Influence Weight Research Articles

Psychological resilience factors in intensive care nursing: a hybrid multi-criteria decision-making model

PurposeTo analyze the key factors influencing the psychological resilience of intensive care unit (ICU) nurses during the COVID-19 pandemic and put forward suggestions promoting resilience based on key improvement factors and clinical experience.MethodsData were collected from 35 ICU nurses in a hospital in Zhejiang Province, China, through a questionnaire survey conducted between January and February 2023. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then used to construct and visualize the relationship structure between the factors. The DEMATEL-based Analytical Network Process (DANP) was applied to determine the influential weights of all factors. Finally, the key improvement factors were identified using importance-performance analysis (IPA).ResultsBased on the cause-effect impact network diagram (CEIND), it was concluded that (C11), (C22), and (C32) are the key factors that promote the improvement of psychological resilience among ICU nurses. Additionally, these factors were the key factors that influence psychological resilience. The confidence levels of these results and the gap were 99.6% and 0.4%, respectively, which exceed the threshold value of 95%, indicating good stability. Finally, for the case hospitals, (C13) was identified as the key improvement factor.ConclusionsHospital administrators should support ICU nurses in enhancing their psychological resilience during major epidemics by: (i) Providing training on comprehensive protective measures and nursing skills; (ii) Effectively managing the human resources of nurses in the hospital to reduce their workload; (iii) Increasing social and organizational support for nurses to alleviate anxiety caused by large-scale public health events and improve their psychological resilience.

Digital transition from industry 4.0 to industry 5.0 in smart manufacturing: A framework for sustainable future

Digital transition to Industry 5.0 (I5.0) has finally arrived after Industry 4.0 (I4.0) was offered ten years ago to help address industry flaws in manufacturing. I5.0 is necessary in contemporary business to achieve competitive advantages for a sustainable future. However, despite the importance of I5.0, the critical success factors (CSFs) for the transition from I4.0 to I5.0 have not been explored extensively in the literature. This study develops a model to investigate potential CSFs for the smooth transition from I4.0 to I5.0. The study ensures systems flexibility, then ranks the identified CSFs based on their influential weights and explores their interrelationships. The study adopts the Bayesian best-worst method (B-BWM) to assess the perceptions of several decision-makers from a probabilistic perspective for reducing information loss. The results from this study reflect that CSFs, such as adoption of advanced technology to create value in I5.0 paradigm, high-powered analytical ability for smart manufacturing, cost and funding in transition from I4.0 to I5.0, aligned organizational strategy in transition to I5.0, and security and privacy to ensure effective digital transformation, contribute significantly towards the digital transformation from I4.0 to I.50 in smart manufacturing in the context of steel manufacturing business environment considering the developing countries. The successful implementation of CSFs can help achieve flexibility in the supply chain, contribute to flexible systems and support managers in framing strategies that help them prioritize for an easy transition towards a sustainable future.

Improving linear orthogonal mapping based cross-lingual representation using ridge regression and graph centrality

Orthogonal linear mapping is a commonly used approach for generating cross-lingual embedding between two monolingual corpora that uses a word frequency-based seed dictionary alignment approach. While this approach is found to be effective for isomorphic language pairs, they do not perform well for distant language pairs with different sentence structures and morphological properties. For a distance language pair, the existing frequency-aligned orthogonal mapping methods suffer from two problems - (i)the frequency of source and target word are not comparable, and (ii)different word pairs in the seed dictionary may have different contribution. Motivated by the above two concerns, this paper proposes a novel centrality-aligned ridge regression-based orthogonal mapping. The proposed method uses centrality-based alignment for seed dictionary selection and ridge regression framework for incorporating influential weights of different word pairs in the seed dictionary. From various experimental observations over five language pairs (both isomorphic and distant languages), it is evident that the proposed method outperforms baseline methods in the Bilingual Dictionary Induction(BDI) task, Sentence Retrieval Task(SRT), and Machine Translation. Further, several analyses are also included to support the proposed method.

