• Journal of Distribution Science
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• v.21 no.7
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• pp.65-71
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• 2023

Purpose: This study attempted to analyze the impacts of the backward linkage and output multipliers, and investigate the price fluctuation and the price forecast amongst the manufacturing sectors associated with food processing industrial output of Thailand. Research design, data and methodology: The Thailand Input-Output table with a size of 180 x 180 sectors from 2005, 2010, and 2015 was utilized while the secondary data of the time series from January 2002 to December 2021 were processed via a multiplicative model and Box-Jenkins model. Results: The backward linkage analysis indicates that canning and preserving of the meat sector majorly utilized the factors of production from the slaughtering sector; canning and preservation of fish and other seafoods sector largely used those factors from the ocean and coastal fishing sector; and the sugar sector used those of the sugarcane sector. Notably, the output multiplier analysis indicated that output multipliers of those 3 manufacturing sectors were highly increased; meanwhile the price fluctuation continually existed in all forms. Besides, the price forecast suggested that prices of chicken and sugarcane tended to be higher; whereas, the price of shrimp was unstable. Conclusions: Food processing industry contains the favorable components to be one of the industries of the future of Thailand.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.1-6
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• 2011

As large-scale building projects have recently increased for the residential, commercial and office facilities, construction costs for these projects have become a matter of great concern, due to their significant construction cost implications, as well as unpredictable market conditions and fluctuations in the rate of inflation during the projects' long-term construction periods. In particular, recent volatile fluctuations of construction material prices fueled such problems as cost forecasting. This research develops a time series model using the Box-Jenkins approach and material price time series data in Korea in order to forecast trends in the unit prices of required materials. Building information modeling (BIM) approaches are also used to analyze injection times of construction resources and to conduct quantity take-off so that total material prices can be forecast. To determine an optimal time series model for forecasting price trends, comparative analysis of predictability of tentative autoregressive integrated moving average (ARIMA) models is conducted. The proposed BIM-based time series forecasting model can help to deal with sudden changes in economic conditions by estimating material prices that correspond to resource injection times.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.55-72
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• 1987

The work analyzes the existing situation and defines special problems concerning traffic accidents in the two countries. The report is divided into three parts: 1) Using the global approach of SMEED, the data were evaluated using multiple regression analysis, and homogeneous groups of countries were defined by cluster analysis. In the global approach, the linear model is better than SMEED's non-linear model in explaining the number of fatalities. Among the different groups of countries, the linear approach was found to be better suited for industrialized countries and the non-linear approach better for the developing countries. T도 comparison of traffic fatality data for the Federal Republic the developing countries. The comparison of traffic fatality data for the Federal Republic of Germany and the Republic of Korea showed different regression equations during the same time period. 2) The BOX/JENKINS time series analysis on a monthly basis points out clearly similar seasonal patterns for the two countries over the years studied. The decrease in traffic accidents following the intensification of the safety belt requirement was proved in the ARIMA model. It amounts to 7 to 8 percent fewer personal injury accidents and fatal accidents. The identified increase in safety in the Federal Republic of Germany since the 1970s is mainly due to the reduction of accident severity in residential areas. 3) Speeds and headways on motorways in th3e two countries were also compared. The measurements point out that German road users drive faster, take more risks, and accept shorter time gaps than Korean road users. However, the accident statistics show accident rates for Korea that are several times higher than those in the Federal Republic of Germany.

• Journal of Korean Society for Atmospheric Environment
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• v.4 no.2
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• pp.72-81
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• 1988

