Grey Analytic Hierarchy Process Research Articles

An AI-Powered Product Identity Form Design Method Based on Shape Grammar and Kansei Engineering: Integrating Midjourney and Grey-AHP-QFD

Product Identity (PI) is a strategic instrument for enterprises to forge brand strength through New Product Development (NPD). Concurrently, facing increasingly fierce market competition, the NPD for consumer emotional requirements (CRs) has become a significant objective in enterprise research and development (R&D). The design of new product forms must ensure the continuity of PI and concurrently address the emotional needs of users. It demands a high level of experience from designers and significant investment in R&D. To solve this problem, a generative and quantitative design method powered by AI, based on Shape Grammar (SG) and Kansei Engineering (KE), is proposed. The specific method is as follows: Firstly, representative products for Morphological Analysis (MA) are selected, SG is applied to establish initial shapes and transformation rules, and prompts are input into Midjourney. This process generates conceptual sketches and iteratively refines them, resulting in a set of conceptual sketches that preserve the PI. Secondly, a web crawler mines online reviews to extract Kansei words. Factor Analysis (FA) clusters them into Kansei factors, and the Grey Analytic Hierarchy Process (G-AHP) calculates their grey weights. Thirdly, after analyzing the PI conceptual sketches for feature extraction, the features are integrated with CRs into the Quality Function Deployment (QFD) matrix. Experts evaluate the relationships using interval grey numbers, calculating the optimal ranking of PI Engineering Characteristics (PIECs). Finally, professional designers refine the selected sketches into 3D models and detailed designs. Using a Chinese brand as a case study, we have designed a female electric moped (E-moped) to fit the PI and users’ emotional needs. Through a questionnaire survey on the design scheme, we argue that the proposed innovative method is efficient, applicable, and effective in balancing the product form design of PI and user emotions.

Analyzing barriers to sustainable healthcare waste disposal: a hybrid decision-making framework

PurposeIn the recent post-pandemic era, the globe has been anxious for the sustainable disposal of healthcare waste to protect public health, protect the environment and enhance future preparedness. Developing countries, in particular, have struggled to dispose of healthcare waste (HCW) to eradicate the hazardous effects of medical waste generated during and after the deadly COVID-19 pandemic. Hence the purpose of the research paper is to develop a hybrid decision-making framework to identify various barriers for sustainable disposal of healthcare waste use of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP).Design/methodology/approachA hybrid framework of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP) has been used to rank barriers and sub-barriers in the disposal of healthcare waste.FindingsThe study’s findings suggest that lack of segregation practices, absence of green procurement policy, obsolete technologies and resistance to adopting change management are the topmost causal barriers influencing the remaining barriers. Lack of commitment among healthcare administrations, lack of standard performance measures and resistance to adopting change appear to be the topmost crucial barriers.Practical implicationsThe study’s finding enables all stakeholders to prioritize the barriers systematically for better performance and save resources during the process. The policymakers can use the results to design a clear regulatory framework.Originality/valueThe literature has highlighted the factors and their association with the disposal of healthcare waste mainly in isolation. The results are validated against the Grey-Analytical Hierarchy Process (G-AHP) to ensure the robustness of the proposed framework. This paper is one of the preliminary attempts to propose a framework of the interrelationships of the factors that have a direct role in survival for management education.

Enhancing Decision Fusion for Wastewater Treatment System Selection Using Monte Carlo Simulation and Gray Analytic Hierarchy Process

