Weights Of Sub-criteria Research Articles

Critical success factors for the adoption of AVs in sustainable urban transportation

Before integrating Autonomous Vehicles (AVs) into transportation systems, it's important to evaluate various aspects to facilitate their adoption. Numerous factors are likely to be crucial in this process. This research investigates the critical success factors influencing the adoption of AVs in sustainable urban transportation through a hybrid fuzzy Multiple-Attribute Decision-Making (MADM) approach. The primary aim is to identify key criteria and sub-criteria perceived by transport experts, shedding light on the complex dynamics of AV adoption. Methodologically, a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) is employed to unveil cause-and-effect relationships among the main criteria, determining their respective weights. Subsequently, fuzzy Analytic Network Process (ANP) is applied to calculate the weights of criteria and sub-criteria based on the fuzzy DEMATEL results. The study considers seven major factor dimensions: economic, technical, operational, environmental, safety and risk, social and regulatory, and user acceptance. Key findings underscore user acceptance, financial costs, and environmental impact as the most pivotal criteria, emphasising their significance in the eyes of transportation experts. Contrarily, technological and operational criteria hold the lowest weight in the considered criteria for AV adoption in transportation networks. This research provides valuable insights into critical barriers and opportunities in the adoption of AVs, contributing to the advancement of sustainable urban transportation.

Supply Chain Management Strategies Approach for the UK Textile Industry

This study focuses on the specific types of supply chain strategies throughout the UK textile industry as extant literature has either emphasised on the fashion apparel industry or on sub-industry of fast fashion. A combination of normalised local priority weights of criteria and sub-criteria is used with respect to successive hierarchical levels which modelled in an Analytical Hierarchy Process (AHP) at different levels. This helped in obtaining global composite priority weights for all the sub-criteria at third level of AHP model. The changes in different factors are observed with respect to digitalisation in sensitivity analysis at different levels of variations in the weight for which marginal changes are noted in the following variables: development of key suppliers, supplier capability auditing, and long-term orientation with suppliers. Supply base optimisation and purchasing integration showed changes at all levels of variations. Purchasing and production strategy was crucial as primary criteria for accomplishing the goal of the supply chain management future. There was substantial evidence from the three companies participating in the research that purchasing and production strategies play equally significant roles in successful digitalisation, identification, and delivery.

A novel MCDM approach for design concept evaluation based on interval-valued picture fuzzy sets.

The assessment of design concepts presents an efficient and effective strategy for businesses to strengthen their competitive edge and introduce market-worthy products. The widely accepted viewpoint acknowledges this as a intricate multi-criteria decision-making (MCDM) approach, involving a multitude of evaluative criteria and a significant amount of data that is frequently ambiguously defined and subjectively influenced. In order to tackle the problems of uncertainty and fuzziness in design concept evaluation, our research creatively combines interval-valued picture fuzzy set (IVPFS) with an MCDM process of design concept evaluation. Firstly, this study draws on the existing relevant literature and the experience of decision makers to identify some important criteria and corresponding sub-criteria and form a scientific evaluation indicator system. We then introduce the essential operational concepts of interval-valued picture fuzzy numbers (IVPFNs) and the interval-valued picture fuzzy ordered weighted interactive averaging (IVPFOWIA) operator. Thirdly, an entropy weighting method based on IVPFS is proposed in this research to calculate the weights of criteria and sub-criteria, and based on this, an integrated IVPF decision matrix is further constructed based on the presented IVPFOWIA operator. Finally, the best design concept alternative is selected by applying the extended TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach with IVPFS. The IVPFS combined with improved MCDM method have been proven to be superior in complex and uncertain decision-making situations through experiments and comparative assessments. The information ambiguity in the evaluation of design concept is well characterized by our augmentation based on IVPFS.

Walking as soft mobility: A multi-criteria GIS-based approach for prioritizing tourist routes

Walking, as the main mode of soft mobility, has become an integral aspect of urban tourism. The development of pedestrian tourist routes plays a crucial role in enhancing the positive walking experience in urban tourist destinations. This research employs a hybrid multi-criteria decision-making (MCDM) with GIS to rank street segments, establishing walking-oriented tourist paths in Shiraz's historic district, Iran. The initial steps involve identifying pivotal criteria through literature reviews and expert surveys. The Analytical Hierarchy Process (AHP) establishes criteria and sub-criteria weights using input from 30 experts. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) then prioritizes street segments based on sub-criteria such as traffic safety, image ability and heritage assets, security, land use and activity, accessibility, comfort and convenience, and human scale. Furthermore, a Space Syntax analysis (SSA) is conducted to evaluate the morphology of the street network in the study area and identify streets with potential for pedestrian movement. By integrating these analyses, a prime corridor for a pedestrian tourist route is identified. This study offers planners and policymakers a valuable tool for pre-investment decision-making, aiding the promotion of walkability in tourist-centric areas.

A novel resilient and sustainable supplier selection model based on D-AHP and DEMATEL methods

The natural disasters that cause a sudden violent change in the earth and the disruptions made by humans disrupt operations in the supply chain, causing negative influences such as lost productivity, revenue, competitive advantage, and profitability for the company. Therefore, suppliers need to be capable of being resilient to any disruption and providing sustainable supply. Supplier selection is a multi criteria decision making (MCDM) problem that allows suppliers to evaluate different and often conflicting qualitative and quantitative criteria. Both resilient and sustainable supplier selection problems contain many qualitative criteria. Experts make subjective judgments based on qualitative criteria in the decision-making process. The D number is a method used to find an efficient and feasible solution to uncertain information. In this paper, the DAHP method, which integrates the traditional Analytic Hierarchy Process (AHP) method and the D numbers, is used for the resilient and sustainable supplier selection problem. The Decision Making Trial and Evaluation Laboratory (DEMATEL) method is integrated into DAHP to determine criteria and subcriteria weights. The proposed integrated DAHP-DEMATEL model is implemented in an automobile manufacturing company to demonstrate the effectiveness of the method. The Triantaphyllou method is applied to perform sensitivity analysis. The traditional AHP-DEMATEL hybrid method was applied to the same problem, and sensitivity analysis was performed. The sensitivity analysis results of the hybrid method were compared with the results of the applied AHP-DEMATEL method. It can be said that the proposed model is less affected by subjective evaluations and is a robust method.

Standard deviation and rank sum-based MARCOS model under intuitionistic fuzzy information for hospital site selection

PurposeThis paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).Design/methodology/approachThe IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.FindingsThe authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h2) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.Originality/valueThis study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.

A Markovian-based fuzzy decision-making approach for the customer-based sustainable-resilient supplier selection problem.

The supplier selection problem is one of the most important issues in supply chain management. So, many papers have investigated the mentioned problem. However, the related literature shows that researchers had less attention to the sustainability and resilience aspects based on the customer preferences in supplier selection problem. To cover this gap, this research tries to investigate the customer-based sustainable-resilient supplier selection problem. In this way, a Markovian-based fuzzy decision-making method is proposed. At the outset, the customer preferences are evaluated using a combination of the quality function deployment and the Markov transition matrix. Then, by combining the transition matrix and the fuzzy best-worst method, the weights of the indicators are calculated. Finally, the decision matrix is formed and the performance of suppliers is measured based on the multiplication of the decision matrix and vector of sub-criteria weights. Regarding the recent pandemic disruption (COVID-19), the importance of online marketplaces is highlighted more than the past. Hence, this study considers an online marketplace as a case study. Results show that in a pandemic situation, the preferences of customers when they cannot go shopping normally will change after a while. Based on the Markov steady state, these changes are from the priority of price, availability, and performance in initial time to serviceability, reliability, and availability in the future. Finally, based on the FBWM results, from the customer point of view, the top five sub-criteria for sustainable-resilient supplier selection include cost, quality, delivery, responsiveness, and service. So, based on these priorities, the case study potential suppliers are prioritized, respectively.

A Hybrid Evaluation Model for e-Learning Platforms Based on Extended TOE Framework

E-learning platforms (ELPs) are revolutionizing the higher education system, as they offer tremendous potential to fulfill instructional plans, safeguard students’ learning rights, and improve teaching quality. Higher education institutions (HEIs) have to consider the selection of ELPs from an organizational perspective, which involves multiple stakeholders like university administrators, students, and educators. Therefore, one can take the ELP selection as a complex multi-criteria decision-making (MCDM) problem. This research proposes a new hybrid MCDM approach on the basis of the fuzzy analytic hierarchy process (FAHP) and the evaluation based on distance from the average solution (EDAS) method to select the best ELPs. First, from the organizational perspective, we extend the technology-organization-environment (TOE) framework by adding an auxiliary resource (AR) dimension and define and prioritize 4 criteria and 14 criteria for evaluating and selecting ELPs. Second, the study uses the fuzzy set theory to process the language evaluation of experts, the FAHP method to determine criteria and sub-criteria weights, and EDAS to rank the alternatives. Finally, based on the importance-performance analysis (IPA) method, we identify the most appropriate strategic options for enhancing competitiveness. Three practical cases of China’s ELP evaluation validate the proposed model’s applicability and superiority by comparing to the two other classic evaluation models. In addition, through analysis, we obtain some encouraging results that provide some references for universities to formulate ELP selection policies and offer suggestions for platform producers to further optimize the design.

