Multivariate discrete grey model base on dummy drivers

2016 ◽  
Vol 6 (2) ◽  
pp. 246-258 ◽  
Author(s):  
Ke Zhang
Keyword(s):  
Estimation Method ◽  
Test Methods ◽  
Parameters Estimation ◽  
Content Type ◽  
Model Base ◽  
Grey Forecasting ◽  
Effect Measure ◽  
Proposed Model ◽  
Qualitative Variables ◽  
Post Test

Purpose – The purpose of this paper is to solve the problem that the qualitative relative factors cannot be employed in traditional multivariate grey models. Design/methodology/approach – First, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and post test methods of dummy drivers are proposed. At last, the per capita income forecasting of rural residents in Henan province of China is solved with the proposed model. Findings – The proposed model is the reasonable extension of original one. The accuracy of it is higher than former model. In the case study, the forecasting results of proposed model are compared with other grey forecasting models, and prove that proposed model has not only high accuracy, but also clear physical meaning. Practical implications – The method proposed in the paper could be used in policy effect measure, marketing forecasting, etc., when the predictor variables are influenced by some qualitative variables. Originality/value – It will promote the accuracy of multivariate grey forecasting model.

What can neuroscience offer marketing research?

2019 ◽  
Vol 32 (5) ◽  
pp. 1089-1111 ◽  
Author(s):  
Billy Sung ◽  
Nicholas J. Wilson ◽  
Jin Ho Yun ◽  
Eun Ju LEE
Keyword(s):  
Big Data Analytics ◽  
Marketing Research ◽  
Test Methods ◽  
Self Report ◽  
Future Research ◽  
Content Type ◽  
Neural Representations ◽  
Post Test ◽  
Practical Implications ◽  
Integrate Data

Purpose Neuroimaging technologies such as electroencephalogram and magnetic resonance imaging allow us to analyze consumers’ brains in real time as they experience emotions. These technologies collect and integrate data on consumers’ brains for big data analytics. The purpose of this paper is to identify new opportunities and challenges for neuromarketing as an applied neuroscience. Design/methodology/approach The authors discuss conceptual and methodological contributions of neuromarketing based on studies that have employed neural approaches in market-related investigations, explaining the various tools and designs of neuromarketing research. The authors identify marketing-related questions to which neuroscientific approaches can make meaningful contributions, evaluating several challenges that lie ahead for neuromarketing. Findings The authors summarize the contributions of neuromarketing and discuss synergistic findings that neuromarketing has the potential to yield. Research limitations/implications The authors ask: do consumers’ self-reported choices and their neural representations tell different stories?; what are the effects of subtle and peripheral marketing stimuli?; and can neuromarketing help to reveal the underlying causal mechanisms for perceptual and learning processes, such as motivation and emotions? Practical implications The authors identify marketing-related questions to which neuroscientific approaches can make meaningful contributions, evaluating several challenges that lie ahead for neuromarketing. Originality/value To the best of the authors’ knowledge, no current review has identified avenues for future research in neuromarketing and the emerging challenges that researchers may face. The current paper aims to update readers on what neuroscience and other psychophysiological measures have achieved, as well as what these tools have to offer in the field of marketing. The authors also aim to foster greater application of neuroscientific methods, beyond the more biased/post-test methods such as self-report studies, which currently exist in consumer research.

scholarly journals A New Information Priority Accumulated Grey Model with Hyperbolic Sinusoidal Term and its Application

2021 ◽  
Vol 1 (2) ◽  
pp. 5-19
Author(s):  
Xue Tian ◽  
Wenqing Wu ◽  
Xin Ma ◽  
Peng Zhang
Keyword(s):  
Natural Gas ◽  
Fossil Fuels ◽  
Optimal Parameter ◽  
Estimation Method ◽  
Least Square ◽  
Grey Model ◽  
Grey Forecasting ◽  
New Information ◽  
Proposed Model ◽  
Whale Optimization

Compared to fossil fuels, natural gas is cleaner energy, which has developed rapidly in recent years. Studying the urban supply of natural gas has implications for the development of natural gas. In this paper, the new information priority accumulation method is integrated into the grey forecasting model with the hyperbolic sinusoidal driving term, and then the new grey model is used to predict the urban natural gas supply. The system's linear parameters are calculated by the least square estimation method, and the optimal parameter of the new information accumulated priority is determined by the Whale Optimization Algorithm. Finally, the supply of urban gas is forecasted using the proposed model, and comparative analyses with the four other forecasting models are presented.  