ASSESSING THE DIFFUSION OF FINTECH INNOVATION IN FINANCIAL INDUSTRY: USING THE ROUGH MCDM MODEL

We develop a conceptual structure to explore how financial technology (FinTech) innovation is being implemented to deal with vague, inconsistent and ambiguous knowledge in actual world. The structure of this study is built upon the technology, organization, environment (TOE) context, which one uses the concept of multi-criteria estimation to measure the significance of FinTech innovation. We develop an integrated MCDM (multiple criteria decision-making) model through rough set theory help administrators obtain a strategic influence relation map for enhancing performance approaching towards the aspiration value. This model involves three steps: primary, we apply this rough number to define group views which reflect upon experts’ real experiences; second, we use the rough DEMATEL-based ANP-(RDANP) to acquire the rough influential weights and rough influential network relationship map (RINRM) based on this TOE structure and its corresponding attributes; finally, we utilize the rough modified VIKOR with the influence to analyze the gap between the performance value and the aspirated level. The empirical case was originated from financial industry in Taiwan. According to the weighting results the expected benefits, technology integration, and competitive pressure were the most important criteria. Our results also illustrate how FinTech innovation can be used for promoting financial services.

Sustainability-aware collaborative service composition and recommendation based on multi-attribute correlations

In the context of network collaborative manufacturing and green manufacturing, some researchers have begun to focus on collaboration-awareness or sustainability-awareness service composition separately. However, service collaboration and sustainable performance are interrelated in the service business implementation, so they should be considered simultaneously when establishing service composition to ensure efficient service delivery. In this study, a sustainability-aware collaborative service composition and service recommendation (SCSR) model is formulated, aiming to pursue maximum customer service quality, as well as the synergy effect and eco-efficiency of combined services. Given the interdependencies inherent in service attributes, DEMATEL (Decision Making Trial and Evaluation Laboratory) is presented to acquire the influential weights for aggregating multiple service attributes into the service decisions. To recommend suitable composite services for core enterprises, NSGA-II with two initialization methods and three neighborhood structures is first proposed to produce high-quality solution sets regarding service composition. Then TODIM (an acronym in Portuguese of Interactive and Multi-Criteria Decision Making) is utilized to evaluate the relative dominance of these service composition alternatives under the psychological behavior of the decision-maker. Numerous experiments demonstrate the effectiveness of the improved NSGA-II in handing the SCSR issue. Furthermore, the necessity of considering attribute interrelationships and synergy effects in service composition is verified.

Social Network Analysis and Stakeholders’ Influence on Moringa Plant Development Potential in Mpwapwa District, Tanzania

District in Dodoma Region Tanzania. The Moringa plant had been regarded as a potential for medicinal and income purposes. A number of stakeholders have been realized to contribute efforts to develop the production of the plant in the district. This paper therefore analyzed the interactive efforts of stakeholders and perceived influence on supporting the cultivation and business of the Moringa plant in the district. A questionnaire survey was carried out among 30 Moringa plant farmers. The influence of stakeholder was analyzed using Social Network Analysis (SNA) to investigate the extent of interaction in the business network. Ten (10) potential stakeholders were identified and categorized as Religious, Commission Agents, International actors, Local Authority and Entrepreneurs. Degree of centrality was used as a measure of the real influence of Moringa plant stakeholders. Findings show that all stakeholders played roles with different influential weights. There was a noticeable interaction and cooperation among stakeholders in coordinating Moringa plant activities, especially on technical, financial and material support. A multilevel interaction and cooperation of domestic and foreign stakeholders was realized. Therefore, by strengthening the coordinated efforts of stakeholders, applying feasible economic and policy approaches would be appropriate initiatives to scale-up the Moringa plant in a more positive economic promise.

Consumers' switching intention towards E-commerce platforms’ store-to-store pickup services: The application of the extended PPM model

The knowledge of the preference of innovative service consumers is crucial for e-commerce platforms to boost profit, gain a competitive advantage, and achieve remarkable growth. In this research, the consumer's viewpoint was applied. Furthermore, the extended Push-Pull-Mooring (PPM) model was integrated into the multi-attribute decision-making (MADM) approach to investigate the elements impacting the consumers' attempt of shifting to the store-to-store pickup service developed by e-commerce platforms. Besides, the development of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) was for the investigation into the reciprocal effects of evaluation dimensions and factors and the development of an influential network relation map (NRM). The DEMATEL-based Analytic Network Process (DANP) was used to calculate the influential weights of these dimensions and factors. It could be seen from the NRM that the first dimension that required improvement and adjustment ought to begin with a push and subsequently a pull, mooring, switching intentions, and inertia. The influential weights from the DANP highlighted inertia as the most impactful dimension, with mooring coming in second. Meanwhile, push held the lowest significance. The next discussion focuses on the theoretical, managerial and practical implications.