GIS Based Multi-Criteria Decision Analysis for Locating Bank Branches

In banking industry, optimum location of the bank branch plays an important role in ensuring the success of the bank. It is one of the most important decision making processes. This issue is highly important because of the vibrant competition, limited budgets and high customer expectations .This study’s objective is to provide a hybrid model for selecting optimal site location using available data sources and well accepted decision models, specifically Analytic Network Process (ANP) and Geographic Information System (GIS).The process identified the most commonly used criteria for bank branch location consideration through literature review yielding demographics, competition, transportation, access to public facilities. Criteria and sub-criteria weights were quantified through pair-wise comparison using expert judges, via ANP. The database created for the study area (Khartoum Locality) includes data about demographics, competition, transportation, access to public facilities available in the area. With the help of Esri’s ArcGIS software through using the weighted overlay analysis tool we have identified suitable sites of new bank branches .The results showed five optimal locations for new bank branch in Khartoum locality; location near Madani St, location close to Bashir Elnefedi St, location at Firdous East Square 8, and two other sites in Khartoum West (Shajra Avenue). For the conclusion, these results show the efficiency and applicability of the proposed integrated method.

A Hybrid Fuzzy Multi-Criteria Decision-Making Model for Evaluating the Influence of Industry 4.0 Technologies on Manufacturing Strategies

Manufacturing is transitioning from traditional and mass manufacturing to mass personalization, fast, and intelligent production. Through full automation in various fields and data sharing, Industry 4.0 (I4.0) contributes to the digitalization of manufacturing by enhancing industrial flexibility and product customization. I4.0 is being utilized as a strategy for advanced manufacturing to counter global competitiveness. A company’s manufacturing strategy outputs (MSOs) are critical to its ability to move forward and remain competitive. Despite their importance, I4.0 technologies have received less attention in the literature, and it is unclear how they influence MSOs. Thus, this study aims to build a powerful hybrid MCDM method for ranking the influence of I4.0 technologies on MSOs by adopting a combination of AHP and fuzzy TOPSIS. The application of fuzzy set theory has addressed the ambiguity in comparing various I4.0 technologies. The AHP was used to calculate the weights of criteria and sub-criteria, and the fuzzy-TOPSIS method was utilized to rank the I4.0 technologies. The results revealed that the cost criterion is the most critical factor when implementing I4.0 technologies. In contrast, additive manufacturing (AM) is the most suitable I4.0 technology for countering global competition.

Evaluation of logistics centers in terms of sustainability via MCDM methods

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

SOHCO: A Strategy for Constructing Efficient Teams

Software engineering is concerned with organizational issues, project management, and human behavior. In the process of constructing a work team, leadership faces the task of evaluating the talents and abilities of each professional and combining them into a cohesive unit that matches the profile of the project. This article describes the SOHCO technique, a strategy for forming work teams that calculates a score for each candidate based on the project profile, as well as a ranking for the work team whose desired objective most closely aligns with the project profile. This article presents exploratory research, an experiment, two real-world case studies, and a comparison of methods using WS and RW coefficients to assess ranking consistency and similarity. Results reveal that SOHCO makes constructing a work team more objective, reduces leadership effort, enhances the ability to evaluate new team arrangements, increases the probability of project success, and reduces training costs. As a limitation, the SOHCO method does not take sub-criteria weights into account.

Optimal site selection for establishing solar power plant based on solar radiation using GIS

Although many nations employ solar energy as a backup energy source, not every site is equally conducive to the production of solar power. This is caused by the unequal dispersion of solar energy as well as a number of environmental conditions. The framework incorporates a number of Geographic Information Systems (GIS) features, including model builder and area classification. The framework used to derive the five sub-criteria weights determines the ideal locations for plant in the area based on the quantum of potential photovoltaic electricity production (PVOUT) that could possibly produce from Slope, exposure to sunlight, near to highways and closeness to a residential area. Finding the best locations for solar plant side identification in the “Anantapur” district using multicriteria decision analysis (MCDA).

EVALUATING THE INFLUENCE FACTORS OF THE ELECTRONIC SERVICE QUALITY IN THE BANKING INDUSTRY WITH THE ANP AND FUZZY TOPSIS METHODS

The purpose of this study is to evaluate the influence factors of electronic service quality (E-SQ) in the banking industry. A combination of Analytic network process (ANP) and Fuzzy-TOSIS methods was used in this study. ANP method was used to obtain the weight of criteria and sub-criteria and the Fuzzy TOPSIS method was used to prioritize four state banks of Rasht city. The data collection tool is ANP and TOPSIS questionnaire. Data collection is from October 2022 to January 2023. In the present study, 19 E-SQ sub-criteria were evaluated in the banking industry, and the Customers' trust sub-criteria was ranked first. Also, among the four studied public banks, Bank A1 was ranked first. Investigating the influence factors of E-SQ in the banking industry will make bank managers more familiar with the influence factors, and managers and policymakers in this area can provide better quality electronic services to bank customers.

Allocating weightage to sustainability criteria’s for performance assessment of group housing developments: Using fuzzy analytic hierarchy process

Sustainability assessment is a method to assess the effectiveness of sustainability performance. The construction industry largely acknowledges Green Building Rating Systems (GBRS) as a tool for evaluating sustainability performance. With an emphasis on group housing constructions in India, the present study created a methodology for evaluating sustainability performance. An in-depth analysis of the GBRS and published literature, followed by expert interviews, created a methodology with five building life cycle stages and fifteen criteria’s focusing on sustainability. Stakeholder perception was collected, and the data was assessed using the Fuzzy Analytic Hierarchy Process, to determine the priority weight of sustainability criteria and sub-criteria (FAHP). The development of a comprehensive system to account for sustainability on both the intergenerational and intragenerational levels for sustainability assessment is required. This study serves to be the first study to develop a comprehensive sustainability assessment system specific to group housing in India throughout the building life cycle stages.

A GIS-AHP approach for evaluating site suitability for solar power plant: a case study of Ewekoro LGA., Nigeria

To address Nigeria's electricity shortages and overreliance on traditional methods, solar power plants are being considered. However, selecting suitable sites for this purpose is critical and often poses a serious challenge considering a range of conflicting factors. In this study, the Analytical Hierarchy Process (AHP) technique and Geographic Information Systems (GIS) were combined to determine suitable sites for a solar electric power plant in Ewekoro Local Government Area (LGA). The approach considered road networks, transmission lines, slope, and land use as the key criteria as well as nineteen subcriteria for the site suitability analysis. The criteria and sub-criteria importance were weighted using AHP and the weights were inputted into the weighted overlay tool in the ArcGIS 10.4 for analysis. The resulting sub-criteria weights of land use are 3.5%, 6.8%, 10.6%, 16%, and 63.1% for built-up areas, waterbody, wetlands, rocky areas, and vegetation respectively. Based on the analysis, a suitability map was generated that categorized the study area as best suitable, suitable, and not suitable. On the map, 15% of the area was best suitable, 17% was suitable, and 68% was not suitable for solar power plants. In conclusion, the site suitability analysis of Ewekoro LGA for solar power plants has been evaluated and this approach can be extended to other areas in Nigeria where solar energy integration is of high priority.

Facility Location Selection with Integrated Fuzzy AHP and Fuzzy VIKOR Methods

Kar amacı güden her işletmenin varoluş sebebi maksimum faydayla faaliyet göstermektir. Maksimum fayda sağlama yolunda stratejik kararlar önemlidir. Bu kararlar işletmeleri uzun dönemde etkiler ve hata yapılırsa büyük maliyetler oluşabilir. Stratejik kararlardan biri tesis yeri seçimidir. Tesis yeri yatırımı karar vericilerin hedefleri doğrultusunda karlı sonuçlanmalıdır. Çalışmada Ark Pres Emniyet Kemerleri A.Ş. için tesis yeri seçimi problemi ele alınmıştır. İşletmedeki karar vericilerin kriterlerin önem düzeylerinin tek bir kararda olmaması problemi karmaşıklaştırmıştır. Çözümde Çok Kriterli Karar Verme tekniklerinden Bulanık Analitik Hiyerarşi Prosesi (BAHP) ve Bulanık Çok Kriterli Optimizasyon ve Uzlaşık Çözüm (Bulanık VIKOR) yöntemleri uygulanmıştır. Bulanık AHP ile karar vericilerin değerlendirmeleri doğrultusunda kriterler ağırlıklandırılmış, Bulanık VIKOR ile bu ağırlıklar kullanılarak alternatifler sıralanmış ve seçim yapılmıştır. Çalışmada ana kriter ağırlıklarından en önemlisi maliyet, alt kriter ağırlıklarından en önemlisi işçilik maliyetleri olarak belirlenmiştir. Uygulama sonucunda işletmenin tesis yeri beş alternatif arasından en uygun olan Kocaeli - Arslanbey Organize Sanayi Bölgesi seçilmiştir.

