An integrated neutrosophic ANP and VIKOR method for achieving sustainable supplier selection: A case study in importing field

Evaluating the resilience of residential buildings during a pandemic with a sustainable construction approach

The COVID-19 pandemic has been a catastrophic event that has affected all aspects of human life worldwide. Due to the high genetic mutations of the virus, there has been a prolonged search for definitive therapeutic discovery, leading to extended periods of home quarantine. As a result, homes have become multipurpose spaces for work, education, sports, and other daily activities. Given the importance of residential buildings as the first line of defense against possible future pandemics, a model has been proposed to assess their readiness to handle pandemics using a sustainable development approach. This study investigates the most crucial criteria for evaluating residential buildings and applies them in a Multi-Criteria Decision Making (MCDM) process. The final evaluation model is presented using the SWARA and COCOSO methods, along with a set of criteria selected and weighted by experts. The study shows that the criteria related to health and safety are more critical than other sectors. Buildings that meet the standards of this group better are likely to have a higher score.

Addressing the supplier selection problem by using the analytical hierarchy process

ACI Pharma spends $ 12 to 15 million yearly to promote its brands. The brand promotional activities of the company were hampered, due to supplier selection subjectively, which impacted market share. The study selects the best supplier with supplier management and purchasing policy for printing materials for ACI Pharma based on objective judgments. The required data has been collected from the company. This study uses the Analytical Hierarchy Process (AHP) to address supplier selection and management problems. Five attributes, cost, quality, delivery, flexibility, and communication, and ten suppliers have been evaluated to select the best supplier. Spark Printers is the best supplier for ACI Pharma as it obtains the highest score, 0.968, whereas Marvelous Printers Limited and Lutfur Enterprise are the second-best and third-best suppliers. The application of AHP in the pharmaceutical supply chain industry is very limited. Further, Previous studies emphasized supplier selection rather than management and purchasing policy. Moreover, industry practitioners, especially in developing countries, might not use complex methodologies due to time, money, or technical constraints. Considering these thoughts, this study is conducted to select and manage the right supplier with purchasing policy using AHP in industry-friendly language and analysis patterns. Other organizations suffering from similar problems, such as ACI Pharma, may benefit from this research. The study has selected AHP, purposively, without any methodological justifications, although many Multi-Criteria Decision-Making (MCDM) techniques are present. Further studies might be conducted to find which MCDM method fits best to address the supplier selection problem in the pharmaceutical supply chain industry.

A hybrid DEMATEL-COPRAS method using interval-valued probabilistic linguistic term set for sustainable hydrogen fuel cell supplier of new energy vehicles

With the continuous development of the global economy, global environmental pollution, climate degradation and global warming are becoming increasingly serious. In order to deal with the increasingly serious environmental problems, the government is vigorously supporting and promoting the development of new energy vehicles (NEVs). As the core unit of NEVs, one of the main challenges faced by hydrogen fuel cell (HFC) supplier is to select the best supplier for their business among all possible suppliers. Selecting the optimal supplier is a key decision in green supplier management. Therefore, it is extremely important and meaningful to select an optimal HFC supplier to provide power for NEVs. This paper proposes a new decision-making framework based on Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and Complex proportional assessment (COPRAS) method under interval-valued probabilistic linguistic environment to select the appropriate HFC supplier of NEVs. Firstly, this paper establishes the evaluation criteria system of HFC supplier assessment which is the synthesis of economical, environmental, social, technical, organisation and service aspects. Then, in order to express the uncertainty of expert decision-making, this paper uses interval-valued probabilistic linguistic term set (IVPLTS) to describe the evaluation information. Next, the interval-valued probabilistic linguistic term set decision-making trial and evaluation laboratory (IVPLTS-DEMATEL) method is applied to calculate the criteria weights. Moreover, this paper constructs the interval-valued probabilistic linguistic term set Complex Proportional Assessment (IVPLTS-COPRAS) model for the selection of HFC supplier of NEVs. Finally, a case in China with sensitivity analysis and comparison analysis are executed to illustrate the feasibility and validity of the proposed approach. This paper provides valuable references for investors and companies to select the most appropriate HFC supplier of NEVs under uncertain environment.

An MAGDM approach with 2-tuple linguistic neutrosophic number for mental health education evaluation of college students

Generally speaking, the evaluation of mental health education (MHE) in colleges is an activity and process of evaluating the elements, processes and effects of MHE in schools by systematically collecting relevant information, following reasonable evaluation principles and applying specialized evaluation methods and techniques according to certain evaluation index systems and value judgment systems. The fundamental goal of MHE evaluation in colleges is to promote and regulate the scientific, healthy and smooth development of MHE in colleges and universities, improve the quality of MHE, promote the reform of MHE, build a good psychological atmosphere in colleges and universities, and effectively improve the psychological quality and mental health of college students. The MHE evaluation of college students is looked as multiple attribute group decision-making (MAGDM). In this paper, the 2-tuple linguistic neutrosophic number cross-entropy (2TLNN-CE) method is defined based on the traditional cross-entropy and 2-tuple linguistic neutrosophic sets (2TLNSs). Then, 2TLNN-CE method is established for MAGDM. Finally, a numerical example for MHE evaluation of college students was given and some comparisons are also conducted to further illustrate advantages of the built method.

An improved CLVA method for evaluating the endurance quality level of young male basketball players with 2-tuple linguistic neutrosophic information

For a long time, the level of endurance quality of our male basketball athletes is not high, and there is a gap with the strongest countries in Europe and America. The former head coach of Chinese men’s basketball team diagnosed the biggest problem of Chinese men’s basketball team and Chinese youth men’s basketball team is the poor quality of endurance. It is especially important to strengthen the endurance training of our basketball players and improve their endurance level. However, from the current situation, the teams in the training due to the lack of standards for endurance quality training has led to a great blindness in endurance quality training. The endurance quality level evaluation of young male basketball players is a classic multiple attribute group decision making (MAGDM) issue with vague, inconsistent, and indeterminate information. The 2-tuple linguistic neutrosophic sets (2TLNSs) is an appropriate form to express the indeterminate decision-making information in the endurance quality level evaluation of young male basketball players. Therefore, in this paper, the 2-tuple linguistic neutrosophic numbers CLVA (2TLNN-CLVA) is built based on traditional close value (CLVA) method and applies it to evaluate the endurance quality level of young male basketball players. Finally, a numerical example for evaluating the endurance quality level of young male basketball players has been given and some decision comparisons are also conducted to further illustrate the advantages of the 2TLNN-CLVA method.

A novel two-phase group decision-making model for circular supplier selection under picture fuzzy environment

Circular supply chain management (CSCM), which incorporates circular thinking into supply chain management, promotes supply chain sustainability by offering a novel and compelling viewpoint. In the CSCM, supplier selection is crucial in establishing a competitive edge among businesses by decreasing environmental degradation and related supply chain expenses. This paper aims to propose a novel two-phase group decision-making approach, which combines the picture fuzzy Analytical Hierarchical Process (PF-AHP) and grey Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS-G) model to select railway material suppliers within the scope of circular economy perspective. In group decision-making, a picture fuzzy number-based approach aggregates individual decision makers'(DMs) opinions and provides a lower level of computing complexity and a higher level of performance. The PF-AHP has been used to produce the weights of the criteria, and the MARCOS-G technique has been used to rank the suppliers and choose the most appropriate one. The results and verification of the novel method are carried out throughout a comprehensive sensitivity analysis. For this purpose, 50 scenarios with changes in the weight values of criteria were developed. In the validation analysis, a comparison with other grey COPRAS, TOPSIS, ARAS and WASPAS methods were performed. Due to the ranking results obtained from Spearman's correlation analyses, the MARCOS-G is almost consistent and it can be seen that the A4 remains the top supplier in all 50 scenarios.

Gender inequality and self-publication are common among academic editors

Scientific editors shape the content of academic journals and set standards for their fields. Yet, the degree to which the gender makeup of editors reflects that of scientists, and the rate at which editors publish in their own journals, are not entirely understood. Here, we use algorithmic tools to infer the gender of 81,000 editors serving more than 1,000 journals and 15 disciplines over five decades. Only 26% of authors in our dataset are women, and we find even fewer women among editors (14%) and editors-in-chief (8%). Career length explains the gender gap among editors, but not editors-in-chief. Moreover, by analysing the publication records of 20,000 editors, we find that 12% publish at least one-fifth, and 6% publish at least one-third, of their papers in the journal they edit. Editors-in-chief tend to self-publish at a higher rate. Finally, compared with women, men have a higher increase in the rate at which they publish in a journal soon after becoming its editor.

Intelligent decision methodology for business English teaching quality evaluation based on GHM and PG operators with 2-tuple linguistic neutrosophic numbers

Business English teaching quality evaluation Business English is a new type of composite specialty, which is a discipline innovation made by China’s higher education to adapt to the new market demand and international standards since the reform and opening up. Over the past 20 years, it has cultivated a number of compound talents for the cause of China’s reform and opening up. However, the backwardness of business English theoretical research has greatly restricted the development of business English. At present, Business English has been officially approved as a new major for undergraduate enrollment by the Ministry of Education of the People’s Republic of China. Its subject nature, specialty structure, training objectives, and specialty compound characteristics need to be qualitatively studied theoretically. The business English teaching quality evaluation is viewed as the multiple attribute decision making (MADM) issue. In this paper, we connect the geometric Heronian mean (GHM) operator and power geometric (PG) with 2-tuple linguistic neutrosophic numbers (2TLNNs) to propose the generalized 2-tuple linguistic neutrosophic power geometric HM (G2TLNPGHM) operator. Then, the G2TLNGHM operator is applied to deal with the MADM problems under 2TLNNs. Finally, an example for business English teaching quality evaluation is used to show the proposed methods. Some comparative analysis and parameter influence analysis are fully given. The results show that the built algorithms method is useful for business English teaching quality evaluation.

A new approach for spherical fuzzy TOPSIS and spherical fuzzy VIKOR applied to the evaluation of hydrogen storage systems

This study proposes a new perspective of the TOPSIS and VIKOR methods using the recently introduced spherical fuzzy sets (SFSs) to handle the vagueness in subjective data and the uncertainties in objective data simultaneously. When implementing these techniques using SFSs, two main problems might arise that can lead to incorrect results. Firstly, the reference points might change with the utilized score function. Secondly, the distance between reference points might not be the largest, as known, among the available ratings. To overcome these deficiencies and increase the robustness of these two methods, they are implemented without utilizing any reference points to minimize the effect of defuzzification and without measuring the distance to eliminate the effect of distance formulas. In the proposed methods, when using an SFS to express the performance of an alternative for a criterion, this SFS per se can be viewed as a measure of proximity to the aspired level. On the other hand, the conjugate of the SFS can be viewed as a measure of proximity to the ineffectual level. Two practical applications are presented to demonstrate the proposed techniques. The first example handles a warehouse location selection problem. The second example evaluates hydrogen storage systems for automobiles with different types of data (crisp, linguistic variables, type 1 fuzzy sets). These data are transformed to SFSs to provide a more comprehensive analysis. A comparative study is conducted with earlier versions of TOPSIS and VIKOR to explicate the adequacy of the proposed methods and the consistency of the results.

A novel MADM-based efficient methodology with 2-tuple linguistic neutrosophic numbers and applications to physical education teaching quality evaluation

With the successful promotion of the new round of basic education curriculum reform, China’s physical education (PE) teaching ideology and PE teaching mode have undergone profound changes, and these changes urgently require schools to establish a PE teaching quality (PETQ) evaluation system that is compatible with them, and urgently resolve the contradiction between theory and practice. The evaluation of teaching quality is not only a value judgment of teachers’ teaching ability and teaching effect, but also a value judgment of students’ learning ability and learning achievement changes. Therefore, it is an important issue of higher education research to construct a university PE teaching quality evaluation system and actively promote the healthy development of university PE teaching evaluation. The PETQ evaluation is viewed as the multi-attribute decision-making (MADM). In order to take the full use of power average (PA) operator and Heronian mean (HM) operator, in this article, we combine the generalized Heronian mean (GHM) operator and PA with 2-tuple linguistic neutrosophic numbers (2TLNNs) to propose the generalized 2-tuple linguistic neutrosophic power weighted HM (G2TLNPWHM) operator. The G2TLNPWHM could relieve the influence of the awkward data through power weights and it could also consider the relationships between the attributes, and it can give more accurate ranking order then the existing methods. The new MADM method is built on G2TLNPWHM operators. Finally, an example for PETQ evaluation in is used to show the proposed methods.