This research presents an innovative data fusion model that utilizes Monte Carlo simulations (MC) and the Gray Analytic Hierarchy Process (G-AHP) to address the complexity and uncertainty in decision-making processes, particularly in selecting sustainable wastewater treatment systems. The study critiques and extends the Dempster–Shafer and Yager’s theories by incorporating a novel MC algorithm that mitigates the computational challenges of large numbers of experts and sensors. The model demonstrates superior performance in synthesizing diverse expert opinions and evidence, ensuring comprehensive and probabilistically informed decision-making under uncertainty. The results show that the combined MC algorithm produces satisfactory results, and thus, offers wide applicability in decision-making contexts. To determine its effectiveness, an extensive empirical study was conducted to identify an appropriate wastewater treatment system for the busy city of Tehran, incorporating the insights and perspectives of respected experts in the field. The selection was based on three technical, economic, and environmental–social criteria. Due to the large dimensions of each of the defined criteria, sub-criteria were also defined to achieve better results for each of the criteria. The in-depth analysis conducted revealed that enhanced aeration activated sludge (EAAS) emerged as the best choice for Tehran’s most urgent needs among various competitors, with a remarkable priority rating of 34.48%. Next, the Gray Analytic Hierarchy Process (G-AHP) was used to determine the most important sub-criterion, based on which resistance to hydraulic shock is most important in the enhanced aeration activated sludge system. Due to its versatility in different fields and industries, this method is a powerful tool for managers to optimize system efficiency and identify defects and risks and eventually to minimize costs.

Overcoming barriers to integrated management systems via developing guiding principles using G-AHP and F-TOPSIS

Implementing Integrated Management Systems (IMS) has become a prerequisite for transforming businesses into more competitive and sustainable enterprises. However, the various barriers impede the effective implementation of IMS. Although prior studies have associated several barriers with implementation, they neither elaborate on the degree to which these barriers hinder integration nor offer any strategies to overcome them. To fill this gap in the literature, this study offers a systematic decision-making framework to prioritize barriers and develop various guiding principles to overcome them. First, we conducted a literature review to identify twenty-three sub-barriers nested in five main barrier categories of Resources & Assets, Employees, Implementation, Financial, and Organization Culture. The literature review also helped us to develop fifteen guiding principles. Next, we employed the Grey Analytical Hierarchy Process (G-AHP) method to prioritize barriers and sub-barriers. Finally, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS) is used to evaluate the guiding principles for sustainable implementation of IMS. The results of the G-AHP method reveal “Resources & Assets”, “Employees”, and “Implementation” as the most critical IMS barriers. Besides, the results of the F-TOPSIS method show that “Encourage standardization of processes”, “Standardize organizational practices and concepts”, and “Engage employees in IMS development” are the most feasible guiding principles to overcome the IMS barriers. Finally, sensitivity analyses were conducted to check the robustness of the results. The contributions of this study help managers and policymakers overcome the barriers of IMS integration while simultaneously fostering sustainability through the implementation of guiding principles.

Unlocking the Potential of E-Commerce in Yemen: Identifying Key Impacting Factors and Exploring Strategic Solutions

This study offers a comprehensive analysis of the e-commerce ecosystem in Yemen, identifying key opportunities and impacting factors to growth, and suggesting suitable strategies for e-commerce startups. The study employs an integrated methodical approach, combining a literature review, and data analysis using Grey Analytic Hierarchy Process (Grey AHP) and Grey Technique for Order of Preference by Similarity to Ideal Solution (Grey TOPSIS). The literature review identifies opportunities, challenges, and strategic solutions. The Grey AHP assesses the relative importance of opportunities and challenges. The Grey TOPSIS ranks the best strategies that e-commerce startups in Yemen can adopt to leverage these opportunities and manage the negative effects of the barriers. The results show that large market potential, the underserved market, and the growing middle class represent the most significant opportunities. In contrast, economic and political instability, logistical challenges, and the lack of trust in online payments are the most significant impacting factors. To overcome these challenges, the top three strategies recommended are building strategic partnerships, offering secure payment and delivery options, and targeting the underserved market. By implementing these strategies, the e-commerce ecosystem in Yemen can prosper, take advantage of opportunities, and contribute to the country’s economic development.