A novel multi-criteria decision-making framework for selecting municipal solid waste management alternative with 2-dimensional uncertain linguistic sets.

Municipal solid waste management (MSWM) has been considered as a complicated multi-criteria decision-making problem for the uncertain context and related criteria. To select an optimal MSWM scenario, this paper provides a comprehensive MCDM framework for decision-makers under 2-dimensional uncertain linguistic (2-DUL) environment. Distinguished from traditional approaches, this framework not only guarantees the consistency of comparison matrix but improves effectiveness and efficiency in the decision process. Moreover, it accurately solves the cardinal and ordinal information of MSWM scenarios. Firstly, due to ambiguous and uncertain decision context, the 2-DUL set, characterized by I class of the linguistic evaluation information and II class of the reliability of the assessment results, is adopted to describe decision-makers' preference. An expectation reduced-dimension is developed to effectively handle 2-DUL set. Secondly, to guarantee consistency and reduce numerical pairwise comparisons, a best-worst-method (BWM)-based analytic network process (ANP) is utilized to form the local priority vectors of the main criteria and sub-criteria. Main criteria weights and sub-criteria weights are then obtained by aggregating all local priority vectors. Thirdly, an extended QUALIFLEX approach is employed to rank all alternative MSWM scenarios by comparing the weighted concordance/discordance index among overall possible permutations of all alternative scenarios. Finally, the developed framework is applied in a case study to determine an optimal MSWM scenario in Beijing. Additionally, a comparison analysis is complemented. The results demonstrate that the proposed framework is feasible, efficient, and superior in MSWM scenarios selection.

Ranking online shopping websites by considering the criteria weights

In this study, a three-step methodology is proposed. To begin with, a total of seven main criteria and 23 sub-criteria that affect the selection of online shopping websites are determined by searching the literature and interviewing people. Next, a questionnaire is applied to the people from Turkey and Croatia. It is evaluated using AHP methodology to find the main and sub-criteria weights from the perspective of Turkish and Croatian people. Furthermore, a second questionnaire for ranking three popular online shopping websites in Turkey has been applied. Finally, online shopping websites are ranked as B, A, and C based on the scores obtained from the second questionnaire and criteria weights found in the second step. After estimating the decision weights of the sample from Croatia, we use that as a “what if” analysis for websites A, B, and C. Customers’ shopping behaviors from those online shopping websites are analyzed using SPSS.

A Novel Integration of IF-DEMATEL and TOPSIS for the Classifier Selection Problem in Assistive Technology Adoption for People with Dementia.

The classifier selection problem in Assistive Technology Adoption refers to selecting the classification algorithms that have the best performance in predicting the adoption of technology, and is often addressed through measuring different single performance indicators. Satisfactory classifier selection can help in reducing time and costs involved in the technology adoption process. As there are multiple criteria from different domains and several candidate classification algorithms, the classifier selection process is now a problem that can be addressed using Multiple-Criteria Decision-Making (MCDM) methods. This paper proposes a novel approach to address the classifier selection problem by integrating Intuitionistic Fuzzy Sets (IFS), Decision Making Trial and Evaluation Laboratory (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The step-by-step procedure behind this application is as follows. First, IF-DEMATEL was used for estimating the criteria and sub-criteria weights considering uncertainty. This method was also employed to evaluate the interrelations among classifier selection criteria. Finally, a modified TOPSIS was applied to generate an overall suitability index per classifier so that the most effective ones can be selected. The proposed approach was validated using a real-world case study concerning the adoption of a mobile-based reminding solution by People with Dementia (PwD). The outputs allow public health managers to accurately identify whether PwD can adopt an assistive technology which results in (i) reduced cost overruns due to wrong classification, (ii) improved quality of life of adopters, and (iii) rapid deployment of intervention alternatives for non-adopters.