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A decision framework with nonlinear preferences and unknown weight information for cloud vendor selection
No full textCloud vendor selection (CVS) is a complex decision-making problem, which actively adheres to human behavior/cognition. The complex nature of the problem is due to personal biases/hesitation, trade-offs among attributes, uncertainty in rating, and the nonlinear relationship among cloud vendors and associated attributes. In recent times, researchers started paying more attention to user/expert behavior, which led to non-linear decision -making. Most of the extant decision models for CVS considered the linear form of decision-making, which is not realistic due to expert opinions' complexity and dynamism. Motivated by the claim, in this paper, a non-linear decision approach is put forward for CVS. Likert scale rating is adopted for rating cloud vendors based on some attributes, which are transformed to polynomial space from the linear fuzzy space. After this, weights of attri-butes are determined by using CRITIC in the non-linear space. Following this, cloud vendors are ranked in a personalized fashion using the proposed algorithm that encompasses the WASPAS procedure and rank fusion schemes. Finally, a case study is exemplified to validate the usefulness of the decision approach. Comparison and sensitivity analysis showcases the efficacy and robustness of the developed approach
The selection of appropriate Ro-Ro Vessel in the second-hand market using the WASPAS' Bonferroni approach in type 2 neutrosophic fuzzy environment
No full textThe 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
Sustainable E-scooter parking operation in urban areas using fuzzy Dombi based RAFSI model
No full textOver the last five years, e-scooters have gradually become commonplace in most urban areas. However, short-comings in infrastructure provision, especially with parking, make it awkward to use these vehicles. This study presents a novel hybrid fuzzy multi-criteria decision-making model for determining optimal e-scooter parking locations by combining the Logarithmic Methodology of Additive Weights (LMAW) and the RAFSI (Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval) methods. In the first stage, the fuzzy Aczel-Alsina function based LMAW approach is used to address the uncertainty of experts' opinions in the decision process and to calculate the weights of the twelve criteria. Afterward, fuzzy Dombi based RAFSI is applied to obtain the ranking of e-scooter parking locations. A case study is presented to propose a solution for the operation of e-scooter parking by taking into consideration three different alternatives based on four different aspects and twelve criteria. According to the findings, the third option, which is a hybrid operation with geo-fencing hubs in primary catchment areas of public transportation, is the most practical choice for a sustainable operation of e-scooter parking. This option also has the potential to be the most environmentally friendly
Performance assessment of sustainable transportation in the shipping industry using a q-rung orthopair fuzzy rough sets-based decision making methodology
No full textThis paper proposes a novel ship energy systems (SESs) benchmarking model for performance measurement of sustainable transportation based on the extension of q-rung orthopair fuzzy rough sets (q-ROFRS) and multicriteria decision-making (MCDM) methods. The underlying research methodology consists of two main stages: (i) Formulation of the SES decision matrix between SESs and the sustainability, (ii) Development of a q-ROFRS and fuzzy-weighted zero-inconsistency (q-ROFRS–FWZIC) model to determine the weights of each criterion. The integrated model of the q-ROFRS and fuzzy decision by the opinion score method (q-ROFRS-FDOSM) is offered as a tool for benchmarking the SESs. Sixty-two SESs are evaluated and benchmarked according to the three layers of criteria concerning the five design alternatives. The analysis of the proposed q-ROFRS–FWZIC methodology revealed that decision support methods (C2) is the most important criterion with a weight of 0.4174, followed by gas emissions (C1.1.2) and economic criterion (C1.1.1) with weights of 0.1661 and 0.1498, respectively; and energy efficiency design index (C1.2.1) is the least important. Furthermore, the results from q-ROFRS-FDOSM reveal that SES62 is the most suitable SES followed by SES60, whereas SES37 is the least suitable. Finally, the robustness of the proposed method is assessed by conducting a sensitivity analysis
Komparativna analiza open-source data mining alata
No full textCompanies strive to draw valuable conclusions from large amounts of data. These conclusions help improve decision-making, predict future trends, and gain a comparative advantage for that company. Mentioned processes can be provided using the data mining methods. Through data analysis, data mining indicates the connections between the data and provides valuable information. Numerous data mining tools are present on the market, some of them being free and others having to be purchased.
