• Asia-Pacific Journal of Business
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• v.11 no.1
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• pp.17-26
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• 2020

Purpose - This paper studies the welfare impacts of behavior-based price discrimination (BBPD) when firms are asymmetric in quality improvement costs. Design/methodology/approach - To this end, we consider a differentiated duopoly model with an inherited market share, where firms first make quality decisions and then compete in prices according to the pricing scheme, namely, uniform pricing or BBPD. Findings - We show that BBPD increases social welfare relative to uniform pricing if the firms' cost gap is large enough. This is because BBPD induces more consumers to buy a high-quality product than under uniform pricing, and because a low-cost firm's profit loss from BBPD decreases as the cost difference increases. Research implications or Originality - Our analysis offers policy implications for markets where BBPD raises antitrust concerns, and quality competition prevails.

• Journal of Distribution Science
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• v.12 no.2
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• pp.73-79
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• 2014

Purpose - The Korean government has revised the distribution industry development law to regulate large-scale retailer operations to protecting medium- and small-scale retailers and traditional markets. According to the revised law, large-scale retailers must follow regulations on operating hours and compulsory store closures two days per month. Based on the revised distribution industry development law, most local governments regulate operation hours and they have adopted compulsory closure programs for large-scale retail stores. However, it is argued that fresh food producers suffer from a decrease in sales based on the compulsory closure of stores operated by large-scale retailers. Large-scale retailers reduce their fresh food orders from agricultural and fishery producers because of the compulsory store closures. Fresh food producers also suffer from a decrease in prices because reduced orders lead to a decrease in auction prices based on the availability of excess goods in wholesale markets. This paper investigates the effects of operation regulations for large-scale retailers on agricultural producers by surveying agricultural and fishery producer organizations. Research design, data, methodology - A survey was conducted on 117 producer organizations of fruits and vegetables, cereals, fisheries, and livestock products from September 10 to October 4, 2012. Survey items are annual sales, shares of sales accounted for by large-scale retailers, reduction of orders and prices from large-scale retailers, methods to deal with the sales reduction, unfair trade practices of large-scale retailers, opinion of the large-scale retailer regulations, and so on. The average sales of the sampled producer organizations are 13.7 billion won and the average share of sales accounted for by large-scale retailers is 35.4%. Results - Survey results show that the sample producer organizations' sales decreased 10.1% because of the compulsory closures of stores operated by large-scale retailers. It is estimated that the total sales of producer organizations decreased 371.2 billion won because of the regulations on the operation of large-scale retailers. In addition to the direct effect of a sales decrease due to order reduction, agricultural and fishery producer organizations suffered from the secondary effect of price reduction in wholesale markets. When orders from large-scale retailers decreased, most agricultural and fishery producer organizations shipped redundant products to wholesale markets, decreasing auction prices. It was estimated that the price received decreased 21.9% when sold in other marketing channels. As producer organization sales decreased, it was reported that the labor force employed by producer organizations also decreased by 15.1%. Therefore, we can conclude that the regulations for large-scale retailer operations resulted in negative impacts on agricultural producers. Conclusions - Although the sales reduction due to the regulations for large-scale retailer operations are not great, the cumulative effects due to the continued compulsory closure of stores operated by large-scale retailers could be great. This paper suggests governmental programs that could help agricultural producer organizations to find new and effective marketing channels such as direct marketing, farmers' markets, exports, Internet shopping, and so on.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.27-43
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• 2024

The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.

• The Research Journal of the Costume Culture
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• v.22 no.1
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• pp.86-98
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• 2014

This study analyzed fashion businesses based on the 6P's, products, prices, place, promotion, people, and patron for business owners in the Myeongdong commercial fashion district. Furthermore, this study proposed plans that would activate the Myeongdong fashion district and continuously develop it as a global fashion city. A survey was conducted from August to September, 2012 for 249 fashion business owners in Myeongdong. Eventually, only 208 questionnaires were used for the analysis. The research results were as follows. First, domestic brands have the largest share in the market and sales of fashion accessories were higher than the sales of clothes. Second, the prices for those fashion items ranged from low to mid-price. Third, the opening of new shops keeps increasing, and the size of the shops falls between ten and twenty pyeong generally. 'Self-production' was the highest form of production compared to any other form, and regarding importation sites, importation from overseas was the highest. Fourth, regarding promotion types, the sales in shops was the most commonly used promotion method compared to television and magazine advertising, and personal selling. Fifth, the proportion of male proprietors was larger than that of female proprietors. Most employees had less than five years of sales experience. Sixth, the main customers were females in their 20s and the proportions of Korean and foreign customers was similar.