Grey relational analysis method for typhoon vulnerability assessment of civil engineering structures based on the 2-tuple linguistic neutrosophic number

As one of the severe natural disasters, typhoon hazard brings tremendous tragedy to human beings. The foreland in the southeast of China is one of the most typhoon prone areas in the world. There are amount of damage of civil engineering structures induced by typhoon every year. Especially for the spacious villages, the low-rise buildings are vulnerable to typhoon so that many of them are destroyed regionally. The typhoon vulnerability assessment of civil engineering structures is a classical multiple attribute group decision making (MAGDM) issues. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is built based on the grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNSs) with incomplete weight information. For deriving the weight information of the attribute, an optimization model is built on the basis of the GRA, by which the attribute weights can be decided. Then, the optimal alternative is chosen through calculating largest relative relational degree from the 2-tuple linguistic neutrosophic number positive ideal solution (2TLNNPIS) which considers both the largest grey relational coefficient (GRC) from the 2TLNNPIS and the smallest GRC form 2-tuple linguistic neutrosophic number negative ideal solution (2TLNN NIS). Then, combine the traditional fuzzy GRA model with 2TLNNSs information, the 2TLNN-GRA method is established and the computing steps for MAGDM are built. Finally, a numerical example for typhoon vulnerability assessment of civil engineering structures has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

A Hybrid OPA and Fuzzy MARCOS Methodology for Sustainable Supplier Selection with Technology 4.0 Evaluation

The concern of sustainable supplier selection has been raised recently in organizations’ decision making to enhance their competitiveness. Many tools have been developed to support supplier evaluation, yet the factors of Industry 4.0 (I4.0) have been ignored despite their impact on sustainable performance. Hence, this paper aims to include the technology of I4.0 as the criteria to evaluate the competence of suppliers in sustainability. Multiple-criteria decision making (MCDM) has been used to build decision-making systems; thus, this study employed two advanced methods of MCDM, the ordinal priority approach (OPA) and measurement of alternatives and ranking according to compromise solution (MARCOS) in a fuzzy environment. To test the feasibility of the proposal, five manufacturers of Vietnam’s leather and footwear industry were hypothetically assigned. Firstly, the evaluation criteria were weighted by OPA. Then, the ranking of alternatives was determined by fuzzy MARCOS. The results show that “green image”, “green product innovation”, “cloud computing”, “service level”, and “blockchain” are the topmost significant criteria in evaluating sustainable practices in the supply chain from the I4.0 perspective. Furthermore, sensitivity and comparison analyses were carried out to verify the robustness of the methodology. The outcomes of this paper contribute a new model of decision making with respect to the involvement of sustainability and I4.0.

Method for 2-tuple linguistic neutrosophic number MAGDM and applications to physical education teaching quality evaluation in colleges and universities

The quality of physical education (PE) teaching in colleges and universities is the basis for the development of PE disciplines in colleges and universities, so currently thinking about how to effectively improve the quality of PE teaching in colleges and universities has become the first and foremost problem for many college and university PE departments to solve. In order to solve this problem, it is necessary to build a reasonable and scientific evaluation and monitoring system of PE teaching quality, because only by establishing an effective evaluation and monitoring system of teaching quality can we evaluate and supervise all the PE operation properly and scientifically, and then give feedback in the process of evaluation and supervision, such evaluation and monitoring system can greatly promote the continuous improvement of PE teaching quality in colleges and universities. This is also one of the most effective means to improve the quality of PE and achieve the goal of PE in colleges and universities. The PE teaching quality evaluation in Colleges and Universities is frequently viewed as the multiple attribute group decision making (MAGDM) issue. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is built based on the traditional grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNNSs). Then, a numerical example for PE teaching quality evaluation in Colleges and Universities has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

The Homogeneous MADM Methods: Is Trade-Off between Attributes Important?

Compensatory multiattribute decision-making (MADM) methods are founded on the trade-offs between attributes, allowing an alternative to compensate for its weakness in an attribute with its strength in another attribute. We call them heterogeneous MADM methods because they generally consider the unlimited trade-off between attributes. In other words, they even allow that very poor performance of an attribute to be compensated by the strong performance of another attribute. However, this may not be acceptable to decision makers (DMs). They may accept the limited trade-offs between attributes, making them more homogeneous. In these situations, MADM methods should be modified to consider the limited trade-offs between attributes. This modification comes with some conceptual and technical difficulties. This study presents some examples to show the concept of limited trade-offs clearly and presents a modified version of the simple additive weighting (SAW) method, H-SAW, considering the limited trade-offs between attributes. We also integrate H-SAW and fuzzy analytic hierarchy process (FAHP) methods to supplier selection and illustrate the real application of H-SAW method.

Performance evaluation of family business strategic transition based on the 2-tuple linguistic neutrosophic number multiple attribute group decision making

Since 2010, China’s traditional industry has entered a critical stage of development and enterprise reform and development is imminent. Product homogenization is serious in this market, so that the competition among enterprises is fierce. At the same time, international brands continue to enter the Chinese consumption market, which intensifies the competition and seriously squeezes the market share of Chinese local brands. However, the popularization and development of the Internet and the change of people’s consumption concept and level make the market put forward higher requirements for the development of business operation and many traditional family enterprises have embarked on the road of transformation. It is of great significance and value to clarify the influence of internal factors of family enterprises on strategic transformation. The performance evaluation of family business strategic transition is really a multiple attribute group decision making (MAGDM) problems. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is proposed along with on the traditional grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNNSs). Firstly, the 2TLNNSs is introduced. Then, combine the traditional fuzzy GRA model with 2TLNNSs information, the 2TLNN-GRA method is established and the computing steps for MAGDM are built. Finally, a numerical example for performance evaluation of family business strategic transition has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

An intelligent decision methodology for physical health evaluation of college students based on generalized 2-tuple linguistic neutrosophic geometric HM operators

Physical Health is an important part of health education and health promotion in my country, and the health literacy level of students majoring in physical education in colleges and universities is an important factor in the development of health education in primary and secondary schools, and also directly affects the implementation of school health education in the future. The physical health evaluation of College students is frequently viewed as the multiple attribute decision making (MADM) issue. In our article, we combine the geometric Heronian mean (GHM) operator, generalized weighted Heronian mean (GWHM) operator with 2-tuple linguistic neutrosophic numbers (2TLNNs) to propose the generalized 2-tuple linguistic neutrosophic geometric HM (G2TLNGHM) operator and generalized 2-tuple linguistic neutrosophic weighted geometric HM (G2TLNWGHM) operator. Meanwhile, some ideal properties of built operator are studied. Then, the G2TLNWGHM operator is applied to deal with the MADM problems under 2TLNNs. Finally, an example for Physical health evaluation of College students is used to show the proposed methods.

Incorporating management opinion in green supplier selection model using quality function deployment and interactive fuzzy programming

The need for environmental protection and involvement of ecological aspects in the business operations is forcing the organizations to re-examine their action plans and rebuild their supply chain activities. Many organizations are incorporating environmental rules and regulations in their everyday matters by focusing on green supplier selection. The proposed research paper develops a multi-objective interactive fuzzy programming model for the selection of suppliers. This model works on a business quartet of green appraisal score, cost, quality, and time. The model uses an environmental scale for different green parameters and all the suppliers are scored based on this scale. In this research model, Quality Function Deployment (QFD) methodology is integrated with the multi-objective interactive fuzzy programming. QFD technique is utilized to compute the weights of several green factors used for the selection of suppliers. The model uses a Fuzzy linguistic scale and a triangular membership function to link expert opinions along with their experience to solve the problem. Finally, the model is validated on a numerical case study of the textile industry for green supplier selection which achieves a 100% satisfaction for cost and time, 75% satisfaction for green appraisal score, and 93.95% for the quality. The proposed model assists the decision-makers in selecting green suppliers to improve the overall sustainability of their organizations.

Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry

The assessment of sustainable supplier is very significant for supply chain management (SCM). The procedure of sustainable supplier selection (SSS) is a complex process for decision experts (DEs) due to the association of diverse qualitative and quantitative attributes. As the uncertainty is usually ensued in the SSS and hesitant fuzzy set (HFS), an extension of fuzzy set (FS) has been demonstrated as one of the effective ways to treat the uncertain information in realistic problems. The objective of this paper is to propose an integrated hesitant fuzzy–data envelopment analysis (DEA)–full consistency method (FOCUM)–multi attribute border approximation area comparison (MABAC) method called HF-DEA-FUCOM-MABAC framework to assess the multi-attribute decision-making (MADM) problems on HFSs settings. In this line, first, the efficient alternatives are chosen using the DEA method. Second, The FUCOM is used to compute the subjective weight of attributes. Third, The HF-MABAC method is presented to prioritize the alternatives in an MADM problem. In the following, a case study of SSS problem for an Auto-making company is taken to show the practicality and utility of the presented approach. Next, we present a sensitivity investigation with different attribute weights set to observe the steadiness of the presented approach. Finally, we draw attention toward a comparison between presented approach with the extant HF-FOCUM-TOPSIS model to show its advantage and potency as well.

Decision-making framework for supplier selection using an integrated MCDM approach in a lean-agile-resilient-green environment: evidence from Indian automotive sector

Purpose

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

Design/methodology/approach

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

Findings

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

Practical implications

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

Originality/value

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

A Supplier Selection Model Using Alternative Ranking Process by Alternatives’ Stability Scores and the Grey Equilibrium Product

Supply chain management begins with supplier evaluation and selection. The supplier selection deals with various criteria with different contexts which makes it a complex multi-criteria decision-making (MCDM) method. In this paper, a novel MCDM method, called the alternative ranking process by alternatives’ stability scores (ARPASS), is proposed to solve supplier selection problems. ARPASS considers each alternative as a system that is constructed on integrated components. To perform properly, a system requires high integrity and stability. ARPASS utilizes the stability of alternatives as an effective element for ranking the alternatives. The ARPASS is developed in two forms, ARPASS and ARPASS*. The new method utilizes standard deviations and Shannon’s entropy to compute the alternatives’ stabilities. In this paper, in addition to the new MCDM methods, a new method called the grey equilibrium product (GEP) is introduced to convert grey linguistic variables into crisp values, using decision makers’ subjective perceptions and judgments. To highlight and validate the novel methods’ performance, they are applied to two sustainable supplier selection problems. For evaluation of the reliability of ARPASS and ARPASS*, their results were compared with the results of the popular MCDM methods. We compared the methods in terms of calculation time, simplicity, transparency, and information type.

A Risk Assessment Model for Cyber-Physical Water and Wastewater Systems: Towards Sustainable Development

Cyber-physical systems (CPS) and their Supervisory Control and Data Acquisition (SCADA) have attracted great interest for automatic management of industrial infrastructures, such as water and wastewater systems. A range of technologies can be employed for wastewater treatment CPS to manage risks and protect the infrastructures of water systems and their wastewater against cyberattacks. In this paper, we develop a novel risk assessment framework, named RAF-CPWS, which perfectly estimates the risks of water and wastewater technologies. To do this, a multi-criteria group decision-making (MCGDM) approach is designed by neutrosophic theory to assess the risks of wastewater treatment technologies (WWTTs). The proposed approach evaluates the best WWTTs, considering various economic, environmental, technological and cybersecurity, and social factors. A decision-making trial and evaluation laboratory (DEMATEL) is employed to evaluate the significance of the adopted factors in a real testbed setting. The proposed approach contributes to a comprehensive measure of WWTTs through several factors, revealing its high sustainability and security in assessing the risks of cyber-physical water and wastewater systems.

A facilitating framework for a developing country to adopt smart waste management in the context of circular economy

To achieve higher standards of sustainability, the waste management sector now requires the incorporation of circular economy (CE) principles. However, an easy transition toward the particular goal would require the use of smart waste technologies. To achieve the aforementioned goal, this study aims to provide a facilitating framework for the adoption of smart waste management in the context of CE for Pakistan. To help Pakistan transition toward the new paradigm, a total of 16 critical facilitators are evaluated based on five distinctive criteria using a novel fuzzy hybrid multi-criteria decision-making (MCDM) approach. The hybrid MCDM approach includes fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) for allocating weights to the determined criteria; whereas, the fuzzy VIšekriterijumsko kompromisno rangiranje (VIKOR) approach is used to rank the critical facilitators adopted from the secondary literature. The fuzzy approach in both cases is to deal with any kind of uncertainty during the data collection process. Based on the achieved results, the study suggests that before the application of smart waste technologies in the country, Pakistan should first focus on devising regulations that effectively address the mismanagement of waste produced in the country. Also, the industries in the country need to become more responsible and should adopt environmental management systems that foster waste minimization. Lastly, the country in the third phase should focus on the wide application of digitalization both in the streams of ICT and IoT, for collecting, sharing, and receiving waste data. The study further provides policy recommendations to the respective stakeholders that will help the country achieve zero-waste CE.

Selection of Suppliers for Speech Recognition Products in IT Projects by Combining Techniques with an Integrated Fuzzy MCDM

In today’s environment, as the complexity of actual events develops, products become increasingly complicated. As a result, companies should collaborate to integrate disparate technologies while developing a product or service. Additionally, collaborating with the right supplier helps a company increase the flexibility, competitiveness, and profitability of its goods or services. The goal of this study is to look into the factors that influence supplier selection for speech recognition. Twelve sub-criteria for quality, affordability, maintenance, and adaptability are used to evaluate prospective providers. Two separate hybrid methodologies for finding the best supplier of an information technology product are presented. intuitionistic Fuzzy Due to the uncertainty of the data, VIKOR operates as the decision-making matrix and solves the issue by determining the ideal alternative for group utility using VIKOR. The second technique, Q-ROF TOPSIS, selects suppliers by utilizing q-rung orthopair fuzzy sets, which provides decision makers with greater expression flexibility than the majority of uncertainty-related strategies. To demonstrate the effectiveness of the recommended measures, a case study is conducted. The outcomes of various strategies are compared, as well as the associated advantages.

A group consensus decision making based sustainable supplier selection method by combing DEMATEL and VIKOR

Sustainable supplier selection (SSS) plays an increasingly critical role in the stability and development of the organization with increasing environmental awareness. This article proposes a linguistic multiple attribute group decision-making method to select the appropriate sustainable supplier by combing Decision Making and Trial Evaluation Laboratory(DEMATEL) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). To do that, a distribution linguistic based DEMATEL technique is developed to deal with the complexity in criteria of SSS. To eliminate the inconsistency among multiple decision-makers providing the preference information of evaluation criteria, a minimum adjusting cost feedback mechanism is utilized to reach group consensus. Therefore, the proposed weights obtaining method can not only deal with the subjectivity of evaluation criterion but also satisfy group decision-makers with different profits and backgrounds. Then, based on the evaluation matrices of supplier performance, it calculates the ranking of alternative suppliers by the VIKOR method. Hence, it can deal with the ambiguity of decision makers’ evaluation and provide the best solution for decision-makers, as a consequence, it makes the final evaluation result more feasible and operable. Finally, the effectiveness and efficiency of this method are verified based on the actual situation of ABC Company. This study proposed a linguistic multiple attribute group decision-making method to select the appropriate sustainable supplier by combing Decision Making and Trial Evaluation Laboratory(DEMATEL) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). What’s more, the proposed method considered the group consensus reaching processes.

Fermatean fuzzy set extensions of SAW, ARAS, and VIKOR with applications in COVID-19 testing laboratory selection problem

The multiple attribute decision-making models are empowered with the support of fuzzy sets such as intuitionistic, q-rung orthopair, Pythagorean, and picture fuzzy sets, and also neutrosophic sets, etc. These concepts generate varying representation opportunities for the decision-maker's preferences and expertise. Pythagorean and Fermatean fuzzy sets are special cases of q-rung orthopair fuzzy set when q = 2 and q = 3, respectively. From a geometric perspective, the latter provides a broader representation domain than the former does. In this study, the emerging concept of Fermatean fuzzy set is studied in detail and three well-known multi-attribute evaluation methods, namely SAW, ARAS, and VIKOR are extended under Fermatean fuzzy environment. In this manner, the decision-makers will have more freedom in specifying their preferences, thoughts, and expertise, and the abovementioned decision approaches will be able to handle this new type of data. The applicability of the propositions is shown in determining the best Covid-19 testing laboratory which is an important topic of the ongoing global health crisis. To validate the proposed methods, a benchmark analysis covering the results of the existing Fermatean fuzzy set-based decision methods, namely TOPSIS, WPM, and Yager aggregation operators is presented.

An integrated approach for a sustainable supplier selection based on Industry 4.0 concept

The recent advances in sustainable supply chain management are integrated with Industry 4.0 concepts. This study develops a new integrated model to consider the sustainability and Industry 4.0 criteria for the supplier selection management. The proposed approach consists of the fuzzy best worst method (FBWM) and the two-stage fuzzy inference system (FIS) to assess the selection of suppliers. Firstly, this study determines a comprehensive list of Industry 4.0 and sustainability criteria along with their definitions. Then, the importance weight of each criterion is computed by the FBWM. Subsequently, a two-stage FIS is devoted to nominate the suppliers' performance with regard to the sustainability and Industry 4.0 criteria. To show the applicability of our integrated model, a case study for a textile company in Iran is provided. Finally, some sensitivity analyses are done to assess the efficiency of the proposed integrated approach. One finding is to establish a decision-making framework to evaluate suppliers separately, rather than relatively in a fuzzy environment using Industry 4.0 and sustainability criteria.

Multi-criteria decision-making toward supplier selection: exploration of PROMETHEE II method

Purpose

Supplier Selection (SS) is one of the vital decisions frequently executed by numerous industries. In recent times, the number of suppliers has increased enormously depending on a wide range of criteria. A selection of suppliers is a sensitive process that may impact various supply chain activities. The purpose of this research is to explore an underutilized technique called PROMETHEE II method for SS.

Design/methodology/approach

Various tools and techniques are available under multi-criteria decision-making tools, which sometimes creates confusion in researchers' minds regarding reliability. PROMETHEE II was the most prominent method for ranking all available alternatives that ultimately avoid decision-making errors. To execute this equal and unequal weights approach has been used with three case studies.

Findings

In this research, three case studies have been used and soved with the help of the PROMETHEE II approach. The study also provides fundamental insights into the supplier's ranking on different criteria using sensitivity analysis. Further, criteria were divided as per benefits and non-beneficial to get a robust result. The pros and cons of PROMETHEE II approaches are also highlighted compared to other MCDM tools in this study.

