Quality improvement of smart senior care service platform in China based on grey relational analysis and Fuzzy-QFD

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lan Xu ◽  
Yu Zhang
Keyword(s):  
Quality Improvement ◽  
Grey Relational Analysis ◽  
Care Service ◽  
The Elderly ◽  
Service Platform ◽  
Content Type ◽  
Relational Analysis ◽  
Improvement Method ◽  
Grey Relational ◽  
Quality Improvement Method

PurposeSmart senior care industry in China currently faces a series of practical difficulties such as an imbalance in the demand and supply structure, service products unable to cater to the actual needs of the elderly and a low degree of marketization. This study therefore proposes using grey relational analysis and the Fuzzy-quality function development (QFD) quality improvement method to help solve these problems.Design/methodology/approachThe proposed method converts the fuzzy requirements of the elderly into the technical characteristics of technologically augmented senior care service products. It then, uses the QFD relationship matrix, combined with grey relational analysis, to analyze the relationship between the needs of elderly and the converted technical characteristics, and subsequently identifies key technical characteristics.FindingsResults show that an improvement in the smart senior care service platform according to the differences of the elderly's preferences can significantly improve users' satisfaction with the service in addition to enhancing market competitiveness of the technologically assisted senior care service products.Originality/valueA novel method to improve the need of smart senior care is proposed by considering age difference. The proposed grey relational analysis and Fuzzy-QFD quality improvement method can help improve the service quality of the smart senior care service platform.

Negative grey relational model and measurement of the reverse incentive effect of fields medal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu
Keyword(s):  
Grey Relational Analysis ◽  
Research Output ◽  
Analysis Model ◽  
Content Type ◽  
Relational Analysis ◽  
Fields Medal ◽  
Definition Of ◽  
Grey Relational ◽  
Analysis Models ◽  
The Relationship

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

Application of grey relational analysis to expose individual student's cognitive difficulties in English public speaking

2014 ◽  
Vol 4 (2) ◽  
pp. 232-249
Author(s):  
Yow-jyy Joyce Lee ◽  
Lawrence W. Lan
Keyword(s):  
Grey Relational Analysis ◽  
Teaching And Learning ◽  
Public Speaking ◽  
Learning Difficulties ◽  
Cognitive Learning ◽  
Content Type ◽  
Cognitive Difficulties ◽  
Relational Analysis ◽  
Grey Relational ◽  
Grey Relation

Purpose – The purpose of this paper is to propose a formative assessment framework to expose individual student's cognitive learning difficulties in English public speaking. The paper aims to provide student feedback and information during the teaching and learning process. A grey student-construct (S-C) chart is developed to represent the students’ cognitive mapping of the speech difficulties in relation to their overall speech conceptualization. This grey S-C chart can facilitate the instructors to ameliorate the classroom teaching and learning performance in English public speaking. Design/methodology/approach – In total, 26 students in a class of English Speech and Rhetoric participate in the experiment – each student views the online video segments of a great speaker's speech, and then decides what segments would best support the speaking skill constructs and also reflects on his/her own difficulties in the same constructs. The grey relational analysis (GRA) method is used to analyze the empirical data. The individual student's construct localization grey relation grade values are calculated to rank the grey relation for both students and constructs. Accordingly, a grey S-C matrix is constructed and a grey S-C chart can thus be developed. Findings – The grey S-C chart manifestly displays the cognitive difficulties in sequences of both students and constructs. Practical implications – According to the grey S-C chart, the instructors may modify teaching strategies to enhance the overall classroom performance. The students may adjust learning strategies to eliminate their specific difficulties. Offering individualized advanced and remedial practices to those largely deviating from the norm is also possible. Originality/value – The study is the first of its kind to apply the GRA method to expose individual student's cognitive learning difficulties in English public speaking. The grey S-C chart is novel in education literature, which can reveal individual student's learning difficulty patterns.

