Linguistic Scale Research Articles

Predicting Outcomes 2 Months and 1 Year After Inpatient Rehabilitation for Youth With TBI Using Duration of Impaired Consciousness and Serial Cognitive Assessment.

To examine predictive utility of the Glasgow Coma Scale (GCS), time to follow commands (TFC), length of posttraumatic amnesia (PTA), duration of impaired consciousness (TFC+PTA), and the Cognitive and Linguistic Scale (CALS) scores in predicting outcomes on the Glasgow Outcome Scale-Extended, Pediatric Revision (GOS-E Peds) for children with traumatic brain injury (TBI) at 2 months and 1 year after discharge from rehabilitation. A large, urban pediatric medical center and inpatient rehabilitation program. Sixty youth with moderate-to-severe TBI (mean age at injury = 13.7 years; range = 5-20). A retrospective chart review. Lowest postresuscitation GCS, TFC, PTA, TFC+PTA, inpatient rehabilitation admission and discharge CALS scores, GOS-E Peds at 2-month and 1-year follow-ups. CALS scores were significantly correlated with the GOS-E Peds at both time points (weak-to-moderate correlation for admission scores and moderate correlation for discharge scores). TFC and TFC+PTA were correlated with GOS-E Peds scores at a 2-month follow-up and TFC remained a predictor at a 1-year follow-up. The GCS and PTA were not correlated with the GOS-E Peds. In the stepwise linear regression model, only the CALS at discharge was a significant predictor of the GOS-E Peds at the 2-month and 1-year follow-ups. In our correlational analysis, better performance on the CALS was associated with less long-term disability, and longer TFC was associated with more long-term disability, as measured by the GOS-E Peds. In this sample, the CALS at discharge was the only retained significant predictor of GOS-E Peds scores at 2-month and 1-year follow-ups, accounting for roughly 25% of the variance in GOS-E scores. As previous research suggests, variables related to rate of recovery may be better predictors of outcome than variables related to severity of injury at a single time point (eg, GCS). Future multisite studies are needed to increase sample size and standardize data collection methods for clinical and research purposes.

Fuzzy DEMATEL Approach to Assess Factors Leading to Navigational Equipment Defect

The increasing attention to the improvement and continuous enhancement of navigational safety has led to a high standard of navigation systems and the introduction of new technologies. Although several conventions, recommendations, guidelines, and performance standards for navigational equipment are set out by the International Maritime Organization (IMO), unexpected defects on this equipment may still occur on board. Any defect on this equipment may cause both accidents and commercial loss. This paper presented A fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique to assess factors that may cause navigational equipment defects, considering the academic and industrial gaps. Five homogeneous experts were asked to evaluate the relationship among the factors with respect to the linguistic scale. After the factors were ascertained and evaluated, preventive measures for most important factors were recommended in the view of experts’ opinions in order to minimize and avoid their effect. The findings of the study will contribute to understanding the causes of navigational equipment defects and provide a basis for the continuous safety process of the ship’s bridge operations in a comprehensive aspect.

Комплексный подход к оцениванию защищенности значимых объектов критической информационной инфраструктуры от несанкционированного доступа

The number of cybersecurity events in the modern world has increased significantly, of which a significant number fall on objects of critical information infrastructure. This paper discusses the main requirements for models for assessing the security of significant objects of critical information infrastructure from unauthorized access, classification of ambiguous source information, a generalized algorithm for assessing the level of security of significant objects of critical information infrastructure from unauthorized access, a fuzzy model for assessing the level of security using point and linguistic scales. It also determines the procedure for assessing the security of significant objects of critical information infrastructure from unauthorized access. Among the main requirements for models for assessing the security of significant objects of critical information infrastructure from unauthorized access are the following: versatility, extensibility, formalizability, simplicity, multifactoriality. The generalized algorithm for assessing the level of security of significant objects of critical information infrastructure from unauthorized access includes four computational blocks: in block 1, the collection and primary processing of information is carried out; in block 2, calculations using fuzzy evaluation algorithms with linguistic and point scales are used; in block 3, the effectiveness of information security employees is evaluated; in block 4, the levels of security of significant objects of critical information infrastructure from unauthorized access are predicted using fuzzy time series; in block 5, the estimates obtained at previous stages of calculations are examined using data processing techniques and draw appropriate conclusions for decision-making.

Applications of Hesitant Interval Neutrosophic Linguistic Schweizer-Sklar Power Aggregation Operators to MADM

Hesitant interval neutrosophic linguistic sets (HINLSs) are one of the core generalization of various sets, such as neutrosophic set (NS), interval neutrosophic set (INS), and interval neutrosophic linguistic set (INLS). HINLS can represent the uncertainty, inconsistency, and reluctance of assessment specialists by expressing qualitative and quantitative information. The goal of this article is to introduce a novel MADM technique that can account for changes in the semantic environment as well as negative consequences of experts’ excessive evaluation values. First, several innovative operational rules based on Schweizer-Sklar (SS) t -norm and t -conorm and a novel comparison procedure for HINLS are established by integrating different linguistic scale functions. This allows for varied semantic settings to be handled. Then, various innovative HINL Schweizer-Sklar power aggregation operators (AOs) are suggested, containing hesitant interval neutrosophic SS power average (HINLSSPA) operator, weighted hesitant interval neutrosophic SS power average (WHINLSSPA) operator, hesitant interval neutrosophic SS power geometric average (HINLSSPGA) operator, weighted hesitant interval neutrosophic SS power geometric average (WHINLSSPGA) operator, some core properties, and various special cases of these AOs are examined. Additionally, based on the initiated AOs, a multiple attribute decision making (MADM) technique with HINL information is anticipated. Finally, a numerical example is illustrated to show the effectiveness and practicality of the anticipated MADM method. A comparison with existing approaches are also discussed.

Energy Sustainability Performance Index of Biodigester Using Energy LCA-Based Indicators

Nowadays, it is still difficult to measure organizations’ performances due to the complexity of energy systems, their multiple functions, and the usage of unclear indicators. Organizations need to consider energy issues to contribute to sustainability. This paper aims to develop a methodology for measuring energy sustainability performance for a biogas plant, but the idea of the study is to establish to which degree the methodology may be substituted for the traditional methods based on multicriteria decision-making, which are used for sustainability assessment. Hence, the evaluation performance method combines fuzzy numbers, linguistic scale, and energy life-cycle indicators. The evaluation is carried out for the biodigester, presenting its results in terms of energy sustainability performance index for two scenarios (p and q) considering the three-dimensional sustainability structure. The results pictured that the value of energy sustainability performance index q (0.382) is relatively lower than the index achieved for scenario p (0.815). Biodigester for scenario q does not demonstrate a positive perspective on a transition toward energy sustainability. The presented methodology is a new simple method aimed at replacing the current energy performance assessments into a technology evaluation solution considering uncertainties, which is not supported by the software. The suggested energy life cycle analysis indicators could be used to evaluate similarly sized biogas plants across countries. They might be also used for prioritization of plants modeling various energy parameters or inspirational for energy decision-makers to deliver more flexible and reliable outcomes within an uncertain environment.

Management of Obesity Using Fuzzy Analytic Hierarchy Process

Obesity has been linked to several heart diseases .Unfortunately, Malaysian today are the most overweight or obese people among Asian nations. That is, half of the population is overweight. These are serious social consequences. Therefore, specific and serious actions are needed to reduce or eliminate this threat. The rapid increase in obesity rates has directed the link with the factors such as low physical activities, ease of transportation, food intake and emotional factor. Thus, this study aims at identifying the most significant factors affecting obesity in Peninsular Malaysia. The factors that are detected to be the cause of obesity can help manage individuals with obesity problems. Fuzzy Analytic Hierarchy Process (F-AHP) approach was used for the identification and ranking of each factor. The method adopted was one of the most reliable methods for both identification and the ranking off the most significant factors affecting obesity. The study selected seven respondents and applied the calculations. The calculations consist of seven steps. Initially, the goals and criteria to construct the hierarchy process were determined. This followed by questionnaires distribution to the respondents by using the linguistic scale. After that, two parameters were calculated, these include geometric mean weight and fuzzy weight. Lastly, the fuzzy weight and all the calculation were defuzzified and normalized. The results show the factors that affect obesity the most in Peninsular Malaysia is physical inactivity with the weight of 41.6% after normalized. The physical inactivity has been ranked the first factor, the food intake ranked second, the third rank is emotional factor and lastly is technology. The precise identification and ranking are very meaningful to the management of obesity problem. Firstly, there is a need to increase healthy physical activity. Secondly, the need to change their diet according to experts. Lastly, they need to manage their emotions and technology well.

