• East Asian Economic Review
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• v.27 no.3
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• pp.213-242
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• 2023

This paper investigates whether the price of cryptocurrency is determined by the US dollar index, the price of investment assets such gold and oil, and the implied volatility of the KOSPI. Overall, the returns on cryptocurrencies are best predicted by the trading volume of the cryptocurrency both in-sample and out-of-sample. The estimates of gold and the dollar index are negative in the return prediction, though they are not significant. The dollar index, gold, and the cryptocurrencies seem to share characteristics which hedging instruments have in common. When investors take notice of the imminent market risks, they increase the demand for one of these assets and thereby increase the returns on the asset. The most notable result in the out-of-sample predictability is the predictability of the returns on value-weighted portfolio by gold. The empirical results show that the restricted model fails to encompass the unrestricted model. Therefore, the unrestricted model is significant in improving out-of-sample predictability of the portfolio returns using gold. From the empirical analyses, we can conclude that in-sample predictability cannot guarantee out-of-sample predictability and vice versa. This may shed light on the disparate results between in-sample and out-of-sample predictability in a large body of previous literature.

• Journal of Information Technology Applications and Management
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• v.30 no.1
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• pp.1-9
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• 2023

Interest in the future of the battery market is growing as Tesla announces plans to increase production of electric vehicles and to produce batteries. Tesla announced an action plan to reduce battery prices by 56% through 'Battery Day', which included expansion of factories to internalize batteries and improvement of materials and production technology. In the trend of automobile electrification, the expansion of the battery market, which accounts for 40% of the cost of electric vehicles, is inevitable, and the size of the electric vehicle battery market in 2026 is expected to increase more than five times compared to 2016. With the development of materials and process technology, the energy density of electric vehicle batteries is increasing while the price is decreasing. Soon, electric vehicles and internal combustion locomotives are expected to compete on the same line. Recently, the mileage of electric vehicles is approaching that of an internal combustion locomotive due to the installation of high-capacity batteries. In the EV battery market, Korean, Chinese and Japanese companies are fiercely competing. Based on market share in the first half of 2020, LG Chem, CATL, and Panasonic are leading the EV battery supply, and the top 10 companies included 3 Korean companies, 5 Chinese companies, and 2 Japanese companies. All-solid, lithium-sulfur, sodium-ion, and lithium air batteries are being discussed as the next-generation batteries after lithium-ion, among which all-solid-state batteries are the most active. All-solid-state batteries can dramatically improve stability and charging speed by using a solid electrolyte, and are excellent in terms of technology readiness level (TRL) among various technology alternatives. In order to increase the competitiveness of the battery industry in the future, efforts to increase the productivity and economy of electric vehicle batteries are also required along with the development of next-generation battery technology.

• Asia Marketing Journal
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• v.14 no.1
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• pp.83-98
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• 2012

