• Korean Journal of Construction Engineering and Management
• /
• v.10 no.3
• /
• pp.42-52
• /
• 2009

From the beginning of 2000, Korean housing market has experienced cyclical volatility because of the global economic fluctuation such as steady decline in the interest rate and the house price bubble. In response to these state Korean Government announced policies about housing sales system kinds of Sales Unit Price Restraint and Post-Sales System to stabilize housing market. But such policies has brought unprecedented arguments both for and against, most of whom still seem to stick to self-centered judgement ahead of impact on housing market. In an integrated point of view, applying the system dynamics modeling, the paper aims at proposing basic Korean housing market dynamics models based on basis principles of housing market determined by supply and demand. And then, after research policies about housing sales system, analyze Impact on Korean Housing Market by change of Sales Systems applying policies to basic Korean housing market dynamics models.

• Journal of the Economic Geographical Society of Korea
• /
• v.15 no.2
• /
• pp.192-205
• /
• 2012

This study estimates how much climate variables affect the land price and acreage of rice paddy and dry farm field in agriculture with the case of Gangwon-do in Korea. To this end, we capitalize upon the Ricardian approach based upon the panel data on climate, soil and geography, farmland prices and acreage, other economic and social variables for 11 municipal units comprising Gangwon-do during the period of 1992-2010. Our empirical analysis shows that the temperature variable has negative economic impacts on the price and acreage of rice paddy and dry farm field, confirming that the temperature variable is much significant than that of precipitation in global warming. On the other hand, the other determinants of farmland price and acreage are different with the type of farmland in Gangwon-do.

• Journal of Information Technology Applications and Management
• /
• v.24 no.2
• /
• pp.25-37
• /
• 2017

The aim of this study is to analyze the effect of the growing activities of large purchasing enterprises on the trust of small and medium size contractors, which is mediated by 'purchase accompany activity'. This subject study includes the first and second contractor companies in Korea. The results of this study are as follow. First, the knowledge and cost price sharing activities of major purchase vendor with cooperative company had a positive effect on the trust of cooperative company, however this was not so with the information sharing activities in that case. Second, the trust of contractors on large purchasing enterprises was positively influenced by sharing activities with purchasing activities of major company. Third, the knowledge and cost price sharing activities of purchasing enterprise with contractors on the sharing activities were mediated by the trust of contracting company on the large purchase enterprise. According to this study, the mediated effect of trust relationship can influence a contracting company. Whereas preceding studies of sharing activities were conducted about unidirectional instruct of large purchase enterprises to small and medium size contracting companies, this study was conducted on bidirectional effects, which included knowledge, cost price, information sharing activities between contracting companies and large purchasing enterprises. Conclusively, this study showed the possibility of spreading cognitive and change about mutual benefits strategy between small and medium size contracting company and large purchasing enterprise.

• Journal of Digital Convergence
• /
• v.18 no.7
• /
• pp.223-228
• /
• 2020

The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

• Journal of Digital Convergence
• /
• v.17 no.11
• /
• pp.163-170
• /
• 2019

A new revenue recognition standard was adopted in 2018. The purpose of this paper is to analyse how K-IFRS 1115 'Revenue from Contracts with Customers' affects the revenue recognition of the telecommunication firms and to suggest a regulatory policy for the telecommunications industry. It shows identifying performance obligations for bundles, determining the transaction price and allocating the transaction price to the performance obligation and how to account for it using case study. The most important change in the telecommunication companies's revenue is to allocate the transaction price to two performance obligations: telecom services and mobile handset sales. As a result, sales revenue are expected to drop en masse. This study provides important implications for the regulatory accounting policy of the telecommunications industry.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.1-7
• /
• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.1
• /
• pp.32-41
• /
• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• Korean Journal of Agricultural Science
• /
• v.39 no.1
• /
• pp.125-132
• /
• 2012

The 2009 Agricultural Survey is one of the most important official statistics about agricultural sector, which is mostly used by experts. However users have kept claiming about the problems of the 2009 Agricultural Survey, which need to be discussed in the academic area. The purpose of this paper is to analyze the 2009 Agricultural Survey and the level of satisfaction of users and to evaluate the 2009 Agricultural Survey. Then, the paper presents some suggestions to upgrade the 2009 Agricultural Survey. The results of studies present a few findings: First, the 2009 Agricultural Survey shows overall excellence but should focus on adding more various topics in agricultural sector, Second, the 2009 Agricultural Survey need to consider offering micro level data for experts such as data in the city or county level, Third, the 2009 Agricultural Survey had better to offer more specific examination and guide line for general users.

• Current Photovoltaic Research
• /
• v.8 no.3
• /
• pp.86-93
• /
• 2020

The investment in solar and wind generation is rapidly increasing with government's renewable expansion policy and Renewable Portfolio Standard (RPS). Since the large penetration of solar and wind generation increases the variability and uncertainty of supply and demand balance in power system, the government is pursuing the policy of supplying energy storage system (ESS) linked to renewable energy. ESS contributes to the ease of transmission and distribution grid by shifting PV generation from daytime to evening hours. Recently, the declining market price of REC as ESS incentive, policies to cut down incentives and limited ESS storage due to fire events lead to the aggravation of long-term profitability, thus working as a barrier of ESS spreading. In this study, the factors affecting the profit of ESS are analyzed and brief indicators are derived. Based on the indicators, the profit changes are analyzed considering the variation of REC market price and REC incentive weights. Based on the profit change with respect to the increase of ESS capacity, economical ESS installation capacity is suggested.

• Journal of Distribution Science
• /
• v.14 no.11
• /
• pp.29-36
• /
• 2016

Purpose - Intense debate is occurring over support for farmers in Korea, specifically on the justification, policy design, and equality issues of the farm support programs. Given this debate, a new type of farm program in the US, a market flexible revenue program(the Average Crop Revenue Election, ACRE), is examined. ACRE stands in contrast to traditional programs that tie payments to price and have parameters that are fixed or change only infrequently. Research design, data, and methodology - Based on the ACRE program formulas, the potential payments are estimated by crop year, program crop and geographical area using the FSA acreage and payment rate data. Results - If all US farm program acres were in ACRE over the 2009-2013 crop years, payments would have totaled $7.95 billion or 1.2 percent of average market receipts for US crops. Enacting ACRE as a revenue program instead of a similarly-structured price-only program increased payments by $1.75 billion or 28 percent. Conclusions - Potential payments by ACRE largely reflected the distribution of the value of production across the program crops eligible for ACRE as well as across state geographical areas. If program parameters can be made acceptable and if data availability issues can be addressed, market flexible revenue programs offer a farm policy option that can address many of the concerns that have arisen over farm policy in Korea.