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To come up with a prudent decision on the installation of an appropriate green wall (GW) on buildings, this study presents a novel decision-making algorithm. The proposed algorithm considers the importance of barriers hampering GW adoption, as well as their relationships with regard to different types of GWs existing in a contextual setting.

The proposed methodological approach is based on the integration of qualitative and quantitative techniques by employing focus group discussion, fuzzy-based best-worst method and fuzzy TOPSIS.

Based on the experiences of qualified experts involved in related projects in Hong Kong, the following conclusions are drawn: (1) cost, installation and maintenance-related barriers are perceived to have the highest importance, (2) modular living wall system is the most suitable GW system for the context of Hong Kong and (3) existing barriers are found to have a pivotal role in the ranking of the most suitable GW systems.

The findings provide valuable insight not only for policymakers and stakeholders, but also for establishing a methodological approach that can assist decision-makers in identifying the most beneficial GW system rather than the most applicable one. This could have significant implications and introduce potential changes to the common way of practice within the industry and lay the foundation for wider adoption of GW.

While previous studies have investigated the sustainability-related issues of GW façade applications, the current body of knowledge is deprived of a comprehensive methodological approach for the selection of the most suitable GW systems.

The fourth industrial revolution and digital transformation have caused paradigm changes in the procedures of goods production and services through disruptive technologies, and they have formed new methods for business models. Health and medicine fields have been under the effect of these technology advancements. The concept of smart hospital is formed according to these technological transformations. The aim of this research, other than explanation of smart hospital components, is to present a model for evaluating a hospital readiness for becoming a smart hospital.

This research is an applied one, and has been carried out in three phases and according to design science research. Based on the previous studies, in the first phase, the components and technologies effecting a smart hospital are recognized. In the second phase, the extracted components are prioritized using type-2 fuzzy analytic hierarchical process based on the opinion of experts; later, the readiness model is designed. In the third phase, the presented model would be tested in a hospital.

The research results showed that the technologies of internet of things, robotics, artificial intelligence, radio-frequency identification as well as augmented and virtual reality had the most prominence in a smart hospital.

The innovation and originality of the forthcoming research is to explain the concept of smart hospital, to rank its components and to provide a model for evaluating the readiness of smart hospital. Contribution of this research in terms of theory explains the concept of smart hospital and in terms of application presents a model for assessing the readiness of smart hospitals.

This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.

Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.

This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.

In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.

In this research, the initial list of internal capabilities in small and medium-sized enterprises (SMEs) leading to success in international markets has been extracted. Then, the most relevant capabilities to international SMEs under servitisation and hybrid offerings have been screened. Next, the selected capabilities have been classified, and ultimately the relationship amongst the capabilities has been analysed. The conceptual model for SMEs participating in international markets with hybrid offerings has been illustrated.

A literature review has been employed to extract the initial list of internal capabilities to address the research objectives. Then, a novel hesitant fuzzy Delphi (HFD) method has been developed to select the most relevant capabilities for SMEs for hybrid offerings in international markets by using the experts opinions. Subsequently, a novel hesitant fuzzy interpretive structural modelling (HFISM) has been developed to classify the capabilities, design a level-based conceptual model and present the relationship amongst the prominent capabilities.

After the literature review, sixteen internal capabilities leading to success in the international market via hybrid offerings have been extracted. Then, eight selected capabilities were chosen for further investigation by applying 15 expert opinions and via the HFD approach. According to HFISM results, a level-based conceptual model was emanated, and “ability to take advantage of international opportunities”, “financial strength”, “technology level” and “efficient innovation management” were considered as the most fundamental capabilities resulting in successful hybrid offerings in international markets.

Alongside the multi-layer decision-making approach developed in this manuscript to analyse the internal capabilities roles in hybrid offering success towards international markets, to the best knowledge of the authors, the hesitant fuzzy approaches developed in this article have not been previously presented by any other scholar. A novel HFD approach has been designed for consensus amongst the experts under uncertain circumstances. Furthermore, a novel HFISM has been suggested and employed in this research to comprehend the relationship amongst the internal capabilities.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

This study aims to explore supply chain resilience (SCR) and provides a unique resilience index. The work measures the resilience status of 37 organizations across 22 industries and provides insight into accessing the supply chain (SC) vulnerability in an uncertain environment.

This study involves measuring the resilience status of 37 organizations across 22 industries based on a subjective decision-making approach using fuzzy logic. Experts from industries rated the importance and level of implementation of 33 attributes of SCR, which are used to develop a fuzzy index of implementation that explains the resilience status of organizations.

A novel coexistent resilience index is computed based on mutualism to exhibit the proportion of contribution or learning of each attribute of an organization in an industry. The research will enhance the response plans and formation of strategic alliances for mutual coexistence by industry.

Evidence-based interpretations and suggestions are provided for each industry to enhance resilience through coexistence.

The work uniquely contributes to academic literature and SC strategy. The novel coexistent resilience index is computed based on mutualism, facilitating researchers to access SC resiliency.

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.

Delay and disruption claims involve a complex process that often result in disputes, unnecessary expenses and time loss on construction projects. This study aims to review and synthesize the contributions of previous research undertaken in this area and propose future directions for improving the process of delay and disruption claims.

This study adopted a holistic systematic review of literature following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A total of 230 articles were shortlisted related to delay and disruption claims in construction using Scopus and Web of Science databases.

Six research themes were identified and critically reviewed including delay analysis, disruption analysis, claim management, contract administration, dispute resolution and delay and disruption information and records. The systematic review showed that there is a dearth of research on managing the wide-ranging information required for delay and disruption claims, ensuring the transparency and uniformity in delay and disruption claims’ information and adopting an end-user’s centred research approach for resolving the problems in the process of delay and disruption claims.

Complexities in delay and disruption claims are real-world problems faced by industry practitioners. The findings will help the research community and industry practitioners to prioritize their energies toward information management of delay and disruption claims.

This study contributes to the body of knowledge in delay and disruption claims by identifying the need for conducting more research on its information requirements and management. Subsequently, it provides an insight on the use of modern technologies such as drones, building information modeling, radio frequency identifiers, blockchain, Bigdata and machine learning, as tools for more structured and efficient attainment of required information in a transparent and consistent manner. It also recommends greater use of design science research approach for delay and disruption claims. This will help to ensure delay and disruption claims are the least complex and less dispute-prone process.

Considering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator and preview controller, is considered to address the tracking control problem.

The authors employ an augmentation technique to construct an augmented error system for uncertain T-S fuzzy discrete-time systems with time-varying uncertainties. Additionally, the authors obtain the corresponding linear matrix inequality (LMI) conditions for designing the preview controller.

This paper discusses the preview tracking problem for nonlinear systems. First, considering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator, and preview controller, is considered to address the tracking control problem. Then, using the fuzzy Lyapunov functional with the linear matrix inequality (LMI) technique, new sufficient conditions for the asymptotic stability of the augmented system are derived by applying the LMI technique. The preview controller and fuzzy observer can be designed in one step. Finally, a numerical example is used to illustrate the effectiveness of the results.

An augmented error system is successfully constructed by the state augmentation approach. A novel preview controller is designed to address the tracking control problem. The preview controller and fuzzy observer can be designed in one step.