Evaluation of Crawler Cranes for Large-Scale Construction and Infrastructure Projects: an Intuitionistic Fuzzy Consensus-Based Approach
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Choosing the proper and best crawler crane is a complicated decision-making issue due to several conflicting criteria and vagueness in the construction and project logistics industries. This decision-making problem has become compounded due to insufficient studies on crawler crane selection in the relevant literature. The current study introduces an intuitionistic fuzzy consensus-based complex proportional assessment model (IF-c-COPRAS) developed to address the existing research gaps and identify the best and most suitable crawler crane. The acquired conclusions revealed that the most potent criterion influencing the crawler crane selection is "job potential," with a weighted score of 0.7665, followed by "periodic control and inspection" and "crane model year." Once the following findings of the paper regarding crawler crane variants are evaluated, the crawler crane manufactured by Liebherr Co. is the most feasible alternative, with a relative significance score of 0.8324. These outcomes provide sensible implications and insights for practitioners and decision-makers in the construction and project logistics (overweight/oversized cargo lifting and transport firms) industries, providing an applicable guideline for improving the quality of construction operations. Additionally, crane manufacturers can consider these managerial and policy implications and insights to improve the abilities and quality of the crawler cranes they produce.
Description
Ecer, Fatih/0000-0002-6174-3241
ORCID
Keywords
Crawler Crane, Construction Industry, Mcdm, Intuitionistic Fuzzy Sets, Consensus Reaching, Non-Linear Optimization, Non-linear optimization, Crawler crane, Construction industry, Intuitionistic fuzzy sets, MCDM, Consensus reaching
Fields of Science
Citation
WoS Q
Q1
Scopus Q
Q1

OpenCitations Citation Count
N/A
Source
Journal of Industrial Information Integration
Volume
44
Issue
Start Page
100784
End Page
PlumX Metrics
Citations
CrossRef : 2
Scopus : 7
Captures
Mendeley Readers : 19
SCOPUS™ Citations
7
checked on Feb 11, 2026
Web of Science™ Citations
6
checked on Feb 11, 2026
Page Views
3
checked on Feb 11, 2026
Google Scholar™

OpenAlex FWCI
21.64620703
Sustainable Development Goals
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE


