Identification of critical quality factors and critical satisfaction gaps in emergency training courses for new nurses by the multi-criteria network structure model.

OBJECTIVE: To identify critical quality factors and critical satisfaction gaps in emergency training courses for new nurses through a systematic decision-making model. METHODS: Firstly, the service quality (SERVQUAL) was used in the evaluation index system of this study. Then, the decision-making trial and evaluation laboratory (DEMATEL) method was used to analyze the relationship structure and the corresponding weights between the indicators. Finally, the importance-performance analysis (IPA) method was used to identify the categories of all indicators and the corresponding strategic directions. Fifteen new nurses in Taizhou Hospital of Zhejiang Province were selected as participants in this study. RESULTS: The IPA results showed that "(C13)," "(C22)," "(C52)," "(C53)," "(C54)," "(C55)," "(C56),"and "(C57)" are critical satisfaction gaps. From the results of influence network and weight, empathy (C5) was the critical quality factor of the entire training course. The influence network relationship structure and weight had a 98.1% significant confidence level, indicating good stability. CONCLUSION: Teachers' empathy is key to the learning outcomes of new nurses in emergency nursing training courses. Hence, teachers should be attentive to the empathetic quality of their teaching methods to help new nurses gain knowledge and experience in emergency care, especially when they come from different professions and departments.

Assessment and improvement of wetlands environmental protection plans for achieving sustainable development.

Although wetland environmental protection plans are synonymous with wetland management and erosion control plans, the public perceptions of such plans often focus on their impact on the human enjoyment of wetland areas. These plans are affected by many interrelated influence factors, such as human welfare, property, safety, management, operations, maintenance, ecology, environment, artificial structures, climate control, and sustainable development. The purpose of this paper is to probe how to use qualitative and quantitative measurements of wetland environments to create plan indexes using criteria/attributes as well as how to help these indexes for achieving the aspiration levels in each criterion/attribute. Previous studies that attempted to measure environmental evaluations and plans have assumed that these criteria are independent, but this assumption does not hold in real-world applications of real problems. Therefore, in this proof-of-concept study, using an empirical exam among various attributes and to measure and evaluate the real conditions for improving the wetland environmental problems. A DEMATEL technique can be used to construct the INRM, the basic concept of an ANP was modified to determine the influential weights of criteria/dimensions in our research alternative, called DANP (DEMATEL-based ANP). Then we can construct a decision-making model via a hybrid modified VIKOR method to improve wetlands environmental management manager strategy formulation in performance evaluation toward for achieving the aspiration level. Using these techniques, a proposed model appeared, which can be used to explain interdependence and feedback problems. Based on the final results, we can also propose a gap improvement in the development of a sustainable development plan for the environment while taking comfort and safety into account to improve standards and achieve human welfare expectations.

Mechanism and early warning of coal mine rockburst accident based on SD-STAMP-DEMATEL.

As coal mines shift from shallow to deeper excavation, the number of mines facing the risk of rock burst disasters is gradually increasing. Rockburst, with their characteristics of vibration, suddenness, complexity, and unpredictability, make it increasingly difficult to prevent and control these disasters. Therefore, the challenges of preventing and controlling rock burst disasters are becoming more and more severe. This paper, based on the system-theoretic accident model and processes (STAMP) theory, extracts the causal factors affecting coal mine rock burst accidents. Using the interpretative structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) method, the accident-causing factors are quantitatively assigned. By constructing model equations and drawing causal loop diagrams and stock-flow diagrams, the event is dynamically simulated and early warnings are issued. The results show that the control defects leading to the accident are analyzed from the perspectives of the government level, management level, grassroots level, physical layer, and the dynamic process of the accident. In the short term, safety investment in grassroots operations is the most effective control. In the long run, the most effective measure is for the management level to strengthen its supervisory work. By changing the input ratios of various variables, it can be seen that different variables in the system dynamics (SD) model have different impacts on coal mine rock burst accidents. It is necessary to continuously strengthen the implementation of the safety responsibility system, improve the work efficiency of the government and management level, and enhance the timeliness of emergency decision-making.

Assessing evidence-based practice competencies of undergraduate nursing students using a developed multi-criteria decision-analysis model.

