• Journal of Korea Trade
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• v.23 no.8
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• pp.1-26
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• 2019

Purpose - This paper investigates the recent trade collapse, recovery, and prolonged slowdown to shed light on the discussions about whether the current slowdown is structural or cyclical. I examine structural, cyclical, and heterogeneous aspects of the recent trade trends using detailed statistics of a small open economy, South Korea, whose economic success and growth have been heavily dependent on exports. Design/methodology - I use both aggregated and disaggregated trade statistics of South Korea. I apply the following methodologies: 1) I decompose the trade growth into the extensive and the intensive margin and observe the effect of prices over time. 2) I estimate the trade-income elasticities focusing on the world's import demand, separately for goods from the world and from Korea. 3) I compare the drop in goods exports in slowdown and trade collapse, which are the two unusual periods in the recent history when world trade has substantially dropped altogether. Findings - I show that while the last drop of trade after 2015 has cyclical aspects, there is evidence that the continued slowdown from 2012 is structural: 1) the so-called 'China factor' is found in the analysis of trade-income elasticity of the world and China for imports from Korea. 2) The bilateral trade barriers between Korea and its principal trading partners are universally tightening. 3) Firm sizes, destination countries, and the mode of transactions affect disaggregated trade flows during the slowdown periods. Originality/value - This paper contributes to the debate regarding whether the current trade slowdown is structural or cyclical. I provide two concrete evidence that the export drop in 2015 stems from low oil prices: one is the divergence of Korean export value index from its export quantity index, which started in late 2014 when oil prices plunged. I also contribute to the literature by providing evidence that Korea's trade barriers with important trading partners are steadily increasing since 2012 as the protectionist measures toward Korea's export products are steeply increasing after the global financial crisis.

• Journal of Families and Better Life
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• v.28 no.4
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• pp.127-138
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• 2010

This study examines the consumer behavior towards service satisfaction and loyalty in the wedding service market when differentiated services were provided through a market segmentation that includes products, prices, and channels for service choices. This study uses the questionnaire research method to compare the wedding service consumer satisfaction between Korea and Japan. As for married couples, the convenience of transportation and name-recognition were the most important considerations among Koreans when it comes to choosing a place for wedding ceremonies. Meanwhile, Japanese counterparts considered reasonable prices and wedding services quality as the most important factors. In terms of the level of satisfaction in services provided by wedding halls, Korean married couples were found to be more satisfied than Japanese counterparts. Second, the impact of the level of satisfaction with wedding services on consumer loyalty was analyzed. It was found that name-recognition was an important influencing factor among both Koreans and Japanese. An increased satisfaction with name-recognition, resulted in higher loyalty by individuals to wedding halls. In terms of showing loyalty to wedding halls, Koreans were found to be more influenced by name-recognition than the Japanese. Third, there was no significant difference found in japan in terms of the impact of the level of satisfaction with wedding services loyalty.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.8
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• pp.1403-1414
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• 2010

Consumer decisions and responses about the price to pay vary. Some consumers might decide the appropriate price range prior to shopping, while others compare and evaluate prices. Especially, consumers can have different reference points for price evaluation based on various price searching behavior that represent heterogeneous responses for prices in the clothing purchase decision-making process. This research identifies how consumers evaluate the price and helps explain their decision-making based on price searches. By analyzing qualitative research, we found that consumers recalled price information as a representative indicator and product level price information through the internal search. Their level of internal references can be an important factor affecting price evaluations. In addition, each consumer groups were subdivided into high and low external searching. The four types of responses to price were classified in the price search process and the identified differences in the price evaluation. Therefore, pricing strategy needs to be differentiated for these various consumer types.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• Journal of the Korean Society of Clothing and Textiles
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• v.37 no.7
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• pp.972-983
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• 2013

This study investigates the effects of fashion innovativeness and utilization on the price perception of formal wear and climbing wear as well as gender differences on price perception and the relationship of the variables. Price perception measurements were based on reference price and reservation price; subsequently, a premium price ratio was calculated based on the measured prices. A survey that involved male and female adult consumers was conducted in Daegu in August 2011. A total of 321 responses were analyzed using descriptive statistics, factor analysis, reliability analysis, correlations and independent sample t-test. Two factors of fashion innovativeness were derived and named as unique-oriented innovativeness and change-oriented innovativeness. The utilization of formal wear and climbing wear was higher in the male group versus the female group. Reference price and reservation price were identified similar to the actual consumer purchasing prices reported in previous studies. Male consumers showed a tendency in price perception in accordance with the utilization. The change-oriented innovativeness of the female group led to a positive relationship with the perceived price of climbing jackets.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.1
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• pp.1-17
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• 2008

