Criteria Importance Through Intercriteria Correlation Research Articles

Neutrosophic CRITIC MCDM Methodology for Ranking Factors and Needs of Customers in Product's Target Demographic in Virtual Reality Metaverse


 Affective design has come to place a premium on customer-centric creativity, which ultimately results in the creation of a product tailored to the requirements of a certain demographic. Designing a fresh and original item that appeals to clients remains challenging, despite the abundance of literature on customer-centric creativity and impact product design. This is so because optimizing technological and aesthetical design aspects and variables for a group of consumers is highly complicated, and for the same reasons that it is hard to know a customer's choice, enable the product's functioning, etc. One of the most important parts of creating cutting-edge technological items is the technical product requirement. In reality, we can generally glean insights about a product's design by looking at the hidden desires of a comparable set of potential buyers. In this study, we provide a unique combined structure for evaluating the factors and needs of customers in product design in virtual reality (VR) metaverse by merging the CRiteria Importance Through Intercriteria Correlation (CRITIC) approach with single-valued neutrosophic sets (SVNSs). The characteristic weights in this approach are calculated using the CRITIC technique. The CRITIC method computes the rank of needs. The neutrosophic set is used to overcome the uncertain data. The application of this study shows thermal dissipation, airtight construction, weight, and control mechanisms are among the most crucial considerations.

Smartphone Addiction Assessment Using Pythagorean Fuzzy CRITIC-TOPSIS

Addiction to smartphones, particularly among adolescents, has reached alarming proportions, rivaling or perhaps exceeding internet addiction as the most widespread kind of dependence in modern culture. Evaluating the degree of problematic smartphone use habits by experts and identifying the vulnerable ones to steer to the right treatment program has become a critical issue. Since such a task may involve an abundance of criteria and candidates, as well as the inherent subjectivity of multiple decision experts participating in the process, the assessment of smartphone addiction can be framed as an uncertain multi-criteria decision-making (MCDM) problem. As an extension of intuitionistic fuzzy sets, Pythagorean fuzzy sets can be used to efficiently manage ambiguity and uncertainty during decision-making. This study provides an integrated fuzzy MCDM methodology based on Pythagorean fuzzy sets for evaluating the smartphone addiction level of adolescents. The Criteria Importance Through Inter-criteria Correlation (CRITIC) method is used to determine the importance levels of criteria in an objective manner, and smartphone addiction levels of the selected candidates are ranked using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach. A sensitivity analysis is conducted to examine the variations in candidate rankings caused by changes to the criteria and weights of the decision experts. Moreover, in the context of comparative analysis, the Evaluation based on Distance from Average Solution (EDAS) approach is used to validate the acquired findings.

A comparative assessment of multicriteria parametric optimization methods for plasma arc cutting processes

Plasma arc cutting (PAC) has evolved as an efficient process to cut complex profiles on many hard-to-machine engineering materials due to its many advantages, like higher dimensional accuracy, higher productivity, and the capability to cut thick materials. Optimization of this process is challenging due to existence of many input parameters, complex cutting mechanism, and interactions of the process parameters with the responses. In this paper, the applications of four newly developed multicriteria decision-making (MCDM) tools, i.e., Proximity Indexed Value (PIV), Evaluation by an Area-based Method of Ranking (EAMR), Pareto-Edgeworth Grierson (PEG), and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI) are presented for optimization of two PAC processes. To study the effects of criteria (response) weights on the optimization performance of the adopted MCDM techniques, two objective criteria weighting techniques, i.e., Criteria Importance Through Intercriteria Correlation (CRITIC) and Method based on the Removal Effects of Criteria (MEREC) are considered. All four MCDM techniques identify similar optimal parametric combinations at two different criteria weighting scenarios. The calculated Gini indexes also validate the superiority of the derived optimal parametric intermixes over the other experimental trials and similarity of the ranking performance of all four MCDM techniques.

