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The purpose of this paper is to investigate a fuzzy hybrid approach for ranking the flare gas recovery methods and allocating to refineries.

The proposed approach is containing four stages: in the first stage, experts' assessment is applied to identify relevant criteria and sub-criteria in the evaluation of flare gas recovery methods. In the second stage, the corresponding weights of criteria and sub-criteria are determined via fuzzy decision-making trial and evaluation (DEMATEL)-analytical network process (ANP) (DANP) method. In the third stage, the flare gas recovery methods are ranked using fuzzy weighted aggregated sum product assessment method (WASPAS) multi-criteria decision-making (MADM) technique. In the fourth stage, an optimization model is developed to allocate gas recovery methods to refineries while maximizing the total utility of allocations based on model constraints.

According to the results of fuzzy DANP method, technical and operational criterion was the most important followed by economic, political, managerial and environmental criteria. With respect to sub-criteria, international sanctions and political stability were the most important. The results of fuzzy WASPAS method indicated that gas injection was the first ranked alternative. Finally, the mathematical modeling allocated the recovery methods to five refineries of South Pars gas field in Iran based on budget and time constraints.

The proposed approach provides a systematic tool in the selection of flare recovery methods and allocation to refineries. This approach uses a new combination of fuzzy DEMATEL-ANP (DANP) method, fuzzy WASPAS method and mathematical programming. The approach is effectively implemented in a case study for ranking the flare gas recovery methods and allocating to refineries of South Pars gas field in Iran.

The aim of this paper was to investigate the criteria and sub-criteria with the most impact on determining a suitable location for refugee camps. This paper also analysed the relationships between the main criteria used in the selection process.

This study applied a combination of fuzzy methods and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) methods as tools for multiple-criteria decision analysis. A questionnaire was distributed to field workers in an international humanitarian organization team.

Five main criteria and twenty sub-criteria were defined. Between them, the highest ranked sub-criteria were long-term planning, optimal distribution and opportunity for growth. These findings were specific to the interviewed respondents of presented research at the time the data were collected and offer a potential research design for future research examining different organizations and teams.

The methods and evaluation were based on human opinions that were potentially biased.

The results of this study could be useful to government organizations, UN agencies, humanitarian organizations and other decision-making parties in selecting camp locations for refugees or internally displaced people according to how the importance of particular sub-criteria is understood.

New sub-criteria were included in this research. To date, the combination of fuzzy, DEMATEL and ANP methods has not been previously used in relation to these issues. Scientific knowledge concerning refugee camp siting problems is limited. This research extends this knowledge with the involvement of humanitarian workers as respondents. This paper also offers organizations a process for solving complex decision-making problems with long-term results or effect.

The present situation of COVID-19 pandemic has put the health-care systems under tremendous stress and stringent tests for their ability to offer expected quality of health-care services, as it decides the sustainability and growth of health-care service providers. This study aims to deliver a quantitative framework for service quality assessment in the health-care industry by classifying the health-care service quality parameters into four balanced scorecard (BSC) perspectives.

To determine the service quality for the Indian health-care system, decision-making trial and evaluation laboratory and analytical network process are integrated in a fuzzy environment to contemplate the interaction among BSC perspectives and respective performance measures.

The results indicate “internal processes” perspective assumes the key role within BSC perspectives, while performance measures “nursing staff turnover” and “staff training” play the key roles. The results also signify that “patient satisfaction” is the most vital issue and can be strongly influenced by measures belonging to the “learning and growth” perspective. In “learning and growth” perspective, “staff training” is the most decisive criteria, very highly influencing “patient satisfaction”, highly influencing “profitability,” “change of cost per patient (both in and out patients)” and “outpatient waiting time” while moderately influencing “staff satisfaction,” “bed occupancy” and “nursing staff turnover”. Moreover, “staff training” criteria have a positive influence on “nursing staff turnover.”

The contributions of this study are in two folds in the domain of quantification of service quality for the health-care system. First, it delivers an assessment framework for Indian health-care service quality. Second, it demonstrates an application of the framework for a case situation and validates the proposed framework.

The purpose of this paper is to select the optimal Lean Six Sigma (LSS) project using hybrid fuzzy-based Multi-Criteria Decision-Making (MCDM) approach for an automotive component manufacturing organization.