Grey relational analysis between Turkey’s macroeconomic indicators and domestic savings

2017 ◽  
Vol 7 (1) ◽  
pp. 45-59 ◽  
Author(s):  
Engin Duran ◽  
Burcu Uzgur Duran ◽  
Diyar Akay ◽  
Fatih Emre Boran
Keyword(s):  
Grey Relational Analysis ◽  
Data Set ◽  
Content Type ◽  
Relational Analysis ◽  
Domestic Savings ◽  
Macroeconomic Indicators ◽  
Private Savings ◽  
Grey Relational ◽  
High Degree ◽  
The Relationship

Purpose It is of great importance for economy policy makers to comprehend the relationship between macroeconomic indicators and domestic savings, and to find out which indicator is more determinative on the dynamics of domestic savings. The purpose of this paper is to analyze the degree of relationship between Turkey’s domestic savings and selected macroeconomic indicators. Design/methodology/approach To examine the relationship, grey relational analysis (GRA) is applied together with the entropy method to determine the weight of the indicators according to the information level they provide. The analysis covers the data of the period from 1990 to 2014. In practice, however, the data set is used by dividing into two separate periods including before and after the 2001 crisis. Findings The results indicate that the unemployment rate and the gross domestic product (GDP) per capita growth stand out with a relatively high degree of relationship for the period before 2001. When examining the post-2001 period, current balance ratio and GDP growth are ascertained as indicators which have a high degree of relationship with domestic savings. Practical implications These indicators have different aspects affecting both public and private savings. Therefore, it may be beneficial to concentrate on these indicators when designing a policy in order to increase the domestic saving rate. Originality/value There are many econometric models used for investigating Turkey’s macroeconomic indicators and domestic savings causality. But before now, any study which investigates relationship between macroeconomic indicators and domestic savings by GRA could not be encountered. Using one of the newest developed theories (the grey systems theory) for this subject is the significance of this research.

Optimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey relational analysis

2020 ◽  
Vol 16 (5) ◽  
pp. 937-949
Author(s):  
Alagappan K M ◽  
Vijayaraghavan S ◽  
Jenarthanan M P ◽  
Giridharan R
Keyword(s):  
Epoxy Resin ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Natural Fibres ◽  
Content Type ◽  
Relational Analysis ◽  
Optimization Of Process Parameters ◽  
Machining Force ◽  
Drill Diameter ◽  
Grey Relational

PurposeThe purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using Taguchi–Grey Relational Analysis.Design/methodology/approachThe contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.FindingsThe optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.Originality/valueOptimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey Relational Analysis has not been previously explored.

A hybrid grey based artificial neural network and C&R tree for project portfolio selection

2017 ◽  
Vol 24 (3) ◽  
pp. 651-665 ◽  
Author(s):  
Farshad Faezy Razi ◽  
Seyed Hooman Shariat
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Decision Tree ◽  
Portfolio Selection ◽  
Grey Relational Analysis ◽  
Project Portfolio ◽  
Content Type ◽  
Relational Analysis ◽  
Project Portfolio Selection ◽  
Grey Relational

Purpose The purpose of this paper is twofold: the selection of project portfolios through hybrid artificial neural network algorithms, feature selection based on grey relational analysis, decision tree and regression; and the identification of the features affecting project portfolio selection using the artificial neural network algorithm, decision tree and regression. The authors also aim to classify the available options using the decision tree algorithm. Design/methodology/approach In order to achieve the research goals, a project-oriented organization was selected and studied. In all, 49 project management indicators were chosen from A Guide to the Project Management Body of Knowledge (PMBOK Guide), and the most important indicators were identified using a feature selection algorithm and decision tree. After the extraction of rules, decision rule-based multi-criteria decision making matrices were produced. Each matrix was ranked through grey relational analysis, similarity to ideal solution method and multi-criteria optimization. Finally, a model for choosing the best ranking method was designed and implemented using the genetic algorithm. To analyze the responses, stability of the classes was investigated. Findings The results showed that projects ranked based on neural network weights by the grey relational analysis method prove to be better options for the selection of a project portfolio. The process of identification of the features affecting project portfolio selection resulted in the following factors: scope management, project charter, project management plan, stakeholders and risk. Originality/value This study presents the most effective features affecting project portfolio selection which is highly impressive in organizational decision making and must be considered seriously. Deploying sensitivity analysis, which is an innovation in such studies, played a constructive role in examining the accuracy and reliability of the proposed models, and it can be firmly argued that the results have had an important role in validating the findings of this study.