A two-phase decision making based on the grey analytic hierarchy process for evaluating the issue of park-and-ride facility location

Planning a Park-and-Ride (P&R) system in an urban area of a city depends on a group of transportation planning professionals with different areas of expertise in mobility, agreeing on which criteria or set of criteria are the most important. In addition to analysing the criteria established as mobility policies in the Sustainable Urban Mobility Plan (SUMP), when establishing a set of facilities belonging to the P&R system. To find out which criterion is the most important one when combining the mobility criteria established in the SUMP with the criteria of transportation planners with different expertise, this paper applies the multi-criteria method known as the Grey Analytic Hierarchy Process (G-AHP). In this method, at first the main and secondary criteria are determined at two levels that allow building a hierarchical structure, then transportation professionals are surveyed, and finally, the formulation of the multi-criteria method is designed. The result of the study illustrates the effectiveness and usefulness of the proposed multi-criteria method to determine the hierarchy of criteria from most to least important to solve the problem of locating a P&R system. Also, the results are compared with two different multicriteria methods (FAHP and BWM) to see how they are alike and how they are different. The finding suggests that the planning of a P&R system and the criterion for the accessibility of public transport go hand in hand, regardless of the multi-criteria method employed.

Modeling the Quality of Urban Life using Grey Analytical Hierarchy Process

Economic growth has recently been crowded out by life quality in the new development pattern. Unlike the income-based measurement of economic growth, the life quality measure has become a challenge because it is a multi-dimensional concept that relies on the subjective evaluation of the involved stakeholders in a particular context. The objective of this study was to investigate the model of quality of urban life in Ho Chi Minh City, Vietnam based on subjective indicators. The word clouds and grey analytical hierarchy process were employed to analyze the data from thirty in-depth interviews with experts in the field. The empirical model of quality of urban life in Ho Chi Minh City was found with three levels. The ranking results at the second level emphasized the high shares of health, employment, and income compared to self-esteem, socialization, and family happiness. The ranking results at the second level emphasized the high shares of health, employment, and income compared to self-esteem, socialization, and family happiness. Further investigation at the third level has confirmed the superiority of non-material components in the quality of urban life model in Ho Chi Minh City, Vietnam. The findings were critical in implying the policy concentration on non-material values enhancement to raise the quality level of urban life. It was a milestone in switching the focus from material to non-material factors in the life quality model in Vietnam.

Sustainable and resilient e-commerce under COVID-19 pandemic: a hybrid grey decision-making approach.

E-commerce saw a paradigm shift during COVID. Consumers turned to online shopping when pandemic lockdowns caused brick-and-mortar stores to shut for extended periods. Although the pandemic drove more buyers online, it had negative impacts that affected e-commerce performance. This study assesses both positive and negative impacts and their relative significance. The findings are then used to prioritize different strategies for e-commerce development in four vibrant Middle Eastern economies: United Arab Emirates, Saudi Arabia, Qatar, and Kuwait. The study employs a hybrid approach incorporating grey analytical hierarchy process (GAHP) and grey relational analysis (GRA). The GAHP evaluates the relative significance of impacts, whereas the GRA ranks the strategies. The study is based on the responses from 36 local e-commerce specialists. The findings revealed that the supply chain disruption was a rather significant factor, and that "expanding supplier base" was a top-ranked strategy. The study suggests that increasing market share of e-commerce will necessitate the improvement of the supply chains, including the expansion of the supply base, as well as the establishment of sustainable supply chains. In addition to that, the moment has come to implement meaningful changes, such as digital transformation of supply chains, in order to fulfil customer expectations.

Usability Evaluation of in-Vehicle AR-HUD Interface Applying AHP-GRA

Usability is regarded to be a fundamental requirement for in-vehicle HMIs, and usability evaluation reflects the impact of the interface and the acceptance from the users. This study introduced a usability evaluation model of AR-HUD interface by applying grey analytic hierarchy process (AHP). First, based on the ameliorated PSSUQ (Post-Study System Usability Questionnaire), the usability evaluation system was modified and optimized according to the characteristics of AR-HUD. On this basis, the preference weights for evaluation indexes were calculated by AHP and the idea of group decision. Finally, the criteria of usability were integrated into grey relational degree by applying grey relational analysis (GRA) to obtain optimal design. A case study was conducted to demonstrate the applicability of the developed model to the usability evaluation of AR-HUD interface design. According to the existing AR-HUD interface design, 7 dimensions of design elements (A-G) and 18 interface prototypes (S1-S18) were selected by Taguchi orthogonal array test (TOAT). As the results indicated, the grey relational degree of S5 was 0.923, signifying that it was the optimal sample; and the results were also compared with entropy-TOPSIS to verify the feasibility of the proposed method. The grey-based AHP evaluation model can be used to evaluate the usability level of AR-HUD interface effectively, which may help designers achieve insights for design process and samples decision-making.

Study on model selection and evaluation method of weapon system based on ISM and GAHP

Model selection & evaluation is the key focus and urgent problems to solve in comprehensive argumentation and conceptual design of weapon system, and has great significance for the weapon system to realize function demand, hierarchy management, and decision optimization. Aimed at model selection & evaluation of weapon system, the model selection & evaluation method based on interpretation structure model (ISM) and gray analytic hierarchy process (GAHP) is designed, hierarchical relationship between structure and performance of weapon system is qualitatively described through setting up directed-graph of system structure, and overall evaluation value of design plan is quantitatively represented by determining influence weight between the elements of system and the gray evaluation vector. Combined with evaluation execution procedure, the mathematical model is given, and taking an airborne weapon system as example, Matlab program is compiled, the best plan among the three is selected, and the theoretical basis is provided. Model selection evaluation method of weapon system based on ISM & GAHP has solved the problem from qualitative demand to quantitative decision-making, and with guiding significance for the model selection evaluation of weapon system.

Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

The importance of public stadiums has become increasingly prominent, but the efficiency of its performance management operation mechanism is low, which affects the overall operation efficiency of the whole stadium. However, due to the diversity and incompleteness of its data types, the traditional analytic hierarchy process is difficult to construct its index system. This article introduces the grey fuzzy analytic hierarchy process. Based on the analysis of its performance management problems, this article constructs the index system and makes an application case analysis. The results show that the GFAHP method (group fuzzy analytic hierarchy process) can ensure the integrity of information data. In data classification, the highest accuracy of sample classification is 40.13%, and the relative error rate is basically less than 6%. The performance effect is much higher than other classification algorithms. At the same time, the total score of the evaluation index system constructed by GFAHP is more than 3, the overall operation is good, and the risk evaluation effect of each influencing index factor is also good. Using the grey analytic hierarchy process to evaluate the operation and performance management of public stadiums and gymnasiums will help managers do a good job in risk control and quality dynamic adjustment, so as to improve the operation efficiency and benefit of stadiums and gymnasiums.

Locating temporary waste treatment facilities in the cities to handle the explosive growth of HCWs during pandemics: A novel Grey-AHP-OCRA hybrid approach.

The COVID-19 outbreak has not only put the community health at stake but, also the environmental health. Usually, the healthcare wastes (HCWs) are composed of 15-20% of the infectious wastes and the rest of the non-infectious wastes. But, during any communicable health outbreak like COVID-19, the whole HCWs coming from the infected people become contagious. During the COVID-19 outbreak, the infectious waste is not only limited to the hospitals’ premises, but also comes from the households, where COVID19 infected people are under home quarantine. Hence, keeping in mind the explosive growth in generation rates of infectious HCWs, the present study targets to expand the treatment and disposal capacity by installing temporary healthcare waste treatment facilities (HCWTFs). The study identifies ten criteria from the literature review and in consultation with the field experts, to evaluate the potential candidates for setting up temporary HCWTF during the health outbreaks. The study proposes a hybrid methodology based on grey analytical hierarchy process (G-AHP) and grey operational competitiveness rating analysis (grey-OCRA) for prioritizing the evaluation criteria and selecting the optimal temporary HCWTF location by considering the experts’ inputs, respectively. The stakeholders consider the ‘proximity to the inhabitation’, ‘infrastructure availability’, and ‘transportation distance’ are the most important criteria for selecting the temporary HCWTF location. The proposed methodology is applied to select the temporary HCWTF location in Sundargarh District, Odisha, India. The study identifies the four locations by using geographical information system (GIS) tools and sequences them as per the preferences given by the stakeholders on various identified criteria. The study may be useful for the administration to set up the temporary facilities to quickly dispose of the extra HCWs during the pandemics. However, the future studies can be targeted to coordinate the collection, storage and transportation activities with the temporary HCWTFs.

State assessment of 750kV electric energy metering device based on grey theory and fuzzy analytic hierarchy process

Abstract It is necessary to evaluate the operation state of 750kV electric energy metering device to predict stop loss. On the basis of previous studies, the state indexes and evaluation methods of electric energy metering devices are improved: the quantitative state indexes are described by nonlinear mathematical scoring model, the qualitative state indexes are clustered by grey theory, and the state weight of each index is determined based on the improved analytic hierarchy process, Finally, the state evaluation results are obtained with the help of weighted average model and fuzzy mathematics theory. The improved state evaluation strategy is more perfect and practical, and realizes the all-round supervision of the operation state of the electric energy metering device.

Selection of Cold Chain Logistics Service Providers Based on a Grey AHP and Grey COPRAS Framework: A Case Study in Vietnam

Choosing the most suitable cold chain logistics service providers (CLPs) is a vital strategic decision for businesses aiming to achieve an effective and sustainable cold supply chain. A sustainable CLP is one that integrates sustainable practices across its whole operation cycle to achieve product quality, on-time deliveries, and satisfied customer requirements, while preventing products from going to waste, which is especially important in the context of a developing country. This study aims to evaluate and select the best CLP regarding their sustainability performance. For this evaluation, a multi-criteria decision making (MCDM)-based framework is proposed that integrates the grey analytic hierarchy process (G-AHP) and grey complex proportional assessment (G-COPRAS) methodologies, in which grey numbers are used to express the linguistic evaluation statements of experts. Initially, the evaluation criteria based on service level, economic, environmental, and social dimensions were determined by means of a literature review and experts’ opinions to employ the MCDM approach. The G-AHP was utilized to identify the criteria weights, and then, G-COPRAS was used to select the best CLP among the alternatives. A case illustration in Vietnam is presented to exhibit the presented approach’s applicability. From the G-AHP findings, product quality, logistics costs, innovation, and effectiveness of cold chain processes, customer experience, and CO emissions of refrigerated vehicle were ranked as the five most important criteria. From the G-COPRAS analysis, Yoshida Saigon Cold Logistic (CPL-05) is the best CLP. The robustness of the applied integrated MCDM approach was also tested by conducting a comparative analysis, in which the priority rankings of the best CLPs were very similar. The assessment in this study is directed towards enabling managers, practitioners, and stakeholders of cold chain businesses to assess the most efficient CLP in the supply chain in the market and also to devise suitable strategies toward sustainable development.

Evaluating Video Conferencing Software for Remote Working Using Two-Stage Grey MCDM: A Case Study from Vietnam

The COVID-19 pandemic has completely changed the world, and businesses are struggling to create a new and effective working environment for their employees. Employees worldwide have moved from traditional face-to-face meetings to remote working using video conferencing software (VCS)—a powerful tool to support companies during the pandemic and that can be an increasing trend in the future. For businesses who intend to adopt VCS for their organizations, choosing an appropriate platform can be an arduous task that requires the consideration of multiple criteria to save costs and optimize efficiency. In this paper, we propose a grey-based multi-criteria decision making (MCDM) framework that combines grey Analytical Hierarchy Process (G-AHP) and grey Evaluation Based on Distance from Average Solution (G-EDAS) methodologies, in which grey numbers are used to express the linguistic evaluation statements of experts. Initially, the evaluation criteria based on functionality, security, usability, technical performance, and pricing have been determined using a literature review and expert’s opinions to employ the MCDM approach. G-AHP was utilized to identify the criteria weights, and G-EDAS was then used to select the best VCS among the alternatives. A case illustration in Vietnam is presented to exhibit the proposed approach’s applicability. From the G-AHP findings, quality of video/audio, ease of use, mobile experience, number of participants allowed, and video recording capability have been ranked as the five most important criteria. From G-EDAS analysis, Microsoft Teams (VCS-03) was found to be the best. In addition, the robustness of the proposed model was tested by conducting sensitivity analysis and comparative analysis of methods, in which the priority rankings of the best VCSs are very similar. With the high demand for the trend of the remote working model, this study can be a basis for informed decisions to assist businesses in choosing their best-suited VCS to save costs and enhance productivity.

Application of grey analytic hierarchy process to estimate mode choice alternatives: A case study from Budapest

This study proposes a multi-criteria decision-making approach using the grey theory to analyze mode choices. An extended analytic hierarchy process (AHP) model, which combines the advantages of the classic AHP and the grey theory for the accurate estimation of the commuting mode weight coefficients, is applied to a real transportation problem involving evaluators. The presented approach is applied for a real-life case study in Budapest. Based on the results, for all distances, public transport is ranked first followed by the car mode; however, for short- and mid-distance commuters, home office and bike might be suitable options, too. The results of this method are compared with the fuzzy AHP method. Having the same ranking in case of the two analyses means that the proposed method provides correct results under uncertainty in a group decision-making process. Thus, the outcomes highlight the applicability of the proposed method to the evaluation of mode choice.

Evaluating renewable and sustainable energy impeding factors using an integrated fuzzy-grey decision approach

The provision of adequate, affordable, and sustainable electricity has become a dream for Pakistani people. In this modern era, people in Pakistan face up to 18 h of power outage a day. To overcome the energy shortage, efforts are already being made to exploit the country’s abundantly available renewable energy (RE) alternatives. However, results achieved so far are not remarkable since the development is impeded by numerous barriers. These barriers are complex, and their significance varies from one alternative to another. Therefore, it is vital to quantify their impact on each alternative as conducted in this study. Initially, the study finalizes barriers related to the scope of this study using Fuzzy Delphi. Later, Grey Analytical Hierarchy Process (G-AHP) is employed to first find the relative importance of barriers and then evaluate RE alternatives under each barrier. Finally, the ranking of alternatives based on overall barriers is obtained. Policy and Regulatory barriers found to be more significant. Whereas, Solar energy faces cumulatively less barriers and therefore tops the ranking followed respectively by Micro-hydro, Biomass, Wind, Municipal Solid Waste, and Geothermal. Based on findings, a new set of policy guidelines are proposed to help speed up the deployment of RE in Pakistan.

A combined Data Envelopment Analysis (DEA) and Grey Based Multiple Criteria Decision Making (G-MCDM) for solar PV power plants site selection: A case study in Vietnam