An integrated personalized decision approach with probabilistic linguistic context for grading restaurants in India

Online reviews from the web are rich data sources that promote tourism analytics. Restaurants make a significant contribution to the growth of tourism in India. The literature studies on restaurant selection show that most decision frameworks do not handle uncertainty effectively and pay subtle attention to heterogeneous sources. Additionally, the extant models (i) cannot accept missing entries and its imputation; (ii) reliability of data source agents are not methodically determined; (iii) attributes’ interactions are not properly considered; and (iv) personalized restaurant ranking is unavailable. The research problem considered in this study is the rational selection of restaurants based on online reviews from heterogeneous sources to support travelers in the tourism process. The main objective of this study is to circumvent the challenge in the literatures by proposing a novel integrated decision framework that collects data from heterogeneous rating sources and transforms them into ‘probabilistic linguistic information (PLI)’, which effectively handles uncertainty by relating occurrence probability to each linguistic term. Due to the uncertain nature of online reviews, missing data are inevitable. For rational imputation of data, a case-based method is proposed. Later, the relative significance of each attribute and the reliability of each rating source are determined using ‘criteria importance through intercriteria correlation (CRITIC)’ and Dempster–Shafer-based Bayesian approximation methods. Furthermore, the PLIs from each source are aggregated by using the newly proposed discriminative weighted Muirhead mean operator. Personalized prioritization of restaurants is achieved by using the newly proposed probabilistic linguistic comprehensive (PLC) method that acquires expectation queries from customers. Lastly, the practicality of the developed framework is testified by a real-case example of restaurant selection based on the data collected from online sources via web crawlers. Results infer that (i) the proposed framework is innovative/original, personalized, significant, and mitigates human intervention compared to the extant models, (ii) robust in terms of ranking of restaurants even after adequate weight alterations, and (iii) finally, supports stakeholders to effectively plan their tourism process and attain win-win conditions for effective growth of hospitality sector.

Evaluation of logistics centers in terms of sustainability via MCDM methods

PurposeThe purpose of the study is the evaluation of choosing the determined logistics centers’ (LCs’) locations via Multi-Criteria Decision-Making (MCDM) methods.Design/methodology/approachSince there is more than one criterion in the evaluation of LC location, MCDM methods are used. The Entropy and CRiteria Importance Through Intercriteria Correlation (CRITIC) methods are used to determine the main criteria and sub-criteria weights. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method is used for ranking and evaluating 12 alternatives in Turkey and sensitivity analysis according to the threshold values of criteria and preference functions.FindingsPossible LC alternatives in Turkey and 12 locations ranked. Changing the criteria weights at a significant level did not affect the ranking results much. In the sensitivity analysis of the criteria for which market data could not be obtained (scored by the experts) it is found that they either made no difference or made little difference in the ranking of the alternatives.Practical implicationsIn terms of sustainability, economic factors along with environmental and social dimensions are important criteria for logistics companies and LC. The use of these variables in the LC location selection makes a difference.Originality/valueThis study focuses on LC location selection, via PROMETHEE with evaluated preference functions for criteria, taking into account nine scenarios that use variable criteria weight calculated via different MCDM methods. The results are evaluated by using sensitivity analysis and taking into account the sustainability aspect for LC. Multiple methods have been used effectively together in a way that support each other.

A comprehensive analytical framework for evaluating the similarity between organizations’ strategic directions and the United Nations’ sustainable development goals

This study presents a comprehensive analytical framework for evaluating the similarity between organizations’ specific strategic directions and the United Nations’ Sustainable Development Goals (SDGs). The proposed framework uses a multi-attribute decision-making method (MADM) in which organizations are evaluated concerning the SDGs. In particular, we use the Integrated Criteria Importance through Intercriteria Correlation (CRITIC) and Evaluation based on the Distance from Average Solution Method (EDAS) because of their computational efficiency. Based on a pre-defined algorithm, we find decision matrices that contain relatedness scores between each organization’s mission statements and the SDGs. This framework evaluates 244 top 300 Philippine higher education institutions (HEIs). The findings reveal that HEIs’ mission statements are related to SDGs concerning climate action, reduced inequalities, and life on land; meanwhile, there were limited mission statements relating to industry, innovation, and infrastructure. The evaluation is used to rank the HEIs. This study can be considered a benchmark for future related studies and an effective tool to help design mission statements that effectively convey organizations’ commitment to SDGs.