scholarly journals Integrated analytical hierarchy process and grey relational analysis approach to measure supply chain complexity

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sujan Piya ◽  
Ahm Shamsuzzoha ◽  
Mohammed Khadem ◽  
Mahmoud Al Kindi
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Analytical Hierarchy Process ◽  
Grey Relational Analysis ◽  
Extensive Literature ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational ◽  
Hierarchy Process

PurposeThe purpose of this paper is to understand the drivers that create complexity in the supply chain and develop a mathematical model to measure the level of supply chain complexity (SCC).Design/methodology/approachThrough extensive literature review, the authors discussed various drivers of SCC. These drivers were classified into five dimensions based on expert opinion. Moreover, a novel hybrid mathematical model was developed by integrating analytical hierarchy process (AHP) and grey relational analysis (GRA) methods to measure the level of SCC. A case study was conducted to demonstrate the applicability of the developed model and analyze the SCC level of the company in the study.FindingsThe authors identified 22 drivers of SCC, which were further clustered into five complexity dimensions. The application of the developed model to the company in the case study showed that the SCC level of the company was 0.44, signifying that there was a considerable scope of improvement in terms of minimizing complexity. The company that serves as the focus of this case study mainly needs improvement in tackling issues concerning government regulation, internal communication and information sharing and company culture.Originality/valueIn this paper, the authors propose a model by integrating AHP and GRA methods that can measure the SCC level based on various complexity drivers. The combination of such methods, considering their ability to convert the inheritance and interdependence of drivers into a single mathematical model, is preferred over other techniques. To the best of the authors' knowledge, this is the first attempt at developing a hybrid multicriteria decision-based model to quantify SCC.

Optimization of dynamic properties of hybrid composite shaft with newly developed resin (NDR) using grey relational analysis

2019 ◽  
Vol 11 (2) ◽  
pp. 248-263
Author(s):  
Sagar Dnyandev Patil ◽  
Yogesh J. Bhalerao
Keyword(s):  
Epoxy Resin ◽  
Grey Relational Analysis ◽  
Hybrid Composite ◽  
Bonding Strength ◽  
Dynamic Properties ◽  
Content Type ◽  
Relational Analysis ◽  
Composite Shaft ◽  
Design Variables ◽  
Grey Relational

Purpose The purpose of this paper is to find the impact of various design variables on the composite shaft, and also the effect of newly developed resin (NDR) on the strength of the fibers of the composite shaft. Design/methodology/approach The Taguchi method is used to optimize the design variables. Also, GRG approach is used to validate the result. Findings NDR improves the bonding strength of fiber than the epoxy resin. With the grey relational analysis (GRA) method, the initial setting (A1B4C4D1) was having grey relational grade 0.957. It was enhanced by using a new optimum combination (A2B2C4D2) to 0.965. It indicates that there is an enhancement in the grade by 0.829 percent. Thus, using the GRA approach of analysis, design variables have been successfully optimized to achieve improved dynamic properties of hybrid composite shaft. Originality/value The findings of this research are helping to optimize the design variables for the composite shaft. Also, the NDR gives the good bonding strength of carbon/glass fibers in dynamic loading condition than the epoxy resin.

Evaluation of healthcare service quality factors using grey relational analysis in a dialysis center

2019 ◽  
Vol 9 (4) ◽  
pp. 432-448 ◽  
Author(s):  
Erdal Aydemir ◽  
Yusuf Sahin
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Grey Relational Analysis ◽  
Healthcare Service ◽  
Successful Implementation ◽  
Quality Factors ◽  
Content Type ◽  
Relational Analysis ◽  
Dialysis Center ◽  
Grey Relational

