• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.11-23
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• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• Management & Information Systems Review
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• v.25
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• pp.321-337
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• 2008

The house price rise suddenly is not only Economic stability but economic, mental state of a heavy burden to people. This paper is a house finance environment analyzed in this research about the rise factor of the house price and the result to present the plan to the natural disposition. The financial institute has an influence on the disguised demand extension of the house and The mortgage Lending in commercial Banks with the earnings as the stability high than the industry loaning. A house finance environment changes and will go from economic factor of the variety of the life style, the housing conditional according to the income level, a children education condition, and the population structure many this little. The disposition of the house need changes according to this and will have an influence on the house price. Necessary for a house market environment house policy of the market need which the consistency reflects so that we are suitable and is desired.

• Korean Journal of Labor Studies
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• v.24 no.1
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• pp.107-156
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• 2018

This article examines the history of the in - house subcontracting and the stabilization of labor - management relations in the steel industry in Japan. The ratio of in-house subcontract workers among steel workers has increased steadily until the mid-2000s, and about 70% in case of the largest company. In-house subcontracting was used as a strategy of the company to increase the quantity flexibility of employment and to save labor costs. The in-house subcontracting company needed company-specialized skills, and the internal labor market was formed because the rate of full-time workers was high and the turnover rate was low. The in-house subcontractor introduced long-term business relationship with the steel factory by introducing the equipment and materials necessary for the performance of the work, and the factory implemented the productivity improvement policy of the in-house subcontractor, and the win-win relationship between the factory and in-house subcontractor was developed. The trade union did not oppose the idea that the expansion of in-house subcontracting contributed to corporate profits, the stability of employment of the members and maintenance of their working conditions. Since 2000, the steel factory has pursued the transformation of in - house subcontractors into subsidiaries, which has been supported by capital relations. By the way, since the mid-2000s, there has been an increase in the number of regular workers' employment. The major factors are as follows: more strengthened compliance with laws and regulations, the higher quality request of customers, stricter keeping of deadlines, and problem in recruiting of workers at in-house subcontract companies. The wage gap between the factory and in - house subcontracting was less at company B than at company S, and the wage level of in - house subcontracting was about 90% of the factory at company B. The relatively small gap at company B seems to be due to the union's movement of narrowing the gap, low market dominance and unfavorable labor market. The internal labor market has been formed in the in-house subcontracting, and the wage gap is not large, and the possibility of labor disputes is low. Industrial relations are stable in the in-house subcontract company as well as the factory. The stabilization of labor-management relations in the steel industry in Korea is required to reduce the wage gap between the factory and in-house subcontract enterprises by raising productivity and expanding the internal labor market at in-house subcontract enterprises.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.151-157
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• 2013

Since the sub-prime mortgage crisis from the US in 2008, the Korean housing market has plummeted. However, the deposit prices of the Korean local lease contract, Chonsei, had been increasing. This increase of Chonsei prices can be a threat to low-income people, most of whom prefer to live in houses with a Chonsei contract. In the housing and Chonsei market, there are many stakeholders with their own interest, hence, simple thoughts about housing and Chonsei market, such as more house supply, will decrease house price, would not work in a real complex housing market. In this research, we suggests system dynamics conceptual model which consists of causal-loop-diagrams for the Chonsei market as well as the housing market. In conclusion, the Chonsei price has its own homeostasis characteristics and different price behavior with housing price in the short and long term period. We found that unless government does not have a structural causation mind in implementing policies in the real estate market, the government may not attain their intended effectiveness on both markets.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.

• Journal of Distribution Science
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• v.12 no.4
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• pp.31-39
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• 2014