The transition from fossil fuels to more clean, affordable, and sustainable energy resources is of strategic importance for developing Asian countries like Vietnam, in which solar energy is an attractive option. The government of Vietnam is implementing various policy measures and has substantial investment plans to accelerate the national spread of solar energy. In this regard, location optimization for solar power installation is a vital strategic decision that needs to be analysed in-depth to harness solar power. This study aims to determine suitable areas for solar power installation in a case study in Vietnam. For the decision-making that influences solar plant site selection, while some criteria can be evaluated based on a numerical database, numerous qualitative criteria must be under experts’ judgements in linguistic terms and can be represented through grey numbers. To deal with the complex nature of the prioritization problem posed by the coexistence of multiple factors, this study proposes a combination of the Data Envelopment Analysis (DEA) method, Grey Analytic Hierarchy Process (G-AHP), and Grey Technique for Order Preference by Similarity to Ideal Solution (G-TOPSIS). With the utilized integrated approach, both quantitative and qualitative effective criteria are considered to evaluate locations. DEA is used in the first phase to select high-efficiency locations based on various measurable criteria. In the second phase, these locations are further assessed in terms of qualitative criteria: technical, economic, environmental, and socio-political factors. For this evaluation, G-AHP is used for criteria weighting, and G-TOPSIS ranks the locations. While the proposed approach is expected to help save costs and resources towards determining hot spots for solar power plants installation all around the country, it is recommended that governments and local authorities take into account suitability policies and support mechanisms for sustainable solar energy development.

E-Learning Platform Assessment and Selection Using Two-Stage Multi-Criteria Decision-Making Approach with Grey Theory: A Case Study in Vietnam

Education has changed dramatically due to the severe global pandemic COVID-19, with the phenomenal growth of e-learning, whereby teaching is undertaken remotely and on digital platforms. E-learning is revolutionizing education systems, as it remains the only option during the ongoing crisis and has tremendous potential to fulfill instructional plans and safeguard students’ learning rights. The selection of e-learning platforms is a multi-criteria decision-making (MCDM) problem. Expert analyses over numerous criteria and alternatives are usually linguistic terms, which can be represented through grey numbers. This article proposes an integrated approach of grey analytic hierarchy process (G-AHP) and grey technique for order preference by similarity to ideal solution (G-TOPSIS) to evaluate the best e-learning website for network teaching. This introduced approach handles the linguistic evaluation of experts based on grey systems theory, estimates the relative importance of evaluation criteria with the G-AHP method, and acquires e-learning websites’ ranking utilizing G-TOPSIS. The applicability and superiority of the presented method are illustrated through a practical e-learning website selection case in Vietnam. From G-AHP analysis, educational level, price, right and understandable content, complete content, and up-to-date were found as the most impactful criteria. From G-TOPSIS, Edumall is the best platform. Comparisons are conducted with other MCDM methods; the priority orders of the best websites are similar, indicating the robust proposed methodology. The proposed integrated model in this study supports the stakeholders in selecting the most effective e-learning environments and could be a reference for further development of e-learning teaching-learning systems.

Contribution of certification bodies and sustainability standards to sustainable development goals: An integrated grey systems approach

The International Organization for Standardization (ISO) and the Global Reporting Initiative (GRI) promote their alignment with the United Nations' Sustainable Development Goals (SDGs). This convergence of standards and information is causing the selection of a certification body to register these sustainability standards to become more complicated. Therefore, this study fills a gap in the literature by developing a framework to prioritize the most critical attributes for selecting a certification body. Initially, we focus on seven attributes using the Grey Delphi method. Further, Grey Analytical Hierarchy Process (GAHP) is employed to find primary and sub-indicators relative importance. Finally, we used a novel Grey Absolute Decision Analysis (GADA) model to rank the widely adapted top six certification bodies. Results reveal that Reputation, Payment Method & Cost, and Quality of Auditors are significant indicators with weighted scores of 0.2120, 0.1704, and 0.1406. In contrast, the auditor's knowledge about the sustainability standards, and review of the meetings obtained the highest weight score 0.5009 and 0.4918 and are seen as essential amongst 35 sub-criteria. Within this study, we identify which ISO and GRI sustainability standards contribute to a given SDG. We also find Bureau Veritas and Société Générale de Surveillance are the best-suited certification bodies help to achieve SDGs as they obtained the highest weights 0.8731, and 0.7340. This study is amongst the first of its kind to address selecting the right certification body for aligning with the SDGs by using the integration of three novel grey models. Outcomes of this study can help assist scholars, managers, government agencies, and decision-makers in selecting certification bodies to achieve SDGs while simultaneously improving sustainability practices.