Cytokine profiles are associated with prolonged hematologic toxicities after B-cell maturation antigen targeted chimeric antigen receptor–T-cell therapy

Background aimsThe considerable efficacy of B-cell maturation antigen–targeted chimeric antigen receptor (CAR)–T-cell therapy has been extensively demonstrated in the treatment of relapsed or refractory multiple myeloma. Nevertheless, in clinical practice, prolonged hematologic toxicity (PHT) extends hospital stay and impairs long-term survival. MethodsThis retrospective study reviewed 99 patients with relapsed or refractory multiple myeloma who underwent B-cell maturation antigen CAR–T-cell therapy at our institution between April 2018 and September 2021 (ChiCTR1800017404). ResultsAmong 93 evaluable patients, the incidence of prolonged hematologic toxicities was high after CAR–T-cell infusion, including 38.71% (36/93) of patients with prolonged neutropenia, 22.58% (21/93) with prolonged anemia and 59.14% (55/93) with prolonged thrombocytopenia. In addition, 9.68% (9/93) of patients experienced prolonged pancytopenia. Our multivariate analyses identified that cytokine profiles were independent risk factors for PHTs, whereas a sufficient baseline hematopoietic function and high CD4/CD8 ratio of CAR-T cells were protective factors for PHTs after CAR–T-cell infusion. Subgroup analyses found that the kinetics of post-CAR-T hematologic parameters were primarily determined by the collective effects of cytokine release syndrome and baseline hematopoietic functions, and showed influential weights for the three lineages. ConclusionsOur findings improve the understanding of the impact of cytokines on hematopoietic functions, which could contribute to the mechanism investigation and exploration of potential intervention strategies.

Finding interrelationships and influential weights of selected key performance indicators: important considerations in developing an overall performance index for water supply systems

Finding interrelationships and influential weights of selected key performance indicators: important considerations in developing an overall performance index for water supply systems

The DEMATEL method explores the interdependent relationship structure and weights for diagnosis-related groups system.

PurposeThis study constructs a structure of interaction between dimensions and criteria within the diagnosis-related groups (DRGs) system from a quantitative system and identifies key factors affecting the overall performance of medical services.MethodFrom September to December 2020, the influence relation structure diagram (IRSD) of the dimensions and corresponding criteria was developed from the practical experience of a group of domain experts, based on the DEMATEL method. Subsequently, all dimensions and criteria construct influential weights from a systems perspective. Finally, the main influential factors were identified based on the analysis results.ResultsThe IRSD results showed that, in the overall performance of medical services, “Medical service capacity (C1)” was the main influential dimension, influencing both “Medical service efficiency (C2)” and “Medical service safety (C3).” At the criteria level, “Case-mix index (CMI) (C12),” “Time efficiency index (C21),” and “Inpatient mortality of medium-to-low group (C32)” were the main influential criteria in the corresponding dimensions. The influential weight results showed that “Medical service capacity (C1)” was also a key dimension. “Case-mix index (CMI) (C12),” “Cost efficiency index (C22),” and “Inpatient mortality of medium-to-low group (C32)” were the key criteria in their respective dimensions.ConclusionPatients and managers should first focus on the capacity of medical service providers when making a choice or deciding using the results of the DRGs system. Furthermore, they should pay more attention to medical safety even if it is not as weighted as medical efficiency.