The typical ARIMA model which was developed by Box and Jenkins, was applied to the monthly $SO_2$ data collected at Seoungsoo and Oryudong in metropolitan area over five years, 1982 to 1986. To find out the changing pattern of $SO_2$ concentration, autocorrelation and partial autocorrelation analysis were undertaken. The three steps of time series model building were followed and the residual series was found to be a random white noise. The results of this study is summarized as follows. 1) The monthly $SO_2$ series was found to be a non-stationary series which which has a periodicity of 12 months. After eliminating the periodicity by differencing, the monthly $SO_2$ series became a stationary series. 2) The ARIMA seasonal model of the $SO_2$ was determined to be ARIMA $(1, 0, 0)(0, 1, 0,)_{12}$ model. 3) The model equations based on the prediction were: for Seoungsoodong: $Y_t = 0.5214Y_{t-1} + Y_{t-12} - 0.5214Y_{t-13} + a_t$ for Oryudong: $Y_t = 0.8549Y_{t-1} + Y_{t-12} - 0.8549Y_{t-13} + a_t$ 4) The validity of the model identified was checked by compairing the measured $SO_2$ values and one-month-ahead predicted values. The result of correlation and regression analysis is as follows. Seoungsoodong: $Y = 0.8710X + 0.0062 r = 0.8768$ Oryudong : $Y = 0.8758X + 0.0073 r = 0.9512$

• Journal of Korea Port Economic Association
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• v.23 no.1
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• pp.149-162
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• 2007

The purpose of this study is to forecast the marine trading volumes using multiplicative seasonal Autoregressive Integrated Moving Average(ARIMA) model. The paper proceeds by comparing the forecasting performances of the unload volumes with those of the load volumes with Box-Jenkins ARIMA model. Also, I present the predicted values based on the ARIMA model. The result shows that the trading volumes increase very slowly.

• Journal of Preventive Medicine and Public Health
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• v.27 no.1 s.45
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• pp.107-116
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• 1994

The United States adopted DRG based prospective payment system (PPS) in order to control the inflation of health care costs. No study used statistical test while many studies reported the cost containing effect of the PPS. To study impacts of the PPS on the Medicare expenditure, this study set the following three hypotheses (1) The PPS decelerated the increase in the hospital expenditure (Part A), (2) the PPS accelerated the increase in the expenditure of outpatients and physicians (Part B), (3) the increase in total expenditure was decelerated inspite of the spill over (substitution) effect because saving in the Part A expenditure were greater than losses in the Part B expenditure. The dependent variables are per capita hospital expenditure, per capita Part B expenditure, and per capita total expenditure for the Medicare beneficiaries. An intervention analysis, which added intervention effect to the time series variation on the Box-Jenkins model, was used. The observations included 120 months from 1978 to 1987. The results are as follows : (1) The annual increase in the per capita Part A expenditure was $5.11 after the implementation of DRG where as that before the PPS had been $11.1. The effect of the reduction ($5.99) was statistically significient (t=-3.9). (2) The spill over (substitution) effect existed because the annual increase in the per capita Part B expenditure was accelerated by $1.73 (t=1.91) after the implementation of the PPS. (3) The increase in the total Medicare expenditure per capita was reduced by $4.26 (t=-2.19) because the spill over effect was less than cost savings in the Part A expenditure.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.179-186
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• 2017

Technology forecasting is predict future trend and state of technology by analyzing the results so far of developing technology. In general, a patent has novel information about the result of developed technology, because the exclusive right of technology included in patent is protected for a time period by patent law. So many studies on the technology forecasting using patent data analysis has been performed. The patent keyword data widely used in patent analysis consist of occurred frequency of the keyword. In most previous researches, the continuous data analyses such as regression or Box-Jenkins Models were applied to the patent keyword data. But, we have to apply the analytical methods of discrete data for patent keyword analysis because the keyword data is discrete. To solve this problem, we propose a patent analysis methodology using Bayesian Poisson discrete model. To verify the performance of our research, we carry out a case study by analyzing the patent documents applied by Apple until now.

