This study was carried out to evaluate the antioxidant and antibacterial activities of Glycyrriza uralensis Fisher (Jecheon, Korea) extracts obtained by various extraction conditions (85% ethanol, heating temperatures and times), and to establish the optimal extraction condition of G. uralensis for the application as cosmetic ingredients. The extracts obtained under different conditions were concentrated and made in the powdered (sample-1) and were the crude extract solutions without concentration (sample-2). The antioxidant effects were determined by free radical scavenging activity (
Experiments were conducted to investigate rice varietal response to low water and air temperatures at different growth stages from 1975 to 1980 in a phytotron in Suweon and in a cold water nursery in Chooncheon. Germination ability, seedling growth, sterility of laspikelets, panicle exertion, discoloration of leaves, and delay of heading of recently developed indica/japonica cross(I/J), japonica, and indica varieties at low air temperature or cold water were compared to those at normal temperature or natural conditions. The results are summarized as follows: 1. Practically acceptable germination rate of 70% was obtained in 10 days after initiation of germination test at 15\circ_C for japonica varieties, but 15 days for IxJ varieties. Varietal differences in germination ability at suboptimal temperature was greatest at 16\circ_C for 6 days. 2. Cold injury of rice seedlings was most severe at the 3.0-and 3.5-leaf stage and it was reduced as growth stage advanced. A significant positive correlation was observed between cold injury at 3-leaf stage and 6-leaf stage. 3. At day/night temperatures of 15/10\circ_C seedlings of both japonica and I/J varieties were dead in 42 days. At 20/15\circ_C japonica varieties produced tillers actively, but tillering of I/J varieties was retarded a little. At 25/15\circ_C, both japonica and I/J varieties produced tillers most actively. Increase in plant height was proportional to the increase in all varieties. 4. In I/J varieties the number of differentiated panicle rachis branches and spikelets was reduced at a day-night temperature of 20-15\circ_C compared to 25-20 or 30-25\circ_C, but not in japonica varieties although panicle exertion was retarded at 20-15\circ_C. The number of spikelets was not correlated with the number of primary rachis branches, but positively correlated with that of secondary rachis branches. 5. Heading of rice varieties treated with 15\circ_C air temperature at meiotic stage was delayed compared to that at tillering stage by 1-3 days and heading was delayed as duration of low temperature treatment increased. 6. At cold water treatment of 17\circ_C from tillering to heading stage, heading of japonica, I/J, and cold tolerant indica varieties was delayed 2-6, 3-9, and 4-5 days, respectively, Growth stage sensitive to delay of heading delay at water treatment were tillering stage, meiotic stage, and booting tage in that order, delay of heading was greater in indica corssed japonica(Suweon 264), japonica(Suweon 235), and cold tolerant indica(Lengkwang) varieties in that order. Delay of heading due to cold water treatment was positively correlated with culm length reduction and spikelet sterility. 7. Elongation of culms and exertion of panicles of rice varieties treated with low air temperature 17\circ_C. Culm length reduction rate of tall varieties was lower than that of short statured varieties at low temperature. Panicle exertion was most severaly retarded with low temperature treatment at heading stage. Generally, retardation of panicle exertion of 1/1 varieties was more severe than that of japonica varieties at low temperature. There was a positive correlation between panicle exertion and culm length at low temperature. 8. The number of panicles was increased with cold water treatment at tillering stage, but reduced at meiotic stage. As time of cold water treatment was conducted at earlier growth stage, culm length was shorter and panicle exertion poorer. 9. Sterility of all rice varieties was negligible at 17\circ_C for three days but 30.3-85.2% of strility was observed for nine-day treatment at 17\circ_C. Among the tested varieties, sterility of Suweon 264 and Milyang 42 was highest and that of Suweon 290 and Suweon 287 was lowest. The most sensitive growth stage to low temperature induced sterility was from 15 to 5 days before heading. There was positive correlation between sterility of rice plants treated with low temperature at meiotic and heading stage. 10. Percentage of spikelet sterility was greatest at cold water treatment at meiotic stage (auricle distance -15～-10cm) and it was higher in 1/1 (Suweon 264, Joseng tongil), japonica (Nongbaek, Towada), and cold tolerance indica(Lengkwang) varieties in the order. Level of cold water and position of young-ear affected on the sterility of varieties at meiotic stage; percentage of spikelet sterility of variety, Lengkwang, of which young-ear was located above the cold water level was high, but that of short statured variety, Suweon 264, of which young-ear was located in the cold water was lower. 11. Percentage of ripened grains was not reducted at 15\circ_C air temperature for three days at full heading stage in all varieties. However, at six-day low temperature treatment Suweon 287, Suweon 264 showed percentage of ripended grains lower than 60%, but at nine-day low temperature treatment all varieties showed percentage of ripened grains lower than 60%. Low temperature treatment of 17\circ_C from 10 days after heading for 20 days did not affect on the ripening of all varieties. 12. Uptake of nitrogen, phosphorous, potassium, calcium, and magnesium in whole plants was higher at average air temperature of 25\circ_C, but concentration of the elements was lower compared to those at 19\circ_C. However, both total uptake and concentration of manganese were higher at 19\circ_C compared to 25\circ_C. 13. Higher application of nitrogen, phosphorus, silicate, and compost increased yield of rice due to increased number of panicles and spike let fertility in cold water irrigated paddy.
