The rental housing market in South Korea, specifically monthly rent with deposit, has been expanding over the last three decades (8.2% in 1990 to 21.0% in 2020), partly replacing the traditional Jeonse market. The distribution of rent has changed due to public rental subsidies and the emergence of luxury rental housing, while the distribution of rental household income has been polarized because of the emergence of rich renters. This study attempts to measure the structural changes in the rental market by developing a new indicator of income-rent mismatch. Using the seven series of the Korea Housing Survey, this study analyzed the changes in rent (reflecting the conversion rate) and income levels of rental households in 2006 (base year) and 10-15 years later (the analysis year) at the national level and at the spatial unit of 16 metropolitan cities and provinces (excluding Sejong), respectively, by dividing them into quartile data. The result reveals that rental housing was undersupplied in middle- and high-income rental housing due to the decline in the highest quartile (25%→18%) and the third quartile groups (25%→20%), while the supply of public rental housing expanded for the second quartile (25%→28%) and the lowest quartile (25%→35) groups. On the demand side, the highest income quartile shrank (25%→21%), while the lowest income quartile grew (25%→31%). Comparing the 16 metropolitan cities and provinces, there were significant regional differences in the direction and intensity of changes in rent and renter household income. In particular, the rental market in Seoul was characterized by supply polarization, which led to an imbalance in the income distribution of rental households. The structural changes in the apartment rental market were different from those in the non-apartment rental market. The findings of this study can be used as a basis for future regional rental housing markets. The findings can support securing affordable rental housing stock for each income quartile group on monthly rent and developing housing stability measures for a balance between income and rent distribution in each region.
Numerous methods have been applied to assess the antibacterial effectiveness of hand hygiene products. However, the different results obtained through various evaluation methods have complicated our understanding of the real efficacy of the products. Few studies have compared test methods for assessing the efficacy of hand hygiene products. In particular, reports on ex vivo pig skin testing are limited. This study aimed to compare and characterize the methodologies applied for evaluating hand hygiene products, involving in vitro, ex vivo, and in vivo approaches, applicable to both leave-on sanitizers and wash-off products. Our further aim was to enhance the reliability of ex vivo test protocols by identifying influential factors. We performed an in vitro method (EN1276) and an in vivo test (EN1499 and ASTM2755) with at least 20 participants, against Serratia marcescens or Escherichia coli and Staphylococcus aureus. For the ex vivo experiment, we used pig skin squares prepared in the same way as those used in the in vivo test method and determined the optimal treated sample volumes for sanitizers and the amount of water required to wash off the product. The hand sanitizers showed at least a 5-log reduction in bacterial load in the in vitro test, while they showed little antibacterial activity in the in vivo and ex vivo tests, particularly those with a low alcohol content. For the hand wash products, the in vitro test was limited because of bubble formation or the high viscosity of the products and it showed low antibacterial activity of less than a 1-log reduction against E. coli. In contrast, significantly higher log reductions were observed in ex vivo and in vivo tests, consistently demonstrating these results across the two methods. Our findings revealed that the ex vivo and in vivo tests reflect the two different antibacterial mechanisms of leave-on and wash-off products. Our proposed optimized ex vivo test was more rapid and more precise than the in vitro test to evaluate antibacterial results.
Purpose: Currently, the only routes that enter Yeongjong Island are Yeongjong Bridge and Incheon Bridge, which are private roads. The purpose of this study is to predict and study changes in transportation demand for new routes and two existing routes according to the plan to open the 3rd Bridge, a new route, in December 2025. Method: The basic data for traffic demand forecast were O/D and NETWORK data from 2021.08, KOTI. In order to examine the reliable impact of Yeongjong Bridge and Incheon Bridge on the opening of the 3rd Bridge, it is necessary to correct the traffic distribution of Yeongjong Island and Incheon International Airport to suit reality, and in this study, the trip distribution by region was corrected and applied using Mobile Big Data. Result: As of 2026, the scheduled year of the opening of the 3rd Bridge, two alternatives, Alternative 1 (2,000 won) and Alternative 2 (4,000 won), were established and future transportation demand analysis was conducted, In the case of Alternative 1, which is similar to the existing private road toll restructuring, the traffic volume of the 3rd Bridge was predicted to be 42,836 out of 199,101 veh/day in the Yeongjong area in 2026, and the traffic volume reduction rate of the existing road was analyzed as 21.5%. Conlclusion: As a result of the review (based on Alternative 1), the proportion of convertted traffic on the 3rd Yanji Bridge was estimated to be 70% of Yeongjong Bridge and 30% of Incheon Bridge, and 21.5% of the predicted traffic reduction on the existing road when the 3rd Yanji Bridge was opened is considered appropriate considering the results of the case review and changes in conditions. It is judged that it is a way to secure the reliability of the prediction of traffic demand because communication big data is used to reflect more realistic traffic distribution when predicting future traffic demand.