• Journal of Preventive Medicine and Public Health
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• v.24 no.3 s.35
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• pp.441-458
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• 1991

The objective of this study was to provide basic reference data for stabilization scheme of medical insurance benefits through forecasting of the medical care utilization rate, the medical expence per case, and the treatment days per case in medical insurance program for government employees & private school teachers and for industrial workers. For the achievement of above objective, this study was carried out by Box-Jenkins time series analysis (ARIMA Model), using monthly statistical data from Jan. 1979 to Dec. 1989, of medical insurance program for government employees & private school teachers and for industrial workers. The results are as follows ; ARIMA model of the medical care utilization rate in medical insurance program for government employees & private school teachers was ARIMA (1, 1, 1) and it for outpatient in medical insurance program for industrial workers was ARIMA (1, 1, 1), while it for inpatient in medical insurance program for industrial workers was ARIMA (1, 0, 1). ARIMA model of the medical expense per case in medical insurance program for government employees & private school teachers and for outpatient in medical insurance program for industrial workers were ARIMA (1, 1, 0), while it for inpatient in medical insurance program for industrial workers was ARIMA (1, 0, 1). ARIMA model of the treatment days per case of both medical insurance program for government employees & private school teachers and industrial workers were ARIMA (1, 1, 1). Forecasting value of the medical care utilzation rate for inpatient in medical insurance program for government employees & private school teachers was 0.0061 at dec. 1989, 0.0066 at dec. 1994 and it for outpatient was 0.280 at dec. 1989, 0.294 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 0.0052 at dec. 1989, 0.0056 at dec. 1994 and it for outpatient was 0.203 at dec. 1989, 0.215 at 1994. Forecasting value of the medical expense per case for inpatient in medical insurance program for government employees & private school teachers was 332,751 at dec. 1989, 354,511 at dec. 1994 and it for outpatient was 11,925 at dec. 1989, 12,904 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 281,835 at dec. 1989, 293,973 at dec. 1994 and it for outpatient was 11,599 at dec. 1989, 11,585 at 1994. Forecasting value of the treatment days per case for inpatient in medical insurance program for government employees & private school teachers was 13.79 at dec. 1989,13.85 at an. 1994 and in for outpatient was 5.03 at dec. 1989, 5.00 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 12.23 at dec. 1989, 12.85 at dec. 1994 and it for outpatient was 4.61 at dec. 1989, 4.60 at 1994.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.2
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• pp.35-46
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• 2008

Soil moisture is one of the important components in hydrological processes and also controls the subsurface flow mechanism at a hillslope scale. In this study, time series of soil moisture were measured at a hillslope located in Gwangneung National Arboretum, Korea using a multiplex Time Domain Reflectometry(TDR) system measuring soil moisture with bi-hour interval. The Box-Jenkins transfer function and noise model was used to estimate spatial distributions of soil moisture histories between May and September, 2007. Rainfall was used as an input parameter and soil moisture at 10 cm depth was used as an output parameter in the model. The modeling process consisted of a series of procedures(e.g., data pretreatment, model identification, parameter estimation, and diagnostic checking of selected models), and the relationship between soil moisture and rainfall was assessed. The results indicated that the patterns of soil moisture at different locations and slopes along the hillslope were similar with those of rainfall during the measurment period. However, the spatial distribution of soil moisture was not associated with the slope of the monitored location. This implies that the variability of the soil moisture was determined more by rainfall than by the slope of the site. Due to the influence of vegetation activity on soil moisture flow in spring, the soil moisture prediction in spring showed higher variability and complexity than that in early autumn did. This indicates that vegetation activity is an important factor explaining the patterns of soil moisture for an upland forested hillslope.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.111-120
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• 2011

High-rise buildings have recently increased over the residential, commercial and office facilities, thus an understanding of construction cost for high-rise building projects has been a fundamental issue due to enormous construction cost as well as unpredictable market conditions and fluctuations in the rate of inflation by long-term construction periods of high-rise projects. Especially, recent violent fluctuations of construction material prices add to problems in construction cost forecasting. This research, therefore, develops a time-series model with the Box-Jenkins methodologies and material prices time-series data in Korea in order to forecast future trends of unit prices of required materials. BIM (Building Information Modeling) approaches are also used to analyze injection time of construction resources and to conduct quantity takeoff so that total material price can be forecasted. Comparative analysis of Predictability of tentative ARIMA (Autoregressive Integrated Moving Average) models was conducted to determine optimal time-series model for forecasting future price trends. Proposed BIM based time series forecasting model can help to deal with sudden changes in economic conditions by estimating future material prices.