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PurposeThe occurrence of COVID-19 has impacted the wide-reaching dimensions of manufacturing, materials, procurement, management, etc., and has loaded disruptions in the wide range of supply chain (SC) activities. The impact of COVID-19 has twisted supplier performance and influenced stakeholders' thinking towards selecting supplier sources and making strategic sourcing decision for convinced arrangement of construction management (CM) resources. Nowadays, suppliers are intently evaluated by stakeholders in post-COVID-19 phase to induce agile availability of CM resources. Accordingly, this paper aims to demonstrate competent CM dimensions under post COVID-19 scenario for ease managing construction projects by the stakeholders.Design/methodology/approachThe authors have implicated Grey Sets Theory along with decision-making trial and evaluation laboratory (DEMATEL) technique for understanding significant outcomes. Varieties of diverse decision aspects responsible for strategically influencing supplier sourcing decision is projected under post COVID-19 scenario for handling construction projects by the stakeholders.FindingsThis study investigated sustainable construction management dimensions (SCMD) at the stage of resource deliveries and client aspirations under post COVID-19 situation. The study demonstrated "Lead time” as the most crucial, "Product Range” as the second and "Customers dealings and relationship” as the third crucial aspect considering by the stakeholders for selecting supplier sources based on the attainment of performance score of 0.1338, 0.1273 and 0.1268, respectively. It is found that high lead time stimulates the stakeholders to divert their orders to other competent supplier sources holding a low degree of lead time as compared.Research limitations/implicationsThe present study rollovers its existence by serving critical thinking, conceptual modelling, criteria identification and evaluation under CM domain for drafting effectual strategies by the suppliers. The study investigated the impact of COVID-19 on stakeholders' decision-making and enlisted SCMD that strategically stimulated them in choosing supplier sourcing decision.Originality/valueThe present study realizes the insights of stakeholders in the post COVID-19 scenario related to the supplier sources based on performance score. The study quantified sustainable supplier attribute for construction work and practices. The study analysed the expectations of the stakeholders purchasing different varieties of construction materials from supplier sources for civil works in the post COVID-19 scenario.
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The ageing population is increasing rapidly in Taiwan, where the ageing rate exceeds even that of Japan, the United States and France. The increase in the disabled population and the impact of the COVID-19 pandemic have resulted in an increase in the demand for long-term professional care, and the shortage of home care workers is one of the most important issues in the development of such care. This study explores the key factors that promote the retention of home care workers through multiple-criteria decision making (MCDM) to help managers of long-term care institutions retain home care talent. A hybrid model of multiple-criteria decision analysis (MCDA) combining Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the analytic network process (ANP) was employed for relative analysis. Through literature discussion and interviews with experts, all factors that promote the retention and desire of home care workers were collected, and a hierarchical MCDM structure was constructed. Then, the hybrid MCDM model of DEMATEL and the ANP was used to analyze the questionnaire data of seven experts to evaluate the factor weights. According to the study results, the key direct factors are improving job satisfaction, supervisor leadership ability and respect, while salary and benefits are the indirect factor. This study uses the MCDA research method and establishes a framework by analyzing the facets and criteria of different factors to promote the retention of home care workers. The results will enable institutions to formulate relevant approaches to the key factors that promote the retention of domestic service personnel and to strengthen the intention of Taiwan's home care workers to stay in the long-term care industry.
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The use of emergency departments (EDs) has increased during the COVID-19 outbreak, thereby evidencing the key role of these units in the overall response of healthcare systems to the current pandemic scenario. Nevertheless, several disruptions have emerged in the practical scenario including low throughput, overcrowding, and extended waiting times. Therefore, there is a need to develop strategies for upgrading the response of these units against the current pandemic. Given the above, this paper presents a hybrid fuzzy multicriteria decision-making model (MCDM) to evaluate the performance of EDs and create focused improvement interventions. First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) technique is used to estimate the relative priorities of criteria and sub-criteria considering uncertainty. Then, the intuitionistic fuzzy decision making trial and evaluation laboratory (IF-DEMATEL) is employed to calculate the interdependence and feedback between criteria and sub-criteria under uncertainty, Finally, the combined compromise solution (CoCoSo) is implemented to rank the EDs and detect their weaknesses to device suitable improvement plans. The aforementioned methodology was validated in three emergency centers in Turkey. The results revealed that the most important criterion in ED performance was ER facilities (14.4%), while Procedures and protocols evidenced the highest positive D + R value (18.239) among the dispatchers and is therefore deemed as the main generator within the performance network.
