scholarly journals New tourism product forecasting – application of Bass Diffusion Model and Grey Forecasting Model

2020 ◽  
Vol 1 (01) ◽  
pp. 37-43
Author(s):  
N. Abu ◽  
S.M Khaidi ◽  
N. Muhammad
Keyword(s):  
Diffusion Model ◽  
New Product ◽  
Forecasting Model ◽  
Factors Affecting ◽  
Product Demand ◽  
Grey Forecasting ◽  
Grey Forecasting Model ◽  
Tourism Product ◽  
Bass Diffusion ◽  
Bass Diffusion Model

Previous researches usually applied Bass diffusion model (BDM) in forecasting the new product in various areas. This is the first application of BDM to the new tourism product since the model had been developed by Frank M. Bass in 1969. On the other hand, Grey forecasting model able to deal with limited number of data. Both BDM and grey forecasting model have been used in various areas in the forecasting studies. Taking advantages of both models, the combination of both Bass and grey model, called grey Bass forecasting model is applied in the context of the new tourism product forecasting. The objective of this study is to forecast the new tourism product demand in Malaysia using the developed model. Yearly visitors from two ecotourism resorts in Pahang, Tanah Aina Fahad and Tanah Aina Farrah Soraya from 2014 until 2018 are used. The results show that both BDM and grey Bass forecasting model are suitable in forecasting the new tourism product. The authors also suggest other factors affecting the attendance of visitors to be included in further research to conclude which model perform better in the future.

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.

A comparative study of univariate models for container throughput forecasting of major ports in Asia

2021 ◽  
pp. 147509022110236
Author(s):  
Juan Huang ◽  
Ching-Wu Chu ◽  
Hsiu-Li Hsu
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Forecasting Model ◽  
Short Term ◽  
Autoregressive Integrated Moving Average ◽  
Port Authorities ◽  
Grey Forecasting ◽  
Grey Forecasting Model ◽  
Short Term Forecasting ◽  
Trigonometric Regression

This study aims to make comparisons on different univariate forecasting methods and provides a more accurate short-term forecasting model on the container throughput for rendering a reference to relevant authorities. We collected monthly data regarding container throughput volumes for three major ports in Asia, Shanghai, Singapore, and Busan Ports. Six different univariate methods, including the grey forecasting model, the hybrid grey forecasting model, the multiplicative decomposition model, the trigonometric regression model, the regression model with seasonal dummy variables, and the seasonal autoregressive integrated moving average (SARIMA) model, were used. We found that the hybrid grey forecasting model outperforms the other univariate models. This study’s findings can provide a more accurate short-term forecasting model for container throughput to create a reference for port authorities.

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