{"title":"Strategic feasibility outlook for blue energy investments using an integrated decision-making approach","authors":"Serkan Eti , Serhat Yüksel , Hasan Dinçer","doi":"10.1016/j.suscom.2025.101085","DOIUrl":null,"url":null,"abstract":"<div><div>Conducting feasibility analysis in blue energy investments is very critical to provide performance analysis of the projects. However, a significant portion of the studies in the literature focus on general energy projects. Nevertheless, there are not enough studies for a more specific area such as blue energy. This situation significantly increases the need for this type of priority analysis. Accordingly, the purpose of this study is to identify the most appropriate strategies to increase the effectiveness of the feasibility analysis of blue energy investments via a novel decision-making model. In the first stage of the model, the importance levels of experts are computed using machine learning technique. The second stage includes weighting the feasibility criteria set for blue energy project investment by Fermatean fuzzy entropy. After that, the strategic alternatives for increasing the capacity of blue energy projects are ranked with Fermatean fuzzy CoCoSo. The main contribution of this study to the literature is making a detailed evaluation to generate appropriate strategies for the feasibility analysis of the blue energy investments via a novel decision-making model. The integration of AI system provides some advantages to the proposed model. In this way, the decision matrix is obtained by calculating the importance weights of each expert. This situation allows to have more accurate analysis results. It is defined that the technological infrastructure of the company plays the most critical role (weight: 0.173) when conducting feasibility analysis for blue energy investments. Similarly, it is also identified that the financial performance of the business (weight: 0.172) is also important to conduct a more successful feasibility analysis for blue energy investments. On the other side, the ranking results demonstrate that collaborating with the investment-ready companies for increasing the innovative technologies is the most appropriate strategy to increase the capacity of blue energy projects.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101085"},"PeriodicalIF":3.8000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Computing-Informatics & Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210537925000058","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
Conducting feasibility analysis in blue energy investments is very critical to provide performance analysis of the projects. However, a significant portion of the studies in the literature focus on general energy projects. Nevertheless, there are not enough studies for a more specific area such as blue energy. This situation significantly increases the need for this type of priority analysis. Accordingly, the purpose of this study is to identify the most appropriate strategies to increase the effectiveness of the feasibility analysis of blue energy investments via a novel decision-making model. In the first stage of the model, the importance levels of experts are computed using machine learning technique. The second stage includes weighting the feasibility criteria set for blue energy project investment by Fermatean fuzzy entropy. After that, the strategic alternatives for increasing the capacity of blue energy projects are ranked with Fermatean fuzzy CoCoSo. The main contribution of this study to the literature is making a detailed evaluation to generate appropriate strategies for the feasibility analysis of the blue energy investments via a novel decision-making model. The integration of AI system provides some advantages to the proposed model. In this way, the decision matrix is obtained by calculating the importance weights of each expert. This situation allows to have more accurate analysis results. It is defined that the technological infrastructure of the company plays the most critical role (weight: 0.173) when conducting feasibility analysis for blue energy investments. Similarly, it is also identified that the financial performance of the business (weight: 0.172) is also important to conduct a more successful feasibility analysis for blue energy investments. On the other side, the ranking results demonstrate that collaborating with the investment-ready companies for increasing the innovative technologies is the most appropriate strategy to increase the capacity of blue energy projects.
期刊介绍:
Sustainable computing is a rapidly expanding research area spanning the fields of computer science and engineering, electrical engineering as well as other engineering disciplines. The aim of Sustainable Computing: Informatics and Systems (SUSCOM) is to publish the myriad research findings related to energy-aware and thermal-aware management of computing resource. Equally important is a spectrum of related research issues such as applications of computing that can have ecological and societal impacts. SUSCOM publishes original and timely research papers and survey articles in current areas of power, energy, temperature, and environment related research areas of current importance to readers. SUSCOM has an editorial board comprising prominent researchers from around the world and selects competitively evaluated peer-reviewed papers.