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COVID-19 , Decision Making , Humans , Fuzzy Logic , Uncertainty , TurkeyABSTRACT
The vaccine distribution system, being a bio-pharmaceutical cold chain, is a complicated and sensitive system that must be effectively managed and maintained due to its direct impact on public health. However, vaccine supply chains continue to be affected by concerns, including vaccine expiry, inclusion of counterfeit vaccines, and vaccine record fraud. The blockchain technology integrated with the Internet of Things (IoT) can create a solution for global vaccine distributions with improved trust, transparency, traceability, and data management, which will help monitor the cold chain, tackle counterfeit drugs, surveillance, and waste management. Several theoretical models for vaccine management with blockchain have recently been published, and a few pilot studies for COVID-19 vaccine management using blockchain have been started in India. Still, full-scale adoption of blockchain technology in vaccine distribution and management has yet to be achieved due to underlying barriers. This study explores the adoption barriers utilizing Technology-Organization-Environment (TOE) framework with the help of extant literature and inputs from administrators, academics, immunization, and blockchain experts and then analyzed using the Delphi and fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) techniques. The finding shows that the requirement of change in organizational structure and policies is the most prominent barrier, and the barrier related to requirement of large-scale IoT infrastructure and lack of technical expertise are the most impactful barriers. The theoretical contribution of this study lies in the identification and analysis of barriers that should be addressed to achieve blockchain technology adoption in the vaccine supply chain. © 2022 Elsevier B.V.
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Purpose: As the COVID-19 epidemic ravages the world in the fourth industrial revolution era, the manufacturing sector faces its worst situation in a century. Lean philosophy, renowned as a "warrior philosophy,” can be an able rescuer to these industries. This study aims to identify the hurdles to lean strategy implementation and conduct an analysis to provide cognizance to policymakers, practitioners and decision-makers. Design/methodology/approach: This study aims to identify the obstacles that obstruct lean implementation into seven primary barriers/components, with the fuzzy DEMATEL approach being used to evaluate the critical factors as well as the cause and effect factors among them. Expert opinions are sought to obtain the relevant data for evaluation purposes. Findings: The results reveal that a firm should focus on firm cultural conflict scenario, resources–responses incapability, improve on suppliers' attitude and execute a proper planning and logistics equation to alleviate the hindrances of implementing lean. As these causal factors influence the effect factors, namely, top management vision, management–employee relationship and human resource building, focusing on them automatically improves the effect factors;thus, the surge to overcome resistance to lean implementation is alleviated. Practical implications: This research aids in identifying and analyzing lean implementation issues in the manufacturing and industrial sectors. The observations, results and insights drawn can act as a guiding force to rupture the resistance envelope covering the domain of lean implementation and possibly reinstating industries to survive and excel in the business post-COVID era. Originality/value: This research introduces barriers to lean implementation in a unique way, as it articulates all sections of an industry and group the barriers based on the classification. It further prioritizes the barriers for their importance in the Indian industrial scenario. This would help the industry professionals and managers access the barriers and generate insight on how and where to start implementing lean. © 2023, Emerald Publishing Limited.