A spectral analysis based heteroscedastic model for the estimation of value at risk

2018 ◽  
Vol 19 (3) ◽  
pp. 295-314
Author(s):  
Yang Zhao
Keyword(s):  
At Risk ◽  
Time Series ◽  
Spectral Analysis ◽  
Value At Risk ◽  
Financial Time Series ◽  
Estimation Method ◽  
Reliable Estimate ◽  
Content Type ◽  
Financial Time ◽  
Proposed Model

Purpose This paper aims to focus on a better model to capture the trait of varying volatility in various financial time series, as well as to obtain reliable estimate of value at risk (VaR). Design/methodology/approach The typical methods in spectral analysis are used to obtain the sample of conditional mean, conditional variance and residual term. The generalized regression neural network is used to establish a time-varying non-linear model, and the non-parametric kernel density estimation method is applied for the estimation of VaR. Findings The proposed model is able to follow the heteroscedastic characteristic which is common in financial time series, and the estimated VaR is satisfactory. Practical implications The analysis method in this study allows the hedgers, bankers, financial analysts as well as economists to draw a better inference from financial time series. Also, relatively more precise estimate of the VaR value for a certain kind of financial asset is available. The model with its derived estimates would definitely help in developing other models. Originality/value Up-to-date, the study in literature which models financial time serial from the viewpoint of spectral analysis is rare to see. Thus, the proposed model, along with a comprehensive empirical study which reveals desirable result for the estimation of VaR would enrich the related researches at present.

Verification of the Vibration Characteristics of a Reciprocating Compressor in Operation and the Proposal of the Model Parameters Estimation Method

2014 ◽  
Author(s):  
Yoshifumi Mori ◽  
Takashi Saito ◽  
Katsuhide Fujita
Keyword(s):  
Natural Vibration ◽  
Estimation Method ◽  
Frequency Characteristics ◽  
Vibration Characteristics ◽  
Parameters Estimation ◽  
Eigenvalue Analysis ◽  
Model Parameters ◽  
Reciprocating Compressor ◽  
Proposed Model ◽  
Natural Vibration Characteristics

Vibration characteristics of a reciprocating compressor are discussed. To investigate the frequency characteristics in the operation of unhealthy and healthy, we employed the proposed model, which includes stiffness characters about both the connecting and the sliding parts. Expressing the motion of the reciprocating compressor as a rigid body model with eleven degrees of freedom, we numerically investigated the frequency characteristics in operation and the natural vibration characteristics based on a locally linearized method. To examine the frequency characteristics, we carried out vibration tests using a small experimental machine and the eigenvalue analysis based on the proposed model. Comparing the analytical results with experimental results, we found that the proposed model could simulate the fundamental frequency characteristics in operation and the natural modes. Eigenvalue analysis shows that the natural frequencies and modes for a reciprocating compressor depend upon the angle of the crankshaft. In the proposed model, it can express the dominant frequencies occurring during operation and the natural vibration characteristics.

Business management in the football industry from a supply chain management perspective

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhaleh Memari ◽  
Abbas Rezaei Pandari ◽  
Mohammad Ehsani ◽  
Shokufeh Mahmudi
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Business Management ◽  
Relationship Management ◽  
Flow Management ◽  
Manufacturing Firm ◽  
Chain Management ◽  
Content Type ◽  
Proposed Model ◽  
Football Industry

PurposeTo understand the football industry in its entirety, a supply chain management (SCM) approach is necessary. This includes the study of suppliers, consumers and their collaborations. The purpose of this study was to present a business management model based on supply chain management.Design/methodology/approachData were collected through in-depth interviews with 12 academic and executive football experts. After three steps of open, axial and selective coding based on grounded theory with a paradigmatic approach, the data were analysed, and a football supply chain management (FSCM) was developed. The proposed model includes three managerial components: upstream suppliers, the manufacturing firm, and downstream customers.FindingsThe football industry sector has three parts: upstream suppliers, manufacturing firm/football clubs and downstream customers. We proposed seven parts for the managerial processes of football supply chain management: event/match management, club management, resource and infrastructure management, customer relationship management, supplier relationship management, cash flow management and knowledge and information flow management. This model can be used for configuration, coordination and redesign of business operations as well as the development of models for evaluation of the football supply chain's performance.Originality/valueThe proposed model of a football supply chain management, with the existing literature and theoretical review, created a synergistic outcome. This synergy is presented in the linkage of the players in this chain and interactions between them. This view can improve the management of industry productivity and improve the products quality.

scholarly journals An Alternative Promotion Time Cure Model with Overdispersed Number of Competing Causes: An Application to Melanoma Data

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1815
Author(s):  
Diego I. Gallardo ◽  
Mário de Castro ◽  
Héctor W. Gómez
Keyword(s):  
Estimation Method ◽  
Selection Criterion ◽  
Likelihood Method ◽  
Simulation Studies ◽  
Cure Rate ◽  
Nested Models ◽  
Proposed Model ◽  
The Em Algorithm ◽  
Competing Causes ◽  
The One

A cure rate model under the competing risks setup is proposed. For the number of competing causes related to the occurrence of the event of interest, we posit the one-parameter Bell distribution, which accommodates overdispersed counts. The model is parameterized in the cure rate, which is linked to covariates. Parameter estimation is based on the maximum likelihood method. Estimates are computed via the EM algorithm. In order to compare different models, a selection criterion for non-nested models is implemented. Results from simulation studies indicate that the estimation method and the model selection criterion have a good performance. A dataset on melanoma is analyzed using the proposed model as well as some models from the literature.