AIM: The developed multi-criteria decision analysis model was used to identify the inter-influence relationships and key factors affecting the EBP competencies of UNSs, to assess the EBP competencies of UNSs and based on these results, to formulate an improvement strategy to enhance the EBP competencies of UNSs. BACKGROUND: EBP is considered a core competency in international nursing practice. However, few studies have developed EBP evaluation models and applied them to assessing and improving the EBP competencies of UNSs. DESIGN: This is a quantitative study with multi-criteria decision-analysis model. METHODS: Firstly, the questionnaire was designed based on the characteristics of the DEMATEL and VIKOR-AS methods, which was completed by 17 nursing experts from a case hospital in Zhejiang Province, China. Subsequently, the DEMATEL method was used to analyze the inter-influence relationships among various criteria to determine their respective weights. Finally, the VIKOR method is utilized to integrate multiple criteria and their relative weights to assign comprehensive scores to each UNSs. RESULTS: The use of the DEMATEL method reveals that "Knowledge (C1)", "Mastering the basic scientific research methods during the study of the undergraduate courses (C11)", "Being able to consult clinical experts appropriately when encountering problems in clinical practice (C23)" and "Understanding the importance of reading journals related to the nursing profession regularly (C34)" were critical influencing factors. "Skill (C2)," "Being able to explain the essential roles of the best research evidence in determining clinical practice (C15)," "Being able to apply the collected research evidence to the individual case in nursing care (C25)" and "Paying attention to using the evidence-based nursing practice concept to determine the best clinical practice (C35)" were the most influential factors. According to the VIKOR method, the performance of the UNSs in the case hospitals in terms of EBP competencies from highest to lowest was Student C, Student B and Student A. However, all of these students suffered from deficiencies at the knowledge level. CONCLUSIONS: The application of the DEMATEL and VIKOR methods provides a systematic and comprehensive approach to the assessment of EBP competencies of UNSs. The lack of EBP competencies of UNSs in case hospitals is mainly reflected in knowledge level. To improve UNSs' EBP competencies, medical schools and hospital educators should propose short- and long-term strategies to improve knowledge.

Key Factors for Enhancing Home Care Workers' Intention to Stay by Multiple-Criteria Decision Analysis.

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.

Exploring the restrictive factors for the development of the construction waste recycling industry in a second-tier Chinese city: a case study from Jinan.

Recycling construction waste in urban cities has attracted wide attention in the government department and building industry worldwide owing to numerous benefits in economics, the environment, and society for sustainable development. Most of the research was focused on the scope of first-tier/new first-tier cities. At the same time, less attention has been paid to second-tier cities, which should be further considered because of their significant potential for increasing construction waste. Jinan is one of the pilot cities for construction waste treatment in China. This city has been chosen as the case in this study to explore critical restrictive factors for developing the construction waste recycling industry (CWRI) in second-tier cities with the adoption of combined methods of the DEMATEL-ISM-EWM. It was revealed by the results that (1) the government is the main stakeholder. In addition, the legislation, management system, incentive/support for stakeholders, and technical standards were closely associated with CWRI development in Jinan. Low landfill fees and natural ore tax rates are unique and vital restrictive factors that should receive more attention. (2) Other key restrictive factors that should be given priority were (i) the lack of green design for designers, (ii) poor classification and management of construction waste for constructors on site, (iii) tight operating funds and insufficient publicity for recycling enterprises, and (iv) insufficient research funds for research institutions. Finally, a comparison of the similarities and differences of the restrictive factors on CWRI development between second-tier and first-tier/new first-tier cities was conducted, and a series of reasonable suggestions were provided, considering the perspective of stakeholders. The research will offer a valuable reference for industry practitioners and academics interested in CWRI.

Analyzing causes of urban blight using cognitive mapping and DEMATEL.

Blight is a concept not commonly discussed. However, blight is a problem that exists in the lives of many people, especially if they reside in urban areas. Blight originates whenever properties are neglected, contributing to both a functional and social depreciation process and ultimately leading to uninhabitable dwellings. Despite being blighted, these properties and surrounding neighborhoods often are occupied by families who fail to have sufficient income to afford residences that meet minimum standards or to live in neighborhoods free from drug trafficking and prostitution or other forms of crime. Blight may spread rapidly, thus, experts must, in a timely manner, analyze its causes, which are essential to preventing and mitigating blight problems. The purpose of this study is to seek an understanding of blight and identify its causal factors. The generic methods commonly applied in previous blight research present limitations that this study aims to overcome by using cognitive mapping and the decision making trial and evaluation laboratory (DEMATEL) technique. This dual methodology provides a more transparent and less restrictive approach for analyzing and complying with the dynamics of cause-and-effect relationships among variables. Group debate involving a panel of specialists in this field identified six causation clusters based on the experts' experience and knowledge. The resulting framework and its application were validated both by these specialists and the head of the Territorial and Environmental Assessment and Monitoring Division of Cascais City Council Strategic Planning Department, Portugal.

