• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.767-780
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• 2021

The purpose of this research is to analyze the effect of financial elements (asset growth, liability growth, equity growth, revenue growth, and profit growth) on stock price performance and to analyze the growth of Corporate Social Responsibility (CSR) costs as a moderating effect. The technique analysis used is regression analysis. Samples in this analysis are manufacturing firms listed on the Indonesian Stock Exchange (IDX) for the period 2014-2018. The use of regression models for hypothesis testing must fulfill several applicable assumptions such as Normality Test, Heteroscedasticity Test, Multicollinearity Test, Autocorrelation Test, Model Fit Test, Determination Coefficient Test, and Hypothesis Test. Data analysis used two research models, namely model 1 and model 2. Model 1 is without the moderating variable, and model 2 is with the moderating variable, that is, CSR cost growth. Based on the result of the regression analysis, it can be inferred that the asset, revenue, and profit growth have a positive impact on stock price results. Liabilities and equity growth do not affect stock price performance. Operating expense growth has a significant effect on price performance. CSR cost growth can moderate the effect of growth in financial statement elements on stock price performance but is not significant.

• Journal of KIBIM
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• v.11 no.2
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• pp.43-53
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• 2021

The 'public agency oil joint purchase system' was introduced to lower public sector oil prices and contribute to the stability of the overall consumer oil market. The present study used spatial regression to analyze the factors affecting domestic gasoline price, focusing on the impact of potential implicit collusion among gas stations in determining domestic gasoline prices. Also, this study investigated the effect the location characteristics of the market convention gas stations and government offices on the pressure of price competition in the market and the gasoline price at general gas stations. To summarize the results of the spatial lag model (SLM), the individual characteristics of gas stations such as convenience stores (+), self-fuelling (-), commercial areas (+), subway stations (+), population density (-), and sales (-) are correlated to gasoline prices at gas stations, and the institutional location factors of gas stations (+) affected the average of 9 won per liter, 11 won per liter. In order to solve these problems, the establishment of a monitoring system reflecting the location characteristics of the region and the ongoing review of the system should be carried out. In addition, separate, expanded and promotional measures should be prepared for the convenience of general and public oil buyers.

• Smart Media Journal
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• v.11 no.3
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• pp.62-73
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• 2022

Researches on the prediction of domestic apartment sales price have been continuously conducted, but it is not easy to accurately predict apartment prices because various characteristics are compounded. Prior to predicting apartment sales price, the analysis of major factors, influencing on sale prices, is of paramount importance to improve the accuracy of sales price. Therefore, this study aims to analyze what are the factors that affect the apartment sales price in Gwangju, which is currently showing a steady increase rate. With 6 years of Gwangju apartment transaction price and various social factor data, several maching learning techniques such as multiple regression analysis, random forest, and deep artificial neural network algorithms are applied to identify major factors in each model. The performances of each model are compared with RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R² (coefficient of determination). The experiment shows that several factors such as 'contract year', 'applicable area', 'certificate of deposit', 'mortgage rate', 'leading index', 'producer price index', 'coincident composite index' are analyzed as main factors, affecting the sales price.

• Land and Housing Review
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• v.2 no.4
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• pp.367-377
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• 2011

This paper investigates the determination factors' variation of real estate price after sub-prime financial crisis, in korea, using a VAR model. The model includes land price, housing price, housing rent (Jensei) price, which time period is from 2000:1Q to 2011:2Q and uses interest rate, real GDP, consumer price index, KOSPI, the number of housing construction, the amount of land sales and practices to impulse response and variance decomposition analysis. Data cover two sub-periods and divided by 2008:3Q that occurred the sub-prime crisis; one is a period of 2000:1Q to 2008:3Q, the other is based a period of 2000:1Q to 2011:2Q. As a result, Comparing sub-prime crisis before and after, land price come out that the influence of real GDP is expanding, but current interest rate's variation is weaken due to the stagnation of current economic status and housing construction market. Housing price is few influenced to interest rate and real GDP, but it is influenced its own variation or Jensei price's variation. According to the Jensei price's rapidly increasing in nowadays, housing price might be increasing a rising possibility. Jensei price is also weaken the influence of all economic index, housing price, comparing before sub-prime financial crisis and it is influenced its own variation the same housing price. As you know, real estate price is weakened market basic value factors such as, interest rate, real GDP, because it is influenced exogenous economic factors such as population structural changes. Economic participators, economic officials, consumer, construction supplyers need to access an accurate observation about current real estate market and economic status.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.64-68
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• 1985

