Decision Model For Evaluation Research Articles

An improved failure mode and effect analysis method for group decision-making in utility tunnels construction project risk evaluation

The risk factors of utility tunnels construction project (UTCPs) are diverse and complex, which can easily lead to serious accidents. And these accidents are usually the result of ignoring the most serious risk sources due to the lack of comprehensive risk evaluations. Therefore, this paper proposes an improved failure mode and effect analysis (FMEA) multi-criteria group decision model for utility tunnels construction project risk evaluation. First, expert groups are invited to evaluate the project risk failure modes, and k-means clustering is used to group the experts and form the aggregated matrix. Then, the CCSD (correlation coefficient and standard deviation) method, regret theory and MULTIMOORA method are used to rank the failure modes. Subsequently, the superiority of the model is illustrated by sensitive and comparative analyzes through a case study of the utility tunnels construction project for Beijing Winter Olympics. Finally, a systematic application model is proposed to provide some decision basis for project risk management.

Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks

Routing protocols based on trust mechanisms have been widely investigated for wireless sensor networks, and the works have achieved good results, while there are few works on trusted routing for underwater acoustic networks (UANs). However, trust-aware routing is the key to improving the packet delivery rate and the energy efficiency of UANs. Therefore, inspired by the theory of trust evaluation, a trust-aware and fuzzy logic-based reliable layering routing protocol (TAFLRLR) is proposed. In the TAFLRLR protocol, to avoid the problem of the void area and improve the transmission reliability, the candidate nodes of the next-hop forwarding nodes are determined according to the layers of neighbor nodes. Moreover, a fuzzy logic-based trust evaluation mechanism (FLTEM) is provided, which employs the fuzzy comprehensive evaluation decision model to calculate the comprehensive trust value for underwater sensor nodes. Further, the node density of a candidate node and its comprehensive trust value are taken as the input of a fuzzy control system and the forwarding probability (FP) of the node is taken as the output, and the candidate node with the highest FP is selected as the best forwarding node. Simulation results illustrate the superiority and effectiveness of the TAFLRLR protocol in terms of energy efficiency, routing reliability, and transmission reliability.

Development of an Intuitive GUI-Based Fuzzy Multi-Criteria Decision Model for Comprehensive Hospital Service Quality Evaluation and Indexing

Recently, hospital care and other services have become increasingly important for patient satisfaction. Better hospital care and assistance improve patients’ medical conditions, management trust, and financial success. In this regard, monitoring and measuring hospital service quality is necessary to improve patient satisfaction and wellness. However, the evaluation of healthcare service quality is a complex and critical task due to its intangible nature. Existing methodologies often struggle to effectively incorporate multiple criteria and address uncertainties inherent in healthcare evaluations. To address these challenges, this research work seeks to develop a comprehensive and robust approach for evaluating hospital service quality to improve decision making and resource allocation for service enhancement. This study aims to evaluate multi-faceted healthcare service quality by combining many criteria and uncertainties into a single index. The model is constructed methodically utilizing fuzzy logic and decision modeling. A dataset collected from diverse healthcare facilities covering various medical specialties and regions is employed to validate and refine the model. Numerous criteria, factors, and dimensions are examined and embedded into the development of the model. Fuzzy logic is used to capture and manage healthcare evaluations’ inherent vagueness and imprecision, yielding more accurate and comprehensive outcomes. The model’s outcome is the hospital service quality fuzzy index (HSQFI), an easy-to-understand single performance measure. A graphical user interface (GUI) is developed for collecting data, and then it shows the results in the form of barriers and recommendations. Based on the findings, recommendations in terms of barriers (service criteria) to enhance the hospital’s service quality have been made. This approach can be a tool for managers or other stakeholders to quickly realize the success of their service plans and pinpoint areas that may need improvement in the future.

Supplier evaluation using AHP for a small scale iron and steel plant in eastern India

The paper presents a multi-criteria decision-making model for evaluation of suppliers using the analytic hierarchy process (AHP) for a small-scale sponge iron and steel plant in eastern India. A systematic research framework has been proposed for the same. The process uses a pair-wise comparison of the criterion importance based on decision-makers' opinions to find their relative weights. The main criteria are identified based on literature review and experts' opinions. The criteria are cost, delivery, quality, location, communication, management, performance history and reputation. The next stage involves a pair-wise comparison of the suppliers based on each criterion to find their relative importance. Overall sensitivity analysis has been conducted using MS Excel to inspect the flexibility of the model for evaluating suppliers, i.e., how the change in the ranking of the suppliers occurs when there is a change in relative weightage of criteria.