Artificial intelligence and change management in small and medium-sized enterprises: an analysis of dynamics within adaptation initiatives.

Given the increasingly significant role of small and medium-sized enterprises (SMEs) in the global economy and the ever more competitive markets in which these companies operate, SMEs' ability to adopt artificial intelligence (AI) technologies is of utmost importance. Due to constantly evolving social, environmental, and technological scenarios, the managers of these firms must increasingly focus on incorporating new tools such as AI into SME operations in order to enjoy their benefits. However, the subjectivity and complexity of this adaptation process makes integrated analyses of key factors challenging. The present study sought to develop a multi-criteria decision-support system that applies cognitive mapping and the decision-making trial and evaluation laboratory technique in a neutrosophic context. The main objective is to overcome the limitations of previous studies and models by structuring the decision problem and identifying and understanding which factors should be central to adaptation initiative analyses. A panel of experts in AI were recruited to facilitate the construction of an analysis system that takes into account indeterminacy in decision-making processes. The results were validated by both the panel members and project managers at COTEC Portugal-a leading think-and-action network that seeks to advance technology diffusion and business innovation cooperation. The proposed system's practical implications and benefits are also analyzed.

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

Purpose: This 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. Method: From 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. Results: The IRSD results showed that, in the overall performance of medical services, "Medical service capacity (C 1)" was the main influential dimension, influencing both "Medical service efficiency (C 2)" and "Medical service safety (C 3)." At the criteria level, "Case-mix index (CMI) (C 12)," "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 (C 1)" was also a key dimension. "Case-mix index (CMI) (C 12)," "Cost efficiency index (C 22)," and "Inpatient mortality of medium-to-low group (C 32)" were the key criteria in their respective dimensions. Conclusion: Patients 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.

Application of a Hybrid Multi-Criterion Decision-Making Model for Evaluation and Improvement of Nurses' Job Satisfaction.

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.

A Novel Integration of IF-DEMATEL and TOPSIS for the Classifier Selection Problem in Assistive Technology Adoption for People with Dementia.

The classifier selection problem in Assistive Technology Adoption refers to selecting the classification algorithms that have the best performance in predicting the adoption of technology, and is often addressed through measuring different single performance indicators. Satisfactory classifier selection can help in reducing time and costs involved in the technology adoption process. As there are multiple criteria from different domains and several candidate classification algorithms, the classifier selection process is now a problem that can be addressed using Multiple-Criteria Decision-Making (MCDM) methods. This paper proposes a novel approach to address the classifier selection problem by integrating Intuitionistic Fuzzy Sets (IFS), Decision Making Trial and Evaluation Laboratory (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The step-by-step procedure behind this application is as follows. First, IF-DEMATEL was used for estimating the criteria and sub-criteria weights considering uncertainty. This method was also employed to evaluate the interrelations among classifier selection criteria. Finally, a modified TOPSIS was applied to generate an overall suitability index per classifier so that the most effective ones can be selected. The proposed approach was validated using a real-world case study concerning the adoption of a mobile-based reminding solution by People with Dementia (PwD). The outputs allow public health managers to accurately identify whether PwD can adopt an assistive technology which results in (i) reduced cost overruns due to wrong classification, (ii) improved quality of life of adopters, and (iii) rapid deployment of intervention alternatives for non-adopters.

Analysis of coal mine occupational disease hazard evaluation index based on AHP-DEMATEL.

The main purpose to analysis the occupational-disease-inductive index in coal mine is to protect the life and health of the workers and reduce the losses caused by it. According to the occupational-disease-inductive factors "produce source-cause factors-function object" to analyze the whole process of occupational disease hazard control in coal mine, determined the occupational-disease-inductive factors cause of coal mine. Then, the occupational disease hazard of coal mine based on the energy release cause model was established, built the evaluation index system of coal mine occupational disease hazard. The AHP-DEMATEL evaluation model was used to analyze the indicators. Combined with the application of case study, the evaluation results were in good agreement with the actual situation of occupational hazard management in coal mines. It indicated that the indicator system has a strong generalization and adaptability.