A Novel Interval-Valued q-Rung Dual Hesitant Linguistic Multi-Attribute Decision-Making Method Based on Linguistic Scale Functions and Power Hamy Mean.

The interval-valued q-rung dual hesitant linguistic (IVq-RDHL) sets are widely used to express the evaluation information of decision makers (DMs) in the process of multi-attribute decision-making (MADM). However, the existing MADM method based on IVq-RDHL sets has obvious shortcomings, i.e., the operational rules of IVq-RDHL values have some weaknesses and the existing IVq-RDHL aggregation operators are incapable of dealing with some special decision-making situations. In this paper, by analyzing these drawbacks, we then propose the operations for IVq-RDHL values based on a linguistic scale function. After it, we present novel aggregation operators for IVq-RDHL values based on the power Hamy mean and introduce the IVq-RDHL power Hamy mean operator and IVq-RDHL power weighted Hamy mean operator. Properties of these new aggregation operators are also studied. Based on these foundations, we further put forward a MADM method, which is more reasonable and rational than the existing one. Our proposed method not only provides a series of more reasonable operational laws but also offers a more powerful manner to fuse attribute values. Finally, we apply the new MADM method to solve the practical problem of patient admission evaluation. The performance and advantages of our method are illustrated in the comparative analysis with other methods.

‘They are asking me why I am speaking Gagauz’: family language practices and the level of linguistic (in)security of adolescents speaking an endangered language

ABSTRACT In this study, the relationship between the family language practice and the level of linguistic (in)security of adolescent Gagauz speakers is examined in the context of an endangered language. To this end, a language-use questionnaire and linguistic insecurity scale were administered to 674 participants. The questionnaire included questions exploring demographic information, self-reported language skills, language acquired at home, parents’ speaking proficiency and the language of interaction. The linguistic insecurity scale comprised (self)-evaluations of language practices, linguistic status and linguistic quality. Using a quantitative methodology, ten interviews were conducted. The findings show that the participants felt more secure while using Russian and there was a strong correlation between family language practice and linguistic insecurity perceived by the adolescent speakers. Moreover, language choice in interactions was found to be speaker-specific. In other words, as a part of the family language policy, the participants spoke Gagauz with their parents, siblings and grandparents. In some cases, however, the language choice was based on the ethnicity of the interlocutor and the language which friends and neighbours were speaking. It was found that although speakers felt secure and motivated to speak the Gagauz language, the use of Gagauz seemed to be limited to family contexts.

О ДИНАМИКЕ СМЕРТНОСТИ В ТУЛЬСКОЙ ОБЛАСТИ

The aim of the study is to evaluate and analyze the dynamics of mortality in the Tula region on the basis of Bayesian intelligent technologies. The actual values of the number of deaths are transferred to the linguistic scale, which makes it possible to assess and analyze the mortality rate within the nine classes formed. The constructed model of mortality dynamics allowed us to conclude about the probable future trend of the indicator. A comparative analysis of the forecast results for four variants with the actual value of the mortality rate in 2021 allowed us to conclude that the presented forecasting methodology can be used.

Pythagorean Fuzzy Linguistic Power Generalized Maclaurin Symmetric Mean Operators and Their Application in Multiple Attribute Group Decision-Making

As an extension of Pythagorean fuzzy sets and linguistic term sets, Pythagorean fuzzy linguistic sets (PFSs) are powerful to describe decision-making information quantificational and qualitatively, which have received much scholars’ attention. The purpose of this paper is to propose a new multiple attribute group decision-making (MAGDM) approach with Pythagorean fuzzy linguistic (PFL) information. To this end, we firstly analyze the drawbacks of existing operations of PFL numbers and propose new operational rules based on linguistic scale function. The power average (PA) operator is famous for its capacity of reducing the negative influence of unreasonable evaluation values provided by prejudiced decision makers on the decision results. The generalized Maclaurin symmetric mean (GMSM) can not only capture the interrelationship among multiple inputs but also manipulate the effect of related properties by adjusting the parameters. When considering aggregation operators of PFL numbers, we combine PA with GMSM and propose the PFL power generalized Maclaurin symmetric and the PFL power generalized weighted Maclaurin symmetric operators. We also study important properties and special cases of these operators. We continue to investigate MAGDM problems with PFL decision information and propose a novel method to determine the optimal alternative. Finally, we conduct numerical examples to demonstrate the effectiveness of our proposed method. We also attempt to illustrate the advantages and superiorities of the proposed method via comparative analysis.