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.
Introduction As consumers' purchase behavior change into a rational and practical direction, the discount store industry came to have keen competition along with rapid external growth. Therefore as a solution, distribution businesses are concentrating on developing PB(Private Brand) which can realize differentiation and profitability at the same time. And as improvement in customer loyalty beyond customer satisfaction is effective in surviving in an environment with keen competition, PB is being used as a strategic tool to improve customer loyalty. To improve loyalty among PB users, it is necessary to develop PB by examining properties of a customer group, first of all, quality level perceived by consumers should be met to obtain customer satisfaction and customer trust and consequently induce customer loyalty. To provide results of systematic analysis on relations between antecedents influenced perceived quality and variables affecting customer loyalty, this study proposed a research model based on causal relations verified in prior researches and set 16 hypotheses about relations among 9 theoretical variables. Data was collected from 400 adult customers residing in Seoul and the Metropolitan area and using large scale discount stores, among them, 375 copies were analyzed using SPSS 15.0 and Amos 7.0. The findings of the present study followed as; We ascertained that the higher company reputation, brand reputation, product experience and brand familiarity, the higher perceived quality. The study also examined the higher perceived quality, the higher customer satisfaction, customer trust and customer loyalty. The findings showed that the higher customer satisfaction and customer trust, the higher customer loyalty. As for moderating effects between PB and NB in terms of influences of perceived quality factors on perceived quality, we can ascertain that PB was higher than NB in the influences of company reputation on perceived quality while NB was higher than PB in the influences of brand reputation and brand familiarity on perceived quality. These results of empirical analysis will be useful for those concerned to do marketing activities based on a clearer understanding of antecedents and consecutive factors influenced perceived quality. At last, discussions about academical and managerial implications in these results, we suggested the limitations of this study and the future research directions. Research Model and Hypotheses Test After analyzing if antecedent variables having influence on perceived quality shows any difference between PB and NB in terms of their influences on them, the relation between variables that have influence on customer loyalty was determined as Figure 1. We established 16 hypotheses to test and hypotheses are as follows; H1-1: Perceived price has a positive effect on perceived quality. H1-2: It is expected that PB and NB would have different influence in terms of perceived price on perceived quality. H2-1: Company reputation has a positive effect on perceived quality. H2-2: It is expected that PB and NB would have different influence in terms of company reputation on perceived quality. H3-1: Brand reputation has a positive effect on perceived quality. H3-2: It is expected that PB and NB would have different influence in terms of brand reputation on perceived quality. H4-1: Product experience has a positive effect on perceived quality. H4-2: It is expected that PB and NB would have different influence in terms of product experience on perceived quality. H5-1: Brand familiarity has a positive effect on perceived quality. H5-2: It is expected that PB and NB would have different influence in terms of brand familiarity on perceived quality. H6: Perceived quality has a positive effect on customer satisfaction. H7: Perceived quality has a positive effect on customer trust. H8: Perceived quality has a positive effect on customer loyalty. H9: Customer satisfaction has a positive effect on customer trust. H10: Customer satisfaction has a positive effect on customer loyalty. H11: Customer trust has a positive effect on customer loyalty. Results from analyzing main effects of research model is shown as