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To cater to the senior tourist market, it is essential to comprehend the factors motivating and deterring them from international travel post-COVID-19. This study aims to focus on senior citizens’ destination choice intentions and aims to develop a model that prioritizes positive and negative factors leading to international travel destination choices. It uses push–pull factors, perceived travel risks (PTRs) and perceived travel constraints (PTCs).

Decision-making trial and evaluation laboratory (DEMATEL) and fuzzy technique for order of preference by similarity to ideal solution (Fuzzy TOPSIS) are two multi-criteria decision-making (MCDM) techniques used to identify connections between variables and determine their relative importance in the decision-making model.

DEMATEL found push and pull factors are “effects” while PTCs and PTRs are “causes” affecting senior citizens’ destination choices. Push factors and PTCs have a greater impact than pull factors and PTRs. Fuzzy TOPSIS highlighted “improving health and wellness” and “self-fulfillment and spirituality” as key push factors, “health safety and security quotient” as the most important pull factor, and “interpersonal constraints” as the most critical PTC. Finally, “health risks” is the top PTR.

This paper adds to the tourism literature by looking at the relationship between senior tourists’ motivation, PTRs and PTCs and showing how the subfactors affect their choice of destination rank. The data analysis techniques used in this study are also novel, having never been used before in senior tourism research. Finally, even though there is a lot of research on senior tourism, not much is known about how Indian senior tourists act. In light of this study’s findings, practical recommendations were offered to tourism stakeholders worldwide, interested in tapping into the market of Indian outbound senior tourists or repositioning product or destination offerings to take this promising market or similar markets into account.

为了成功迎合蓬勃发展的老年旅游市场, 了解激励和阻止老年人国际旅行的因素尤为重要, 尤其是在 COVID-19 之后。本研究侧重于老年人的目的地选择意向, 并基于推拉因素、感知旅行风险 (PTR) 和感知旅行限制 (PTC), 旨在开发影响老年人国际旅游目的地选择的积极和消极因素的模型。

决策试验和评估实验室 (DEMATEL), 和与理想解决方案相似度的模糊偏好顺序 (Fuzzy TOPSIS) 是两种多标准决策 (MCDM) 技术, 用于识别变量之间的联系并找出它们在决策模型中的相对重要性。

DEMATEL的结果表明, 推力和拉力因素是“影响”, 而感知旅行约束（PTC）和感知旅行风险（PTR）是影响老年人目的地选择意愿的因素中的“原因”。推动因素和 PTC 比拉动因素和 PTR 发挥更重要的作用。 Fuzzy TOPSIS分析结果表明, “改善健康”和“自我实现和精神”是推动因素下最重要的因素。此外, 目的地的“健康安全商数”是拉动因素中最重要的, “人际约束”是PTC中最重要的。最后, 研究结果表明, “健康风险”是 PTR 中最重要的。

本文通过评估旅游动机、PTR 和老年游客 PTC 之间的相互关系, 为现有的旅游文献做出了贡献。此外, 该研究展示了影响老年游客目的地选择意愿的因素中各个子因素的比较优先级。本研究中使用的数据分析技术也很新颖, 以前从未在老年人旅游研究中使用过。最后, 虽然对老年旅游有丰富的研究, 但印度老年旅游者的行为相对不为人知。研究结果向有兴趣进入印度出境老年游客市场或重新定位产品或目的地的全球旅游利益相关者提供了切实可行的建议, 以考虑这个有前景的市场或类似市场。

Para atender a un mercado turístico de la tercera edad, es esencial comprender los factores que les motivan y les disuaden de realizar viajes internacionales tras el COVID-19. Este estudio se centra en las intenciones de elección de destino de las personas mayores y pretende desarrollar un modelo que priorice los factores positivos y negativos que conducen a la elección de un destino de viaje internacional. Utiliza los factores push-pull, los riesgos de viaje percibidos (PTR) y las limitaciones de viaje percibidas (PTC).

Decision Making Trial and Evaluation Laboratory (DEMATEL) y Fuzzy Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) son dos técnicas de toma de decisiones multicriterio (MCDM) utilizadas para identificar las conexiones entre variables y determinar su importancia relativa en el modelo de toma de decisiones.

DEMATEL descubrió que los factores de empuje y atracción son “efectos,” mientras que las PTC y las PTR son “causas” que afectan a las elecciones de destino de las personas mayores. Los factores de empuje y los PTC tienen un mayor impacto que los factores de atracción y los PTR. El Fuzzy TOPSIS destacó la “mejora de la salud y el bienestar” y la “autorrealización y espiritualidad” como factores de empuje clave, el “cociente de seguridad y protección de la salud” como el factor de atracción más importante y las “limitaciones interpersonales” como el PTC más crítico. Por último, los “riesgos para la salud” son el principal PTR.