In a market where new and used cars are competing with each other, we would run the risk of obtaining biased estimates of cross elasticity between them if we focus on only new cars or on only used cars. Unfortunately, most of previous studies on the automobile industry have focused on only new car models without taking into account the effect of used cars' pricing policy on new cars' market shares and vice versa, resulting in inadequate prediction of reactive pricing in response to competitors' rebate or price discount. However, there are some exceptions. Purohit (1992) and Sullivan (1990) looked into both new and used car markets at the same time to examine the effect of new car model launching on the used car prices. But their studies have some limitations in that they employed the average used car prices reported in NADA Used Car Guide instead of actual transaction prices. Some of the conflicting results may be due to this problem in the data. Park (1998) recognized this problem and used the actual prices in his study. His work is notable in that he investigated the qualitative effect of new car model launching on the pricing policy of the used car in terms of reinforcement of brand equity. The current work also used the actual price like Park (1998) but the quantitative aspect of competitive price promotion between new and used cars of the same model was explored. In this study, I develop a model that assumes that the cross elasticity between new and used cars of the same model is higher than those amongst new cars and used cars of the different model. Specifically, I apply the nested logit model that assumes the car model choice at the first stage and the choice between new and used cars at the second stage. This proposed model is compared to the IIA (Independence of Irrelevant Alternatives) model that assumes that there is no decision hierarchy but that new and used cars of the different model are all substitutable at the first stage. The data for this study are drawn from Power Information Network (PIN), an affiliate of J.D. Power and Associates. PIN collects sales transaction data from a sample of dealerships in the major metropolitan areas in the U.S. These are retail transactions, i.e., sales or leases to final consumers, excluding fleet sales and including both new car and used car sales. Each observation in the PIN database contains the transaction date, the manufacturer, model year, make, model, trim and other car information, the transaction price, consumer rebates, the interest rate, term, amount financed (when the vehicle is financed or leased), etc. I used data for the compact cars sold during the period January 2009- June 2009. The new and used cars of the top nine selling models are included in the study: Mazda 3, Honda Civic, Chevrolet Cobalt, Toyota Corolla, Hyundai Elantra, Ford Focus, Volkswagen Jetta, Nissan Sentra, and Kia Spectra. These models in the study accounted for 87% of category unit sales. Empirical application of the nested logit model showed that the proposed model outperformed the IIA (Independence of Irrelevant Alternatives) model in both calibration and holdout samples. The other comparison model that assumes choice between new and used cars at the first stage and car model choice at the second stage turned out to be mis-specfied since the dissimilarity parameter (i.e., inclusive or categroy value parameter) was estimated to be greater than 1. Post hoc analysis based on estimated parameters was conducted employing the modified Lanczo's iterative method. This method is intuitively appealing. For example, suppose a new car offers a certain amount of rebate and gains market share at first. In response to this rebate, a used car of the same model keeps decreasing price until it regains the lost market share to maintain the status quo. The new car settle down to a lowered market share due to the used car's reaction. The method enables us to find the amount of price discount to main the status quo and equilibrium market shares of the new and used cars. In the first simulation, I used Jetta as a focal brand to see how its new and used cars set prices, rebates or APR interactively assuming that reactive cars respond to price promotion to maintain the status quo. The simulation results showed that the IIA model underestimates cross elasticities, resulting in suggesting less aggressive used car price discount in response to new cars' rebate than the proposed nested logit model. In the second simulation, I used Elantra to reconfirm the result for Jetta and came to the same conclusion. In the third simulation, I had Corolla offer $1,000 rebate to see what could be the best response for Elantra's new and used cars. Interestingly, Elantra's used car could maintain the status quo by offering lower price discount ($160) than the new car ($205). In the future research, we might want to explore the plausibility of the alternative nested logit model. For example, the NUB model that assumes choice between new and used cars at the first stage and brand choice at the second stage could be a possibility even though it was rejected in the current study because of mis-specification (A dissimilarity parameter turned out to be higher than 1). The NUB model may have been rejected due to true mis-specification or data structure transmitted from a typical car dealership. In a typical car dealership, both new and used cars of the same model are displayed. Because of this fact, the BNU model that assumes brand choice at the first stage and choice between new and used cars at the second stage may have been favored in the current study since customers first choose a dealership (brand) then choose between new and used cars given this market environment. However, suppose there are dealerships that carry both new and used cars of various models, then the NUB model might fit the data as well as the BNU model. Which model is a better description of the data is an empirical question. In addition, it would be interesting to test a probabilistic mixture model of the BNU and NUB on a new data set.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.47-55
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• 2016

The proliferation of the Internet and related technologies has led to a new form of distribution channels, namely online retailers. The conventional offline and the new online retailers have different transaction costs perceived by the consumers in the following perspectives: the accessibility to the product information, the traffic cost and the opportunity cost for the time to visit the store, the delivery time and the possibility of 'touch and feel' to test the quality of the product. In particular, the online retailers have lower distribution cost structure in that they do not have physical stores, which results in lower selling price. Thus they continuously offer price competition against offline retailers using the lower selling cost as competitive weapon. Moreover the emergence of the social commerce is likely to intensify the competition between the online and offline retailers. To survive in this fierce competition, the offline retailers are trying to defend their business interests by sticking to offline transaction in anticipation of increased customer loyalty, customer's preference for 'touch and feel' style shopping, and others. Despite of these efforts, customers who touch and feel a product in an offline store but purchase the product through an online retailer are increasing. To protect such customers, recently, some of the offline retailers began to provide the mobile discount service (MDS) which enables the offline customers to purchase a product at a discounted price through the mobile applications. In business competitions, the price discount strategy is usually considered to secure more market share at the cost of lower profit. In this study, however, we analyze the effect of MDS as a weapon for securing more profit. To do this, we set up a game model between the online and offline retailers which incorporates the effect of the MDS. By numerically analyzing the Nash equilibrium of the game, some managerial implications for using the MDS for more profit are discussed.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.132-141
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• 2019