Efficient Model for Emergency Departments: Real Case Study

There are several challenges that hospitals are facing according to the emergency department (ED). The main two issues are department capacity and lead time. However, the lack of consensus on performance criteria to evaluate ED increases the complication of this process. Thus, this study aims to evaluate the efficiency of the emergency department in 20 Egyptian hospitals (12 private and 8 general hospitals) based on 13 performance metrics. This research suggests an integrated evaluation model assess ED under a framework of plithogenic theory. The proposed framework addressed uncertainty and ambiguity in information with an efficient manner via presenting the evaluation expression by plithogenic numbers. Data Envelopment Analysis (DEA) technique is used in order to measure the efficiency of the emergency department of 20 hospitals according to the number of treated patients and effect on patient's life quality based on 11 factors. Using the Analytic Hierarchy Process (AHP), the weight of efficiency factors will be measured based on neutrosophic linguistic scale pairwise comparison. Plithogenic operations provide more accurate aggregation result according to contradiction degree between criteria values. The results show that ten of the hospitals are providing efficient service in their emergency department, while the other ten are less efficient. The analysis of the results shows that 58% of private hospitals emergency department is operating efficiently, while the efficient general hospitals represent 38%.

Implementasi Analytic Hierarchy Process Sebagai Metode Penilaian Dalam Seleksi Calon Pemain Handball

Any sports club would expect a good composition of players and in accordance with the standards that have been set. As in the Handball Sports Club. To obtain these players, it is necessary to carry out a selective and comprehensive recruitment. The process of recruiting players is a vital thing because it can determine the success and success of a sports club. This procession is not an easy matter, because it involves many player criteria that must be assessed and accumulating the results of the assessment also needs to be done with an objective method/algorithm. This study aims to design a scoring system for prospective handball players using the Analytic Hierarchy Process method and implemented into web-based software. The research process and system implementation use the Waterfal method which was developed according to the needs of the research. The results of this study are web-based software and criteria data and assessment sub-criteria consisting of posture criteria with height sub-criteria with eigenweights of 0.07 and body weight of 0.04, posture criteria with situp sub-criteria with eigenweights of 0.06, pushups 0.10, sprints 0.13, and shuttle run 0.14, and technical criteria with passing sub-criteria with eigenweight 0.16, flying shoot 0.14, and standing throw shoot with eigenweight 0.15. For the rating scale using a linguistic scale, the category is very good with an eigenweight of 0.55, good 0.26, quite good 0.12, and not good with an eigenweight of 0.05.

Integrating Linguistics Theories in Developing Foreign Language Teaching Materials (German Grammar Textbook for Indonesian Learners)

This study aims to investigate the effectiveness of German grammar textbook using linguistic approaches in increasing students’ academic motivation, learning outcome, and linguistic understanding. This German grammar textbook is composed for Indonesian learners. This study employed experimental approach by involving two experimental groups without control group. The total research participants were 45 Indonesian students in the second semester of the German language education department divided into two classes. There were three variables observed in this study. Students’ learning outcome was measured by a grammar test developed by the researchers, while students’ academic motivation was measured using a scale developed by Vallerand et al. (1992) consisting of 28 items that had been translated into Indonesian and tested by Natalya & Purwanto (2018). Students’ linguistic understanding was measured using the linguistic understanding scale developed by Hasmawati (2021). The treatment was conducted in six meetings in which each meeting took place for two hours using Zoom video conference platform. Data were analyzed using a descriptive statistic, a correlation test, and a paired sample t-test using the SPSS-26 application. The study found that the integration of linguistic approach, error analysis and contrastive analysis, in composing a grammar textbook of a foreign language is more likely to positively affect students’ academic motivation, learning outcome, and linguistic understanding.

