• 한국의상디자인학회지
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• 제12권4호
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• pp.183-195
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• 2010

The purpose of this study is to find out the difference of evaluation of product and service quality according to consumers' attitude toward price in internet clothing purchase. This study surveyed 400 male and female consumers in their 20s-30s for empirical analysis in August 2010 who have ever purchased clothing through internet shopping malls. For statistical analysis, descriptive statistics, factor analysis, ANOVA analysis, Duncan test and cluster analysis are carried out using SPSS for Windows 12.0. The results are as follows. First, consumers' attitude toward price dimensions in internet clothing purchase are found 6 factors of sales proneness, price-prestige, price-comparison, low price, utility value and pricequality. Second, based on the attitude toward price dimensions, consumers are categorized into utility value seeking, sales price seeking, multi-dimension price seeking, lack price consciousness, low price seeking group. Third, there are significant differences in product quality and service quality depending on attitude toward price-based consumer types. In particular, sales price seeking and multi-dimension price seeking groups have higher values on product and service quality than other groups. The results of this study will help internet fashion mall businesses to develop price strategy and manage product and service quality.

• 한국농공학회논문집
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• 제50권3호
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• pp.71-79
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• 2008

Generally the price of agricultural products has much different characteristics from that of manufacturing products. If products have the limitation of long-term storage and the short period of cultivation, the price of products can be more unstable. Moreover, the price forecasting is very difficult because it doesn't follow any cycle or trend. However price can be regarded as risk instead of uncertainty if we can calculate the probability of price. Reliability analysis techniques are used for forecasting the price change of Chinese cabbage. This study aims to show the usability of reliability analysis for price forecasting. A price-forecasting model was developed based on weather data of the first 10 days of the full cultivating cycle (80 days) 70 days and the average price and standard deviation of wholesale market prices from 1996 to 2001 and applied to forecast the boom price, or the orice which is over the tolerance of market prices, of upland Chinese cabbage in 2002 and 2003. Applied results showed the possibility of boom price forecasting using reliability analysis techniques.

• 대한가정학회지
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• 제45권6호
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• pp.49-59
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• 2007

The purposes of this study were to determine the price elasticities of foodcourt-styled university foodservice, and to identify the attributes that affect these price elasticities. Questionnaires were distributed to 700 students at the K University in Masan, from September 21-27, 2006. 478 questionnaires were ultimately included in the final analysis(response rate: 68.3%). For statistical analysis, SPSS(12.0) was used to conduct the descriptive analysis, t-test, and ANOVA. The results of this study were as follows. The average meal price for in-campus foodservice was \ 2,196 and the average meal price for an off-campus restaurant was \3,044. The university students recognized that the proper price for in-campus foodservice and an off-campus restaurant were, respectively, \2,127 and \ 2,884. The price elasticities for foodcourt-styled university foodservice were 4.20(Kko-Bul-Kko-Bul), 3.83(Il-Poom-Hyang), and 4.10(Ne-Mo-Baek_Ban). The factors that affected price elasticity included the frequency of visiting foodservice, foodservice satisfaction, price satisfaction, and customer's responses to increased meal prices. The recommended price strategy for foodcourt-styled university foodservice was to lower meal price, which would attract more students and increase the sales volume. Simultaneously, foodservice managers should attempt to improve and increase customer satisfaction and the customer's perceived value for meal price. Overall, price elasticity may prove helpful in predicting the customer's behaviors on price changes, and may provide useful basic data for foodservice managers when establishing price strategy.