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• AI promotes the sustainability development in higher education. • A soft-computing technique extracts key factors from large amounts of data. • DEMATEL analysis accounts for dependence and feedback among factors. • A framework of AI-enabled Higher Education was proposed. • "Intelligent instructional systems" is the most important criterion. The application of AI in higher education has greatly increased globally in the dynamic digital age. The adoption of developmentally appropriate practices using AI-enabled techniques for facilitating the performance of teaching and learning in the higher education domain is thus a necessary task, especially in the COVID 19 pandemic era. The development and implementation of such techniques involve many factors and are related to the classical multiple criteria decision-making (MCDM) issue;however, these factors surrounding supervisors will confuse them and may result in misjudgment. To clarify the relevant issues and illustrate the cause-and-effect relationships among factors, a hybrid soft-computing technique (i.e., the fuzzy rough set theory (FRST) with ant colony optimization (ACO)) and a DEMATEL approach was proposed in this study, which can help decision makers capture the best model necessary for achieving aspiration-level in a higher education management strategy. In the results submitted, the improvement priority for dimensions is based on the measurement of the influences, running in order of tutors for learners (A), skills and competences (B), interaction data to support learning (C), and universal access to global classrooms (D), and which can serve as a reference for the plan of AI-enabled teaching/learning for higher education. [ FROM AUTHOR]
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Smart product-service systems (PSSs) have emerged as a solution for the ongoing digitalization of products and services, especially during the COVID-19 pandemic and under social distancing. However, the conditions for smart PSS adoption remain unclear, requiring the identification of driving attributes and the interrelationships of the attributes for smart PSS implementation in the healthcare industry. This study contributes by determining the cause-effect interrelationship among smart PSS attributes and by identifying and prioritizing the criteria that drive smart PSS adoption in chronic disease management. The study constructed a five-aspect theoretical model to deepen the understanding of digital health service adoption drivers. Data were collected from 233 healthcare industry practitioners to validate the smart PSS adoption attributes. Exploratory factor analysis (EFA) determined the structure of the attributes, the reliability of the criteria, and the validity of the aspects. The EFA result suggested 24 valid and reliable criteria drivers of smart PSS adoption in the healthcare industry, and they were grouped into five aspects. Following the smart PSS literature and stakeholder theory, the aspects are named digital health service adoption, intelligent connected products, stakeholder communication, environmental benefits, and use schemes. In addition, 17 practitioners treating patients with chronic conditions were interviewed to understand the interrelationships among the aspects and criteria. The fuzzy decision-making trial and evaluation laboratory (FDEMATEL) determined the cause-effect interrelationships based on their dependence and driving power. The FDEMATEL results indicated that intelligent connected products and stakeholder communication are the causal and focal attributes of improving digital health service adoption and providing alternative use schemes. For patients and physicians, the driving criteria include managing data, multifunctionality, data reliability, interoperability, patient communication, and resource efficiency. The theoretical and managerial implications are discussed.
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COVID-19 pandemic is the worst humanitarian crisis that economies across the globe have witnessed. Forced lockdowns, social distancing, and restricted mobility have contributed to large scale disruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting global supply chain and evaluate strategies for risk reduction in the supply chain network by making it resilient.Our study incorporates multi-criteria decision approach using Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) to analyze factors that affected the supply chain networks with the onset of COVID-19. The AHP method enabled to hierarchically rank the factors based on the relative weightage while DEMATEL ascertained the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the cost–optimization as the most significant factor and the human resource management as the least important factor in reducing vulnerabilities of the supply chain network. Our analysis from DEMATEL approach indicate that government support is a significant causal factor which can effectively eliminate the issues plaguing supply chains during this pandemic. The results from our study aim to help policymakers in developing a risk resilient framework that can enhance performance and operational capability of the supply chain, thereby ensuring sustainability and socio-economic well-being of all the stakeholders involved in the entire network.