This paper analyzes three open-source data mining software products: Knime, RapidMiner, and H2O. It aims to contribute to a more straightforward decision-making process when choosing the data mining tool that meets the company's needs for quality analysis
Small Family Farms In The Republic Of Serbia - Analysis Of Entrepreneurial Orientation And The Need For Support
No full textFamily farms in the Republic of Serbia are mostly small agricultural producers with arable land of small and medium size and with a low degree of process mechanization, where family members work mostly, and farm management is assigned to one family member. Such farms are often in a subordinate position, with weak bargaining power compared to large agricultural producers and large enterprises engaged in agricultural production. Nevertheless, the chance of further development of such farms lies in their positive entrepreneurial orientation and readiness for innovation and change. This paper presents research on the entrepreneurial orientation of family farms in the Republic of Serbia. The survey sample consisted of 72 farms from different locations in the Republic of Serbia. Entrepreneurial orientation was observed through the following elements: readiness of farms to join efforts, participation in large supply chains, readiness to standardize products and processes, readiness to export, readiness for changes and delegation of management processes, as well as readiness for farm development by improving knowledge about agriculture, management, and entrepreneurship. The results presented in the paper provide a clear insight to the support creators about the potential for improving the position of small farms in the Republic of Serbia.Proceeding link: http://isae.agrif.bg.ac.rs/archive/Proceedings_ISAE_2023.pd
On the Distribution of Kurepa's Function
No full textKurepa's function and his hypothesis have been investigated by means of numerical simulation. Particular emphasis has been given to the conjecture on its distribution, that should be one of a random uniform distribution, which has been verified for large numbers. A convergence function for the two has been found
Improving the Economic Sustainability of the Fashion Industry: A Conceptual Model Proposal
No full textThis study aimed to define the specific relationships between fashion style preference on the one side and product, promotion, word of mouth (WOM) and fashion lovers' behavior on the other side during the COVID-19 crisis. Structural equation modelling (SEM) analysis was employed to unveil the mutual relations of the two and to verify the proposed conceptual model. The conceptual model was tested based on the answers of 642 respondents. The preference for a specific fashion style proved to have an impact on the product, promotion, WOM and fashion lovers' behavior during COVID-19. Moreover, those elements have an impact on the frequency of fashion apparel consumption. Based on these results, fashion companies can tailor their activities in line with the predominant style of their fashion apparel to improve their economic sustainability during the post-COVID-19 era
FairDEA-Removing disparate impact from efficiency scores
No full textAchieving fairness in algorithmic decision-making tools is an issue constantly gaining in need and popularity. Today, unfair decisions made by such tools can even be subject to legal consequences. We propose a new constraint that integrates fairness into data envelopment analysis (DEA). This allows the calculation of relative efficiency scores of decision-making units (DMUs) with fairness included. The proposed fairness constraint restricts disparate impact to occur in efficiency scores, and enables the creation of a single data envelopment analysis for both privileged and unprivileged groups of DMUs simultaneously. We show that the proposed method FairDEA produces an interpretable model that was tested on a synthetic dataset and two real-world examples, namely the ranking between hybrid and conventional car designs, and the Latin American and Caribbean economies. We provide the interpretation of the FairDEA method by comparing it to the basic DEA and the balanced fairness and efficiency method (BFE DEA). Along with calculating the disparate impact of the model, we performed a Wilcoxon rank-sum test to inspect for fairness in rankings. The results show that the FairDEA method achieves similar efficiency scores as other methods, but without disparate impact. Statistical analysis indicates that the differences in ranking between the groups are not statistically different, which means that the ranking is fair. This method contributes both to the development of data envelopment analysis, and the inclusion of fairness in efficiency analysis
An integrated decision model for cloud vendor selection using probabilistic linguistic information and unknown weights
No full textBecause of the high competition among IT sectors, companies are planning to migrate to the cloud for effective growth and development. Driven by the importance of the cloud, new cloud vendors emerge each day to satisfy the demand of IT sectors. As a result, selection of an apt cloud vendor is critical. To this end, researchers have proposed different decision models, but these models do not effectively capture uncertainty during the decision -making process. To handle this issue, probabilistic linguistic information (PLI) is adopted in this paper, which associates occurrence probability to each term. Furthermore, weights of criteria are systematically determined using a deviation method, and cloud vendors are prioritized using a mathematical model under the PLI context. These methods are integrated to form the decision model, validated for its applicability using real case data from Cloud Armor. Finally, the advantages and weaknesses of the model are analyzed by using sensitivity analysis and comparison with extant models