• 한국의류산업학회지
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• 제15권3호
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• pp.381-392
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• 2013

This study analyzed the effects of internet fashion consumer characteristics and shopping motivation on price sensitivity as well as the effect of price sensitivity on negative purchasing behavior. A survey was conducted from August 10 to September 20 in 2012 and 364 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The characteristics of internet fashion consumers were composed of innovation tendency, impulse buying tendency, information orientation, and variety seeking tendency. Shopping motivation was composed of convenient motivation, social motivation, hedonic motivation, product motivation, and economic motivation. The information orientation and variety seeking tendency of internet fashion consumers influenced the price search. The innovation tendency, impulse buying tendency, and variety seeking tendency of internet fashion consumers influenced the price importance. Convenient motivation, hedonic motivation, and product motivation positively affected the price search; however, social motivation negatively affected the price search. The social motivation, hedonic motivation, and economic motivation of internet fashion consumers positively affected price importance. Price search and price importance influenced the purchasing delay; in addition, price search influenced the switching intention. The results of this study provide useful information for customer management and internet shopping mall marketing strategies.

• 유통과학연구
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• 제15권1호
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• pp.71-81
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• 2017

Purpose - Consumers heuristically have a specific stereotype on the price level of individual retail format because each format provides them with a different level of purchase satisfaction and emotional benefits. However, if price image which is consumers' overall impression of the aggregate price level of a retailer does not match with their expectations, its price level would be perceived as unfair. It will eventually lead to dissatisfaction and decreased revisit intention. Focused on department store and discount store, this study was designed to verify whether the price fairness plays a role of mediating effect on two influential relationships between price image and post-purchase satisfaction, and price image and repatronage intention. Research design, data, and methodology - A main survey was conducted to 140 students and 128 effective responses were used for the related analysis. T-test, factor analysis, reliability test, and mediated regression analysis were performed. Six hypotheses were developed to examine the mediating effect of price fairness on the two influential relationships between price image and post-purchase satisfaction, and price image and repatronage intention. It was also examined whether the price image of two different retail format is formed differently or not. Results - People perceived the price images of the two retail formats differently. Overall price level of department store is much higher than that of discount store. Analysis results showed that price image did not solely have a significant influence on post-purchase satisfaction unless price fairness as a mediating variable is added. Price fairness turned out to be having a significant influence on relationship between price image and repatronage intention. It influences on repatronage intention directly and also via price fairness. Conclusions - Post-purchase satisfaction can be achieved only if people perceive the price image as fair no matter how the price level is high or low according to traits of retail formats. If they think it's not fair, they would disapprove of the rightness for the price image, and also express their dissatisfaction with it. Consumers willingly make repeated visits to a store if they are convinced of appropriate price level which is perceived as fair, and if they experienced a satisfaction with overall benefits a particular store offered.

• Ocean and Polar Research
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• 제36권4호
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• pp.327-341
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• 2014

This study aims to analyze causality among Wando abalone producer prices by size using a vector autoregressive model to expiscate the leading-price of Wando abalone in various price classes by size per kg. This study, using an analytical approach, applies a unit-root test for stability of data, a Granger causality test to learn about interaction among price classes by size for Wando abalone, and a vector autoregressive model to estimate the statistical impact among t-1 variables used in the model. As a result of our leading-price analysis of Wando abalone producer prices by shell size using a VAR model, first, DF, PP, and KPSS tests showed that the Wando abalone monthly price change rate by size differentiated by logarithm were stable. Second, the Granger causality relationship analysis showed that the price change rate for big size abalone weakly led the price change rate for the small and medium sizes of abalone. Third, the vector autoregressive model showed that three price change rates of t-1 period variables statistically, significantly impacted price change rates of own size and other sizes in t period. Fourth, the impulse response analysis indicated that the impulse responses of structural shocks for price change rate for big size abalone was relatively more powerful in its own size and in other sizes than shocks emanating from other sizes. Fifth, the variance decomposition analysis indicated that the price change rate for big size abalone was relatively more influential than the price change rates for medium and small size abalone.

