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[Display omitted] • Developed a model to assess the sustainability performance of micro-mobility modes. • A novel tool the IVFNN-Delphi method to identify the criteria. • Proposed the IVFNN-LOPCOW methodology to calculate the criteria weights. • The IVFNN-CoCoSo approach is utilized to determine the preference of the options. • The validity of the presented decision tool is confirmed through a case study. Almost all megacities worldwide are under pressure from environmental pollution and excessive resource usage due to rapid urbanization and increasing urban population. Within this scope, micro-mobility solutions (MMSs), an extension to the primary urban transportation network, have become even more critical recently. However, when we executed a preliminary investigation concerning MMSs' sustainability, we noted some critical theoretical and managerial gaps: (1) the number of studies assessing MMSs using decision-making approaches is excessively scarce, (2) no paper in the literature deals with the MMSs' sustainability performance, and (3) there are no commonly accepted criteria set to assess the sustainability of the MMSs in the literature. The current study aims to present a practical and robust decision-making framework that can overcome excessively complicated uncertainties to evaluate the sustainability performance of MMSs. Further, it suggests a novel methodological framework, i.e., Delphi, Logarithmic Percentage Change-Driven Objective Weighting (LOPCOW), and Combined Compromise Solution (CoCoSo) methods with interval-valued fuzzy neutrosophic number (IVFNN) information, which can be defined as a reconciliation tool to set the criteria affecting the assessment processes. Findings present that computing time, scenic adoption, and accidents are the foremost criteria, whereas mini-electric VH, powered standing scooter, and powered seated scooter are the most promising MMSs, respectively. Findings reveal that computing time, scenic adoption, and accidents are the critical factors for the sustainability assessment of MMSs, whereas mini-electric VH, powered standing scooter, and powered seated scooter are the most promising MMSs, respectively. The current paper's overall outcomes and findings can assist practitioners and policy-makers in the urban transportation industry in setting sustainability policies and investing in the more rational and sustainable MMSs. [ABSTRACT FROM AUTHOR]

Selecting appropriate LNG tankers is paramount in the maritime sector. Opting for suitable second-hand LNG vessels is a significant and efficient strategy for managing transportation operations effectively and meeting industry standards. Given LNG tanker specifications and shipbuilding capacity, the second-hand LNG tanker market adequately meets maritime industry demands. Thus, there is a strong motivation to evaluate the current second-hand vessel market. However, uncertainties prevail, necessitating decision-makers to employ a resilient and practical methodological framework to address uncertainties and complex decision-making scenarios effectively. This study proposes a decision-making framework integrating the Delphi and Additive Ratio Assessment (ARAS) methods, leveraging interval type-2 fuzzy sets (IT2FSs). This framework resolves real-life challenges associated with selecting second-hand LNG tankers, demonstrating the practicality of the approach. Using IT2FSs, the Delphi method identifies critical criteria influencing second-hand tanker vessel selection. "Cargo carriage capacity" emerged as the most influential criterion, followed by "purchasing costs" and "year of construction." Moreover, "Mediterranean Energy" was deemed the most suitable second-hand LNG tanker among the six alternatives assessed. Thorough sensitivity analysis validated the proposed model and its implications, confirming its validity and applicability. Fresh food supplier selection for global retail chains via bipolar neutrosophic methodology. [Display omitted] • The current paper presents the IT2F –ARAS approach, which is robust MCDM tool. • It can be applied to solve highly complicated second-hand LNG tanker selection problems. • It has identified criteria for second-hand LNG tanker selection for the first time. • It presents a novel approach, namely IT2F-Delphi, to select the proper criteria. • It presents a flexible decision-making approach for real decision-making problems. [ABSTRACT FROM AUTHOR]

[Display omitted] • Proposed a novel fuzzy MCDM model to evaluate e-scooters. • Criteria were determined by employing FF-Delphi approach. • The fuzzy model can tolerate irrational/undesirable values existing in the indexes. • It is maximally consistent and doesn't need extra computations for consistency. • A validation test was performed to verify the proposed model. The efficient selection of road freight transport (RFT) firms plays a critical role in constructing well-operating logistics systems for large-scale third-party logistics (3PL) providers. However, the decision-making process for such selection is often complex and uncertain due to various influential criteria and dynamic industry nature. To address this challenge, a novel decision-making model that integrates Delphi, CRiteria Importance Through Intercriteria Correlation (CRITIC) and Combined compromise ranking solution (CoCoSo) methods based on T-Spherical Fuzzy sets has been proposed in this paper. The model integrates expert opinions with an extensive literature review to identify the influential criteria and their corresponding weights. Subsequently, it employs a comprehensive evaluation approach to rank the RFT firms based on their performance. The model accommodates uncertainties and subjectivity by utilizing T-Spherical Fuzzy Numbers, offering robustness and transparency in decision-making. A case study involving 15 evaluation criteria and 12 RFT firms were selected to demonstrate the applicability and aptness of the proposed model. Flexibility and Integrability to different transport modes emerged as the two most essential criteria, whereas RFT firm A2 emerged as the best alternative with the highest performance score of 3.0861, followed by RFT firm A7 with a score value of 3.0499. [ABSTRACT FROM AUTHOR]