• International Commerce and Information Review
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• v.7 no.4
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• pp.325-349
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• 2005

One aspect of the globalization of the financial market after the 1980s is represented by the concurrent monetarization of the national stock markets. As the IR activity is regarded as a new financial productivity measure, the IR activity in the stock market is being emphasized domestically and internationally. This study analyzes domestic IR activities and compares them with foreign IR activities. Specifically the "road show", a typical IR activity, which is known to resolve the information asymmetry between the firm and the investors is analyzed to see the extent of the their value increase impact on the firm. The study employs domestic and international firms that publicly announced "road shows" after April 2004. Event studies are done to see the existence of abnormal return after the public announcement of road shows. Domestic firms were found to have positive IR impacts on the stock prices, but international firms were found to have negative IR impacts on the stock prices. Also it was found that international public announcement of the road show have stronger positive impact on the stock price than domestic public announcement. The investigation of the statistically significant difference of CAR before and after the fair public announcement enforcement rule showed that the positive CAR impact is strengthened after the adoption of the rule. The conclusion is that increase of the firm value after the road show implies that the information asymmetry is reduced by the active IR actions on the firm side. The policy implication is that we have to reassure the understanding of the role of the IR activities. Specifically Korean firms may have to encourage IR activities to share the information of the firms with the investors, which may result in the trustworthy relationship between the firms and investors.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.47-54
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• 2019

This study confirms the polarity of news articles on apartment prices using Opinion Mining which has widely been used for a big data analysis. The analyses were carried out utilizing internet news articles posted on the Naver for two years: 2012 and 2018. We proposed a sentiment analysis model and modeled a topic-oriented sentiment dictionary construction methods. As a result of analyzing the proposed sentiment analysis model, it was confirmed that there was a difference according to the tendency of the media companies in selecting social issues at the time of rising apartment prices. At the same time, we were able to find more affirmative articles in the media companies which share similar sentiment with the government in charge. In this paper, we proposed a sentiment analysis model that can be used in real estate field and analyzed the polarity of unformatted data related to real estate. In order to integrate them into various fields in the future, it is necessary to build the sentiment dictionaries by themes, as well as to collect various unformatted data over extended periods.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.137-143
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• 2018

Korea's air passenger traffic has been growing steadily. In this paper, we propose a forecasting model of air passenger demand to ascertain the growth trend of air passenger transportation performance in Korea. We conducted a simulation based on System Dynamics with the demand as a dependent variable, and international oil prices, GDP and exchange rates as exogenous variables. The accuracy of the model was verified using MAPE and $R^2$, and the proposed prediction model was verified as an accurate prediction model. As a result of the demand forecast, it is predicted that the air passenger demand in Korea will continue to grow, and the share of low cost carriers will increase sharply. The addition of the Korean transportation performance of foreign carriers in Korea and the transportation performance of Korean passengers due to the alliance of airlines will provide a more accurate forecast of passenger demand.

• Korean Journal of Construction Engineering and Management
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• v.7 no.4 s.32
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• pp.109-117
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• 2006

The domestic construction market is recovered after a foreign exchange crises but recently it's daunted again because of the sustainable real estate regulation policy by the government. The other aspect, after the WTO(World Trade Organization) system opened overseas construction is growing continuously with growth of international economy and opening of market through world. Moreover, for ballooning oil prices an orders increase by oil-producing countries, the Middle East, gives good chances to domestic construction enterprises. But, the domestic firms decrease on our domain by chases of developing country and high-technology or advanced country. This research will indicate processes of our construction business to analyze performance record about our overseas construction from the 1970s to present. Based on the results it intends to search for problems of our construction enterprises and provide useful analytic data for expansion of overseas construction market.

• Management & Information Systems Review
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• v.32 no.1
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• pp.63-85
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• 2013

This study tries to investigate the fundamental implications inherent in inventory asset information(specifically, unexpected inventory investment) by analyzing how the relationship between unexpected inventory investment and future operating performance. And we study how is the response of the stock market participants to the fundamental implications inherent in inventory asset information. Prior papers often assume the efficient market and they view the significant relation between stock prices and financial indicators as evidence of the contribution of such indicators to future earnings. Leading indicators are attracting the market's attention for equity valuation. We study whether one leading indicator (unexpected Inventories) forecasts future earnings, and whether market participants fully reflect the predictive ability when they sets share prices(Mishkin test, 1983). Our empirical results of the study are summarized as follows. Current unexpected inventory investment is negatively associated with future operating performance. Also, our evidence is that the stock market participants overprice the contribution of unexpected inventory investment when predicting future earnings. Furthermore, a hedge strategy that uses the overpricing gives significant future abnormal returns. The overall results help the users of financial reports, researchers of accounting, and the accounting principle setting body.