Internet commerce has been growing at a rapid pace for the last decade. Many firms try to reach wider consumer markets by adding the Internet channel to the existing traditional channels. Despite the various benefits of the Internet channel, a significant number of firms failed in managing the new type of channel. Previous studies could not cleary explain these conflicting results associated with the Internet channel. One of the major reasons is most of the previous studies conducted analyses under a specific market condition and claimed that as the impact of Internet channel introduction. Therefore, their results are strongly influenced by the specific market settings. However, firms face various market conditions in the real worlddensity and disutility of using the Internet. The purpose of this study is to investigate the impact of various market environments on a firm's optimal channel strategy by employing a flexible game theory model. We capture various market conditions with consumer density and disutility of using the Internet.
shows the channel structures analyzed in this study. Before the Internet channel is introduced, a monopoly manufacturer sells its products through an independent physical store. From this structure, the manufacturer could introduce its own Internet channel (MI). The independent physical store could also introduce its own Internet channel and coordinate it with the existing physical store (RI). An independent Internet retailer such as Amazon could enter this market (II). In this case, two types of independent retailers compete with each other. In this model, consumers are uniformly distributed on the two dimensional space. Consumer heterogeneity is captured by a consumer's geographical location (ci) and his disutility of using the Internet channel (${\delta}_{N_i}$).
shows various market conditions captured by the two consumer heterogeneities.
(a) illustrates a market with symmetric consumer distributions. The model captures explicitly the asymmetric distributions of consumer disutility in a market as well. In a market like that is represented in
(c), the average consumer disutility of using an Internet store is relatively smaller than that of using a physical store. For example, this case represents the market in which 1) the product is suitable for Internet transactions (e.g., books) or 2) the level of E-Commerce readiness is high such as in Denmark or Finland. On the other hand, the average consumer disutility when using an Internet store is relatively greater than that of using a physical store in a market like (b). Countries like Ukraine and Bulgaria, or the market for "experience goods" such as shoes, could be examples of this market condition.
summarizes the various scenarios of consumer distributions analyzed in this study. The range for disutility of using the Internet (${\delta}_{N_i}$) is held constant, while the range of consumer distribution (${\chi}_i$) varies from -25 to 25, from -50 to 50, from -100 to 100, from -150 to 150, and from -200 to 200.
summarizes the analysis results. As the average travel cost in a market decreases while the average disutility of Internet use remains the same, average retail price, total quantity sold, physical store profit, monopoly manufacturer profit, and thus, total channel profit increase. On the other hand, the quantity sold through the Internet and the profit of the Internet store decrease with a decreasing average travel cost relative to the average disutility of Internet use. We find that a channel that has an advantage over the other kind of channel serves a larger portion of the market. In a market with a high average travel cost, in which the Internet store has a relative advantage over the physical store, for example, the Internet store becomes a mass-retailer serving a larger portion of the market. This result implies that the Internet becomes a more significant distribution channel in those markets characterized by greater geographical dispersion of buyers, or as consumers become more proficient in Internet usage. The results indicate that the degree of price discrimination also varies depending on the distribution of consumer disutility in a market. The manufacturer in a market in which the average travel cost is higher than the average disutility of using the Internet has a stronger incentive for price discrimination than the manufacturer in a market where the average travel cost is relatively lower. We also find that the manufacturer has a stronger incentive to maintain a high price level when the average travel cost in a market is relatively low. Additionally, the retail competition effect due to Internet channel introduction strengthens as average travel cost in a market decreases. This result indicates that a manufacturer's channel power relative to that of the independent physical retailer becomes stronger with a decreasing average travel cost. This implication is counter-intuitive, because it is widely believed that the negative impact of Internet channel introduction on a competing physical retailer is more significant in a market like Russia, where consumers are more geographically dispersed, than in a market like Hong Kong, that has a condensed geographic distribution of consumers.