1990s, Construction market continued to grow in South Korea exceeding 20% of GDP. In 2015, more than 30 years of old multi-family dwellings amounted to 4.93 million and it continues to increase until 2019. In Particular, the share of Public rental Housing accounts for 90.6% of South Korea's Total aging housing. Before checking the feasibility of Construction Project Management such as Renovation and Reconstruction, Checklists were presented through price impact factor analysis and analysis of housing construction system(Regulation). Based on 32 Price Influencing factors and 20 Indicators based on the housing construction system The Construction project management seems appropriate. As a result, the 22 complexes were found to be suitable for remodeling. This study is meaningful enough to be used for Domestic rental Housing construction and Construction project management and to suggest specificity. Future Research is needed to Quantify the checklist.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.105-113
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• 2016

This study analyzed and verified panel data based on CSMAR (China Stock Market & Accounting Research) DB from 2002 to 2014 in order to find out significant differences of conservative accounting before and after Chinese companies adopted international accounting standards. Financial changes in companies can occur at the point of change in accounting standards, and as the difference would affect conservative accounting, it is important to understand conservatism in financial transaction. In this study, earnings per share and price, return on equity, and debt ratio were measured. As a result of analysis, conservative accounting has increased after the introduction of accounting standards, and as the debt ratio was higher, the proportion of conservative accounting was higher. Thus, at a certain point of change in accounting standards, companies apply conservative accounting in order to improve reliability in an unstable future financial environment. Therefore, this study is expected not only to practically influence business practice in changes in GAAP rules but also to provide useful guidance for future studies.

• Journal of agriculture & life science
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• v.43 no.5
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• pp.63-72
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• 2009

The flower industry in Gyeongnam Province is the second largest flower producing area after Gyeonggi Province in Korea. Gyeongnam Province is also one of the provinces where flower industry was first introduced, which has started in the middle of 1960s. The share of Gyeongnam Province was 16.2% in area and 14.3% in sales in 2006. The most outstanding feature of Gyeongnam's flower industry is that it has been particularly specialized in cut-flower industry, the share of which was 77.6% of Gyeongnam Province in area. Another feature is that the industry continued to be shrunk in size due to the expansion of urban area. For Gyeongnam's floral industry to be competitive not only in domestic market but in international market, its competitiveness in quality and price is kept being promoted. In addition, the availability of land is essential to the growth of the flower industry of Gyeongnam Province.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.559-575
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• 2014