Originality/value

Most of the SS research uses either AHP or TOPSIS as per existing literature. There are very few attempts highlighted in the literature that use PROMETHEE II for the SS problem with sensitivity analysis. The proposed method is probable to motivate decision-makers to consider using a more sophisticated method like PROMETHEE II in supplier evaluation processes. This study opens a new direction for the ranking of suppliers in the field of the supply chain. The study also bears significant practical as well as managerial implications.

Prioritization of water erosion-prone sub-watersheds using three ensemble methods in Qareaghaj catchment, southern Iran

Water-induced erosion poses severe harm to the sustainable development of land and water resources that is essential for attaining agricultural sustainability in Qareaghaj catchment of Fars Province, Iran. This study evaluates the topo-hydrological, morphometric, climatic, and environmental characteristics of Qareaghaj catchment for prioritizing the sub-watersheds that are susceptible to erosion caused by water. We tested and compared a novel ensemble multi-criteria decision-making (MCDM) model, namely the weighted aggregated sum product assessment-analytical hierarchy process (WASPAS-AHP) with prevailing benchmark ensemble MCDM models including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR)-AHP and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-AHP for ranking sub-watersheds and determining the most significant parameter that influences water erosion (WE) in Qareaghaj catchment. The outcome of weights using pairwise comparison matrix (PCM) of AHP reveals that normalized difference vegetation index (NDVI), mean annual rainfall (MAR), slope degree (SD), and slope length and steepness factor (LS) governs the WE in Qareaghaj catchment. The prioritization rankings of sub-watersheds obtained using the VIKOR-AHP, TOPSIS-AHP, and WASPAS-AHP models demonstrate that SW31, SW63, and SW94 had the highest priority rank with a score of 0.047, 0.69, and 0.477, respectively. The comparison of rankings from the models using Spearman's correlation coefficient tests (SCCT) and Kendall's tau correlation coefficient tests (KTCCT) revealed that WASPAS-AHP had a higher correlation with TOPSIS-AHP and VIKOR-AHP ensemble models. The outcome of MCDM models was validated based on the erosion potential method (EPM), which displayed that the VIKOR-AHP model was better for mapping the erosion susceptibility than TOPSIS-AHP and WASPAS-AHP models. Thus, the erosion susceptibility mapping based on the VIKOR-AHP ensemble model can be considered for developing new strategies and land use policies in order to control WE in Qareaghaj catchment.

A Comprehensive Framework for Evaluating Sustainable Green Building Indicators under an Uncertain Environment

The development of sustainable green buildings (GBs) is a major contribution to the preservation of the environment. Sustainable thinking in GB construction is not a supplementary element, but rather necessary to achieve the building’s functional, economic, and environmental efficiency in order to preserve resources and meet current and future needs. In particular, developing countries can apply the idea of sustainability in GBs by following international policies and standards, combined with their local characteristics, to construct GBs that are aligned with the environment and are in line with the available local capabilities and resources. The paper focuses on the dimensions and indicators of sustainable design for GBs in developing countries to achieve the positive dimensions of building sustainability, such as preserving energy and natural resources, water management, adaptation to the surrounding environment, and respecting the needs of its users. We assess and prioritize the dimensions and indicators of GBs through the use of a multi-criteria decision-making (MCDM) method under a neutrosophic environment. Initially, the Delphi method is employed to capture preference and to determine the dimensions and their indicators in addition to provide preference among sub-indicators. The relative importance of the selected dimensions and indicators is assessed through the analytical hierarchy method (AHP) method. The results indicate that the water efficiency dimension is the most significant, with a weight of 0.330, while the energy efficiency dimension is the least significant for GBs in developing countries, with a weight of 0.100. The paper concludes with a set of administrative implications for applying sustainable development strategies in GBs.

Application of Interval Fuzzy Logic in Selecting a Sustainable Supplier on the Example of Agricultural Production

The selection of sustainable suppliers (SSS) is the first step in applying a sustainable supply chain and sustainable production. Therefore, it is necessary to select the supplier that best meets the set sustainability criteria. However, the selection of suppliers cannot be done by applying symmetric information, because the company does not have complete information, so asymmetric information should be used when selecting suppliers. Since the SSS applies three main sustainability criteria, environmental, social, and economic criteria, this decision-making problem is solved by applying multi-criteria decision-making (MCDM). In order to solve the SSS for the needs of agricultural production, interval fuzzy logic was applied in this research, and six suppliers with whom agricultural pharmacies in Semberija work were taken into consideration. The application of interval fuzzy logic was performed using the methods PIPRECIA (Pivot pairwise relative criteria importance assessment) and MABAC (Multi-Attributive Border Approximation Area Comparison). Using the PIPRECIA method, the weights of criteria and sub-criteria were determined. Results of this method showed that the most significant are economic criteria, followed by the social criteria. The ecological criteria are the least important. The supplier ranking was performed using the MABAC method. The results showed that supplier A4 best meets the sustainability criteria, while supplier A6 is the worst. These results were confirmed using other MCDM methods, followed by the sensitivity analysis. According to the attained results, agricultural producers from Semberija should buy the most products from suppliers A4, in order to better apply sustainability in production. This paper showed how to decision make when there is asymmetric information about suppliers.

Supplier selection and evaluation in e-commerce enterprises: a data envelopment analysis approach

Purpose

E-commerce refers to the facilitation and delivery of goods and services to the customers employing an electronic arrangement. For an e-commerce firm, the customer service level provided by its suppliers can make or break the firm. The purpose of this research is to help e-commerce enterprises in addressing the vast challenge of complex supplier selection and evaluation process that must be performed vigilantly.

Design/methodology/approach

The present study utilizes a three-pronged approach that integrates supplier management practices with the operational business practices of an e-commerce enterprise. In the first step, key performance factors for e-commerce capable suppliers are identified through an expert opinion and existing supplier management literature. Further, Data Envelopment Analysis (DEA) is employed to obtain the efficiency score for each supplier that enables their ranking on various performance parameters. Lastly, the suppliers are classified into different categories based on their performance and efficiency.

Findings

Under the proposed classification scheme, top five suppliers, i.e. supplier 1, 7, 9, 11 and 17 are categorized as HE (High Performance and Efficient). It is suggested that e-commerce enterprises must build long-term relationship with the identified top performing suppliers. The study also provides real insights into supplier's performance on a number of objective criteria. Further, the present study enhances the overall performance and productivity of an e-commerce firm by achieving input cost minimization and output quality maximization, simultaneously.