Market segmentation is a key strategic factor in increasing the expected profits, especially in the practice of revenue management. A manufacturing firm should manage both manufacturing quantities and pricing decisions over its segmented markets to maximize the expected profits, setting different price for each different segment. Also, market segments should be kept separate in order to prevent demand leakages between different market segments. In fact, even though the markets for different products are firmly segmented, it is not easy to keep separate segmentation because many products might be substitutable by customer buying behavior. That is, customers respond to price changes by purchasing other market's products instead of purchasing the originally requested products, which causes demand substitution effect ; This kind of substitution is referred to as price-driven substitution. Therefore, decisions on optimal prices should take into account the differences in customers' valuation of the different products. We consider a deterministic model for deciding optimal prices in the presence of price-driven substitution, and we compare both symmetrical-and asymmetrical-type demand substitutions between two segmented markets. The objective of this study is to develop analytical and numerical models to examine the impact of price-driven substitution on the optimal price levels and the total expected profits.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.106-110
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• 2021

In this study, the main factors affecting the number of passengers and cargo volume transported by air between Korea, China and Japan over the past 20 years are to be identified. For the analysis, data from three countries' GDP and per capita as well as exchange rates and international oil prices were used, and OLS multiple regression analysis and fixed effect analysis were performed. As a result of the analysis, both the number of passengers and cargo volume transported by air showed a negative (-) direction for GDP, which represents the country's economic power, and a positive (+) direction, for per capita GDP, which represents income level. And the increase in the exchange rate between China and Japan acted in a positive (+) direction on the increase in the number of passengers, and the effect of oil prices was found to be limited.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.6
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• pp.621-634
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• 2011

This study analyzed the influencing factors on consumer purchase deferrals for internet clothing shopping. In addition, based on consumer demographics, it compared the differences of purchase deferrals with respect to clothing items, prices, and types of shopping malls. For an empirical study, 405 questionnaires were answered by respondents in their 20s and 30s with internet clothing purchase deferral experience. Data were analyzed using: SPSS for Windows 12.0 and descriptive statistics, reliability analysis, factor analysis, $X^2$-test, and regression analysis. The results of this study were as follows. First, the order of items with many purchase deferrals in internet clothing shopping were casual T-shirt>casual skirts>pants, one-piece>suits>sportswear>blouse/shirts and 58.3% of purchase deferrals happened when the price was below \50,000. Second, the significant differences in products, prices, and shopping malls for purchase deferrals were identified according to consumer demographics. There were significant differences in clothing items according to gender, age, marriage, and education; however, there were significant differences only according to gender in terms of price. There were significant differences according to gender, age, marriage, education, and income in terms of the used shopping malls. Third, for the analysis of the influence of diverse factors that can affect purchase deferrals for internet clothing shopping, the more information search, purchase deferral habits, perceived risks, and deficiency in shopping mall supply conditions were when higher purchase deferrals occurred. For a strong competitive online market, this study can help internet clothing shopping mall entrepreneurs manage products and customers by analyzing the lists of purchase deferrals indicated in "cart" and by administrating the influential factors for purchase deferral.

• Journal of the Korean Society of Safety
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• v.33 no.4
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• pp.62-71
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• 2018

The purpose of this study is to conduct surveys on demanders using financial aid projects to prevent industrial accidents and to improve them. It is divided into clean business and loan support business through the structured questionnaire. In the case of clean business, the following results were obtained. Most of the applications were received within three months after application. The most important factor considered by the consumer is the amount of support, which is considered to consider the substantial improvement as follows.The expectation for the reduction of industrial accidents after the project was 96.1% and compared to before and after the actual business, it showed a 46.8% decrease from the previous year. In addition, the cost decreased by 21.8%, the facility utilization rate increased by 24.4%, the sales increased by 15.9%, and the average number of workers increased by 6.0. As for the sustainability of the business, 86.6% of the respondents said that they should continue to do so. The following results were obtained in the case of loan support projects. Industrial accidents decreased by 45.2% from the previous year. Costs decreased by 19.4%, facility utilization rose by 26.7%, sales increased by 14.9%, and the number of workers increased by an average of 2.8. In the case of suppliers, prevention of industrial accidents at the business sites participating in the clean business was the highest factor (67.0%). 89% of respondents were aware of the disposal criteria for ineligible suppliers. 50.6% of the respondents answered that it is appropriate to maintain the current level, and 39.4% of respondents answered that they should strengthen. The prices for the support items were more than 15% higher than the market prices.

• Smart Media Journal
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• v.11 no.3
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• pp.62-73
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• 2022

Researches on the prediction of domestic apartment sales price have been continuously conducted, but it is not easy to accurately predict apartment prices because various characteristics are compounded. Prior to predicting apartment sales price, the analysis of major factors, influencing on sale prices, is of paramount importance to improve the accuracy of sales price. Therefore, this study aims to analyze what are the factors that affect the apartment sales price in Gwangju, which is currently showing a steady increase rate. With 6 years of Gwangju apartment transaction price and various social factor data, several maching learning techniques such as multiple regression analysis, random forest, and deep artificial neural network algorithms are applied to identify major factors in each model. The performances of each model are compared with RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R² (coefficient of determination). The experiment shows that several factors such as 'contract year', 'applicable area', 'certificate of deposit', 'mortgage rate', 'leading index', 'producer price index', 'coincident composite index' are analyzed as main factors, affecting the sales price.