This paper considers the following case: (1) the product is paid by the right price for a lot accepted by a given consumer's acceptance sampling plan, and (2) the product is paid by the discounted price for a lot rejected by this plan. In such a case, the producer's sampling plan need not be the same as that of the consumer's. From the producer's view point, the producer need to determine the preliminary sample size which maximizes his revenue. This paper, therefore, determines an optimal preliminary sample size from the producer's view point. This preliminary sample size is affected by the consumer's acceptance sampling plan, percent defective, preliminary inspection cost and the discount rate of the price.

• Journal of Technology Innovation
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• v.10 no.2
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• pp.107-129
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• 2002

Expansion and enhancement of information and communication infrastructure can create a market closer to an ideal type for a perfect competition, utilizing a cyber space in the network (with the expanded usage of Internet and e-commerce) and it could be a market of a monopolistic form. The government can take one of the two approaches responding to this monopolization of the digital market. First, the government maintains laissez-faire policy since the monopoly cannot be maintained over a long period of time due to an increasing in the production, decrease in the price, profit resulting from this and rapid technology evolution. Second, the government can actively interrupt the monopolization of the digital market. Monopolization in a digital market can lead to a market failure. Unstable market structure and too much frequent merger and acquisition contribute to making the digital market very dynamic. Information goods exchanged in the digital market have the features of very low marginal cost required to copy the original product whereas its initial fixed cost is very high. This explains why the information products are not priced based on the existing marginal price determination principles and why companies producing them have various product sales strategies (price/product differentiation strategy, and other sales strategies).

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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• pp.95-107
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• 1995

This paper deals with the problem of determining optimal credit period and production lot size from the perspective of producer. We assume that a ratailer jointly determines the unit retail price and order size to maximize profit when he/she puechases a product for which the producer offers a trade credit. Two widely used demand functions are adopted for the study in which demands are decreasing function of the retail price. Mathematical models for producer-retailer system are developed and a solution procedure is presented which show how to achieve an optimal length of trade credit and production lot size for producer. The effect of production rate on the behavior of both producer and retailer is also investigated using an example.

• Journal of the Korean housing association
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• v.18 no.2
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• pp.75-82
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• 2007

Under the premise that the housing market is not fixed, but changes organically according to social and systematic environment, it has important meaning as the object of this study to identify the recent housing market's movement by deducing the changed characteristics of the factors to compose the recent new houses. By using the following methodology, this study analyzed the characteristics and mutual relations of the economical and house-composing factors, categorized the investigation object into sub-markets, and executed comparative analysis. First, based on the leading studies analyzing the factors of house price determination and the assessment indicators of 'Green Building Certification Program', the composing factors are deduced. Second, the factors are categorized as economic, housing complex planning and geographical condition. Third, to identify the influence of housing environmental factors on economic factors, the correlation between the former and the latter, and the difference between economic factors are analyzed. Fourth, by segmenting and categorizing the housing market into time and location subgroups, the chronicle trend and the geographical characteristics are analyzed.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.3
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• pp.239-246
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• 2003

Individual items are produced continuously from an industrial process. Each item is checked to determine whether it satisfies a lower screening limit for the quality characteristic which is the weight of an expensive ingredient. If it does, it is sold at a regular price; if it does not, it is reprocessed or sold at a reduced price. The process mean may be adjusted to a higher value in order to reduce the proportion of the nonconforming items. Using a higher process mean, however, may result in a higher production cost. In this paper, the optimal process mean and lower screening limit are determined in situations where the probability that an item functions well is given by a logistic function of the quality characteristic. Profit models are constructed which involve four price/cost components; selling prices, cost from an accepted nonconforming item, and reprocessing and inspection costs. Methods of finding the optimal process mean and lower screening limit are presented and numerical examples are given.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.44-48
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• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.