Research limitations/implications

The results are valid for e-commerce enterprises in general. However, the present DEA model can be further evolved when applied in case of any particular e-commerce enterprise depending upon the internal capabilities of that firm. The nuances related to a firm's own supply capability development can be further explored by practitioners and researchers.

Practical implications

The proposed approach is expected to motivate decision-makers to consider using more sophisticated approached like DEA in supplier evaluation processes. Also, as a benchmarking technique, the proposed supplier classification approach is expected to be highly useful for practitioners in real-life settings.

Originality/value

The novel contribution of this study includes the supplier evaluation, ranking and classification for e-commerce enterprises based on the real-life data. The insights would help the practitioners to formulate novel strategies for appropriately investing in supplier relationships.

Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era

In recent years, municipal authorities especially in the developing nations are battling to select the best health care waste (HCW) disposal technique for the effective treatment of the medical wastes during and post COVID-19 era. As evaluation of various disposal alternatives of HCW and selection of the best technique requires considering various tangible and intangible criteria, this can be framed as multi-criteria decision-making (MCDM) problem. In this paper, we propose an assessment framework for the selection of the best HCW disposal technique based on socio-technical and triple bottom line perspectives. We have identified 10 criteria on which the best HCW disposal techniques to be selected based on extant literature review. Next, we use Fuzzy VIKOR method to evaluate 9 HCW disposal alternatives. The effectiveness of the proposed framework has been demonstrated with a real-life case study in Indian context. To check the robustness of the proposed methodology, we have compared the results obtained with Fuzzy TOPSIS (Technique of Order Preference Similarity to the Ideal Solution). The results help the municipal authorities to establish a methodical approach to choose the best HCW disposal techniques. Our findings indicate that incineration is the best waste disposal technique among the available alternatives. Even if the dataset indicates 'incineration' is the best method, we must not forget about the environmental concerns arising from this method. In COVID time, incineration may be the best method as indicated by the data analysis, but "COVID" should not be an excuse for causing "Environmental Pollution".

A SCIENTOMETRIC ANALYSIS OF THE EMERGING TOPICS IN GENERAL COMPUTER SCIENCE

Citations have been an acceptable journal performance metric used by many indexing databases for inclusion and discontinuation of journals in their list. Therefore, editorial teams must maintain their journal performance by increasing article citations for continuous content indexing in the databases. With this aim in hand, this study intended to assist the editorial team of the Journal of Information and Communication Technology (JICT) in increasing the performance and impact of the journal. Currently, the journal has suffered from low citation count, which may jeopardise its sustainability. Past studies in library science suggested a positive correlation between keywords and citations. Therefore, keyword and topic analyses could be a solution to address the issue of journal citation. This article described a scientometric analysis of emerging topics in general computer science, the Scopus subject area for which JICT is indexed. This study extracted bibliometric data of the top 10% journals in the subject area to create a dataset of 5,546 articles. The results of the study suggested ten emerging topics in computer science that can be considered by the journal editorial team in selecting articles and a list of highly used keywords in articles published in 2019 and 2020 (as of 15 April 2020). The outcome of this study might be considered by the JICT editorial team and other journals in general computer science that suffer from a similar issue.

A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics

The managerial and environmental studies conducted in the energy research area reflect its substantial importance, particularly when optimizing and modifying consumption patterns, transitioning to renewable sources away from fossil ones, and designing plans and systems. The aim of this study is to provide a systematic review of the literature allowing us to identify which research subjects have been prioritized in the fields of energy and sustainability in recent years, determine the potential reasons explaining these trends, and categorize the techniques applied to analyze the uncertainty faced by decision-makers. We review articles published in highly ranked journals through the period 2003–2020 and apply text analytics to cluster their main characteristics; that is, we rely on pre-processing and text mining techniques. We analyze the title, abstract, keywords, and research methodology of the articles through clustering and topic modeling and illustrate what methods and fields constitute the main focus of researchers. We demonstrate the substantial importance of fuzzy-related methods and decision-making techniques such as the Analytical Hierarchy Process and Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS). We also show that subjects such as renewable energy, energy planning, sustainable energy, energy policy, and wind energy have gained relevance among researchers in recent years.

A Multi-Criteria Decision-Making Method Based on Single-Valued Neutrosophic Partitioned Heronian Mean Operator

A multi-criteria decision-making (MCDM) method with single-valued neutrosophic information is developed based on the Partitioned Heronian Mean (PHM) operator and the Shapley fuzzy measure, which recognizes correlation among the selection criteria. Motivated by the PHM operator and Shapley fuzzy measure, two new aggregation operators, namely the single-valued neutrosophic PHM operator and the weighted single-valued neutrosophic Shapley PHM operator, are defined, and their corresponding properties and some special cases are investigated. An MCDM model is applied to solve the single-valued neutrosophic problem where weight information is not completely known. An example is provided to validate the proposed method.

An integrated decision-making model for supplier evaluation in public healthcare system: the case study of a Spanish hospital

Purpose

In this study, an integrated decision-making model consisting of decision-making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and a modified version of evaluation based on distance from average solution (EDAS) methods is proposed for supplier selection problem in a public procurement system considering sustainable development goals.

Design/methodology/approach

DEMATEL and BWM methods are used to determine weights of the criteria that are defined for the supplier selection problem. Weight aggregation method is applied to combine the weights obtained from these two methods. A modified version of EDAS method is then used in order to rank the alternative suppliers.

Findings

The proposed decision-making model is investigated for a supplier selection problem for a hospital in Spain. The validity of the results is checked using comparison with other decision-making methods and several performance analysis tests.

Practical implications

The proposed multi-criteria decision-making (MCDM) model contributes to the healthcare supply chain management (SCM) and aims to lead the policy makers in selecting the best supplier.

Originality/value

There is no such study that combines DEMATEL and BWM together for weight generation. The application of the modified EDAS method is also new. In real time situations, the decision experts may confront to the difficulty of using BWM while identifying the best and the worst criteria choices. The idea of using DEMATEL is to aid the experts to make them enable in distinguishing between the best/worst criteria and handle BWM easily.