• 수산경영론집
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• 제52권1호
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• pp.47-63
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• 2021

The purpose of this study is to identify the leading price between Jeju and Wando's oliver flounder producer price and to analyze the dynamic effect of the regional producer price using the panel VAR model. In the process of analysis, it was confirmed that there are unit roots in the monthly data of Jeju and Wando's oliver flounder producer price. So, in order to avoid spurious regression, the rate change of producer price which carries out log difference was used in the analysis. As a result of the analysis, first, the panel Granger causality test showed that the influence of the change rate of producer price in oliver flounder in Jeju was slightly larger than that in Wando, but it was found that each region all leads the change rate of the producer price in oliver flounder. Second, the panel VAR estimation showed that the rate change of producer price in Jeju and Wando a month ago had a statistically significant effect on the change rate of producer price of each region. Third, the impulse response analysis indicated that other regions are affected a little more than the same region in case of the occurrence of the impact on the error terms of the change rate of produce price in Jeju and Wando oliver flounder. Fourth, the variance decomposition analysis showed that the change rate of producer price in the two regions was higher explained by Jeju compared to Wando. In conclusion, it is expected that the above results can not only be useful as basic data for the stabilization of oliver flounder producer price and the establishment of policies for easing volatility but can also help the oliver flounder industry operate its business.

• 정보기술과데이타베이스저널
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• 제6권2호
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• pp.115-130
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• 1999

The price structure of housing market varies depending upon market price policy rather than low or high price policy because of IMF. The object of this study is to develop an analysis system for analyzing housing market and its demand. The analysis system consists of four major categories: macro index analysis, market decision analysis, housing market analysis, and consumer analysis. We model each category by using a variety of techniques such as generalized linear model, categorical analysis, bubble analysis, drill-down analysis, price sensitivity meter analysis, optimum price index analysis, profit index measurement analysis, correspondence analysis, conjoint analysis, and multidimensional scaling analysis. Seoul apartment data is analyzed to demonstrate the practical usefulness of the system.

• 대한임베디드공학회논문지
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• 제17권1호
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• pp.51-58
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• 2022

Various studies have been conducted from the past to the present because stock price forecasts provide stability in the national economy and huge profits to investors. Recently, there have been many studies that suggest stock price prediction models using various input data such as macroeconomic indicators and emotional analysis. However, since each study was conducted individually, it is difficult to objectively compare each method, and studies on their impact on stock price prediction are still insufficient. In this paper, the effect of input data currently mainly used on the stock price is evaluated through the predicted value of the deep learning model and the error rate of the actual stock price. In addition, unlike most papers in emotional analysis, emotional analysis using the news body was conducted, and a method of supplementing the results of each emotional analysis is proposed through three emotional analysis models. Through experiments predicting Microsoft's revised closing price, the results of emotional analysis were found to be the most important factor in stock price prediction. Especially, when all of input data is used, error rate of ensembled sentiment analysis model is reduced by 58% compared to the baseline.

• 대한지역사회영양학회지
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• 제4권4호
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• pp.587-593
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• 1999

The purpose of this study were to : (a) analyzed price elasticity of university students in foodservice operations and (b)provide insight for price decision-making. Questionnaires were composed of price elasticity, the utilization and opinions of students on university foodservice operations, and demographic information regarding respondents. The questionnaires were distributed to 600 university students of 6 universities located in Seoul. Statistical data analysis was completed using the SAS package for descriptive analysis, t-test, ANOVA, and Pearson’s correlation. The results of this study can be summarized as follows: The average price for lunch was ￦1,663 for campus food, and ￦2,965 for off-campus restaurants. The frequency of utilizing the university cafeteria was fairly high. Students felt that the proper price for lunch was ￦1,446, presenting a lower price than the actual average price for lunch. The price elasticity was investigated in relation to the change in utilization rate when these was a price increase. The price elasticity was 2.03, with significant differences between sex, age, and major. The groups utilizing the university cafeteria frequently, taking longer time to go to off-campus or that were satisfied with the university cafeteria, had a lower price elasticity than those that did not. The results of this study suggest that predicting the price elasticity of the target market would assist the pricing policy, and the fact that the same students have different price elasticity by place and atmosphere can be used in marketing strategies.