Which food delivery platforms are winning the restaurant food delivery wars? Analysis from a consumer perspective

AbstractThe emergence of the COVID‐19 pandemic dramatically lowered the foodservice industry's income overnight. Conversely, the practical measure of remaining at home to deal with the pandemic's impact has boosted the online food delivery business. In this study, a consumer perspective was adopted and an adapted version of the extended unified theory of acceptance and use of technology (UTAUT2) was used alongside multi‐attribute decision‐making methods (DEMATEL, DANP and modified VIKOR) to construct a model for evaluating and selecting a food delivery platform (FDP). The results of the INRM (influential network relation map) revealed that the first dimension to be improved upon and adjusted should be security, followed by effort expectancy, performance expectancy, social influence, facilitating conditions, hedonic motivation and habit. The DANP influential weights suggested that habits were the most important dimension, followed by hedonic motivation, while performance expectancy was the least important. According to the results of the gap analysis, the first dimension that required improvement was performance expectancy, followed by effort expectancy, facilitating conditions, security, social influence, habits and hedonic motivation. It is expected that the findings of this study can serve as a reference for consumers selecting FDPs to better satisfy their dining needs. The novel model is discussed in terms of theoretical, practical and managerial implications.

Performance Index Model of River and Infrastructure

The study of river performance and infrastructure is not only conducted qualitatively. An instrument is needed to examine the object being observed quantitatively (usually with a minimum and maximum number scale interpretation). The review of the physical condition assessment for the river performance index and river infrastructure has not been developed based on a study of the variables that influence it. Therefore, this study aims to develop a mathematical model of the index of river performance and infrastructure as a decision support system for the integration of programs and activities related to river management. The research location was chosen based on the consideration that there has been no preparation of a performance index model in the Babon River. In this study, the authors use the Smart-PLS (Partial Least Square) application to analyze and narrow the variables and then re-analyze them using the Generalized Reduced Gradient (GRG) method to calculate non-linear equations. There are four variables, eight dimensions, and 51 (indicators) used, with the types of technical, spatial, social, and regulatory variables. Based on the PLS-SEM analysis, the results were narrowed into 4 (four) variables, 8 (eight) dimensions, and 51 (fifty one) indicators that were interrelated with one another. The GRG (Generalized Reduced Gradient) analysis with the solver in Microsoft Excel showed the most influential weights consisting of: technical variables, namely rivers (0.475) and flood problems (0.582); spatial variables, namely land use (0.418) and land cover (% Urban) (0.498); social variables, namely community activities (0.454), settlement density and socio-cultural conditions (0.289), and community participation (0.257); and regulation variables, namely law enforcement efforts (1.000). This research can be used for other watersheds with conditions or characteristics relatively similar to the Babon River. However, research related to this formulation on other watershed conditions still needs to be done.

PERFORMANCE INDEX MODEL OF GROUNDWATER IRRIGATION SYSTEMS

This research will develop a groundwater irrigation system performance index model with the aim of identifying the groundwater irrigation system performance index; this information can be used by stakeholders to determine management steps. The research location is in Gunungkidul Regency and includes surrounding areas — acknowledging that the karst aquifer has complex characteristics and non-karst aquifer, namely high heterogeneity as a result of the formation of a groundwater flow system through fractures which eventually becomes completely underground runoff. Screening for the variables was carried out using the smart-PLS (Partial Least Square) tool, which was then analyzed using the GRG (Generalized Reduced Gradient) method which is useful for solving non-linear equations. In this research, it examines the physical aspects, social aspects and management aspects as variables. The groundwater irrigation system performance index model examines 3 (three) variables, namely physical aspects, social aspects, and management aspects, then 11 (eleven) dimensions and 42 (forty two) indicators. The analysis using PLS SEM using smart PLS tools determined that the 3 (three) variables, 11 (eleven) dimensions and 30 (thirty) indicators are interrelated and effective. Whereas by using GRG (Generalized Reduced Gradient) analysis with the solver tool in Microsoft Excel, the most influential weights were obtained from the physical aspects, namely physical infrastructure (0.5782), geological conditions (0.2311), water quality (0.1286) and recharge area conditions (0.0475); the social aspects that obtained the most influential weight are socio-cultural (0.7471) and economy (0.2529); the management aspects that obtained the most influential weights are budgeting (0.2534), plant productivity (0.2270), WUA organizational conditions (0.2090), JIAT management organizational conditions (0.1987) and spatial planning directives (0.0674). In general, the weight of the influence of groundwater irrigation performance for these three aspects is 0.6686 physical aspects, 0.0856 social aspects and 0.2458 management aspects which are formulated into a performance index model for groundwater irrigation systems "Kautsar", namely IL = 0.6686 physical IL + 0.0856 social IL + 0.2458 IL management. For development, further research is needed on the performance index model of the groundwater irrigation system using Geography Information System (GIS) and a software application on android, iOS, or windows operation systems. A groundwater irrigation system performance index that consists of these three aspects is unique and has never been assembled in previous studies; it conveniently allow the user to determine survey results immediately.