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The application of AI in higher education has greatly increased globally in the dynamic digital age. The adoption of developmentally appropriate practices using AI-enabled techniques for facilitating the performance of teaching and learning in the higher education domain is thus a necessary task, especially in the COVID 19 pandemic era. The development and implementation of such techniques involve many factors and are related to the classical multiple criteria decision-making (MCDM) issue;however, these factors surrounding supervisors will confuse them and may result in misjudgment. To clarify the relevant issues and illustrate the cause-and-effect relationships among factors, a hybrid soft-computing technique (i.e., the fuzzy rough set theory (FRST) with ant colony optimization (ACO)) and a DEMATEL approach was proposed in this study, which can help decision makers capture the best model necessary for achieving aspiration-level in a higher education management strategy. In the results submitted, the improvement priority for dimensions is based on the measurement of the influences, running in order of tutors for learners (A), skills and competences (B), interaction data to support learning (C), and universal access to global classrooms (D), and which can serve as a reference for the plan of AI-enabled teaching/learning for higher education.
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Background: The global shortage and turnover of nurses is a current challenge. Past studies have shown that nurse job satisfaction may ameliorate nurse shortage. Although there are many studies on the criteria influencing nurses' job satisfaction, few have examined the causal relationships and weight of each criterion from a systematic perspective. Objective: Identify the key criteria and causal relationships that affect nurses' job satisfaction, and help nurse leaders identify high-weight, high-impact dimensions and contextualize them for improvement. Methods: The study developed a hybrid multi-criterion decision-making model, which incorporated the McCloskey/Mueller satisfaction 13-item scale (MMSS-13), and the Decision-Making Trial and Evaluation Laboratory and the Importance-Performance Analysis methods the model was used to analyze key factors of nurse satisfaction and their interrelationships based on the experience of 15 clinical nurse specialists. Results: In MMSS-13's dimension level, "satisfaction with work conditions and supervisor support" (C5) had the highest impact, and "satisfaction with salary and benefits" (C1) had the highest weight. In criteria level, "salary" (C11), "flexibility in scheduling time off" (C24), "maternity leave time" (C31), "opportunities for social contact after work" (C41), and "your head nurse or facility manager" (C51) had high influence under their corresponding dimensions. The "benefits package" (C13) was the top criterion with the highest impact on MMSS-13. Conclusions: This study assessed nurses' job satisfaction from a multidimensional perspective and revealed the causal relationships between the dimensions. It refined the assessment of nurse job satisfaction to help nurse leaders better assess nurse job satisfaction and make strategic improvements. The study found that compensation and benefits had the highest weight in nurses' job satisfaction. Meanwhile, support for family responsibilities and working conditions, and support from supervisors were the cause dimensions of job satisfaction. Among the more detailed criteria, salary, benefits package, maternity leave time, and leadership had a greater impact on nurses' job satisfaction. Nurse leaders should start with these dimensions to achieve efficient improvement of nurses' job satisfaction.
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Job Satisfaction , Nurses , Delivery of Health Care , Employment , Female , Humans , PregnancyABSTRACT
The purpose of this study is first to propose a comprehensive evaluation model for sustainable island tourism, and then to provide guidelines and suggestions for the development thereof. Based on the advantages of using fuzzy set theory, this study’s method included the fuzzy Delphi method (FDM), the decision-making trial and evaluation laboratory (DEMATEL), the analytic network process (ANP), and FDM-DEMATEL-ANP (FDANP). From the literature review results and experts’ surveys, the dimensions of the evaluation criteria for sustainable island tourism are governance, economy and finance, socio-culture, and the environment. Compared with other studies, its major contributions and differences are the governance and finance dimensions, and the evaluation criteria for the marine industry, marine cultures, and marine environments. The findings show that the relative importance of the dimensions from high to low are economy and finance, governance, the environment, and socio-culture. The top five key criteria begin with having an of-ficial administration organization, having a tourism industry, and revenue uncertainties based on public health events. These, along with policies and regulations, and local food and drink, are thought to provide the necessary conditions for sustainable island tourism. The implications for theory and practice and future research directions are discussed. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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The continuation of the environmental deterioration, the coronavirus pandemic, and the financial stagger have invoked the attention of sustainability. Developing sustainable information systems becomes crucial for ensuring the success of enterprise information management and sustainable competitiveness. This study analyzed a set of critical factors for sustainable information systems. Using decision making trial and evaluation laboratory (DEMATEL) method and referring to the theory of practice-based view (PBV), this study constructed a research framework in which the factors reflect the common practices of a sustainable information system. The cause and effect relationships among the factors are illustrated with a discussion of the implications. © 2022 ACM.