Evaluation of the competitiveness of the container multimodal port hub

The research on the competitiveness of container multimodal transport port hub, comprehensively considering the software and hardware strength of port hub, is of great significance to analyze the specific source competitiveness of port hub, the optimal allocation of multimodal transport capacity resources and port operation management planning. Based on this, according to the principle of fuzzy set and membership function in fuzzy theory, this paper adopts the modeling method of multi-attribute decision-making to deeply analyze the key influencing factors of port hub competitiveness, extract the core indicators from the four aspects of business capacity, transport capacity resources, infrastructure and service quality, and then construct the fuzzy multi-attribute decision-making evaluation model of port hub competitiveness, and take the container transportation in Northeast China as an example. The research shows that the key influencing factors of multimodal transport port hub competitiveness have changed from traditional infrastructure factors to flexible influencing factors such as transportation service quality, transportation capacity and resource integration ability, transportation business efficiency, and port enterprises are in the critical period of industry transformation and upgrading. Strengthening inter industry integration, building industrial ecological alliance and building a multi-mode transportation integrated service chain with port as the core play an obvious role in promoting the formation of the core competitiveness of port hub. Among the ports along the coast of Liaoning, Yingkou Port has the strongest competitiveness against the supply of corn containers in Northeast China, and the competitiveness of other ports from strong to weak is Jinzhou port, Beiliang port, Panjin Port, Huludao port, Dandong port, Dalian port and Suizhong port. The research results enrich the theoretical system of multimodal transport port hub competitiveness research, and provide reference suggestions for port enterprises, transportation enterprises, government departments and other relevant subjects in strategy formulation, policy implementation, layout planning and so on.

Three-way decision approach for water ecological security evaluation and regulation coupled with VIKOR: A case study in Beijing-Tianjin-Hebei region

Owing to the great correlation between human survival and water ecological security (WES), the research on the evaluation and regulation of WES is of great significance. However, the evaluation thought of WES is not clear enough and most of the evaluation methods can only get ranking results subjectively, which are not suit to judge the grade, especially in the complex and uncertain decision environment. Thus, under the guidance of the resilience idea, it is proposed to build an evaluation indicator system of WES from three aspects: resistance, restorative and adaptability. Then the data were transformed into Pythagorean fuzzy number (PFN), and the resilience index was obtained based on VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method to realize ranking; After that, the comprehensive thresholds were estimated by the resilience index, and a new three-way decision (3WD) model for the WES evaluation was constructed for grade evaluation; Finally, the model was applied to the evaluation of WES in Beijing-Tianjin-Hebei region (BTH) of China from 2006 to 2020. The results show that the WES in BTH has significant spatial-temporal differentiation; From 2006 to 2020, except Hebei, the WES level has not been significantly improved; Beijing, Tianjin and Hebei were respectively in grade III, V and I in 2016–2020; The resistance of WES is an urgent direction to be optimized in Beijing and Tianjin, while Tianjin and Hebei should strengthen the restorative of WES. The model framework constructed in this study is effective and has good generalizability, which can provide a new way for WES evaluation.

Decision Modeling and Evaluation of Enterprise Digital Transformation Using Data Mining

The paper discusses the commercial opportunities for digitalization, as well as the changes that occur when digital technology is adopted throughout all business areas. A survey of digital firms found that maturing digital organisations are concentrating on integrating digital technologies to revolutionise how businesses operate. A digital strategy supported by management who nurture a culture of change and innovation is a primary predictor of a company’s ability to digitally remake itself. Companies that integrate big data, cloud, mobile, and social technologies into their infrastructure are more lucrative, have larger sales, and have a better market valuation than competitors with a weak vision. This paper aims to conduct an in-depth study on the evaluation and decision-making model of the effectiveness of enterprise transforming to digitalization based on data mining in order to address the shortcomings of self-evaluation, promote and improve the process and promote enterprise transforming to digitalization. First, it determines the evaluation index and uses triangular fuzzy numbers to clarify the index weight. It also gathers the opinions of various experts in the decision-making process. Afterward, the decision tree evaluation model is generated through the information gain and ROC curve. Based on enterprises’ relevant transforming to digitalization data, the decision tree model is used as the evaluation decision model, and the research on the evaluation model of the point of enterprise transforming to digitalization is completed. Experiments show that the method proposed in this paper has high accuracy, fast algorithm operation efficiency, and robust data mining ability. It can effectively improve and promote the progress of enterprise transforming to digitalization.