EDAS METHOD FOR MULTIPLE ATTRIBUTE GROUP DECISION MAKING WITH PROBABILISTIC DUAL HESITANT FUZZY INFORMATION AND ITS APPLICATION TO SUPPLIERS SELECTION

Probabilistic dual hesitant fuzzy set (PDHFS) is a more powerful and important tool to describe uncertain information regarded as generalization of hesitant fuzzy set (HFS) and dual HFS (DHFS), not only reflects the hesitant attitude of decision-makers (DMs), but also reflects the probability information of DMs. Score function of fuzzy number and weighting method are very important in multi-attribute group decision-making (MAGDM) issues. In many fuzzy environments, the score function and entropy measure have been proposed one after another. Firstly, based on the detailed analysis of the existed score function of PDHF element (PDHFE) and with the help of previous references, we build a novel score function for PDHFE. Secondly, a combined weighting method is built based on the minimum identification information principle by fusing PDHF entropy and Criteria Importance Through Intercriteria Correlation (CRITIC) method. Thirdly, a novel PDHF MAGDM approach (PDHF-EDAS) is built by extending evaluation based on distance from average solution (EDAS) approach to the PDHF environment to solve the issue that the decision attribute information is PDHFE. Finally, the practicability and effectiveness of the PDHF MAGDM technique is verified by suppliers selection (SS) and comparing analysis with existing methods.

Exurban and suburban forests have superior healthcare benefits beyond downtown forests

Forests in urban areas provide great healthcare benefits to citizens, but it is less well known whether this benefit is related to different geographical spaces. We selected exurban forest, suburban forest, downtown forest, and urban control in Guangzhou, China to analyze the change characteristics of negative air ion concentration (NAIC), air oxygen content (AOC), and human comfort index (HCI). Based on Criteria Importance Through Intercriteria Correlation (CRITIC) method, the urban forest comprehensive healthcare index (UFCHI) was established. Finally, the evaluation criteria for UFCHI were identified by cluster analysis. The results demonstrated that (1) The NAIC in exurban forest (2,713 ± 1,573 ions/cm3) and suburban forest (2,147 ± 923 ions/cm3) was evidently better than downtown forest (1,130 ± 255 ions/cm3) and urban control (531 ± 162 ions/cm3). (2) The AOC was in the order of exurban forest (21.17 ± 0.38%) > suburban forest (21.13 ± 0.30%) > downtown forest (21.10 ± 0.16%) > urban control (20.98 ± 0.12%). (3) The HCI in urban control (5.56 ± 2.32) and downtown forest (5.15 ± 1.80) is higher than suburban forest (4.02 ± 1.53) and exurban forest (3.71 ± 1.48). (4) The UFCHI in exurban forest (1.000), suburban forest (0.790), and downtown forest (0.378) were beneficial to human health to some extent, while urban control (0.000) was at Level IV, having no healthcare benefit. Except in winter, the UFCHI in exurban forest and suburban forest were all at Level II and above; while downtown forest and urban control were all at Level III and below at all seasons. Overall, urban forests in the exurbs and suburbs have better healthcare benefits than those in the downtowns. Furthermore, it is recommended that urban residents visit exurban and suburban forests for forest therapy in spring, summer, and autumn.