Rasch Properties of the Cognitive and Linguistic Scale and Optimization for Outcome Trajectory Modeling in Pediatric Acquired Brain Injury

ObjectivesTo (1) determine if items on the Cognitive and Linguistic Scale (CALS) follow a Rasch distribution and (2) explore the relationship between Rasch-derived Cognitive Ability Estimates and outcome trajectory parameters using a nonlinear mixed-effects modeling approach. DesignRetrospective study. SettingPediatric inpatient rehabilitation hospital. ParticipantsA total of 252 children (N=252) aged of 2-21 years (median, 11.8 [IQR, 6.4-15.9] years) consecutively admitted to an inpatient rehabilitation brain injury unit (2008-2014) for a first inpatient admission after acquired brain injury. InterventionsNot applicable. Main Outcome MeasuresRasch-derived Cognitive Ability Estimates from the CALS and associated outcome trajectory parameters. ResultsThe CALS demonstrates adequate interval-scale properties with removal of scores from the arousal and responsivity items. Rasch-derived Cognitive Ability Estimates were associated with age (β=0.025, P<.001) such that older age was associated with a faster rate of recovery and more complete ultimate recovery. Slower recovery initiation was associated with a less complete overall cognitive recovery (Spearman ρ=−0.31; P<.001). ConclusionsThe Cognitive Ability Estimates derived from the CALS and associated outcome parameters (eg, rate of recovery) may serve as an ideal outcome measure for clinical trials evaluating interventions for acquired brain injury in a pediatric rehabilitation setting.

Multiple attribute group decision-making based on interval-valued q-rung orthopair uncertain linguistic power Muirhead mean operators and linguistic scale functions.

Fuzzy set theory and its extended form have been widely used in multiple-attribute group decision-making (MAGDM) problems, among which the interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs) got a lot of attention for its ability of capturing information denoted by interval values. Based on the previous studies, to find a better solution for fusing qualitative quantization information with fuzzy numbers, we propose a novel definition of interval-valued q-rung orthopair uncertain linguistic sets (IVq-ROULSs) based on the linguistic scale functions, as well as its corresponding properties, such as operational rules and the comparison method. Furthermore, we utilize the power Muirhead mean operators to construct the information fusion method, and provide a variety of aggregation operators based on the proposed information description environment. A model framework is constructed for solving the MAGDM problem utilizing the proposed method. Finally, we illustrate the performance of the new method and investigate its advantages and superiorities through comparative analysis.

Increasing the Reliability of FMEA Evaluation by Modifying Rating Scales and Applying Pairwise Comparison Method

Failure Mode and Effect Analysis (FMEA) is a frequently applied risk assessment methodology in different fields of industry. It provides the opportunity for deep analysis of risky events, connecting to their potential causes and effects. Due to its robust method, risk can be identified and managed but, because of its complexity, the assessment can be time-consuming, and the answers can be inconsistent. In the authors’ experience, the scale used to quantify the priority number can influence these outcomes. To identify and measure the significance level of this connection, a survey was organized with experts of digital manufacturing, who were asked to rank the probability of risk occurrence in planning a production process based on digital manufacturing principles. Participants had to use three assessment methods: 1) traditional ‘linguistic’ scale; 2) ‘ratio scale; 3) pairwise comparison. In the case of the linguistic scale, probabilities were defined by their descriptions and an integer between number 1 and 7. These numbers did not equal the probability percentage. In contrast, the ranks of the ratio scale equalled the ranges of probability percentage. In the pairwise comparison, risks were compared by the frequencies of their occurrences. The assessment results were compared by time-need, difficulty, priority list, and consistency. Time and difficulty were ranked by the survey participants on a 4-level scale. The priority list was created by the summarized rank values. In the consistency assessment, we looked at how the amended scale affects the assessment uncertainty. In addition, pairwise comparisons were used to examine the consistency of each expert’s evaluation and filter out those that were not accurate enough.

An Extended LBWA Framework in Picture Fuzzy Environment Using Actual Score Measures Application in Social Enterprise Systems

Level-based weight assessment (LBWA) model is a recently introduced algorithm for determining criteria weights for multi-criteria group decision making. In this paper, the authors aim to extend the basic framework of LBWA in the picture fuzzy (PF) environment using actual score (AS) measures of the picture fuzzy numbers (PFN). They apply this extended framework in addressing a real-life problem pertaining to social entrepreneurship or social entrepreneurs (SE) in the context of COVID-19. They endeavor to identify the critical challenging factors of SE in the new normal. They list the challenges as revealed through literature review and take the opinion of a group of SEs using PF linguistic scale. They then apply the proposed framework, actual score-based picture fuzzy LBWA. They notice that ability to withstand disruption risk and show resilience and fund availability and creation of a supporting business ecosystems are the major challenges that SEs face in the new normal. They carry out validity checking and sensitivity analysis, which show reasonable consistency and stability in the result.