The Validity of Visual Communication Design of Online Advertisement Based on Interactivity

Today's society is a society of Internet information, especially the rapid development of new media that is the most distinctive project today. New media has changed the way traditional media are disseminated, and the advertising industry has made new developments with the rapid development of new media, especially with the rise of online advertising, making the dissemination of advertising more influential. In modern advertising information, online advertising has become very influential. This study aims at how to achieve user-matching push and set the right price is the two major problems of Internet advertising push, through the analysis of the emergence and development of network advertising and visual elements in network advertising, starting from the problems appearing in modern online advertisements, and studying the visual communication design in online advertisements. In this paper, a neural network model and a fuzzy comprehensive evaluation decision model are designed; so as to make our online advertisements rich in national characteristics and really cause online users' active clicks. The experimental results show that the proposed method achieves good results and verifies the effectiveness of the model.

A hybrid decision model and case study for comprehensive evaluation of green mine construction level

A hybrid decision model and case study for comprehensive evaluation of green mine construction level

Sustainable supplier evaluation and selection in developing countries: an integrated fuzzy framework

Evaluation and selection of suppliers play a vital role in improving their sustainability performance. In this regard, evaluating the sustainability performance of suppliers is much more critical in developing countries. These countries are among the best destinations for supplying raw materials and workforce utilisation because of lower costs. In recent years, various multi-criteria decision aiding (MCDA) frameworks utilised to evaluate suppliers based on sustainable aspects. However, few studies analysed the evaluation and selection of suppliers' sustainability in an integrated fuzzy MCDA model regarding the supplier selection process and developing nations. This research presents a comprehensive, integrated fuzzy decision model for sustainable supplier evaluation and selection using an integrated FDelphi-FDEMATEL-FANP-FVIKOR by considering sustainability (social, economic and environmental). Also, this research provides a comprehensive analysis of MCDA techniques' literature in terms of the main steps of sustainable supplier selection (e.g., formulation of criteria, handling of criterion's interaction, weight calculation and final selection). The previous research rarely considered the evolution of suppliers' sustainability according to its steps in the literature. This framework assists supply chain managers and practitioners better understand the extraordinary role of these steps on businesses. This research's proposed framework is validated by a numerical example taken from Iran's automotive industry.

Novel Hybrid Decision Model for Electrical Fire Risk Evaluation of High-Rise Buildings based on Asymmetric Proximity

Novel Hybrid Decision Model for Electrical Fire Risk Evaluation of High-Rise Buildings based on Asymmetric Proximity

Research on Decision Evaluation Model of HOV Lane Setting

In order to achieve the purpose of improving the travel efficiency of commuters in the periphery of the city, expanding the beneficiary groups of urban rail transit, and alleviating urban road traffic congestion, when planning and setting up HOV in the periphery of the city, it is necessary to analyze the feasibility of HOV lane setting from both the demand conditions and the setting conditions. This paper combines machine learning to construct a decision-making evaluation model for HOV lane setting and studies the optimal layout model and algorithm of HOV lanes in service rail transit commuter chain. The setting, planning, and layout of HOV lanes are a two-way interactive process of traveler's path selection and designer's road planning. Finally, after the model is constructed, the performance of the system model is verified. The results show that the system studied in this paper can be used for traffic data and lane planning analysis. Therefore, in the process of urban operation, the HOV model constructed in this paper is mainly used to alleviate urban traffic and improve urban operation efficiency.

Supply chain movement risk in the sneaker industry: an empirical study

In light of the COVID-19 pandemic and the Sino–US trade war, this study proposes a grey sharing decision-making evaluation model for production base movement and the sustainable operation of enterprises in the footwear industry. First, a focus group technique was employed; personnel from the footwear industry, corresponding government agencies, and the academic community were invited to jointly identify the most important criteria when considering a production base movement. The group listed seven criteria: labor cost, materials, exchange rate fluctuation, tariff, supply chain, transfer cost, and the government. The grey situation decision-making algorithm based on group knowledge and entropy were used to identify the most suitable country for production base movement.