Evaluating biometrics by using a hybrid MCDM model

Biometrics has been developing for decades in diverse industries, such as consumer electronics, internet of things, financial industry, etc. The purpose of this research is to build a decision-making model to evaluate and improve the performances of biometrics for administrators to design and make suitable biometric systems. This paper adopts a hybrid multiple criteria decision making (MCDM) model, comprising decision-making trial and evaluation laboratory (DEMATEL), and DEMATEL-based analytic network process (called DANP) to probe into the interrelationship and influential weights among criteria of biometrics. According to DEMATEL technique, the empirical results indicate that criteria of biometrics have self-effect relationships. The dimension of biometrics that administrators of biometrics should enhance first when improving the performances is usability. The criterion of universality with the highest influencing value to systematically affect all other evaluation factors is what administrators of biometrics should comprehensively consider. In the top three criteria for evaluation by DANP, biometric systems with the most influential weight is the criterion that can be improved to have higher recognition rates for increasing the performances of biometrics, followed by biometric conditions and permanence.

Key Factors Influencing Talent Retention and Turnover in Convenience Stores: A Comparison of Managers’ and Employees’ Perspectives

This study identifies the main factors influencing turnover among convenience store employees from a managerial perspective and infers the changes necessary to reduce such high turnover rates. Employing the decision-making trial and evaluation laboratory (DEMATEL) methodology, it investigates the degree of mutual influence between evaluation indicators and constructs a network relation map for evaluation dimensions and criteria. This study also uses the DEMATEL-based analytic network process method to compute the influential weights of each dimension and criteria. According to the empirical results of the causality model, convenience store employees must first improve the relatedness dimension, and managers must first improve the existence dimension. These findings can help convenience store managers address talent retention and turnover problems, develop effective strategies to lower the high turnover rates at convenience stores, and offer solutions to new industry entrants to avoid potential problems that might lead to early exit.

Improving the Identification and prioritization of the most important risks of safety equipment in FMEA with a hybrid multiple criteria decision-making technique

The purpose of this paper is to develop a new Failure Mode and Effect Analysis (FMEA) framework for identification, prioritization and improvement of failure modes. A hybrid multiple criteria decision-making (MCDM) method combining Stepwise Weight Assessment Ratio Analysis (SWARA) and VlseKriterijumska optimizacija I KOm-promisno Resenje (VIKOR) is used to rank the risk of failure modes identified in FMEA. For this purpose, the SWARA method is utilized to obtain the influential weights and then VIKOR technique is employed to give the prioritization levels for the failure modes in safety equipment. A case study of a gas company in Lorestan Province (Iran) is provided to illustrate the potential application and benefits of the proposed FMEA approach. The obtained results show that the new risk priority model can be effective to find high risk failure modes and create suitable maintenance strategies. The proposed FMEA also can overcome the shortcomings, improve the effectiveness of the traditional FMEA and provide useful information to help in managing risks of safety equipment.

Environmental Design Strategies to Decrease the Risk of Nosocomial Infection in Medical Buildings Using a Hybrid MCDM Model.

The prevention and control of nosocomial infection (NI) are becoming increasingly difficult, and its mechanism is becoming increasingly complex. A globally aging population means that an increasing proportion of patients have a susceptible constitution, and the frequent occurrence of severe infectious diseases has also led to an increase in the cost of prevention and control of NI. Medical buildings' spatial environment design for the prevention of NI has been a hot subject of considerable research, but few previous studies have summarized the design criteria for a medical building environment to control the risk of NI. Thus, there is no suitable evaluation framework to determine whether the spatial environment of a medical building is capable of inhibiting the spread of NI. In the context of the global spread of COVID-19, it is necessary to evaluate the performance of the existing medical building environment in terms of inhibiting the spread of NI and to verify current environmental improvement strategies for the efficient and rational use of resources. This study determines the key design elements for the spatial environment of medical buildings, constructs an evaluation framework using exploratory factor analysis, verifies the complex dominant influence relationship, and prioritizes criteria in the evaluation framework using the decision-making trial and evaluation laboratory- (DEMATEL-) based analytical network process (ANP) (DANP). Using representative real cases, this study uses the technique for order preference by similarity to ideal solution (TOPSIS) to evaluate and analyze the performance with the aspiration level of reducing the NI risk. A continuous and systematic transformation design strategy for these real cases is proposed. The main contributions of this study include the following: (1) it creates a systematic framework that allows hospital decision-makers to evaluate the spatial environment of medical buildings; (2) it provides a reference for making design decisions to improve the current situation using the results of a performance evaluation; (3) it draws an influential network relation map (INRM) and the training of influence weights (IWs) for criteria. The sources of practical problems can be identified by the proposed evaluation framework, and the corresponding strategy can be proposed to avoid the waste of resources for the prevention of epidemics.