Multi-objective optimization with solution ranking for design of spur gear pair considering multiple failure modes

The performance of a gear pair is totally dependent on correct design considerations which could be based on specifying the permissible safety factors or the minimum residual life which is related to the reliability of the gear pair. The work presented in this paper focusses on adding L10 life as a constraint in the design optimization of spur gear pair along with the different tribological constraints i.e. micro-pitting, flank fracture, wear, scuffing, and scoring. The multiple objectives considered are for weight of gear pair, power loss and gear’s heat treatment time. The CRITIC (Criteria Importance through Intercriteria Correlation) method is used for selecting the best solution from the Pareto optimal solutions obtained through GA (Genetic Algorithm) optimization.

A novel multilevel decision-making evaluation approach for the renewable energy heating systems: A case study in China

Renewable energy (RE) sources are important alternatives to mitigate the energy crisis and achieve sustainable development. Appropriate selection of RE system solutions is extremely crucial. Selection of the best RE technology requires the consideration of conflicting qualitative and quantitative evaluation criteria. Many evaluation criteria are judged with subjectivity and uncertainty. However, the description of uncertainty in the evaluation process remains a large research gap. Therefore, a novel combined evaluation method is developed to describe and visualize the uncertainty in the assessment process. The proposed evaluation method is tested for RE heating system selection. The RE systems are evaluated based on five dimensions and 15 evaluation indicators. This multidimensional indicator framework not only includes the three basic evaluation groups of energy, economy, and environment, but also extends to the performance of technology and policy. The combined weights of the evaluation indicators consist of objective weights and subjective weights. The objective weights are obtained by the Criteria Importance Through Intercriteria Correlation (CRITIC) method and subjective weights are calculated by the improved Fuzzy Analytic Hierarchy Process (FAHP). The set pair analysis (SPA) is introduced to assess the performance of different RE systems. It considers the uncertainty of indicator performance. A novel approach to visualizing the fuzziness of SPA evaluation is developed using the cloud model. Finally, the RE system ranking calculated by the proposed method is performed. The originality of this work is offering a promising method for RE selection and clarifying the degree of ambiguity in the evaluation process. It helps decision makers have an exact idea about the accuracy of the evaluation. It provides insights into multi-objective decision-making problems.

Linguistic Pythagorean fuzzy CRITIC-EDAS method for multiple-attribute group decision analysis

Industrialization plays a significant role in the development and growth of a country. Pakistan is one of the developing countries which entirely depends upon their industrial steel sector to meet their economic growth. Pakistan Steel Mills Corporation (PSMC) is a Pakistan’s largest steel industry producing tonnes of steel every year but this production of steel has resulted in a rapid increase in industrial solid waste. Several techniques are available for industrial waste management, ranging from traditional methods to advanced technologies. But the selection of most suitable alternative is a complex task owing to numerous strategies available and multiple attributes involved in selection. To resolve this issue, we introduced a dynamic model for selecting best industrial waste management technique utilizing the linguistic Pythagorean fuzzy sets (LPFSs). The concept of LPFSs has proven to be a productive and advantageous approach in the development of decision problems to manage inconsistency in the escalating sophistication of expert systems. The main goal of this study is to introduce a general MAGDM model by integrating CRiteria Importance Through Intercriteria Correlation (CRITIC) method and Evaluation based on Distance from Average Solution (EDAS) method. Firstly, some Hamacher relations and operations are adapted to linguistic Pythagorean fuzzy environment which initiated a variety of Hamacher operators in the context of LPFSs. Meanwhile some fundamental properties of proposed operators are investigated. Secondly, a novel LPFH-CRITIC-EDAS technique is introduced. In the developed framework, the LPF-CRITIC method is used to calculate the criteria weights and the LPF-EDAS technique is utilized to evaluate the rank of alternatives. Furthermore, the flowchart of the proposed model is presented in a systematic way. Moreover, an example of the industrial waste management technique selection for PSMC is addressed to illustrate the feasibility of the proposed technique. Finally, the new framework is compared with existing techniques to demonstrate its strength. The comparative study reveals that the results of the proposed method are more feasible and practical than the existing techniques.