Purpose - This study investigates the following two issues. First, we attempt to find the important determinants of housing investment and to identify their significance rank using survey panel data. Recently, the expansion of global uncertainty in the real estate market has directly and indirectly influenced the Korean housing market; households demonstrate a sensitive reaction to changes in that market. Therefore, this study aims to draw conclusions from understanding how the impact of financial strength of the household is related to house investment. Second, we attempt to verify the effectiveness of diverse indices of financial strength such as DTI, LTV, and PIR as measures to monitor the housing market. In the continuous housing market recession after the global crisis, the government places top priority on residence stability. However, the government still imposes forceful restraints on indices of financial strength. We believe this study verifies the utility of these regulations when used in the housing market. Research design, data, and methodology - The data source for this study is the "National Survey of Tax and Benefit" from 2007 (1st) to 2011 (5th) by the Korea Institute of Public Finance. Based on this survey data, we use panel data of 3,838 households that have been surveyed continuously for 5 years. We sort the base variables according to relevance of house investment criteria using the decision tree model (DTM), which is the standard decision-making model for data-mining techniques. The DTM method is known as a powerful methodology to identify contributory variables for predictive power. In addition, we analyze how important explanatory variables and the financial strength index of households affect housing investment with the binary logistic multi-regressive model. Based on the analyses, we conclude that the financial strength index has a significant role in house investment demand. Results - The results of this research are as follows: 1) The determinants of housing investment are age, consumption expenditures, income, total assets, rent deposit, housing price, habits satisfaction, housing scale, number of household members, and debt related to housing. 2) The impact power of these determinants has changed more or less annually due to economic situations and housing market conditions. The level of consumption expenditure and income are the main determinants before 2009; however, the determinants of housing investment changed to indices of the financial strength of households, i.e., DTI, LTV, and PIR, after 2009. 3) Most of all, since 2009, housing loans has been a more important variable than the level of consumption in making housing market decisions. Conclusions - The results of this research show that sound financing of households has a stronger effect on housing investment than reduced consumption expenditures. At the same time, the key indices that must be monitored by the government under economic emergency conditions differ from those requiring monitoring under normal market conditions; therefore, political indices to encourage and promote the housing market must be divided based on market conditions.

• Journal of Korean Society of Rural Planning
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• v.13 no.2
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• pp.93-105
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• 2007

Allotment gardens with log house in rural area as a rural growth tool are able to adapt to current market mechanisms by communication and promotion techniques. It is important to know what and how allotment garden's users seek their benefits to market segmentations. The primary purpose of this study was to segment and profile the benefits of allotment garden's potential users so as to provide a better understanding of allotment garden in Korea. A self-administered survey was obtained from 298 allotment gardens users in the study area. Four distinct segments were identified based on the benefits; relaxer(23.7%), educator(21.9%), want-it-all gardener(42.3%), and grower(12.2%), and these were profiled with respect to socio-demographics and civic garden-related features. We suggest that the relaxers are target market of allotment gardens with log house because they have willingly intented to pay a higher rent.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.86-93
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• 2019

The population of domestic companion animals is estimated to be about 10 million now. In recent years, the domestic pet market has been launching a wide range of products and services for high quality, smart and well-being. As a result, the market size will increase from 900 billion won in 2012 to 2.3 trillion won in 2016, which has more than doubled in five years. The industry expects to reach 6 trillion won by 2020, expecting 3 trillion won this year. In particular, domestic dogs and cats market is estimated at 275.5 billion won, accounting for 19% of the domestic animal market and 1.425 billion won for the world market. However, despite the growing market for companion animals products, unfortunately the import dependence on related industrial goods is still high and the quality of service is very low. Unlike Europe and the United States, 90% of companion animals are housed in apartments, often causing problems in the health and safety of companions and companions. The purpose of this study is to develop a smart house for companion animals with environmental friendliness and AI function that can be won in competition with products of developed countries. The results of this study are expected to contribute to the creation of a new value - added base for the related industries through the strengthening of the competitiveness of the related SMEs and further the effect of employment increase and import substitution.

• Korea Real Estate Review
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• v.24 no.1
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• pp.15-26
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• 2014

Using multivariate GARCH model, we estimate the relationship between the housing sale prices and lease prices in the Korean housing market. In the analysis of relationship between the rate of changes in sale and lease prices, the correlation coefficient of the apartment and detached house is higher than that of the townhouse. By housing type, the correlation coefficient between detached house and townhouse is higher than between apartment and detached house or apartment and townhouse. By housing size, there are no significant different results between the sales price and the rental price. The correlation coefficient between medium and small size is the highest in the apartment housing market, whereas the correlation coefficient between large and medium size is the highest in the detached housing market, resulting from the fact that people may be more interested in medium- and small-sized apartment and large- and medium-sized detached house. In the detached housing market, the correlation coefficient between large-medium size and medium-small size in the rental price is higher than that of sales price. This result implies that the process of the decision making between purchasing and leasing a house might be different.

• Journal of the Korean Geographical Society
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• v.35 no.5
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• pp.717-729
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• 2000

Housing prices in the Korean housing market dropped at an unprecedented magnitude in 1998 after the economic crisis. With the support of housing policies to boost depressed housing markets, house prices managed to bounce back after the mid-1999. During the period of housing price decline and of its recovery, the degrees of house price changes were not even across the country. The cities could be classified into four groups regarding the differential rates of house price changes. The cities which had higher rates of decrease also had higher rates of increase. On the other hand, some other cities continuously experienced a price fall during the recovery period although the rate of housing price changes were relatively low after the economic crisis. Throught the processes of administering housing market depression due to the crisis of the economy, the cities which could fully redeem the level of house prices in housing markets between the Seoul Metropolitan area and the other parts of the country has been widened.