• Journal of Industrial Convergence
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• v.20 no.12
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• pp.179-186
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• 2022

This study aims to develop a predictive model to suggest a used sales price to sellers and buyers when trading used tablet PCs. For model development, we analyzed the real used tablet PC transaction data and additionally collected detailed product information. We developed several predictive models and selected the best predictive model among them. Specifically, we considered a multiple linear regression model using the used sales price as a dependent variable and other variables in the integrated data as independent variables, a multiple linear regression model including interactions, and the models from stepwise variable selection in each model. The model with the best predictive performance was finally selected through cross-validation. Through this study, we can predict the sales price of used tablet PCs and suggest appropriate used sales prices to sellers and buyers.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.265-279
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• 2023

Purpose - The purpose of this paper is to compare and review behavioral economics models that explain stock price changes after large-scale price shocks in the Korean stock market and to find a suitable model. In this paper, among the theories reviewed, it was confirmed that the anchoring heuristics theory has high explanatory power for stock prices after large-scale stock price fluctuations. Design/methodology/approach - This paper conducts an event study on stock price shocks in which the individual stocks that make up the KOSPI200 index show more than 10% fluctuation on a daily basis. In order to materialize the abstract predictions of heuristics theories in a varifiable form, this paper uses the daily stock price index change as a reference point for availability heuristics, and uses the 52-week highest and lowest price as reference point for anchoring heuristics. Research implications or Originality - As a result of the empirical analysis, the stock price reversals did not consistently appear for changes in the daily index. On the other hand, the stock price drifts consistently appeared around the 52-week highest and the 52-week lowest price. And in the multiple regression analysis that controlled for company-specific and event-specific variables, the results that supported the anchoring heuristics were more evident. These results suggest that it is possible to establish an investment strategy using large-scale price change in Korean stock market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.210-217
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• 2020

Since multiple generation technology can have various entry modes by adjusting performance, price, and entry timing, understanding of market entry mode of multiple generation technology is important. This study defined the concept of market entry mode based on multiple dimensions (technology, time, performance, or price) and developed a model for various types of market entry modes. Based on a literature review, the definition and types of market entry mode were provided, and the accuracy of the model was verified based on a case study on the semiconductor and smartphone market. Six market entry modes of multiple generation technology were modeled as moderate performance and early entry, high performance and early entry, low performance and early entry, moderate performance and late entry, high performance and late entry, and low performance and late entry. This study will be useful to understand the market entry mode of multiple generation technology by defining and developing a model for entry mode and can be applied to other markets in addition to multiple generation technology.

• Korean Journal of Agricultural Science
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• v.38 no.3
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• pp.571-581
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• 2011

This study develops a mid-term preceding observation model of radish to complement an existing short-term agricultural observation model. The first purpose of the study is to extend a three seasonal classification(spring, summer, fall) of fruit-vegetables to a four seasonal classification that involves the winter additionally. This allows us to verify the reason for demand and supply unbalance and unstable price of radish. The second purpose is to construct a mid-term preceding observation model that would be used to forecast planted areas, output, monthly shipment and price. To achieve these purposes, several multiple regression models are estimated. A system is consisted of a planted areas equation, a yield equation, monthly shipment distribution equation, and monthly price equation. To calculate output an auxiliary equation is involved in the system and the consumer price index etc are considered as exogenous variables.

• Journal of the Korean Home Economics Association
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• v.40 no.5
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• pp.53-62
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• 2002

The purposes of this study were to examine: 1)the dimensions of online store attitude; 2)the differences in the online store attitude by product category and store type; and 3)the effects of online store attitude on store satisfaction and store loyalty. Data were obtained from an online questionnaire survey to 850 online shoppers who were randomly selected from the panel of an online survey agency, and 615 responses were analyzed. Factor analysis extracted 5 dimensions of store attitude including: process and security; service; promotion and presentation; price and quality; and merchandise. MANOVA revealed a significant difference in the price and quality factor by product category and store type. Multiple regression showed that the effects of price and quality, service, and process and security on store satisfaction were significant. Also, price and quality had a significant direct effect on store loyalty which was also affected by store satisfaction.

• Journal of the Korean Society of Costume
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• v.51 no.8
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• pp.61-75
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• 2001

This study is designed to compare the evaluations of university students on clothing before and after the IMF crisis in Korea. The conclusions of this study are as follows : First, consumers' perceived quality, value and purchase willingness on high price are raised after the IMF crisis in single cue context. Second. consumers' perceived quality, value and purchase willingness on famous brand are raised after the IMF crisis in single cue context. Third, brand has more effect on quality and purchase willingness than price after the IMF crisis. Fourth, consumers' perceived value and purchase willingness get based on the comparison of both pence and brand after the IMF crisis. Fifth, the highest purchase willingness of university students occurs in the multiple cue context of low price and famous brand both before and after the IMF crisis.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.185-194
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• 2020

The study aims to identify and measure factors affecting the perception of the selling price of luxury apartments in Hanoi. We conducted a questionnaire consisting of 29 observation variables with a 5-point Likert scale. Independent variables were measured from 1 "without effect" to 5 "strongly". Based on the desk review and results of interviews, a total of 500 questionnaires were sent to research participants for collection; 458 of them met standard and were subject to be analyzed. This study employs Cronbach's Alpha test, and regression model. The results of Exploratory Factor Analysis (EFA) and Multiple Regression Analysis (MRA) identify five main determinants influencing the perception of the selling price of luxury apartments in Hanoi, including Physical characteristics of a luxury apartment (PC); Location and position of an apartment (LP); Surrounding Area (SA); Quality of service provided by managers; (QS) and Demographics factor (DF). Based on the findings, some recommendations have been proposed to help the firm leaders design appropriate personnel policies for creating better price satisfaction for customers in the future. On this basis, the authors propose a number of recommendations to improve the quality of luxury apartments, thereby contributing to the development of the market for luxury apartments in Hanoi.

• Journal of Distribution Science
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• v.21 no.3
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• pp.93-100
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• 2023

Purpose: The purpose of this paper is to confirm whether stocks belonging to the distribution industry in Korea have reversals, following large daily stock price changes accompanied by large trading volumes. Research design, data, and methodology: We examined whether there were reversals after the event date when large-scale stock price changes appeared for the entire sample of distribution-related companies listed on the Korea Composite Stock Price Index from January 2004 to July 2022. In addition, we reviewed whether the reversals differed depending on abnormal trading volume on the event date. Using multiple regression analysis, we tested whether high trading volume had a significant effect on the cumulative rate of return after the event date. Results: Reversals were confirmed after the stock price shock in the Korean distribution industry and the return after the event date varied depending on the size of the trading volume on the event day. In addition, even after considering both company-specific and event-specific factors, the trading volume on the event day was found to have significant explanatory power on the cumulative rate of return after the event date. Conclusions: Reversals identified in this paper can be used as a useful tool for establishing a trading strategy.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.