Individual investors are increasingly flocking to message boards to seek, clarify, and exchange information. Businesses like Seekingalpha.com and business magazines like Fortune are evaluating, synthesizing, and reporting the comments made on message boards or blogs. In March of 2012, Yahoo! Finance Message Boards recorded 45 million unique visitors per month followed by AOL Money and Finance (19.8 million), and Google Finance (1.6 million) [McIntyre, 2012]. Previous studies in the finance literature suggest that online communities often provide more accurate information than analyst forecasts [Bagnoli et al., 1999; Clarkson et al., 2006]. Some studies empirically show that the volume of posts in online communities have a positive relationship with market activities (e.g., trading volumes) [Antweiler and Frank, 2004; Bagnoli et al., 1999; Das and Chen, 2007; Tumarkin and Whitelaw, 2001]. The findings indicate that information in online communities does impact investors' investment decisions and trading behaviors. However, research explicating the correlation between information on online communities and stock market activities (e.g., trading volume) is still evolving. Thus, it is important to ask whether a volume of posts on online communities influences trading volumes and whether trading volumes also influence these communities. Online stock message boards offer two different types of information, which can be explained using an economic and a psychological perspective. From a purely economic perspective, one would expect that stock message boards would have a beneficial effect, since they provide timely information at a much lower cost [Bagnoli et al., 1999; Clarkson et al., 2006; Birchler and Butler, 2007]. This indicates that information in stock message boards may provide valuable information investors can use to predict stock market activities and thus may use to make better investment decisions. On the other hand, psychological studies have shown that stock message boards may not necessarily make investors more informed. The related literature argues that confirmation bias causes investors to seek other investors with the same opinions on these stock message boards [Chen and Gu, 2009; Park et al., 2013]. For example, investors may want to share their painful investment experiences with others on stock message boards and are relieved to find they are not alone. In this case, the information on these stock message boards mainly reflects past experience or past information and not valuable and predictable information for market activities. This study thus investigates the two roles of stock message boards-providing valuable information to make future investment decisions or sharing past experiences that reflect mainly investors' painful or boastful stories. If stock message boards do provide valuable information for stock investment decisions, then investors will use this information and thereby influence stock market activities (e.g., trading volume). On the contrary, if investors made investment decisions and visit stock message boards later, they will mainly share their past experiences with others. In this case, past activities in the stock market will influence the stock message boards. These arguments indicate that there is a correlation between information posted on stock message boards and stock market activities. The previous literature has examined the impact of stock sentiments or the number of posts on stock market activities (e.g., trading volume, volatility, stock prices). However, the studies related to stock sentiments found it difficult to obtain significant results. It is not easy to identify useful information among the millions of posts, many of which can be just noise. As a result, the overall sentiments of stock message boards often carry little information for future stock movements [Das and Chen, 2001; Antweiler and Frank, 2004]. This study notes that as a dependent variable, trading volume is more reliable for capturing the effect of stock message board activities. The finance literature argues that trading volume is an indicator of stock price movements [Das et al., 2005; Das and Chen, 2007]. In this regard, this study investigates the correlation between a number of posts (information on stock message boards) and trading volume (stock market activity). We collected about 100,000 messages of 40 companies at KOSPI (Korea Composite Stock Price Index) from Paxnet, the most popular Korean online stock message board. The messages we collected were divided into in-trading and after-trading hours to examine the correlation between the numbers of posts and trading volumes in detail. Also we collected the volume of the stock of the 40 companies. The vector regression analysis and the granger causality test, 3SLS analysis were performed on our panel data sets. We found that the number of posts on online stock message boards is positively related to prior stock trade volume. Also, we found that the impact of the number of posts on stock trading volumes is not statistically significant. Also, we empirically showed the correlation between stock trading volumes and the number of posts on stock message boards. The results of this study contribute to the IS and finance literature in that we identified online stock message board's two roles. Also, this study suggests that stock trading managers should carefully monitor information on stock message boards to understand stock market activities in advance.

• Proceedings of the Korean Fiber Society Conference
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• 2003.04a
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• pp.146-149
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• 2003

There are three major bonding types such as chemical bonding, thermal bonding, mechanical bonding to produce nonwoven fabrics. The development of the past few years has shown that the share of thermally bonded webs is growing steadily. The viability of the thermal bonding process is rooted in the price advantage obtained by lower energy costs. However, the thermal bonding process also obtains the quality requirements of the market place. (omitted)

• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.132-151
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• 1994

Quality is a critical competitive factor in today's environment because of the impact of quality on market share, productivity and costs. Especially in Korean companies, the importance of quality is heightened as they are losing price competitiveness compared to the new industrialized countries. The traditional approach to quality improvement has been focused on workers. The primary means to achieving acceptable outgoing quality has been to inspect quality by adding more inspectors and inspection stations. This is an example of quality cost that can be reduced through the preventive actions against bad quality. Quality cost is best viewed as a measure of costs specifically associated with the achievement or nonachievement of product/service quality required by customers. This paper examines the concept of quality cost, provides guidance to implementing a quality cost system, and identifies the limitations of quality cost information. These limitations are the target for future research for an efficient and effective implementation of quality cost system.