Este artículo se suma a la literatura turística al estudiar la relación entre la motivación de los turistas sénior, los PTR y los PTC y mostrar cómo afectan los subfactores a su elección del destino. Las técnicas de análisis de datos empleadas en este estudio también son novedosas, ya que nunca se habían utilizado en la investigación sobre el turismo senior. Por último, aunque existen muchas investigaciones sobre el turismo sénior, el comportamiento de los turistas de la tercera edad en la India es relativamente desconocido. A la luz de los resultados del estudio, se ofrecen recomendaciones prácticas a las partes interesadas en el turismo de todo el mundo, interesadas en aprovechar el mercado de los turistas senior indios emisores o en reposicionar la oferta de productos o destinos para tener en cuenta este prometedor mercado o mercados similares.

This paper aims to evaluate the market concentration and competition in the European Banking Sector using an integrated multi-criteria decision-making approach under the fuzzy environment.

The hybrid model combining fuzzy decision-making trial and evaluation laboratory (DEMATEL), fuzzy analytic network process (ANP) and fuzzy VIKOR methods is applied to measure the market competition and concentration in the European Banking Sector. For this purpose, two academicians and one expert from banking sector with at least five-year experiences are selected to evaluate the dimensions, criteria and alternatives. The academicians are also appointed to define the decision-making problem and determine the dimensions and the criteria on the basis of related literature. The implementation of the model has been constructed in three main phases. The first phase consists of the fuzzy DEMATEL technique for understanding the impact-relation map among the dimensions. The second phase includes the fuzzy ANP method for measuring the relative importance of the criteria. The last phase comprises the fuzzy VIKOR approach to rank the alternatives with the values of the Herfindahl–Hirschman Index (HHI).

Turkey, France, England and Germany are placed in the competitive market structure of the European Banking Sector respectively. Additionally, the comparative results of the study confirm the market shares and the competitive policies of the European and Turkish Banking Sector.

The novelty of the paper is to construct a hybrid multi-criteria decision-making model with the proposed HHI scales under the fuzzy environment and defined competition dimensions and criteria based on the literature for the European Banking Industry.

The purpose of this paper is to propose an integrated fuzzy approach to determine important universal usability problems (UUPs) by providing experts who behave like real users and to establish a work plan to correct the most important ones.

In this study, a fuzzy multi-criteria decision-making approach with three stages is proposed for the evaluation of universal usability. At the first stage, UUPs are identified by performing modified heuristic evaluation, and severity rating of each problem is determined by experts. At the second stage, critical problems are specified by applying the fuzzy Delphi considering these severity ratings. At the third stage, Fuzzy Decision Making Trial and Evaluation Laboratory approach is applied to prioritize critical problems as sub and main criteria. An illustrative example related to emergency service is performed to apply the proposed approach.

Results showed that the elevator button design, the elevator emergency button design and the position of the floor signboard are the first three problems that should be primarily improved as sub-criteria. In terms of main criteria, equitable use, simple and intuitive use, and perceptible information are the first three main criteria that should be improve in emergency service.

This study is original in terms of methodology and providing a new perspective for building design evaluation. The results can help the designers to see the UUPs in buildings, to focus the most important UUPs and to establish improvement ranking. These advantages provide time and cost-effective design improvement actions.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

This study aims to explore the critical influencing factors that lead to the site selection failure of waste-to-energy (WtE) projects in China under the influence of the “Not In My Back Yard” (NIMBY) effect, which can provide references to improve the decision-making process of similar projects in the future.

The fuzzy decision-making trial and evaluation laboratory (DEMATEL) method was used to propose an analytical framework for exploring the critical influencing factors affecting the site selection failure of WtE projects. The causal relationship between different influencing factors is finally determined on the basis of the opinions of 12 experts from universities, government departments, consulting units, planning and design units, construction units and WtE enterprises.

Results showed that six crucial factors resulted in the site selection failure of WtE projects from the NIMBY effect perspective: “Insufficient public participation,” “Near the place of residence,” “Nonstandard government decision-making processes,” “Low information disclosure,” “Destroys the surrounding environment,” and “Imperfect compensation scheme.”

Results can determine the priorities and causal relationships among the various influencing factors. The decision-making optimization suggestions can provide reference for decision- makers, thereby possibly promoting the scientific and standardization of site selection decision process.

The purpose of this study is to evaluate maintenance strategies based on fuzzy decision-making trial evaluation and laboratory (DEMATEL) and fuzzy analytic network process (ANP) in the petrochemical industry.

This study proposes a hybrid-structured multi-criteria decision-making (MCDM) method based on fuzzy Delphi, fuzzy DEMATEL and fuzzy ANP as a structured methodology to assist decision makers in strategic maintenance. The fuzzy Delphi method (FDM) is applied to refine the effective criteria, fuzzy DEMATEL is applied for defining the direction and relationships between criteria and Fuzzy ANP is used for the selection of optimized maintenance strategy.

The results identify “strategic management complexity” as the top criterion. The predictive maintenance (PdM) with the highest priority is the best strategy. It is followed by reliability-centered (RCM), condition-based (CBM), total productive (TPM), predictive (PM) and corrective maintenance (CM).