The LSS project selection has been formulated as the MCDM problem. Hybrid MCDM method based on Decision-Making Trial and Evaluation Laboratory Model (DEMATEL), Analytical Network Process (ANP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been used to select the optimal LSS project. The methodology enabled the practitioners to systematically prioritize LSS projects.

The finding of this study is that, out of five LSS projects, project P3 is the best LSS project. P3 is the optimal LSS project with reduced failure risk, and efforts are being taken to implement the selected project.

The problem formulation and methodology has been tested for a single study. In future, more number of studies could be conducted using the hybrid approach. This method is presently applied for an automotive component manufacturing organization; in future, the approach could be applied in different industrial sectors for improving its effectiveness.

The case study has been conducted in a real-time industrial problem. The practitioners expressed the usefulness of the methodology for prioritizing LSS projects Hence, the inferences derived are found to possess practical relevance.

The original contribution of the study is the selection of optimal LSS project using hybrid MCDM technique.

The concept of sustainable product design (SPD) is gaining significant attention in recent research. However, due to inherent uncertainties associated with new product development and incorporation of multiple qualitative and quantitative criteria; SPD is a complex and challenging task. The purpose of this paper is to introduce a novel approach by integrating quality function deployment (QFD), multi-criteria decision making (MCDM) technique and Six Sigma evaluation for facilitating SPD in the context of Industry 4.0.

The customer requirements are evaluated through the neutrosophic-decision-making trial and evaluation laboratory-analytic network process (DEMATEL-ANP)-based approach followed by utilizing QFD matrix to estimate the weights of the engineering characteristics (EC). The Six Sigma method is then employed to evaluate the alternatives’ design based on the ECs’ values.

The effectiveness of the suggested approach is illustrated through an example. The result indicates that utilization of the neutrosophic MCDM technique with integration of Six Sigma methodology provides a simple, effective and computationally inexpensive method for SPD.

The proposed approach is helpful in upstream evaluation of the product design with limited experimental/numerical data, maintaining a strong competitive position in the market and enhancing customer satisfaction.

This work provides a novel approach to objectively quantify performance of SPD under the paradigm of Industry 4.0 using the integration of QFD-based hybrid MCDM with Six Sigma method.

In this research, extracting the innovation drivers of successful crowdfunding from the literature review, screening them for the entrepreneurial small- and medium-sized enterprises (SMEs), analysing the cause-and-effect relationship amongst them and presenting a basic causal conceptual model and eventually determining the importance/weight of each relevant driver were the primary purposes of this research. As a result, the authors have also designed a score function to measure the future innovative crowdfunding score for SMEs.

A multi-layer multi-criteria decision-making (MCDM) approach has been designed and employed to achieve research objectives. After extracting the initial list of drivers, Fuzzy Delphi was applied to screen the relevant innovation drivers of successful crowdfunding for entrepreneurial SMEs. Decision-making trial and evaluation laboratory (DEMATEL) was used to analyse the cause-and-effect relationship amongst the drivers and illustrate a basic conceptual model. Analytical network process (ANP) and Stepwise Weight Assessment Ratio Analysis (SWARA) were applied to determine the importance of the drivers and by aggregating them to measure the innovative crowdfunding score.

Initially, 28 innovation drivers of successful crowdfunding were extracted from the literature. Then by employing the first-round Delphi fuzzy method amongst 15 international entrepreneurs in SMEs, the relevant drivers, including eleven items, were screened and selected. Then by implementing the DEMATEL method, the relationship amongst these screened drivers was identified, and seven drivers were determined as causes and the rest as effects. Subsequently, a conceptual model based on the causal analysis of the drivers from the DEMATEL method was designed. Eventually, by aggregating the weight of drivers emanated from SWARA, DEMATEL and DANP, the score function for measuring the situation of an SME was designed.

According to the crowdfunding scores in this research from entrepreneurs of SMEs, influential factors in developing countries were recognised as two times more prominent in developing countries. This might be rooted in the circumstances of developing countries where many startups and SMEs are emerging in vast areas and different fields due to investment in innovation management. In these countries, the authorities and officials support these companies to empower their capabilities and innovative ideas to (1) deal with the severe competitive market and (2) benefit from them as potential economic engines. Therefore, crowdfunding platforms and public initiatives can be considered one of the most effective government supports, which may involve financial risks.