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Blockchain (BLC) and the Internet of Things (IoT) are two emerging technologies that have become popular among practitioners for improving the transparency, adaptability, and safety of any industry. This is especially critical for food security, as COVID-19 highlighted the vulnerability of food supply chain (FSC). However, Indian organizations are experiencing problems in implementing the integrated form of BLC-IoT due to limited knowledge and insufficient research. The current study aims to propose a conceptual framework to reduce the impact of adoption barriers against BLC-IoT in FSC. Thirteen key barriers were identified after a thorough literature review and consultation with experts. The relationship among barriers was established using Interpretive structural modeling (ISM) and Decision-making trial and evaluation laboratory (DEMATEL) methods. The analysis shows that the lack of government regulation and workers' low competency significantly influence BLC-IoT adoption. The results also indicate the intricacy of decision-making by demonstrating that 9 of the 13 barriers were a part of the linkage cluster. The study outcome will help practitioners in developing and planning strategies for effective adoption of BLC-IoT in FSC.
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At present, in the face of severe and complex international COVID-19 and the world economic situation, the problems faced by management decision-making are becoming increasingly complex. Therefore, the factor correlation analysis for complex issues is essential for managers to recognize the core of complex things and grasp the main contradictions of things to solve effectively complex social and economic problems. The decision-making trial and evaluation laboratory (DEMATEL), as an effective tool for analyzing the relationship between complex system factors, has received extensive attention from scholars at home and abroad in recent years. Through a systematic study of the relevant literature, the current status and development of DEMATEL are reviewed in the logical order of its operation from five aspects: system structure, evaluation scale, self-dependence among factors, determination of indicators of centrality and causality, and identification of key factors. A comprehensive analysis shows that the main directions of DEMATEL theory needed to be further explored are: the comprehensive integration and organic fit between system hierarchy and DEMATEL analysis methods, the multi-expert differential scale and composite scale in line with the realistic decision-making situation, the in-depth analysis of DEMATEL self-dependency from the interaction process between factors reflecting the dynamic and non-linear characteristics of the system, and the effective solution of the problem of correlating the intrinsic properties of centrality and causality indicators, and the DEMATEL analysis method that considers the interaction of group experts. © 2022, Journal of Computer Engineering and Applications Beijing Co., Ltd.;Science Press. All rights reserved.
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The aim of this study is to investigate the factors that influence the choice of health care for the elderly population after Covid-19. Based on previous studies, the study innovatively adds the influence of the improvement of digital medical technology and the degree of aging-friendly of different hospitals on the choice of medical institutions for the elderly. The study used a combination of literature research, questionnaires, interviews and factor analysis to identify the main factors influencing the choice of healthcare for the elderly. The results of the study showed that the three most important factors influencing older people's choice of medical seeking behavior were their willingness of treatment, community evaluation and the aging-friendly improvements. The data from this study will be used to analysis the pain points of the elderly in seeking medical treatment and to make recommendations to improve their medical experience. It is hoped that this study will provide some ideas for the development of a model of healthcare access for older people, and better guide them in their healthcare seeking behavior. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Purpose>This paper aims to recognise and identify fears of failure in the international entrepreneurship ecosystem and find the effects of these fears on each other to reduce these increasing effects and minimise the mental barriers for potential entrepreneurs. Therefore, this research is beneficial to strengthen international entrepreneurial personality and to reduce the shadows of fears on entrepreneurs’ minds. To address this purpose the international tourism industry has been investigated in the emerging economy of Iran.Design/methodology/approach>This paper is organised based on experts' opinions, and then factors are identified by literature review and are finalised through the Delphi method with a panel of practical and academic experts. These fears are categorised using a questionnaire and factor analysis (FA) technique. The respondents were entrepreneurship students and tourism entrepreneurs. Subsequently, the effect and importance of fears of failure are scored and ranked by some experts. These fears were analysed through decision-making trial and evaluation laboratory (DEMATEL) method. The results presented the effects of fears of failure in the international entrepreneurial in the tourism industry and the relationship amongst them.Findings>The first two fears are respectively “fears of future” which are caused by the unclear situation;and “fear of losing credit” that is due to the importance of “personal relationships” in Iranians culture. As pointed out by results, “fear of future” is the most effective group of factors that may lead to other fears too. This fear seems important in the international entrepreneurial tourism industry because of future ambiguity.Originality/value>This study indicates the relations between groups of fears and offers some practical and applicable solutions to reduce these effects. To the best knowledge of the authors, analysing the relationship between fears amongst the entrepreneurs has not been investigated previously.
