Identifying the factors of China's seasonal retail sales of consumer goods using a data grouping approach–based GRA method

2020 ◽  
Vol 10 (2) ◽  
pp. 125-143
Author(s):  
Zheng-Xin Wang ◽  
Ji-Min Wu ◽  
Chao-Jun Zhou ◽  
Qin Li
Keyword(s):  
Time Series ◽  
Money Supply ◽  
Consumer Goods ◽  
Seasonal Fluctuation ◽  
Relational Model ◽  
Retail Sales ◽  
Content Type ◽  
Data Grouping ◽  
Main Factors ◽  
Grey Relational

PurposeSeasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model for relational analysis of seasonal time series and apply it to identify and eliminate the influence of seasonal fluctuation of retail sales of consumer goods in China.Design/methodology/approachFirst, the whole quarterly time series is divided into four groups by data grouping method. Each group only contains the time series data in the same quarter. Then, the new series of four-quarters are used to establish the grey correlation model and calculate its correlation coefficient. Finally, the correlation degree of factors in each group of data was calculated and sorted to determine its importance.FindingsThe data grouping method can effectively reflect the correlation between time series in different quarters and eliminate the influence of seasonal fluctuation.Practical implicationsIn this paper, the main factors influencing the quarterly fluctuations of retail sales of consumer goods in China are explored by using the grouped grey correlation model. The results show that the main factors are different from quarter to quarter: in the first quarter, the main factors are money supply, tax and per capita disposable income of rural residents. In the second quarter are money supply, fiscal expenditure and tax. In the third quarter are money supply, fiscal expenditure and per capita disposable income of rural residents. In the fourth quarter are money supply, fiscal expenditure and tax.Originality/valueThis paper successfully realizes the application of grey relational model in quarterly time series and extends the applicable scope of grey relational model.

A new grey comprehensive relational model based on weighted mean distance and induced intensity and its application

2019 ◽  
Vol 9 (3) ◽  
pp. 374-384 ◽  
Author(s):  
Kedong Yin ◽  
Jie Xu ◽  
Xuemei Li
Keyword(s):  
Water Resources ◽  
Relational Model ◽  
Weighted Mean ◽  
Domestic Water ◽  
Content Type ◽  
Correlation Degree ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Grey Relational ◽  
Degree Of Similarity

Purpose The purpose of this paper is to study the essential characteristics of grey relational degree of proximity, to analyse the abstract meaning of grey relational degree of similarity and fully consider the two different relational degree models. Design/methodology/approach The paper constructed the grey proximity relational degree by using the weighted mean distance. To analyse the motivation of the development of things, this paper constructed the grey similarity degree by using the concept of induced strength. Finally, the two correlation models are weighted by reliability weighting. Findings The research finding shows that the distance is the essence of the grey relational degree of proximity, and the induced strength is a good explanation of the similarities in the development of things. Practical implications The analyses imply that the total amount of water consumption in China has the greatest correlation with the consumption of agricultural water resources, followed by the consumption of industrial water resources, and the least correlation with the consumption of domestic water resources. Originality/value The paper succeeds in realizing the essential characteristics of grey relational degree of proximity and the abstract meaning of grey relational degree of similarity. Besides, the resolution of the correlation degree can be greatly improved by reliability weighting.

A study of the grey relational model of interval numbers for panel data

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kedong Yin ◽  
Tongtong Xu ◽  
Xuemei Li ◽  
Yun Cao
Keyword(s):  
Panel Data ◽  
Treatment Method ◽  
Interval Number ◽  
Two Dimensions ◽  
Relational Model ◽  
Interval Numbers ◽  
Cross Sectional ◽  
Content Type ◽  
Correlation Degree ◽  
Grey Relational

PurposeThis paper aims to deal with the grey relational problem of panel data with an attribute value of interval numbers. The grey relational model of interval number for panel data is constructed in this paper.Design/methodology/approachFirst, three kinds of interval grey relational operators for the behavior sequence of a dimensionless system are proposed. At the same time, the positive treatment method of interval numbers for cost-type and moderate-type indicators is put forward. On this basis, the correlation between the three-dimensional interval numbers of panel data is converted into the correlation between the two-dimensional interval numbers in time series and cross-sectional dimensions. The grey correlation coefficients of each scheme and the ideal scheme matrix are calculated in the two dimensions, respectively. Finally, the correlation degree of panel interval number and scheme ordering are obtained by arithmetic mean.FindingsThis paper proves that the grey relational model of the panel interval number still has the properties of normalization, uniqueness and proximity. It also avoids the problem that the results are not unique due to the different orders of objects in the panel data.Practical implicationsThe effectiveness and practicability of the model is verified by taking supplier selection as an example. In fact, this model can also be widely used in agriculture, industry, society and other fields.Originality/valueThe accuracy of the relational results is higher and more accurate compared with the previous studies.