Exploration of the Relationship Among Key Risk Factors of Acute Kidney Injury for Elderly Patients Considering Covid-19.

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.

Exploring the Key Factors of Shared Decision-Making Through an Influential Network Relation Map: The Orthopedic Nurse's Perspective.

BACKGROUND: Few studies have used quantitative methods to explore the key factors affecting shared decision-making (SDM) in nursing decision-making from the perspective of orthopedic nurses. PURPOSE: To understand the intercorrelations among shared decision-making questionnaire-nurse (SDM-Q-NUR) factors and identify key factors for clinical nursing care decisions in orthopedics. METHODS: In May 2021, this study investigated the interdependence of the SDM-Q-NUR scale and developed an influential network-relation map (INRM) from the clinical experience of 13 trained orthopedic nurses using the Decision-making Trial and Evaluation Laboratory method. RESULTS: The INRM results showed that the nine criteria corresponded to three stages: preparation, discussion, and decision. "I helped my patient or patient's family understand all the information" (C 5) and "I wanted to know from my patient or patient's family how they want to be involved in making the nursing care decision" (C 2) are the main key factors for the beginning of nursing decision. In the discussion and decision stages, the corresponding key factors are "I made it clear to my patient or patient's family that a nursing care decision needs to be made" (C 1) and "I asked my patient or patient's family which nursing care option they prefer" (C 6). The result's statistical significance confidence and gap error were 98.106% and 1.894%, respectively. CONCLUSIONS: When making nursing decisions with patients, orthopedic nurses need to have detailed information about how patients are involved in SDM and all relevant information. Nurses should also inform patients and their families regarding the purpose of the discussion, namely, to help one understand the content, advantages, and disadvantages of the nursing care options, and finally, make a decision.

Three-stage model based evaluation of local residents' acceptance towards waste-to-energy incineration project under construction: A Chinese perspective.

Incineration is an efficient and economical means of solid waste disposal. And local residents' acceptance has to be acquired for the smooth going of waste-to-energy incineration project (WTEIP). From a Chinese perspective, this paper finds what influence local residents' acceptance towards WTEIP under construction, based on which we rank WTEIPs and figure out the project with the least local residents' acceptance. To achieve this, a three-stage model is developed. Stage 1 involves identifying the criteria based on the expert judgement for local residents' acceptance towards WTEIP under construction. Stage 2 involves the criteria weights determination employing Best Worst-Decision Making Trial and Evaluation Laboratory (BWD). BWD incorporates Best Worst Method and Decision Making Trial and Evaluation Laboratory which is intended to take the interrelationships among the criteria into account. Stage 3 involves project ranking according to the criteria weights determined by BWD. Sensitivity analysis is conducted to check the effectiveness and robustness of the three-stage model. Results show that perceived risk-free is the most influential criterion of local residents' acceptance towards WTEIP under construction and the three-stage model is reliable and robust. The study is helpful to enhance local residents' acceptance towards WTEIP under construction and provide important reference for decision-makers and policymakers in waste management.

Strategies for Heterogeneous R&D Alliances of In Vitro Diagnostics Firms in Rapidly Catching-Up Economies.

Most developed countries already have high-quality in vitro diagnostic (IVD) techniques for diseases, but developing countries often do not have access to these technologies and cannot afford them. Enabling firms to leverage external resources to optimize their research and development (R&D) performance has become one of the most critical issues for small and medium-sized late-coming IVD firms. R&D alliances, especially heterogeneous alliances, are necessary for releasing the resource limitations of late-coming small and medium-sized enterprises (SMEs) and reaching the metaoptimum of the R&D performances. However, to the authors' knowledge, a few, if any, previous studies have investigated the key success factors and strategies of heterogeneous alliances in the IVD industry. Therefore, the authors aim to define the critical factors for evaluating and selecting strategies for heterogeneous alliances in the IVD industry. A Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based analytic network process (DANP) was proposed to prioritize the weights associated with the evaluation criteria. Then, a heterogeneous R&D alliance strategy was derived from the compromise ranking based on the modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. An empirical study of major Taiwanese IVD firms' evaluation and selection of heterogeneous R&D alliance strategies will be used to reveal the practicability of the analytic framework. Based on the analytic results, the joint venture strategy is the most suitable heterogeneous R&D alliance strategy for IVD firms in rapidly catching-up economies. These results can serve as the basis for heterogeneous R&D alliance strategy definitions in the IVD industry in the future.