PNS80 Assessment of Prognostic and Predictive tests by the NICE Diagnostics Assessment Programme

Numerous tests that help to estimate a person’s prognosis or predict treatment effect have been assessed by the NICE Diagnostics Assessment Programme (DAP) to produce recommendations on their use in the NHS. We reviewed NICE diagnostics guidance to identify assessments of such technologies and describe the types of evidence used in decision models for health economic evaluation and the structures of these models used for assessment of cost-effectiveness. We also summarized the NICE Diagnostic Advisory Committee considerations relating to issues and challenges arising in these assessments. NICE diagnostics guidance were checked by a reviewer. For each piece of guidance on prognostics-related or predictive technologies identified, information was extracted by 1 reviewer, and checked by a second reviewer, with differences resolved by discussion. A linked evidence approach was the predominant method used in economic models, in which evidence for test performance was linked to decisions about treatment and the impact of this on longer term health. Sources of data for long term prognosis were varied, including trials and real-world evidence. Issues raised at committee meetings included the impact on people of knowing the prognosis of their condition and how knowledge of prognosis impacts on treatment decisions. Uncertainties about test performance and long-term outcomes are also frequently seen and addressed through sensitivity analyses. Decision modelling is frequently used in NICE DAP assessments to estimate how the performance of prognostic and predictive tests can be extrapolated onto downstream clinical outcomes. This raises a number of challenges which are described here, potentially identifying areas for methodological research.

Evaluation of Cruise Ship Supply Logistics Service Providers with ANP-RBF

To overcome challenges like market dynamic configuration, information integration, and quick response, it is necessary to build an efficient, stable, and well-coordinated supply chain relationship for cruise ship supply. This requires building of a solid evaluation index system of logistics service providers (LSPs) in the cruise ship supply chain. In this paper, we introduce an evaluation index system that consists of four dimensions, based on the characteristics of cruise ship supply and the connotation and type of cruise ship supply LSPs. The four dimensions are business level, collaborative capacity, service price, and information level, including ten subcriteria. We first establish an evaluation decision model for the interdependence and feedback relationship between the criteria by using analytic network process (ANP) for weight definition of each index; then, we use Super Decisions software to simulate the results, combine RBF neural network training and validation, and extract implicit knowledge and laws. We propose an incremental algorithm that can effectively avoid the influence of subjective factors and increase the dynamic nature of evaluation. The results show that the ANP-RBF method has strong practicability in the evaluation of cruise ship supply LSPs.

A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index

In order to take into account cost and timeliness and enhance accuracy testing, this study developed the fuzzy number and membership function, using the confidence interval of ratio operating performance index. Subsequently, according to the statistical test rules and the application of the fuzzy number and membership function, a fuzzy evaluation decision model for the operating performance index is proposed, to evaluate if the business performance reaches the needed level. Based on the abovementioned, the evaluation model in this study took into account not only timeliness but also accuracy, so that it could grasp the opportunity of improvement for operating organizations with poor operating performance after being evaluated. This fuzzy evaluation decision model for the operating performance index constructs a fuzzy membership function retrieved from an index’s confidence interval, reducing the chance of miscalculation due to sampling mistakes and improving the efficiency of evaluation. Finally, in order to facilitate the application of readers and the industry, this paper uses cases to explain the proposed fuzzy verification method. On the whole, the model proposed in this paper is a data-based auxiliary tool for the service operating performance improvement strategy.

Risk and Income Evaluation Decision Model of PPP Project Based on Fuzzy Borda Method

In order to effectively analyze the risk-return decision-making model of PPP project by Yuan et al., (2020) this paper, based on the fuzzy Borda method and synergy effect theory, considers the synergistic effect of PPP project, constructs the model of investment risk sharing, incentive, and supervision punishment, and determines the investment risk sharing, incentive, and PPP project investment. This paper also aims to supervise and punish the decision-making mechanism to achieve the goals of the PPP project. The research results show that the increased synergy of project participants not only reduces the impact of investment risk on project revenue but also promotes project participants to increase their willingness to undertake risks, actively undertake project risks, and achieve synergy effects of PPP projects. Through the cooperation of both parties, the total income of PPP projects is increased. The research results show that the government chooses social capital participants with complementary advantages to form synergy as shown by Jiang et al. (2016); with the increase of synergy, the government needs to increase the incentive intensity, improve the performance behavior of social capital participants as proposed by Junlong et al. (2020), curb their speculation, and promote the two sides. Due to the increased synergy and the willingness of social capital participants to increase cooperation and reduce speculation, the government should reduce the intensity of supervision and punishment.

Characteristics of Liver Functions in Patients With COVID-19 and Construction of a Prognostic Evaluation Decision Model Based on Liver Functions.

