of the management system's components, which allows the creation of an adaptation mechanism.
Practical Implication: The effect on the sector is the improvement of toughness and flexibility within manufacturing firms, enabling them to navigate market uncertainties efficiently and maintain creativity, thereby propelling sectoral expansion and stability.
Social Implication: The results' social impact is that increasing investment in scientific research can contribute to technological and economic development, social well-being, and sustainable growth.
Originality/ Value: This study's novelty lies in advancing methodologies for utilising adaptive management to augment enterprises' efficiency by implementing novel mechanisms and constructing models considering the external environment's dynamic nature.
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