Evaluation Approach for Efficient Countermeasure Techniques Against Denial-of-Service Attack on MPSoC-Based IoT Using Multi-Criteria Decision-Making

Context: Denial-of-Service Attack countermeasure techniques (DoS A-CTs) evaluation is a Multi-criteria decision-making (MCDM) problem based on different MPSoCs of IoT platform design, performance, and design overhead. Therefore, the Fermatean by fuzzy decision opinion score method (F-FDOSM) for prioritizing the powerful countermeasure technique against Denial-of-Service (DoS) attack is the best approach because it employs the most efficient MCDM ranking technique. Nonetheless, the FDOSM method needs to weight the criteria before being submitted for the ranking process. In order to address this theoretical challenge, the Criteria-importance through inter-criteria correlation (CRITIC) technique can be applied as an effective MCDM weighting technique to offer an explicit weight for a set of criteria with no inconsistency based on the standard deviation, which uses correlation analysis to determine the relevance of each criterion. Objectives: This research proposes a Fermatean-FDOSM framework for evaluating DoS A-CTs in the context of MPSoCs-based IoT and CRITIC techniques to weight the criteria. Methods: The methodology is presented in three phases. Firstly, a proposed countermeasure techniques dataset was collected that included eighteen defense approaches (e.g., Sniffer, SeRA, and RLAN) based on thirteen criteria (e.g., size, power, latency, and effectiveness…etc.). Then, the Decision matrix (DM) was built based on an intersection of the countermeasure techniques as an alternative and MPSoC design and performance criteria. Then, the multi-criteria decision-making methods were integrated. The CRITIC method for criteria weighting was followed by the development of the Fermatean-FDOSM method for ranking. Results: (1) CRITIC weighting shows that MPSoC NoC Routing Algorithm (XY and YX) is the highest weight criterion, whereas latency (clock/cycle) is the less weight criterion. (2) The Fermatean-FDOSM-based group ranking shows that the Collision Point Router Detection (CPRD) countermeasure technique is the first-ranked alternative compared to the Secure Model Checkers (SMCs) approach. (3) The DoS A-CTs priority ranks were subjected to a systematic ranking that was confirmed by solid correlation results throughout thirteen criterion weight values. A comparison with recent studies confirmed the feasibility of the proposed framework. Conclusion: The results of this research are expected to provide a specific understanding and guide for those who want to engage in MPSoCs-based IoT and NoC communication security research with decision theory.

Identification of benefits, challenges, and pathways in E-commerce industries: An integrated two-phase decision-making model

The e-commerce industry has seen significant growth over the past decade as it focuses on convenience and accessibility, leading to a surge in online shopping with more and more consumers opting for it. At the same time, the e-commerce industry faces various challenges. In order to fully harness the potential of this industry, it is important to identify its benefits and challenges and focus on pathways to mitigate the challenges and harness its growth. This study utilizes the Delphi approach and involves experts from the e-commerce domain to get their opinions to identify the top ten benefits, challenges, and pathways for the e-commerce industry. Analytic Hierarchy Process (AHP) and Criteria Importance Through Intercriteria Correlation (CRITIC) methods are subsequently, employed to prioritize the identified factors. Results of the study revealed that factors such as affordable advertising & marketing; availability and product variety; and Global reachability are the most important benefits, while technological upgradation; returns or refunds; and counterfeit products posed the greatest challenges for the industry. Government compliance check; better relationship with delivery partners; and strong data privacy and online security policies emerged as the best pathways. This study also provides valuable insights to businesses, policymakers, and researchers in the e-commerce industry on how to navigate the benefits, challenges, and pathways of this rapidly growing sector.