A number of studies have suggested that coronavirus disease 2019 (COVID-19) can cause liver damage. However, clinical features and outcome of COVID-19 in patients with liver injury remain to be further investigated. In this study, the clinical data of 265 COVID-19 patients admitted to seven tertiary hospitals were collected. Based on a threshold for transaminase or total bilirubin levels at two times the normal upper limit, patients were divided into mild or moderate/severe liver injury groups. Among the 265 patients, 183 patients showed liver injury within 48 hours of admission. Aspartate aminotransferase levels were predominantly elevated in the liver injury group, but albumin levels were reduced. Moreover, fibrinogen and D-dimer were significantly increased. Furthermore, 68% of the patients with moderate/severe liver injury had one or more underlying diseases. Almost half of these patients developed acute respiratory distress syndrome (44%) and secondary infections (46%). These patients showed increased interleukin-6 and interleukin-10 levels and a decrease in PaO2 and the oxygenation index. In addition, levels of alanine aminotransferase, aspartate aminotransferase, and albumin were correlated with the oxygenation index, D-dimer and lymphocyte counts. Furthermore, a novel prognostic assessment model based on liver function was established, which accuracy reached 88% and was able to accurately assess the prognosis of COVID-19 patients.

Research on the regional leading industry selection of “Kashgar urban agglomerations” based on multi-attribute weighted intelligent grey target decision-making evaluation model

PurposeThe purpose of this paper is to establish the index system of leading industries in Kashgar urban agglomeration, and use the multi-attribute weighted intelligent grey target decision-making evaluation model to measure the comprehensive effect, so as to select the leading industries of Kashgar urban agglomeration.Design/methodology/approachFirst, 18 industries in Kashgar urban agglomerations are taken as objectives, and four indexes, namely, demand income elasticity index, growth rate index, labor productivity growth rate index and contribution rate of output value, are selected to construct an evaluation system for leading industry selection in Kashgar urban agglomerations. Then, grey incidence degree method is used to determine the decision-making power of each decision-making objective. Finally, multi-attribute weighted intelligent grey target decision-making evaluation model is used to measure the comprehensive effect of the objective system of leading industries in Kashgar urban agglomerations.FindingsIt can be seen that the multi-attribute weighted intelligent grey target decision-making evaluation model is more convenient to be used in selecting regional leading industries, and the results are accurate and feasible. Based on the calculation results and the actual economic development requirements of Kashgar urban agglomeration, the leading industries of Kashgar urban agglomeration can be determined as: wood processing, furniture, paper making and printing; wholesale and retail; construction; equipment manufacturing; transportation, storage and postal services.Originality/valueFirst, it is a new method in selecting regional leading industry by using the multi-attribute weighted intelligent grey target decision-making evaluation model. Second, since there is relatively little research on Kashgar urban agglomeration, especially on leading industries in Kashgar urban agglomeration. The research in this paper can not only enrich the research on selecting leading industries in urban agglomeration but also provide scientific reference for relevant government agencies to formulate economic development plans.

Dynamic sustainability requirements of stakeholders and the supply portfolio

Extant literature on sustainability in procurement and supplier selection suffers from a number of deficiencies. First, studies pertaining to the dynamic nature of stakeholders’ expectations of sustainability and its impact on determining a supply portfolio have not been studied before. Second, there is a genuine lack of study linking the stakeholders’ sustainability requirements, firm procurement strategies, and eventual supplier selection. Third, most of the existing studies address sustainability issues in procurement and supplier selection but fall short of determining an optimal portfolio of suppliers and corresponding optimal order quantities. This study addresses the above research gaps by developing a sustainability-focused multi-criteria decision model for supplier evaluation and determining optimal order allocation among the suppliers linking the stakeholders’ sustainability requirements and firm procurement strategies. Based on dynamic capability theory, we develop a decision support framework integrating multi-phased quality function deployment and dynamic optimization. We apply the decision support framework to a European apparel company which sources apparel from Bangladesh: a country that is a low cost sourcing destination. First, this study identifies the stakeholders’ sustainability requirements. It then explicates the company’s procurement strategies in terms of stakeholders’ requirements followed by translating the procurement strategies to relevant supplier assessment criteria. Finally, a linear optimization model is developed to maximize the suppliers’ sustainability performance in order to determine the optimal supply portfolio. The results identify two distinct groups of suppliers satisfying the overall sustainability performance. However the optimal order quantities among the suppliers vary randomly depending on the variations in demand and priority weights of the suppliers. The paper concludes with a detailed discussion of the results and implications.