The advanced technologies emerging in Industry 4.0 are forcing companies in different industries to review their business models and become more compatible with advanced technological practices. While traditional business models are increasingly inadequate in the face of increasing competition, business models developed thanks to advanced technologies such as deep learning and machine learning have begun to replace them. However, developing business intelligence and intelligent applications using these technologies requires more data processing. In this context, Big Data technology is a unique instrument in providing the data businesses need to design more intelligent systems. In conclusion, the Big Data platform can significantly speed up the processes of structuring and processing the data and information generated and increase businesses' efficiency, performance, and agility. However, being a relatively new concept, the knowledge about the Big Data concept is limited, leading to several challenges for decision-makers concerning choosing the appropriate platform. Also, the number of studies on this subject is highly scarce. Hence, practitioners in various industries lack sufficient support from the research society on this issue. We could not find crisp and definite values to evaluate the BD alternatives despite comprehensive investigation. In that regard, as data, we addressed appraisals and opinions of IT professionals with vast knowledge and experience in assessment, selection, installation, and operation. We developed a novel decision-making model to evaluate and select the most proper BD platforms by processing these data. In this connection, the current investigation suggests a novel, robust, practical decision-making model for defining the combination of the weight of criteria based on pairwise comparisons of adjacently ranked criteria (COmparisons Between RAnked Criteria- COBRAC) and the ARTASI (Alternative ranking technique based on adaptive standardized intervals -ARTASI). It can handle complex ambiguities encountered in appraisal processes to address the Big Data platform selection problem. In addition, the current work developed a negotiation process quantitificated to determine the influential criteria affecting the selection of the Big Data platform. When we evaluate the outcomes of the suggested model, the most influential criterion affecting the selection of the Big Data platform is C12 "Ease of Use." in addition, the most suitable Big Data platform for large-scale enterprises has been identified as A3 Microsoft SQL Server. The proposed model and its results have been validated based on extensive sensitivity and comparison analysis. These results also offer practical and managerial implications for the industry. Although many studies indicate that installation cost and speed are the most critical factors, this research found that, unlike these studies, ease of use is the most critical factor in choosing a BD platform. In this context, the BD alternative that provides the highest ease of use can produce more efficient results and reduce complexities in collecting and processing high volumes of structured and unstructured data. [ABSTRACT FROM AUTHOR]

In recent years, there have been dramatic changes in manufacturing systems in many industries depending on technological developments. Robotics is one of the essential components of these changes. Today, the usage of robotics in manufacturing processes has become widespread in almost all industries. Also, it has become a very strong desire ever-increasing for even small and medium-sized enterprises at present. Almost all the previous studies emphasized that industrial robot selection is a highly complex decision-making problem as there are many conflicting factors and criteria. Besides, different and advanced specifications of these robotics added by robotic manufacturers have caused to increase the complexities much more. Hence, decision-makers encounter more complicated decision-making problems affected by many uncertainties. Because of that, an integrated fuzzy group MCDM framework can help overcome many ambiguities proposed in the current paper. The proposed fuzzy integrated model consists of the fuzzy SWARA (F-SWARA'B) and the fuzzy CoCoSo (F-CoCoSo'B), which are extended with the help of the Bonferroni function. The model selected the appropriate industrial robotics used in the automotive industry by considering 15 criteria and ten alternatives. According to the result of the study, the three most significant criteria have been determined: Working Accuracy, Reaching Distance, and Performance; and the most suitable option is the A8. The obtained results were validated with the help of a comprehensive sensitivity analysis consisting of different 150 scenarios. The results are also compared with some existing techniques. The sensitivity analysis results approve the validity and applicability of the proposed model. [ABSTRACT FROM AUTHOR]

The second-hand vessel market has quite different dynamics than the market of the new-building vessel, and highly complicated and conflicting criteria and many uncertainties affect the ship selection process. Therefore, it is required to use a robust mathematical model to solve these kinds of decision-making problems. For this purpose, this paper presents an extended version of WASPAS (Weighted Aggregated Sum Product ASsessment) techniques with the help of T2NN based on the Bonferroni function (T2NN WASPAS'B). The three main focal points of the proposed approach are (i) setting the influential criteria to select the appropriate Ro-Ro vessel in the second-hand vessel market; and (ii) presenting a flexible group decision-making approach, which is proper to real decision-making problems. (iii) detecting the interrelations among criteria and eliminating the negative impacts of undesirable and excessive values in input variables on the results. Practical use of the proposed approach is demonstrated to select the appropriate Ro-Ro vessel in the second-hand market. The analysis results show that the most effective and determinative factor is Trailer Lane length, and the most effective alternative is GREIFSWALD. Besides, the consistency and validity of the obtained results have been verified with the help of a stability and robustness check. The results prove that the proposed novel T2NN WASPAS'B model is robust, powerful, and reliable for making rational and realistic decisions. • The current paper presents the T2NN WASPAS'B approach strengthen with the help of T2NN based on the Bonferroni function. • The proposed model is applied to solve second-hand Ro-Ro vessel selection problems, which are highly complex and include uncertainties. • It has identified the selection criteria for second-hand Ro-Ro ships for the first time. • It presents a flexible decision-making approach, which is proper for real decision-making problems. • It demonstrates interrelations among factors to make it more understandable in complex situations. [ABSTRACT FROM AUTHOR]