An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers.

In recent years, IoT (Internet of Things)-based smart devices have penetrated a wide range of markets, including connected health, smart home, and wearable devices. Among the IoT-based smart devices, wearable fitness trackers are the most widely diffused and adopted IoT based devices. Such devices can monitor or track the physical activity of the person wearing them. Although society has benefitted from the conveniences provided by IoT-based wearable fitness trackers, few studies have explored the factors influencing the adoption of such technology. Furthermore, one of the most prevalent issues nowadays is the large attrition rate of consumers no longer wearing their device. Consequently, this article aims to define an analytic framework that can be used to explore the factors that influence the adoption of IoT-based wearable fitness trackers. In this article, the constructs for evaluating these factors will be explored by reviewing extant studies and theories. Then, these constructs are further evaluated based on experts' consensus using the modified Delphi method. Based on the opinions of experts, the analytic framework for deriving an influence relationship map (IRM) is derived using the decision-making trial and evaluation laboratory (DEMATEL). Finally, based on the IRM, the behaviors adopted by mass customers toward IoT-based wearable fitness trackers are confirmed using the partial least squares (PLS) structural equation model (SEM) approach. The proposed analytic framework that integrates the DEMATEL and PLS-SEM was verified as being a feasible research area by empirical validation that was based on opinions provided by both Taiwanese experts and mass customers. The proposed analytic method can be used in future studies of technology marketing and consumer behaviors.

Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach.

Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner. In this paper, we propose a hybrid multiple criteria decision making (MCDM) approach to identify key performance indicators (KPIs) for holistic hospital management. First, through integrating evidential reasoning approach and interval 2-tuple linguistic variables, various assessments of performance indicators provided by healthcare experts are modeled. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is adopted to build an interactive network and visualize the causal relationships between the performance indicators. Finally, an empirical case study is provided to demonstrate the proposed approach for improving the efficiency of healthcare management. The results show that "accidents/adverse events", "nosocomial infection", ''incidents/errors", "number of operations/procedures" are significant influential indicators. Also, the indicators of "length of stay", "bed occupancy" and "financial measures" play important roles in performance evaluation of the healthcare organization. The proposed decision making approach could be considered as a reference for healthcare administrators to enhance the performance of their healthcare institutions.

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It is extremely important to identify key factors of marine industrial ecologization and discriminate the factors that influence degrees and causal relationships for the transformation of marine industrial ecologization nowadays. Based on the conceptual model of marine industrial ecologization, this research built an evaluation system for influencing factors in regional marine industrial ecologization, which included the marine industrial structure ecologization, marine industrial organization ecologization, marine production mode ecologization and marine technological innovations ecologization. The DEMATEL method was applied to analyze the relationships between various influencing factors and drew a network diagram. The results showed that the marine production mode ecologization and marine technological innovation ecologization were in the core position of the evaluation system. They not only revealed the causes of the whole ecological evaluation dimension, but affected the marine industrial organization ecologization and marine industrial structure ecologization. Finally, on the basis of specific indicators in each dimension, some countermeasures and suggestions were put forward to improve the transformation of marine industrial ecologization.

Rebuilding DEMATEL threshold value: an example of a food and beverage information system.

This study demonstrates how a decision-making trial and evaluation laboratory (DEMATEL) threshold value can be quickly and reasonably determined in the process of combining DEMATEL and decomposed theory of planned behavior (DTPB) models. Models are combined to identify the key factors of a complex problem. This paper presents a case study of a food and beverage information system as an example. The analysis of the example indicates that, given direct and indirect relationships among variables, if a traditional DTPB model only simulates the effects of the variables without considering that the variables will affect the original cause-and-effect relationships among the variables, then the original DTPB model variables cannot represent a complete relationship. For the food and beverage example, a DEMATEL method was employed to reconstruct a DTPB model and, more importantly, to calculate reasonable DEMATEL threshold value for determining additional relationships of variables in the original DTPB model. This study is method-oriented, and the depth of investigation into any individual case is limited. Therefore, the methods proposed in various fields of study should ideally be used to identify deeper and more practical implications.