Sustainable circular supplier selection: A novel hybrid approach

Circular supplier selection is the process of selecting suppliers in a closed-loop supply chain. Sustainable circular supplier selection addresses the social and environmental concerns in circular supplier selection problems. In this paper, for the first time, we combine the fuzzy best-worst method and the interval VIKOR technique to evaluate and prioritize sustainable suppliers in circular supply chains. The evaluation criteria are classified into three categories of economic, social, and circular factors extracted based on the domain expert's opinions. The fuzzy best-worst method is used to weigh the criteria, and the interval VIKOR technique is applied to evaluate the suppliers in the presence of uncertainty. This study contributes to the sustainable development goals (SDG's) of providing Decent Work and Economic Growth (SDG 8) and Responsible Consumption and Production (SDG 12). The proposed method is then used to evaluate six suppliers in the wire-and-cable industry in Iran. The results obtained from the implementation of the proposed approach and its sensitivity analysis indicate the applicability and efficiency of the proposed approach.

A hybrid approach for selecting sustainable suppliers and determining order allocation based on interval type-2 fuzzy sets

Purpose

This study aims to create a model for defining the best supplier for a company and allocating order that considers sustainability criteria beyond the traditional selection criteria.

Design/methodology/approach

In this paper, sustainable supplier Selection and order allocation (SSS and OA) problem is managed based on a multiobjective linear programming (MOLP) model that incorporates sustainability dimensions. First, an interval type-2 fuzzy analytic hierarchy process (FAHP) method is applied for the main criteria and subcriteria to determine the weight of the selected criteria. Then, these values are used to convert the proposed MOLP model into a single-objective model.

Findings

The economic criterion (0.438) was the most important criterion for SSS in the agricultural machinery sector, followed by the social criterion (0.333) and the environmental criterion (0.229).

Practical implications

The results show that the proposed framework can be utilized by the agricultural machinery industry for SSS and OA.

Originality/value

The proposed framework provides to develop an integrated model by interval type-2 fuzzy sets for SSS and OA, taking into account the relationships between qualitative and quantitative evaluation criteria with different priorities. The validity of the developed model is confirmed by a case study of the agricultural machinery industry in Turkey.

A Combination of DEMATEL and BWM-Based ANP Methods for Exploring the Green Building Rating System in Taiwan

Green buildings are a crucial environmentally friendly component for sustainable human habitation and for the preservation of a healthy ecosystem. This study proposes a novel hybrid model to explore the influential relationship of various indicators and their importance for a green building evaluation system. First, a green building index system is established based on a review of recent literature on green building evaluation systems. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is utilized to determine the influential relationship among the criteria. Finally, a novel best worst method (BWM)-based analytic network process (ANP) model is applied to determine the influential weight of the criteria. The result indicated that the top five ranked criteria are all classified within the two dimensions of waste reduction and energy saving. An empirical case study of an example in Taiwan is carried out to demonstrate the effectiveness of the proposed model. Management implications are also provided.

Analysis of Priority Scale for Watershed Reforestation Using Trapezoidal Fuzzy VIKOR Method: A Case Study in Semarang, Central Java Indonesia

Recently, resolving a problem based on multi-criteria decision-making systems has become an attractive method. One of recent techniques is trapezoidal fuzzy VIKOR method which was used for selecting the best option among criteria. This research is aimed to utilize the VIKOR method in prioritization of watershed reforestation in Semarang City, Indonesia. Several criteria have been set for the prioritization of reforestation areas to select watersheds as reforestation targets. In this case, the six criteria and six alternatives were used in order to determine the best priority of reforestation. The result showed that VIKOR method was successfully applied to determine the best option and Kali Garang watershed was the top priority as it has the highest rank and it meets reforestation criteria compared with other watersheds criteria.

A Hybrid Approach of Interval Neutrosophic Vague Sets and DEMATEL with New Linguistic Variable

Nowadays, real world problems are complicated because they deal with uncertainty and incomplete information. Obviously, such problems cannot be solved by a single technique because of the multiple perspectives that may arise. Currently, the combination of DEMATEL and the neutrosophic environment are still new and not fully explored. Previous studies of DEMATEL and this neutrosophic environment have been carried out based on numerical values to represent a new scale. Until now, little importance has been placed on the development of a linguistic variable for DEMATEL. It is important to develop a new linguistic variable to represent opinions based on human experience. Therefore, to fill this gap, the concept of Interval Neutrosophic Vague Sets (INVS) has been extended to the linguistic variable that can be used in the decision-making process. The INVS is useful tool to deal with uncertainty and incomplete information. Additionally, the advantages of the linguistic variable of INVS allows the greater range of value for membership functions. This study proposes a new framework for INVS and DEMATEL. In addition, a case study on the quality of hospital service has been evaluated to demonstrate the proposed approach. Finally, a comparative analysis to check the feasibility of the proposed method is presented. It demonstrates that different methods produce different relations and levels of importance. This is due to the inclusion of the INVS linguistic variable.

A Bipolar Neutrosophic Multi Criteria Decision Making Framework for Professional Selection

Professional selection is a significant task for any organization that aims to select the most appropriate candidates to fill well-defined vacancies up. In the recruitment process, various individual characteristics are involved, such as leadership, analytical skills, independent thinking, innovation, stamina and personality, ambiguity and imprecision. It outlines staff contribution and therefore plays a significant part in human resources administration. Additionally, in the era of the Internet of Things and Big Data (IoTBD), professional selection would face several challenges not only to the safe selection and security but also to make wise and prompt decisions especially in the large-scale candidates and criteria from the Cloud. However, the process of professional selection is often led by experience, which contains vague, ambiguous and uncertain decisions. It is therefore necessary to design an efficient decision-making algorithm, which could be further escalated to IoTBD. In this paper, we propose a new hybrid neutrosophic multi criteria decision making (MCDM) framework that employs a collection of neutrosophic analytical network process (ANP), and order preference by similarity to ideal solution (TOPSIS) under bipolar neutrosophic numbers. The MCDM framework is applied for chief executive officer (CEO) selection in a case study at the Elsewedy Electric Group, Egypt. The proposed approach allows us to assemble individual evaluations of the decision makers and therefore perform accurate personnel selection. The outcomes of the proposed method are compared with those of the related works such as weight sum model (WSM), weight product model (WPM), analytical hierarchy process (AHP), multi-objective optimization based on simple ratio analysis (MOORA) and ANP methods to prove and validate the results.