Integrated Machine Learning Algorithms and MCDM Techniques in Optimal Ranking of Battery Electric Vehicles

The automobile industries across the world of this present age are streamlining the manufacture of battery electric vehicles (BEV) as a step towards creating pollution free environment. BEVs are used as an alternate strategy to alleviate the carbon emission at global level. As environmental conservation is one of the long standing sustainable 1f ?developmental goals it is the need of the hour to make a paradigm shift from fossil fuels to renewable energy sources, at the same time this also gives rise to a decision-making problem on making optimal choice of the electric vehicles. In this paper a decision making problem based on ten alternative BEVs and eleven criteria is considered from the earlier works of Faith Ecer. The new ranking method of multi-criteria decision making MCRAT(Multiple Criteria Ranking by Alternative Trace) is used together with three different criterion weight computing methods of AHP(Analytical Hierarchy Process) ,CRITIC (CRiteria Importance Through Intercriteria Correlation) & MEREC (MEthod based on the Removal Effects of Criteria). The results obtained are compared and validated using random forest machine learning algorithm. This research work conjoins multi-criteria decision making methods and machine learning algorithms to make optimal decisions on Battery electric vehicles and this integrated approach yields optimal ranking results and it will certainly create new rooms in decision-making approaches in coming days.

MACBETH-MAIRCA Plithogenic Decision-Making on Feasible Strategies of Extended Producer's Responsibility towards Environmental Sustainability

The environmental disarray caused by plastic usage alarms the world leaders to join hands in making coordinated efforts in creating a green globe to support environment for the future generation. The responsibility of promoting environmental sustainability is not confined to government alone as all the producer companies have equal share in mitigating the plastic waste. One of the ideal strategies of environmental conservation practiced by many of the nations at recent times is extended producer’s responsibility (EPR). This research work purposes in building a multi-criteria decision-making model integrating the methods of MACBETH (Measuring attractiveness through a categorical-based evaluation technique) and MAIRCA (Multi Attributive Ideal-Real Comparative Analysis) in plithogenic environment to make optimal decisions on the plastic recycling methods subjected to four core criteria in EPR context. The efficiency of the newly developed integrated model is determined by comparing the model with other models integrating MAIRCA with the methods of CRITIC (CRiteria Importance Through Intercriteria Correlation) FUCOM (Full Consistency Method). The sensitivity analysis helps in listing the merits and limitations of the proposed integrated model and also the consistency of the criterion weights and the ranking of the alternatives are checked.

HABITAT SAFETY EVALUATION OF SUSTAINABLE HOUSING FROM THE PERSPECTIVE OF HOUSEHOLDS

ABSTRACTIn recent years, the housing market has developed rapidly during the process of urbanization. Since people require adequate housing safety, safety challenges associated with housing have received increasing attention. Although development of sustainable housing was rapid in the last few decades, insufficient studies considered households’ needs and examined the health and psychological safety issues in sustainable housing. This study aims to establish an indicator system and develop a model to evaluate habitat safety from three dimensions: physical safety, health safety, and psychological safety. This study develops an evaluation system containing 46 indicators to assess the safety performance of sustainable housing from households’ perspectives. In addition, criteria importance through intercriteria correlation (CRITIC) method is combined with the Cloud Model to provide systematic and visual evaluation results. A government-funded sustainable housing project in Chongqing, China, is selected as a case study and questionnaire surveys were delivered to collect the raw data of subjective ratings on the 46 safety indicators. The following findings are observed: (1) there is a prominent demand for improvement in psychological safety of sustainable housing, followed by health safety; (2) different age groups have different safety needs; and (3) regulations and standards are very important to improve the habitat safety of sustainable housing. The study considers safety issues from households’ perspectives and introduces a different idea of human safety in sustainable housing. It provides an effective method to evaluate housing safety and could be a useful reference for further development of sustainable housing.

