• Journal of Food Hygiene and Safety
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• v.30 no.2
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• pp.196-201
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• 2015

This study was conducted to monitor the current status of pesticide residues and to calculate the correlation between monthly price fluctuation and distribution of pesticide residues in leafy vegetables at the whole market in Gyeonggi-do from 2009 to 2013. From the result, the maximum residue limit (MRL) were frequently exceeded in 5 leafy vegetables which were 48 cases of crown daisy (5.8%), 28 cases of chard (5.1%), 28 cases of spinach (3.4%), 25 cases of perilla leaves (3.4%) and 24 cases of chamnamul (3.7%). The high rate of monthly pesticide residues exceeding MRL showed on crown daisy and chard observed in June and September, spinach in October to November and December to January, perilla leaves in July to August and January, and chamnamul in August to September. To calculate the correlation between monthly price fluctuation and distribution of pesticide residues, we performed the Pearson's correlation analysis. From the results, there were significant differences between monthly price and pesticide residues detected in chamnamul, spinach and perilla leaves (p < 0.05). There were also significant differences between monthly price and pesticide residues exceeding MRL in chamnamul and crown daisy (p < 0.05). Although the small number of leafy vegetables and short period were analyzed in this study, the consolidation monitor of pesticide residues according to the season and price will be needed to acquire the safety of agricultural products.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.617-624
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• 2017

The production of cabbage, which is mainly cultivated in open field, varies greatly depending on weather conditions, and the price fluctuation is largely due to the presence of a substitute crop. Previous studies predicted the production of cabbage using actual weather data, but in this study, we predicted the wholesale price using unstructured agricultural meteorological data on the web. From January 2009 to October 2016, we collected documents including the cabbage on the portal site, and extracted keywords related to weather in the collected documents. We compared the forecast wholesale prices of simple models and unstructured agricultural weather models at the time of shipment. The simple model is AR model using only wholesale price, and the unstructured agricultural weather model is AR model using unstructured agricultural weather data additionally. As a result, the performance of unstructured agricultural weather model was has been found to be more accurate prediction ability.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.411-420
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• 2015

With the rapid increase in the price of house lease, a unique housing form in Korea, a serious social issue has been raised as to the use value of house lease and residence stability of the ordinary people. This study thus aimed to analyze the direct factors that affect lease guaranteed loan and market volatility in order to explore the right direction of financial policy to reduce housing burdens. To this end, the direct variables affecting house lease guaranteed loan, including lease price, transaction price and lending rate, were defined. Vector Error Correction Model (VECM), a time series analysis, was employed to dynamically explain the data. Based on the house lease prices and bank data on loans between January 2010 and December 2014, it was found that the increase in lease price was the direct result of the increase in lease guaranteed loan, not that of the decrease in lending rate or increase in housing transaction price.

• Korean Journal of Construction Engineering and Management
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• v.7 no.5
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• pp.77-84
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• 2006

Indexes have played an important role as a economic indicator or performance indicator in many industries for a long time. In construction industry, indexes, or Construction Cost Index(CCI), have been used to compensate for the gap of time in Estimate Using the Historical Cost Data from Feb. 2004. CCI is composed of index formula and resources. Existing literatures had used Laspyeres Index as a index formula. And, Leontief table, the bills of quantities, and information of price surveyor were used as a resource. When applying Laspyeres formula and the resources to calculating the CCI, the problems such as double application of price fluctuation, calculating the incorrect weights, may be generated. This paper analyzed the existing economic relevant indexes as well as Laspyeres formula. Thus, feasibility of them was analyzed using three practical cases of apartments. And then, Quantity based Base Period Price Index(QBPPI) was developed to consider the characteristics of construction more accurately.

• Korean Journal of Construction Engineering and Management
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• v.11 no.1
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• pp.113-121
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• 2010

Since the cut-down of the purchasing price of the feed in tariff(FIT) in 2008, the numbers of photovoltaic projects get decreased, contrary to investment expansion policy of government on renewable energy. The root cause of the decrease is the irrationality of the current purchasing price structure of FIT as well as the adversity of fund raising due to the global financial crisis. This study proposes the FIT calculating model (Cost & Benefit Risk Based Purchase Price Process : CBRP3) reflecting the fluctuation of cost and benefit risks. The first step is to establish the photovoltaic generation alternatives, and to calculate each distribution data of the investment and the power generation quantity. The FIT for each alternative is, then, assessed through simulations. Finally the proposed FIT scheme is compared to the present FIT scheme and future study subjects are derived.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.389-407
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• 2013

The objective of this research is to provide an understanding of how coffee production has been taking place since the coffee industry in Vietnam came out in the global market after Doi Moi. Current research tries to understand how the local households of coffee production adjusts to their production process according to internal and external influences. In order to explore coffee production in the level of local and household units, the structure of coffee production in Dak Lak is first explored in terms of production and sales with the cases from two communes. The examination reveals that general characteristics of coffee crops that would reflect coffee production structure. Further, this study interrogates farmers' response to reflect some direct and indirect influences in recent years. That shows how the elements of coffee production in global market induce a change of coffee production in the study area. Those aspects are analyzed in relation to yearly coffee price fluctuation and diversification. Also, this research explores some of farmers' responses toward the environmental friendly coffee production.