Leader–follower narcissism and subgroup formation in teams: a conceptual model

2019 ◽  
Vol 34 (6) ◽  
pp. 429-442 ◽  
Author(s):  
Manuel London
Keyword(s):  
Team Performance ◽  
Team Identification ◽  
Goal Congruence ◽  
Content Type ◽  
Team Outcomes ◽  
Performance Pressure ◽  
Proposed Model ◽  
Leaders And Followers ◽  
Trait Activation ◽  
And Performance

Purpose Drawing on existing theory, a model is developed to illustrate how the interaction between leaders and followers similarity in narcissism and goal congruence may influence subgroup formation in teams, and how this interaction influences team identification and team performance. Design/methodology/approach The proposed model draws on dominance complementary, similarity attraction, faultline formation and trait activation theories. Findings Leader–follower similarity in narcissism and goal congruence may stimulate subgroup formation, possibly resulting in conformers, conspirators, outsiders and victims, especially when performance pressure on a team is high. Followers who are low in narcissism and share goals with a leader who is narcissistic are likely to become conformers. Followers who are high in narcissism and share goals with a narcissistic leader are likely to become confederates. Followers who do not share goals with a narcissistic leader will be treated by the leader and other members as outsiders if they are high in narcissism, and victimized if they are low in narcissism. In addition, the emergence of these subgroups leads to reduced team identification and lower team performance. Practical implications Higher level managers, coaches and human resource professions can assess and, if necessary, counteract low team identification and performance resulting from the narcissistic personality characteristics of leaders and followers. Originality/value The model addresses how and under what conditions narcissistic leaders and followers may influence subgroup formation and team outcomes.

Loyalty program in Africa: risk-seeking and risk-averse adventurers

2014 ◽  
Vol 69 (2) ◽  
pp. 137-157 ◽  
Author(s):  
Shogo Mlozi
Keyword(s):  
Consumer Behavior ◽  
Consumer Products ◽  
Loyalty Programs ◽  
Risk Averse ◽  
Loyalty Program ◽  
Content Type ◽  
Risk Seeking ◽  
Proposed Model ◽  
First Time ◽  
The Relationship

Purpose – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Design/methodology/approach – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Findings – The findings for overall model differed from the moderating factors of high risk, low risk, first-time visit and repeat visit. Also, the results are interesting when satisfaction is tested as a mediator. Practical implications – Practitioners could consider the fact that repeat visits may change tourists’ perceptions toward destination and may even increase their inclination to take on risks. This may impact innovation of consumer products in tourism. Also, policy makers could benefit on how loyalty programs can be developed to increase performance. Originality/value – The study offers specific strategic recommendations toward different groups of tourists (i.e. first-time, repeat visitors, risk averse, risk seeking) and proposes logic for setting up a loyalty program as a long-term strategy for success.

Study of a discrete grey forecasting model based on the quality cost characteristic curve

2017 ◽  
Vol 7 (3) ◽  
pp. 376-384 ◽  
Author(s):  
Wenjie Dong ◽  
Sifeng Liu ◽  
Zhigeng Fang ◽  
Xiaoyu Yang ◽  
Qian Hu ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Characteristic Curve ◽  
Grey System Theory ◽  
Forecasting Model ◽  
Quality Level ◽  
Cost Models ◽  
Quality Cost ◽  
Content Type ◽  
Grey Forecasting ◽  
Grey Forecasting Model

Purpose The purpose of this paper is to clarify several commonly used quality cost models based on Juran’s characteristic curve. Through mathematical deduction, the lowest point of quality cost and the lowest level of quality level (often depicted by qualification rate) can be obtained. This paper also aims to introduce a new prediction model, namely discrete grey model (DGM), to forecast the changing trend of quality cost. Design/methodology/approach This paper comes to the conclusion by means of mathematical deduction. To make it more clear, the authors get the lowest quality level and the lowest quality cost by taking the derivative of the equation of quality cost and quality level. By introducing the weakening buffer operator, the authors can significantly improve the prediction accuracy of DGM. Findings This paper demonstrates that DGM can be used to forecast quality cost based on Juran’s cost characteristic curve, especially when the authors do not have much information or the sample capacity is rather small. When operated by practical weakening buffer operator, the randomness of time series can be obviously weakened and the prediction accuracy can be significantly improved. Practical implications This paper uses a real case from a literature to verify the validity of discrete grey forecasting model, getting the conclusion that there is a certain degree of feasibility and rationality of DGM to forecast the variation tendency of quality cost. Originality/value This paper perfects the theory of quality cost based on Juran’s characteristic curve and expands the scope of application of grey system theory.

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