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The short food supply chain (SFSC) is an emerging sustainable supply chain practice that facilitates a direct connection between farmers and consumers by eliminating several intermediaries of complex supply chains. The impact of the COVID-19 pandemic on the Agri-food supply chain has increased the need to establish more sustainable food supply chains practices for supporting local communities. This study aims to investigate critical success factors (CSFs) in SFSC impacted by the COVID-19 pandemic. CSFs in SFSC was identified from a comprehensive literature review, followed by a selection of eight CSFs, based on inputs from experts in the agriculture sector for analysis. The influential and prominent CSFs in SFSC and their causal relationships are determined using Grey Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) approach. Individualised and tailored service offered to consumers, organic production by promoting home garden concepts, and direct and ethical relationships between producers and consumers are the most influencing CSFs to implement SFSC impacted by the COVID-19 pandemic. © 2021 IEEE.
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During the difficult time of coronavirus outbreaks, global environmental disasters, and financial turmoil, developing and deploying sustainable information systems is a crucial management task for ensuring the functionality of enterprise information processing and thus sustaining competitiveness. This study develops a set of criteria for sustainable information systems using the decision-making trial and evaluation laboratory (DEMATEL) method. By referring to the theory of knowledge-based view and sustainability, this study constructed a research framework in which the selection attributes reflect core knowledge elements of a sustainable information system. An empirical study was performed using the DEMATEL method with data collected from industry experts. The results conclude a cause and effect relationship of the knowledge factors influencing information system sustainability. The study discovered that the economical aspect is a causal factor of environmental aspect and social aspect for sustainability considerations. Furthermore, commercial IT solution knowledge, eco-design knowledge, and workplace safety and health knowledge are the most influential knowledge components for the economic, environmental, and social aspects of information system sustainability, respectively. © 2021 International Consortium for Electronic Business. All rights reserved.
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Background: Previous systematic reviews and meta-analyses supported the relationship between frailty and risk of acute kidney injury (AKI) in elderly patients. However, few studies evaluated proactive management to wear down AKI risk in such frail populations. Purpose: To understand how AKI risk factors might influence each other and to identify the source factors for clinical decision aids. Methods: This study uses the decision-making trial and evaluation laboratory (DEMATEL) method to establish influential network-relationship diagrams (INRDs) to form the AKI risk assessment model for the elderly. Results: Based on the DEMATEL approach, the results of INRD identified the six key risk factors: comorbidity, malignancy, diabetes, creatinine, estimated glomerular filtration rate, and nutritional assessment. (The statistical significance confidence is 98.423%, which is higher than 95%; the gap error is 1.577%, which is lower than 5%). After considering COVID-19 as an additional risk factor in comorbidity, the INRD revealed a similar influential relationship among the essential aspects. Conclusion: While evaluating the geriatric population, physicians need to pay attention to patients' comorbidities and nutritional assessment; also, they should note patients' creatinine values and glomerular filtration rate. Physicians could establish a preliminary observation index and then design a series of preventive guidelines to reduce the incidence of AKI risk for the elderly.