• Journal of Distribution Science
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• v.18 no.5
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• pp.99-109
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• 2020

Purpose: This study aims to develop and empirically analyze a research model in order to comprehend the relationship among the service quality of market-wholesaler system, re-transaction intention, and recommendation intention of forwarder. Further, we suggest new six factors reflecting the service quality of market-wholesaler system and highlight market expansion of forwarder as a mechanism in the relationship. Research design, data and methodology: The authors developed the new scales measuring the service quality of market-wholesaler system (i.e. trade price, price fluctuation, payment receipt, settlement period, trade information, and customer service) and conducted a cross-sectional survey for 439 forwarders in a wholesale market. And then we performed a series of path analyses to test hypotheses. The hypotheses are as follows. [H1] The service quality of market-wholesaler system will positively affect forwarders' market expansion, [H2] Forwarders' market expansion will positively affect their re-transaction intention, [H3] Forwarders' market expansion will positively affect their recommendation intention, [H4] Forwarders' re-transaction intention will positively affect their recommendation intention. Results: The results showed that all the six factors for the service quality of market-wholesaler system were positively related to market expansion of forwarders. There was a differential effectiveness in the six factors of the service quality. More specifically, the positive effect of customer service factor was the strongest on market expansion of forwarders. And the respective effects of trade price, price fluctuation, settlement period, trade information factors were followed in order. The positive effect of payment receipt factor was the weakest on market expansion of forwarders. Also, market expansion of forwarders was positively related to their re-transaction intention and recommendation intention. Furthermore, market expansion of forwarders was indirectly related to recommendation intention through re-transaction intention as well. Conclusions: The research findings provide important theoretical and practical implications. This study is the first to attempt to test the perception of forwarders for the service quality of market-wholesaler system by developing and using the new scales. Also, there has been a sharp controversy about the effectiveness of market-wholesaler system. The findings support that market-wholesaler system would be activated by empirically verifying the effectiveness of the service quality on the various outcomes.

• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.593-619
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• 2004

This study analyzes the interfuel substitution of energy demand in Korean manufacturing sector using static and dynamic linear logit models. For the period of 1981~2002, this study uses petroleum, electricity, natural gas and coal as energy sources. According to the empirical results, firstly, the own-price elasticity of coal has been increased steadily even though its elasticity is smallest compared with those of other energy sources. On the other hand, price elasticity of natural gas is largest, but its value has been decreased after 1997. Price elasticities of petroleum and electricity are very stable over the sample period. One of the main features in trends of interfuel substitution is as follows. Substitution effect of a change in price of natural gas on both petroleum and coal has been increased especially after 1997. The implication of the empirical results is summarized as follows: First, the fact of inelastic own-price elasticity of petroleum implies that the dependency of Korean manufacturing sector on petroleum and coal will be persistent even in a sharp fluctuation of petroleum price. Second, the effects of price increase in natural gas on demand for petroleum and coal are very significant. Thus, price decline of natural gas rather than price declines of coal and petroleum could be more effective as an energy price policy for the reduction of $CO_2$ emission. The assessment on this implication will remain for future researches.

• Korea journal of population studies
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• v.25 no.1
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• pp.257-289
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• 2002

In this study we analyse how the tobacco prices have an effect on the national health. The level of tobacco price will fluctuate its consumers demand and eventually affect the national health status. We estimate tobacco consumption function as well as households'demand system in which tobacco and health expenditure functions are included. Demand elasticities are estimated and evaluated in order to find future policies to improve the national health by controlling the national tobacco consumption There are two econometric approaches app1ied in this study. The lent tobacco demand analysis method is mm tobacco consumption function model. Using national indices of tobacco price, tobacco consumption and other related variables, tobacco consumption function is estimated. The other is micro demand system analysis by using Korean urban households expenditure data during the period of 1991 to 1999. The own price elasticity which is estimated from national tobacco demand per capita is -0.19 for all people and -0.176 for the adults over 18, which means 100% price increase will cause decease of tobacco demand at 19% and 17.6% per each The cross vice elasticity which is estimated between tobacco and health expenditure of urban households demand system is -0.2328, which implies 100% of tobacco price increase will decrease 23.28% of health expenditure. The low price elasticities imply that tobacco price increase will increase total tobacco sales volume. 100% of tobacco price increase will bring about 79% increase of total tobacco sales volume according to our scenario. Korea's tobacco demand is negatively responsive to fluctuations in its price. The health expenditure is also negatively relatedto the tobacco price fluctuation. These empirical outputs could be utilized as the basis of government's tax policy to control national tobacco consumption in the future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.204-208
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• 2018

In this paper, we proposed and evaluated the time series deep learning prediction model for learning fluctuation pattern of stock price. Recurrent neural networks, which can store previous information in the hidden layer, are suitable for the stock price prediction model, which is time series data. In order to maintain the long - term dependency by solving the gradient vanish problem in the recurrent neural network, we use LSTM with small memory inside the recurrent neural network. Furthermore, we proposed the stock price prediction model using bidirectional LSTM recurrent neural network in which the hidden layer is added in the reverse direction of the data flow for solving the limitation of the tendency of learning only based on the immediately preceding pattern of the recurrent neural network. In this experiment, we used the Tensorflow to learn the proposed stock price prediction model with stock price and trading volume input. In order to evaluate the performance of the stock price prediction, the mean square root error between the real stock price and the predicted stock price was obtained. As a result, the stock price prediction model using bidirectional LSTM recurrent neural network has improved prediction accuracy compared with unidirectional LSTM recurrent neural network.