ArticleScientific reports2026
Robust ranking of renewable energy alternatives handling uncertainty using novel hesitant bi-fuzzy MEREC-MOORA and Dombi aggregation approach.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The identification of competitive renewable energy (RE) sources often fails to account for non-technical factors, such as environmental, political, and social barriers. These considerations of RE are described in language that accommodates varying levels of hesitancy among decision-makers (DMs). This study develops a multi-criteria group decision-making (MCGDM) method using hesitant bi-fuzzy sets to capture DMs' varying degrees of hesitancy. A HBF extension of multi-objective optimization on the basis of ratio analysis is proposed, incorporating a method based on the removal effect on the criteria to assign parameter importance for each DM. This study also developed a novel HBF-Dombi aggregating operator for logical synthesis of qualitative data. The developed MCGDM framework is applied to determine the optimal RE sources, considering 5 DMs, 6 RE sources, and 15 barriers classified into 5 categories. Solar energy emerges as the top choice since it is favorable in both technical and non-technical RE barriers. A comparative analysis is performed to validate the proposed method, while comprehensive sensitivity analyses are performed to assess the influence of parameter variation on the ranking of RE sources. The insights from this article can serve as a pathway for identifying RE barriers to successful RE installation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.