Investigation of Corporate Sustainability Performance Data and Developing an Innovation-Oriented Novel Analysis Method with Multi-Criteria Decision Making Approach

This study addresses the growing importance of integrating innovation into corporate sustainability strategies by examining the financial and environmental performance of ten firms listed on the Borsa Istanbul Sustainability Index over a five-year period. The main objective is to develop and test a novel, data-driven analytical framework that reduces reliance on subjective expert judgments while providing actionable insights for sustainability-oriented decision-making. Within this framework, the entropy method from the Multi-Criteria Decision Making (MCDM) approach is first applied to calculate the objective weights of sustainability criteria, ensuring that the analysis is grounded in real performance data. Building on these weights, an innovative reverse Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, implemented through a custom artificial neural network-based software, is introduced to estimate direct influence matrices and reveal the causal relationships among criteria. This methodological advance makes it possible to explore how environmental and financial factors interact with R&D expenditures and to simulate their systemic interdependencies. The findings demonstrate that R&D serves as a central driver of both environmental and financial sustainability, highlighting its dual role in fostering corporate innovation and long-term resilience. By positioning R&D as both an enabler and outcome of sustainability dynamics, the proposed framework contributes a novel tool for aligning innovation with strategic sustainability goals, offering broader implications for corporate managers, policymakers, and researchers.

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Publication Details

Journal
Sustainability
Published
2025-10-03
DOI
https://doi.org/10.3390/su17198860
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Investigation of Corporate Sustainability Performance Data and Developing an Innovation-Oriented Novel Analysis Method with Multi-Criteria Decision Making Approach

Ahmet Feyzioğlu, Trevor Omoruyi, Leonardo Piccinetti, Huseyin Haliloglu et al.
Sustainability
Forecasting Techniques and Applications
article

Investigation of Corporate Sustainability Performance Data and Developing an Innovation-Oriented Novel Analysis Method with Multi-Criteria Decision Making Approach

Ahmet Feyzioğlu, Trevor Omoruyi, Leonardo Piccinetti, Huseyin Haliloglu, Akın Emrecan Gök, Muzeyyen Burcu Hidimoglu
article en

Abstract

This study addresses the growing importance of integrating innovation into corporate sustainability strategies by examining the financial and environmental performance of ten firms listed on the Borsa Istanbul Sustainability Index over a five-year period. The main objective is to develop and test a novel, data-driven analytical framework that reduces reliance on subjective expert judgments while providing actionable insights for sustainability-oriented decision-making. Within this framework, the entropy method from the Multi-Criteria Decision Making (MCDM) approach is first applied to calculate the objective weights of sustainability criteria, ensuring that the analysis is grounded in real performance data. Building on these weights, an innovative reverse Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, implemented through a custom artificial neural network-based software, is introduced to estimate direct influence matrices and reveal the causal relationships among criteria. This methodological advance makes it possible to explore how environmental and financial factors interact with R&D expenditures and to simulate their systemic interdependencies. The findings demonstrate that R&D serves as a central driver of both environmental and financial sustainability, highlighting its dual role in fostering corporate innovation and long-term resilience. By positioning R&D as both an enabler and outcome of sustainability dynamics, the proposed framework contributes a novel tool for aligning innovation with strategic sustainability goals, offering broader implications for corporate managers, policymakers, and researchers.

SustainabilityVol. 17(19)
University of Chester (GB), Istanbul University-Cerrahpaşa (TR), Marmara University (TR), Limerick Institute of Technology (IE)
Openalex Percentile: Top 68%
Forecasting Techniques and Applications
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