Purpose The purpose of this paper is to investigate the relative influences of technical and functional quality levels of service quality and patient satisfaction. In this context, the healthcare service quality and the factors affecting customer satisfaction were evaluated using the grey relational analysis (GRA) method. Design/methodology/approach This is a survey-based study which involves 15 patients in a dialysis center, so the GRA is applied to clarify the uncertainty on service quality level with a limited number of patients without any statistical distribution. In order to reveal whether service quality and customer satisfaction are two different structures, a GRA model is built with ten different quality factors. Findings Results show that each quality factor has a different effect on the quality of service. Another important finding is that service quality and customer satisfaction are different structures for customers. Practical implications The results enable healthcare managers to understand the importance of patient care and the importance of service quality if they want to facilitate their use of their expectations in related factors. Originality/value The study is the first in terms of the application of GRA models in a private health institution operating in Turkey. Successful implementation of the GRA method allows a reasonable decision to be made with a limited number of data at hand. It is considered that the method can be used successfully in other health institutions in the Turkish Health System.

Superior grey relational analysis on blood lipids and hematological parameters

2019 ◽  
Vol 9 (2) ◽  
pp. 207-212
Author(s):  
Jingyi Yan ◽  
Jin-Xiu Zhu ◽  
Nan Lu ◽  
Shanshan Gao ◽  
Jianfeng Ye ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Blood Lipids ◽  
White Cell Count ◽  
Hematological Parameters ◽  
Density Lipoprotein ◽  
Blood Lipid ◽  
Distribution Width ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational

Purpose The purpose of this paper is to investigate the superior relationship between blood lipid- and cardiovascular disease (CVD)-related hematological parameters using superior grey relational analysis (GRA). Design/methodology/approach A total of 294 individuals who underwent simultaneous routine blood examination and blood lipid examination in the Physical Examination Center of the First Affiliated Hospital of Shantou University Medical College were included in this study. Superior GRA was performed to find out the superior factor in CVD-related hematological parameters and blood lipids. CVD-related hematological parameters included red blood cell distribution width, white cell count, and platelet count, platelet distribution width, mean platelet volume, as well as platelet crit. The indicators of blood lipids analyzed here consist of low-density lipoprotein, high-density lipoprotein, triglyceride and total cholesterol. Findings The results showed that all the grey relational degree of hematological parameters and blood lipids were over 0.8; the superior factor in hematological parameters was PLT, whereas TC was the superior factor in blood lipids. Practical implications Findings of this study suggested that hematological parameters are closely related to blood lipids and a potential role for hematological parameters in the prediction of dyslipidemia, which need further study; TC has the greatest influence on hematological parameters, whereas TG displays a minimal impact. Originality/value To the authors’ best knowledge, it was the first study to analyze the relationship between various CVD-related hematological parameters and blood lipids via superior GRA.

Hospital readmission prediction based on improved feature selection using grey relational analysis and LASSO

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nor Hamizah Miswan ◽  
Chee Seng Chan ◽  
Chong Guan Ng
Keyword(s):  
Feature Selection ◽  
Grey Relational Analysis ◽  
Hospital Readmission ◽  
Grey System Theory ◽  
Feature Subset ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational

PurposeThis paper develops a robust hospital readmission prediction framework by combining the feature selection algorithm and machine learning (ML) classifiers. The improved feature selection is proposed by considering the uncertainty in patient's attributes that leads to the output variable.Design/methodology/approachFirst, data preprocessing is conducted which includes how raw data is managed. Second, the impactful features are selected through feature selection process. It started with calculating the relational grade of each patient towards readmission using grey relational analysis (GRA) and the grade is used as the target values for feature selection. Then, the influenced features are selected using the Least Absolute Shrinkage and Selection Operator (LASSO) method. This proposed method is termed as Grey-LASSO feature selection. The final task is the readmission prediction using ML classifiers.FindingsThe proposed method offered good performances with a minimum feature subset up to 54–65% discarded features. Multi-Layer Perceptron with Grey-LASSO gave the best performance.Research limitations/implicationsThe performance of Grey-LASSO is justified in two readmission datasets. Further research is required to examine the generalisability to other datasets.Originality/valueIn designing the feature selection algorithm, the selection on influenced input variables was based on the integration of GRA and LASSO. Specifically, GRA is a part of the grey system theory, which was employed to analyse the relation between systems under uncertain conditions. The LASSO approach was adopted due to its ability for sparse data representation.

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