Estimating civil aircraft’s research and manufacture cost by using grey system model and neural network algorithm

2015 ◽  
Vol 5 (1) ◽  
pp. 89-104 ◽  
Author(s):  
Naiming Xie
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Cost Estimation ◽  
Relational Model ◽  
Content Type ◽  
Network Algorithm ◽  
Parameters Selection ◽  
Civil Aircraft ◽  
Neural Network Algorithm ◽  
Grey Relational

Purpose – The purpose of this paper is to propose novel civil aircraft cost parameters’ selection method and novel cost estimation approach for civil aircraft so as to effectively simulate or forecast civil aircraft cost under poor information and small sample. Design/methodology/approach – Based on existent cost estimation indexes, this paper summarized civil aircraft research and manufacturing cost impact index system and adopted grey relational model to select most important impact factors. Consider civil aircrafts’ cost information could not be easily collected, the author must estimate their costs with limited sample and poor information. A combination model of GM (0, N) model and BP neural network algorithm is proposed. Both advantages of simulation of BP neural network algorithm and poor information generation of GM (0, N) were effectively combined. Then steps of combined model were given out. Finally, nine types of aircrafts were used to test the validity of proposed model. As comparing with the traditional multiple linear regression model and simple GM (0, N) model, results indicated that proposed model can do the work better. Findings – Grey relational model can be applied for parameters’ selection and combined GM (0, N) model and BP neural network algorithm can estimate aircraft’s cost as well. Results show that novel combined model could get high forecasting accuracy. Practical implications – Cost estimation is key problem in production management of civil aircraft. Effective cost management could promote competitiveness of aircraft manufacturing company. Proposed combined model can be applied for civil aircraft cost estimation. Similarly, it could be applied for other complex equipment cost estimation. Originality/value – The paper succeeds in proposing grey relational model for cost parameters’ selection and constructing a combination model of GM (0, N) model and BP neural network algorithm. Algorithm of the proposed model was discussed and steps were given out.

scholarly journals A new grey relational model based on discrete Fourier transform and its application on Chinese marine economic

2018 ◽  
Vol 1 (1) ◽  
pp. 79-100 ◽  
Author(s):  
Xuemei Li ◽  
Ya Zhang ◽  
Kedong Yin
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Relational Model ◽  
Relational Models ◽  
Content Type ◽  
Dynamic Correlation ◽  
Model Based ◽  
Cyclical Fluctuation ◽  
Grey Relational ◽  
Time Sequences

Purpose The traditional grey relational models directly describe the behavioural characteristics of the systems based on the sample point connections. Few grey relational models can measure the dynamic periodic fluctuation rules of the objects, and most of these models do not have affinities, which results in instabilities of the relational results because of sequence translation. The paper aims to discuss these issues. Design/methodology/approach Fourier transform functions are used to fit the system behaviour curves, redefine the area difference between the curves and construct a grey relational model based on discrete Fourier transform (DFTGRA). Findings To verify its validity, feasibility and superiority, DFTGRA is applied to research on the correlation between macroeconomic growth and marine economic growth in China coastal areas. It is proved that DFTGRA has the superior properties of affinity, symmetry, uniqueness, etc., and wide applicability. Originality/value DFTGRA can not only be applied to equidistant and equal time sequences but also be adopted for non-equidistant and unequal time sequences. DFTGRA can measure both the global relational degree and the dynamic correlation of the variable cyclical fluctuation between sequences.

Evaluation of key factors influencing process quality during construction projects in Pakistan

2019 ◽  
Vol 9 (3) ◽  
pp. 321-335 ◽  
Author(s):  
Abdul Haseeb Aamir Sheikh ◽  
Muhammad Ikram ◽  
Rana Mamoon Ahmad ◽  
Hamza Qadeer ◽  
Muhammad Nawaz
Keyword(s):  
Construction Projects ◽  
Feedback System ◽  
Process Quality ◽  
Relational Model ◽  
Key Factors ◽  
Content Type ◽  
Factors Influencing ◽  
Importance Index ◽  
Grey Relational

Purpose The quality of construction projects is mainly dependent on the process quality during the construction phase than product quality. The key factors that influence the process quality of building projects in Pakistan during the construction phase of building life cycle are evaluated from literature. This paper aims to discuss these issues. Design/methodology/approach The factors were ranked using the traditional relative importance index (RII) and the second synthetic grey relational analysis method. The findings indicate that during the construction phase the selection of an appropriate contractor is the most important factor. The existence of feedback system and quality of shop drawings received from subcontractors are also very significant factors, according to the grey relational model. Findings Measures for the improvement of process quality in Pakistan are suggested. The results from both methods are not entirely comparable; however, if one considers uncertainty in data, then the second synthetic GRA-based ranking should be preferred over RII in decision making. Originality/value The study is pioneer in the evaluation of key factors influencing process quality during building construction projects in Pakistan using a set of traditional and novel methods. The results of this study are significant in improving the process quality during different phases of construction.

scholarly journals Relational Research between China’s Marine S&T and Economy Based on RPGRA Model

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Kedong Yin ◽  
Suyuan Li ◽  
Xuemei Li
Keyword(s):  
Time Series ◽  
Relational Model ◽  
The Poor ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Marine Economy ◽  
Change Trend ◽  
Grey Relational ◽  
Relative Change ◽  
The Relationship

To make up the defect of the existing model, an improved grey relational model based on radian perspective (RPGRA) is put forward. According to the similarity of the relative change trend of time series translating traditional grey relational degree into radian algorithm within different piecewise functions, it greatly improves the accuracy and validity of the research results by making full use of the poor information in time series. Meanwhile, the properties of the RPGRA were discussed. The relationship between China’s marine S&T and marine economy is researched using the new model, so the validity and creditability of RPGRA are illustrated. The empirical results show that marine scientific and technological research projects, marine scientific and technological patents granted, and research funds receipts of the marine scientific research institutions have greater relationship with GOP, which indicates that they have more impact on China’s marine economy.

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