To the best knowledge of the authors, investigating the innovation drivers of successful crowdfunding via quantitative analysis by multi-layer decision-making approaches has not been considered previously. Moreover, the authors have designed a crowdfunding score function to determine the situation of an entrepreneurial SME in this area. A combination of different MCDM methods, including Fuzzy Delphi, SWARA, DEMATEL, ANP and DANP, to investigate the innovation drivers of successful crowdfunding in SMEs has not been considered previously.

Despite the wide research and discussion on international performance, innovation and digital resilience dimensions of enterprises, the investigation and understanding of their interrelations seem to be limited. The purpose of this study is to identify the influential factors affecting the mentioned dimensions, determine the causal relationships among these identified factors and finally evaluate their importance in an aggregated framework from the viewpoint of small and medium-sized enterprises (SMEs).

A hybrid methodology is used to achieve the objectives. First, the main factors of international performance, innovation and digital resilience are extracted by an in-depth review of the literature. These factors are then screened by expert opinions to localize them in accordance with the conditions of an emerging economy. Finally, the relationship and the importance of the factors are determined using an uncertain multi-criteria decision-making (MCDM) approach.

The findings reveal that there is a correlation between digital resilience and innovation, and both factors have an impact on the international performance of SMEs. The cause-or-effect nature of the factors belonging to each dimension is also determined. Among the effect factors, business model innovation (BMI), agility, product and organizational innovation are known as the most important factors. International knowledge, personal drivers and digital transformation are also determined to be the most important cause factors.

This study extends the literature both in methodological and practical directions. Practically, the study aggregates the factors in the mentioned dimensions and provides insights into their cause-and-effect interrelations. Methodologically, the study proposes an uncertain MCDM approach that has been rarely used in previous studies in this field.

This research paper aims to identify and evaluate the enabling factors of agility capability in humanitarian relief chain network.

The research phases were implemented based on an integrated framework. First, a reference framework of the enablers has been constructed based on a literature review. Then, a hybrid evaluation approach is applied that combines fuzzy decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) to achieve reliable results. It provides a road map to identify and evaluate the interactions between the enabling factors and determines the weights correspond to their relative importance. This approach takes advantage of fuzzy set theory to deal with ambiguities, uncertainties and vagueness inherent in the evaluation process.

Relief chain agility is a vital determinant of the effectiveness to succeed humanitarian missions during and after natural and unnatural disasters such as earthquakes, epidemics and terrorist attacks. Results shed light on the essential enabling factors, relationships among them, and their importance for developing humanitarian relief chain agility enhancing the overall performance quality.

The integrated framework is implemented for the Red Crescent, a nongovernmental organization in Iran, which is trying to optimize the agility of their humanitarian relief chain network. In short, the findings are beneficial for identification and utilization of the essential prerequisites of agility in order to develop an agile humanitarian relief chain.

In 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).

A 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.

The 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.

The 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.

The 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.

International collaboration is a crucial requirement of entrepreneurship, particularly in developing emerging economies. This collaboration seems so necessary in the food industry as a major contributor to environmental, social and economic problems. This paper aims to identify, analyse the influential network relationship and prioritise the key success factors (KSFs) of international collaboration formation in the entrepreneurial food industry with a case study on Iran's emerging economy.

To identify a list of KSFs, a qualitative method, literature review, is initially used. A quantitative method, fuzzy-Delphi, then is employed to finalise the main KSFs based on the entrepreneurial food industry experts' opinion. To analyse the causal relationship, and prioritise the KSFs, a fuzzy decision-making trial and evaluation laboratory (DEMATEL)-analytic network process (ANP) methodology, i.e. FDANP, is applied. At the first stage, the cause–effect diagram of KSFs is extracted using fuzzy DEMATEL and then, the KSFs weights and priorities are evaluated using a fuzzy ANP.

The results illustrate that the characteristics of effective development workers are the leading dimension of a successful international collaboration that directly affects other dimensions. On the other hand, increased marketing and trading is the most important KSF that is directly related to international entrepreneurial collaboration team capabilities and professionalism. The leading and casual role of team members also plays a vital role in strategic and communication issues affecting the collaboration success, e.g. market research and new product development. Availability of financial resources and the ability of partners in continuous financing is also a crucial and required factor for a successful collaboration.

Using an extensive review of the literature to extract the KSFs of international entrepreneurial collaboration and finalising them using a fuzzy-Delphi method and examining the cause-effect relations between them, as well as prioritising the KSFs are the main contributions of this paper.