Improving the urban heritage based on a tourism risk assessment using a hybrid fuzzy MADM method: The case study of Tehran's central district

AbstractA primary reason for the failure of renewal plans for the heritage of urban areas is ignorance of the risk factors of tourism. Urban heritage sites are valuable tourism resources and focus on tourism activities. These sites are affected by risks and negative events. Assessing tourism risks requires an in‐depth knowledge of the current situation. Thus, in order to reduce the risk of tourism on urban heritage, it is necessary to assess the risk of tourist destinations. This study assesses the urban heritage of central districts in Tehran with an emphasis on tourism risk as a real case study. This study provides an in‐depth review of the dimensions and criteria for evaluating tourism risks from the perspectives of social culture, environment, finance, safety and security. Fourteen criteria developed on the basis of the fuzzy decision‐making trial and evaluation laboratory (FDEMATEL) method are adopted for this assessment to construct the fuzzy influential network relation map and find the fuzzy influential weights; this is known as the DEMATEL‐based analysis network process (called DANP). The hybrid modified fuzzy VIKOR method is adopted to evaluate and reduce the tourism risk towards for closing the gap zero. Finally, an empirical case of Tehran city illustrates the availability and effectiveness of the proposed methods. The results revealed that safety and security risks have the greatest influence. The remaining dimensions are sociocultural, financial, and environmental risks. According to the model and the results of the risk assessment in tourism, this method is a reasonable solution for the assessment and risk analysis in real‐world problems. The proposed method can be a useful tool for managers in tourism and urban planning.

A Hybrid MADM Model for Newly Graduated Nurse's Competence Evaluation and Improvement.

Nursing departments in hospitals must evaluate the practical competency of newly graduated nurses and assist them to increase their competence. Competency assessments often consider multiple qualitative attributes and use expert knowledge as the basis for decision-making. This study proposes a hybrid multiple attribute decision-making (MADM) model that determines practical competency of the newly graduated nurse as an evaluation framework. A causal influence-network diagram (CIND) and influential weights are obtained from nursing experts' clinical experience using the decision-making trial and evaluation laboratory (DEMATEL)-based analytical network process analysis (DANP). The MOORA-AS method is then used to evaluate the ability expectation ratio-gap for newly graduated nurses in practice. The CIND is used to allow each newly graduated nurse to reduce the performance ratio-gaps between the current level and the aspirational level from a systematic perspective. The empirical data applies to a third-class and a first-class hospital in China. The results show that the proposed hybrid MADM model has reliable results and allows nursing department decision-makers/managers to easily evaluate and systematically improve competencies for newly graduated nurses.

Entertainment in retailing: Challenges and opportunities in the TV game console industry

This study investigates the key development evaluation indicators of the TV game console industry based on the four dimensions of Saaty's ‘benefits, opportunity, costs, and risks’ model. The hybrid multiple attribute decision-making model is employed to create a new evaluation approach. The proposed hybrid model uses the decision-making trial and evaluation laboratory (DEMATEL) to determine the influential relationships among dimensions and criteria, the DEMATEL-based analytic network process to obtain influential weights, and the modified VlšeKriterijumska Optimizacija I Kompromisno Resenje method to assess performance gaps in industry development. The influential network relationship map and influence weights help TV game console firms' managers understand the industry's complex assessment system and set priorities for improving the industry's performance. The results of the study indicate that the improvement priorities of the model's dimensions have the following order: benefits, opportunity, costs, and risks. Several implications for the industry's management are also discussed.