HABITAT SAFETY EVALUATION OF SUSTAINABLE HOUSING FROM THE PERSPECTIVE OF HOUSEHOLDS

ABSTRACT In recent years, the housing market has developed rapidly during the process of urbanization. Since people require adequate housing safety, safety challenges associated with housing have received increasing attention. Although development of sustainable housing was rapid in the last few decades, insufficient studies considered households’ needs and examined the health and psychological safety issues in sustainable housing. This study aims to establish an indicator system and develop a model to evaluate habitat safety from three dimensions: physical safety, health safety, and psychological safety. This study develops an evaluation system containing 46 indicators to assess the safety performance of sustainable housing from households’ perspectives. In addition, criteria importance through intercriteria correlation (CRITIC) method is combined with the Cloud Model to provide systematic and visual evaluation results. A government-funded sustainable housing project in Chongqing, China, is selected as a case study and questionnaire surveys were delivered to collect the raw data of subjective ratings on the 46 safety indicators. The following findings are observed: (1) there is a prominent demand for improvement in psychological safety of sustainable housing, followed by health safety; (2) different age groups have different safety needs; and (3) regulations and standards are very important to improve the habitat safety of sustainable housing. The study considers safety issues from households’ perspectives and introduces a different idea of human safety in sustainable housing. It provides an effective method to evaluate housing safety and could be a useful reference for further development of sustainable housing.

Determining the objective weight of green manufacturing indicators: a case study of the Indonesian manufacturing company

With the growing of environmental issues, manufacturing companies are compelled to improve their performance to reduce resource consumption and environmental pollution. Accordingly, company's performance should be measured according to the green manufacturing indicators. The importance of the indicators must be determined properly aligned with the company's goals and profiles. This study aims to determine the weight of green manufacturing indicators which becomes the critical input for green performance evaluation. Different weighting methods including entropy and CRiteria Importance Through Inter-criteria Correlation (CRITIC), are integrated using Decision-Making Trial and Evaluation Laboratory (DEA) to determine the final weight. A case study of the Indonesian manufacturing company is presented to illustrate the application of the proposed method. The result indicates that process technology, compliance of environmental quality standards, and operational standards are considered critical in green manufacturing.

A financial performance evaluation of commercial banks traded on Borsa Istanbul with a multi-dimensional perspective

Given that Turkey is an emerging market, it cannot be denied that the banks whose shares are traded on the stock exchange primarily lead the stock market and at the same time the Turkish financial markets. Therefore, a total of eleven commercial banks traded on Borsa Istanbul (BIST) have been included in the study. Since the performance of these commercial banks is evaluated in terms of multiple selected financial ratios (criteria), this study points out that it may be considered as a multi-criteria decision-making (MCDM) problem. Therefore, two effective MCDM techniques have been used in the performance evaluation process of the study. The aim of this study is to evaluate the performance of eleven commercial banks traded on BIST with a set of reasonable assessment criteria by using the integration of the criteria importance through intercriteria correlation (CRITIC) and weighted aggregated sum product assessment (WASPAS) methods for the year 2018.

Selecting cloud database services provider through multi-attribute group decision making: a probabilistic uncertainty linguistics TODIM model

Cloud database services platforms (CDSP) have aided in both the generation of new ideas and the reduction of costs. Choosing the finest CDSP is a critical part of enterprise management for helping businesses respond to increasing market pressure and client demand. This study tried to solve this problem and proposed the integration concept of the TODIM (TOmada de Decisão Interativa e Multicritério) and the probability uncertain linguistic (PUL), which is a typical decision-making technique focused on the theory of prospects (PT-PUL-TODIM). The concept of probability uncertainty linguistic term sets (PULTS) is discussed. The cumulative weight of probabilistic double hierarchy linguistic knowledge is then determined by using the following cumulative prospect theory. Based on the experts’ opinions, complex expressions with experience in the Vietnam market were collected and further transformed into a PULTS matrix. However, the CRiteria Importance Through Inter-Criteria Correlation (CRITIC) technique is implemented to calculate the objective criteria weights. The PT-PUL-TODIM optimization approach is developed and adopted for the CDSP. Finally, we compared other methods and conducted a sensitivity analysis to compare the PT-PUL-TODIM approach with other ways to assess the validity, practicality, and usefulness of the technique, and the comparison revealed the merits and limitations of the model.