Group decision making based on consistency and consensus analysis of dual multiplicative linguistic preference relations

This paper proposes a new group decision making (GDM) method based on the consistency and the consensus analysis of dual multiplicative linguistic preference relations (DMLPRs). A new type of linguistic variables , called dual multiplicative linguistic variables (DMLVs), is presented, which is defined on the multiplicative linguistic scale. DMLVs are used to represent asymmetrical qualitative hesitancy judgments of decision makers (DMs). A maximum-consistency-based interactive algorithm to derive multiplicative linguistic intuitionistic preference relations (MLIPRs) is presented, by which the consistency concept for DMLPRs is obtained. Then, we define the concept of inconsistent DMLPRs and propose an optimal-model-based method for deriving consistent DMLPRs. Furthermore, incomplete DMLPRs also can be dealt with by the proposed maximum-consistency-based interactive algorithm. For GDM, the weights of DMs are determined by the cosine-based correlation coefficient between individual DMLPRs. Moreover, we propose a consensus measure to calculate the agreement degree of DMLPRs and build an optimal model to increase the consensus level of individual DMLPRs. Finally, a new GDM method (call Algorithm III ) is offered and an application example is used to illustrate the proposed GDM method. The proposed GDM method outperforms the former GDM methods for GDM in the environments of DMLPRs.

A novel picture fuzzy linguistic Muirhead Mean aggregation operators and their application to multiple attribute decision making.

The Picture fuzzy linguistic set (PFLS) is an extension of the intuitionistic fuzzy set (IFS) and linguistic variables (LVs), which has been applied successfully in the process of decision making. Considering the lack of closeness of extant PFLS operations and the interrelationship among input attributes do not consider. In this paper, for the sake of addressing those limitations, we firstly redefine some novel operational laws for PFLS by introducing linguistic scale functions and the related properties are studied. Then, a novel score function and accuracy function are also defined to compare PFLSs. Subsequently, in consideration of the superiority of the Muirhead Mean (MM) operator in capturing the interaction relationship between the input parameters, we extend the MM operator to the Picture fuzzy linguistic context and then propose Picture fuzzy linguistic weighted MM operator and its dual form in a new light. After that, these operators have adopted to build two novel models to solve multiple attribute decision-making (MADM) problems. Finally, a practical example for the selection of the innovative “Mobike” sharing bike design is provided to illustrate the practicality and effectiveness of proposed approaches.

Evaluation of sustainable e-waste collection method for urban and rural region of India.

Electronic waste is one of the most challenging waste streams to manage. It has become a significant concern in developing countries due to the ever-increasing volume of generation coupled with deficient growth in collection and processing infrastructure. For the various stakeholders, it is of paramount importance to adopt a robust and sustainable collection method for hazard mitigation. The prevalent e-waste collection methods are categorized under four major heads, namely take-back, retail store, door-to-door and curbside collection. The e-waste collection problems are analysed from various perspective, based on literature that cited developing country-specific survey and data that includes India. Economic sustainability and potential risk are included as attributes in the evaluation scheme. We attempt to establish a decision-making model. Discussion with the field experts and decision-makers (DMs) provided the weights for various attributes and sub-attributes. A fuzzy linguistic scale is used to take care of ambiguity in DMs' opinion. Fuzzy- Analytical Hierarchy Process (FAHP) is used to determine the importance of various attributes and sub-attributes, while Fuzzy-VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) is used to determine the rank of the alternatives. Based on the analysis, 'take-back collection' and 'retail store based collection' are found the most suitable options for urban and rural regions respectively. The attributes, social awareness and economical sustainability are found to have the highest significance in both cases. Implementation of a collection method is an expensive activity, and the proposed Fuzzy-Multi Attribute Decision Making attempts to capture various attributes and their complex interplay to arrive at a decision on optimum e-waste collection option(s) in a specific locality.