Artificial Intelligence and Organizational Sustainability: Neural Network Modeling for Probability-Based Scoring

Herghiligiu Ionuţ Viorel (), Loghin Emil Constantin (), PohonȚu-Dragomir Ștefana-Cătălina () and Budeanu Cătălin Ioan ()
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Herghiligiu Ionuţ Viorel: “Gheorghe Asachi” Technical University of Iași, Romania
Loghin Emil Constantin: “Gheorghe Asachi” Technical University of Iași, Romania
PohonȚu-Dragomir Ștefana-Cătălina: “Gheorghe Asachi” Technical University of Iași, Romania
Budeanu Cătălin Ioan: “Gheorghe Asachi” Technical University of Iași, Romania

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 3523-3537

Abstract: In the context of increasing environmental and social responsibility concerns, organizations are looking for innovative methods to assess and improve sustainability performance. This study explores the role of artificial intelligence (AI) – neural networks, in developing a probability-based evaluation system for organizational sustainability score. Traditional evaluation methods frequently rely on pre-established performance indicators, which can introduce subjectivity and inaccuracies. To overcome these limitations, the research proposes a neural network model that integrates economic, social, and environmental dimensions into a structured evaluation framework. The study uses data collected from 30 companies listed on the Bucharest Stock Exchange. The neural network was developed in MATLAB, with a feed-forward structure with two hidden layers and a Levenberg-Marquardt training algorithm. The results – probabilistic organizational sustainability score reflects an intermediate position associated to the analyzed companies, indicating therefore an acceptable compliance level, but also the existence of improvement opportunities; likewise environmental and social dimensions have a stronger influence on organizational sustainability, while the economic dimension, although relevant, has a lower impact. The findings demonstrate that AI-based models offer a more dynamic and objective approach to sustainability assessment, reducing human error and improving the accuracy of predictions. The research contributes to the literature by introducing a structured, data-driven methodology, providing valuable insights for organizational managers and researchers interested in AI-assisted decision-making.

Keywords: sustainable development; organizational sustainability; neural network; modeling; probability-based score (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:3523-3537:n:1030

DOI: 10.2478/picbe-2025-0269

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