• 수산경영론집
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• 제44권1호
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• pp.59-70
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• 2013

The purpose of this paper is to integrate various models of price formation and let the data choose the most proper model. After the data choose the proper model, one can analyze the price formation process and demand structures for fishery resources under the restriction of Korean fisheries regulations. This study suggests the integrated model including quasi-linear price formation model, Translog price formation model, AIDS price formation model and Lewbel price formation model as level variables. It also suggests another integrated model including AIDS price formation model, Rotterdam price formation model, Latinen-Theil price formation model and Neves price formation model as difference variables. The empirical results show that the AIDS price formation model is the most preferred in both level and difference variables of fishery resources. The estimated parameters show that all sample species have (-) sign of price flexibilities, thus following the law of demand. The scale flexibilities of all species are estimated as (-) sign, thus being adapted to the theory. The contribution and results are summarized as follows. First, the integrated model of fishery market demand has been developed and the data can choose the proper model without arbitrary choice of the researcher. Second, the fishery market demand structure could be analyzed in a way different from the ordinary demand analysis, which is based upon price flexibility and scale flexibility. Third, the integrated model for fishery resources can be used easily when catching restrictions are imposed by policies.

• 유통과학연구
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• 제13권8호
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• pp.61-71
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• 2015

Purpose - Before the year 2000, the housing prices in Korea were increasing every decade. After 2000, for the first time, Korea experienced a decrease in housing prices, and the repetitive cycle of price fluctuation started. Such a "boom and bust cycle" is a worldwide phenomenon. The current study proposes a mathematical model to explain price fluctuation cycles based on the theory of consumer psychology. Specifically, the model incorporates the effects of buyer expectations of future prices on actual price changes. Based on the model, this study investigates various independent variables affecting the amplitude of price fluctuations in housing markets. Research design, data, and methodology - The study provides theoretical analyses based on a mathematical model. The proposed model uses the following assumptions of the pricing mechanism in housing markets. First, the price of a house at a certain time is affected not only by its current price but also by its expected future price. Second, house investors or buyers cannot predict the exact future price but make a subjective prediction based on observed price changes up to the present. Third, the price is determined by demand changes made in previous time periods. The current study tries to explain the boom-bust cycle in housing markets with a mathematical model and several numerical examples. The model illustrates the effects of consumer price elasticity, consumer sensitivity to price changes, and the sensitivity of prices to demand changes on price fluctuation. Results - The analytical results imply that even without external effects, the boom-bust cycle can occur endogenously due to buyer psychological factors. The model supports the expectation of future price direction as the most important variable causing price fluctuation in housing market. Consumer tendency for making choices based on both the current and expected future price causes repetitive boom-bust cycles in housing markets. Such consumers who respond more sensitively to price changes are shown to make the market more volatile. Consumer price elasticity is shown to be irrelevant to price fluctuations. Conclusions - The mechanism of price fluctuation in the proposed model can be summarized as follows. If a certain external shock causes an initial price increase, consumers perceive it as an ongoing increasing price trend. If the demand increases due to the higher expected price, the price goes up further. However, too high a price cannot be sustained for long, thus the increasing price trend ceases at some point. Once the market loses the momentum of a price increase, the price starts to drop. A price decrease signals a further decrease in a future price, thus the demand decreases further. When the price is perceived as low enough, the direction of the price change is reversed again. Policy makers should be cognizant that the current increase in housing prices due to increased liquidity can pose a serious threat of a sudden price decrease in housing markets.

• Journal of applied mathematics & informatics
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• 제5권3호
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• pp.805-810
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• 1998

In this paper we set the stock price model in security market when the price process is a continuous semartingale and find a unigue solution of price process model.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.187-190
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• 2006

We proposed a new real estate price appra isal model that can appreciate the efficiencies of each criteria that would affect the price. The proposed Real Estate Price Appraisal Model is developed by the DEA-AR model which enhances the DEA-CCR model. We used the unit-cost per criteria method to set the assurance region of each weights of the DEA-AR model. In order to estimate the unit cost of major criteria effecting the price of real estate, we used the Goal Programming so that the price of real estate reaches the actual price being traded in. We expect that this approach could be helpful to make an objective real estate price appraisal.

• 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.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.694-706
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• 2019

In this study, we applied the long short-term memory (LSTM) model to classify the cryptocurrency price time series. We collected historic cryptocurrency price time series data and preprocessed them in order to make them clean for use as train and target data. After such preprocessing, the price time series data were systematically encoded into the three-dimensional price tensor representing the past price changes of cryptocurrencies. We also presented our LSTM model structure as well as how to use such price tensor as input data of the LSTM model. In particular, a grid search-based k-fold cross-validation technique was applied to find the most suitable LSTM model parameters. Lastly, through the comparison of the f1-score values, our study showed that the LSTM model outperforms the gradient boosting model, a general machine learning model known to have relatively good prediction performance, for the time series classification of the cryptocurrency price trend. With the LSTM model, we got a performance improvement of about 7% compared to using the GB model.

• 한국경영과학회지
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• 제9권2호
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• pp.9-14
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• 1984

The competitive bidding model with the reserve price has been studied by Riley and Samuelson. We extend their studies to the competitive model with the reserve price and the entry fee. First we present the bidder's optimal strategy, the winner's expected profit, the auctioner's expected revenue in the first-price sealed bidding model, and next those in the second-price sealed bidding model.

• 한국국방경영분석학회지
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• 제28권1호
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• pp.67-82
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• 2002

In this paper, we consider a rule of application of PRICE(Parametric Review of Information for Costing and Evaluation) model to the environment of Korean defense industry. The PRICE model which is a computer model to estimate the cost of an acquisition program, was developed for the regulation of defense acquisition program in the United States. Therefore, it is essential for us to figure out how we can adopt it under our defense acquisition regulations. We will give an alternative method to apply the PRICE model to the mapping problem between two regulations.

• 한국정보시스템학회지:정보시스템연구
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• 제22권4호
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• pp.85-115
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• 2013

Digital knowledge and information goods as experience goods have some unique characteristics such as close to zero reproduction and distribution cost, high price volatility, and low price acceptability. For the reasons, the pricing policies of digital knowledge goods are very difficult and complicate. Also, most consumers of digital goods have experienced cognitive dissonance after buying decision. The purpose of this paper is to investigate what factors affect the price acceptability level and cognitive dissonance of digital knowledge goods buyers. This paper suggest a structural model that was established by the cognitive dissonance theory and S-O-R(Stimulus-Organization-Response) model. The model is consisted of four exogenous variables and three endogenous variables. The empirical test and statistical analysis suggest following results and practical implications. The variables such as product involvement and perception of price fairness that have positive roles to price acceptability have strong influence on the all the three endogenous variables. But the variables such as sale proneness and price mavenism that have negative roles to price acceptability have little influence on the all the three endogenous variables. In the model, the payment intention was very important mediating variable between exogenous variables and two dependent variables, ie. price acceptability and cognitive dissonance. These results imply that the digital knowledge portals must have some differentiated pricing policies to the customers who have price consciousness and price mavenism. Also, they need some special promotions to whom have positive attitude to the value of digital goods.

• 한국의류학회지
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• 제26권11호
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• pp.1605-1614
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• 2002

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.