Today, companies act in an atmosphere that is known with the features of uncertainty. In this atmosphere, only those companies can survive that have a strategy based on presenting the quality services and products to their customers. Similarly, maintenance as a system plays a vital role in availability and the quality of products, which creates value for customers. The selection of maintenance strategy is a kind of MCDM problem, which includes consideration of different factors. This article considers a broad category of alternates, including CM, PM, TPM, CBM, RCM and PdM.

This paper aims to investigate an integrated approach that aims at enhancing the application process of value stream mapping (VSM) method. It also proposes an extended VSM called Economic and Environmental VSM(E-EVSM). The proposed approach highlights the improvement of economic and environmental performances.

The proposed approach has studied the integration of VSM, fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy quality function deployment (QFD) to improve the economic and environmental performances of manufacturing processes. The VSM method is used for data collection and manufacturing process assessment, whereas fuzzy DEMATEL is used to analyse the current state map. Finally, fuzzy QFD is used to organize the improvement phase of VSM method.

The clear findings of this research prove the effectiveness of VSM method on the environmental and economic performances of manufacturing processes. In addition, the proposed approach will show the advantages of fuzzy DEMATEL and fuzzy QFD approaches in improving the application of the VSM method.

The limitation of this study includes the lack of consideration of other dimensions such as social, technological and managerial. In addition, the proposed approach studied an average set of environmental and economic indicators.

The novelty of the proposed approach is proved by the development of an extended VSM method (E-EVSM). Also, the proposed approach contributes by a new methodology for analysing and improving the current state map of manufacturing processes.

Food manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply inefficiencies have been reported to compromise food safety in different regions. Sustainable supplier management and digitalization practices have become cornerstone activities in addressing these shortcomings. Therefore, this paper proposes an integrated method for sustainability management in digital manufacturing supply chain systems (DMSCS) from the food industry.

The Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) was used to weigh the criteria and subcriteria under uncertainty. Second, the Intuitionistic Fuzzy Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL) was applied to determine the main DMSCS sustainability drivers whilst incorporating the expert's hesitancy. Finally, the Combined Compromise Solution (CoCoSo) was implemented to pinpoint the weaknesses hindering DMSCS sustainability. A case study from the pork supply chain was presented to validate this method.

The most important criterion for DMSCS sustainability management is “location” while “manufacturing capacity” is the most significant dispatcher.

This paper presents a novel approach integrating IF-AHP, IF-DEMATEL, and CoCoSo methods for sustainability management of DMSCS pillaring the food industry.

Lean Six Sigma (LSS) is receiving a tremendous attention as a modern process of streaming to improve the organizational ability and customer satisfaction. A successful LSS implementation is influenced by various factors and the execution of all the influencing factors simultaneously is a very difficult task for any organization. From the perspective of limitation of resources, this paper aims to present a basic issue in an LSS implementation of clustering complex and impacting factors into groups to achieve them in a stepwise manner. This paper aims to present a fundamental issue of clustering the complex and impacting factors of an LSS implementation into groups to achieve them stepwise.

A total of 40 relevant influencing factors toward an LSS implementation have been identified from the extensive literature review and duly validated with experts’ opinions. Integrated fuzzy set theory and decision-making trial and evaluation laboratory (DEMATEL) approach are demonstrated to explore the causal relationships among influencing factors of the LSS implementation. An empirical case analysis of an Indian manufacturing organization is carried out to illustrate the utilization of the proposed model.

The proposed framework effectively finds out the significance of each influencing factor of an LSS implementation and clustered into cause–effect groups. As per the results of the empirical case analysis, ten critical success factors (CSFs) of the LSS implementation are evaluated for the successful LSS implementation. Top management pays more attention to achieve them and implement them in a phase-wise approach under the limitations of accessible resources.

The presented framework provides an effective, precise and systematic decision support tool for recognizing CSFs of the LSS implementation. The organization, decision-makers, industrial practitioners and academic researchers may be able to comprehend the cause–effect relationship of the influencing factors of the LSS implementation. The exploratory nature and the single case study are two major limitations of this analysis. The developed model is heavily dependent on the experts’ opinions; hence, any bias in judgment will influence the final result.

This analysis is the first of its kind of effort, according to the best of the authors’ knowledge, to classify the influencing factors of LSS implementation into the cause–effect cluster. The outcomes of this analysis make the complexity of a problem easier in handling and assisting the decision-making.

The purpose of this study is to provide a model for evaluating, prioritizing and allocating orders to suppliers in the supply chain for mega-projects.

By using an integrated model (based on fuzzy analytic network process), suppliers are selected and the appropriate amounts are allocated to them in mega-projects. Initially, a hierarchical model of the research method was introduced. Then, the results on reliability and validity analysis of research measurement tools were presented. Finally, prioritization and allocation of orders to suppliers, with a case study of Iran Mall project, was carried out using Decision Making Trial and Evaluation Laboratory (DEMATEL) and analytic network process (ANP). T-test was used to evaluate the research hypotheses.

The findings were examined against conventional numerical analysis techniques. Finally, implication and recommendations for future work were presented.

The originality of this work is about using multi-criteria decision-making techniques for evaluating suppliers in mega-projects.