• Soft Computing and Machine Intelligence
• /
• 제1권1호
• /
• pp.11-23
• /
• 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.

• 경영과정보연구
• /
• 제25권
• /
• pp.321-337
• /
• 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.

• 산업노동연구
• /
• 제24권1호
• /
• pp.107-156
• /
• 2018

이 글은 일본 철강산업의 사내하청 활용 전개와 노사관계 안정에 관하여 조강생산량 1위와 2위인 대표적 제철회사를 대상으로 역사적으로 살펴보았다. 제철소 노동자 중 사내하청 노동자가 차지하는 비율은 전후 2000년대 중반까지 지속해서 증가하여 1위인 S사의 경우 약 70%였다. 사내하청은 고용의 수량적 유연성을 높여서 인건비 절약을 꾀하려는 기업의 전략으로 활용되었다. 사내하청 기업의 담당업무는 기업 특수적 숙련을 필요로 하였는데 그것에 대응하는 형태로 정규직의 비율이 높아지고 이직률도 낮아 내부노동시장이 형성되었다. 사내하청 기업이 업무수행에 필요한 설비나 자재를 자체 도입함으로서 원청과는 장기적인 거래관계를 맺게 되었고, 원청은 사내하청의 생산성 향상 정책을 실시하여 상생적인 관계가 전개되었다. 노조는 사내하청 확대가 기업 이익, 조합원의 고용안정 및 노동조건 유지 등에 기여하는 것으로 보고 반대하지 않았다. 출향과 전적을 통하여 사내하청이 확대되는 것도 마찬가지로 반대하지 않았다. 2000년 이후 원청이 사내하청 기업의 자회사화를 추진하여 상생적인 관계는 자본관계로 뒷받침 되었다. 그런데 2000년대 중반 이후 직영화의 움직임이 나타나고 있는데 그것은 법령준수 요구 강화, 고객의 품질향상과 납기 달성의 엄격성, 노동력 확보 등이 주요 요인이다. 원청과 사내하청간의 노동조건 격차는 임금의 경우 B사가 S사보다 작았는데 사내하청이 원청의 약 90%였다. 상대적으로 B사의 격차가 작은 것은 노조의 격차 축소 운동, 낮은 시장 지배력과 불리한 노동시장 등에 따른 것으로 보인다. 이와 같이 사내하청에도 내부노동시장이 형성되어 왔고, 원청과의 임금격차도 크지 않아 노사분쟁의 가능성이 낮다. 원청뿐만 아니라 사내하청에서도 노사관계는 안정되어 있다. 우리나라의 철강산업 노사관계 안정화는 원청과 하청기업간의 장기적 상생협력관계 하에서 하청기업에서 내부노동시장을 형성/확대하면서 생산성을 높여 원청과의 격차를 줄여나가는 것이 요구된다.

• 국제학술발표논문집
• /
• The 5th International Conference on Construction Engineering and Project Management
• /
• pp.151-157
• /
• 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
• /
• 제7권8호
• /
• pp.33-40
• /
• 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.

• 유통과학연구
• /
• 제12권4호
• /
• pp.31-39
• /
• 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.

• 농촌계획
• /
• 제13권2호
• /
• pp.93-105
• /
• 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.

• 산업경영시스템학회지
• /
• 제42권2호
• /
• pp.86-93
• /
• 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.

• 부동산연구
• /
• 제24권1호
• /
• pp.15-26
• /
• 2014

본 연구는 다변량 GARCH 모형을 이용하여 우리나라 주택시장의 상호연관성을 분석하였다. 주택 유형별 매매가격증가율과 전세가격증가율 간 상관관계 분석에서는 연립주택보다는 단독주택과 아파트의 상관계수가 더 크게 나타났다. 주택 유형에 따른 분석결과에 의하면 매매가격증가율과 전세가격증가율 두 분석 모두에서 단독주택과 연립주택 간 상관관계가 아파트와 단독주택 간 상관관계나 아파트와 연립주택 간 상관관계보다 높은 것으로 밝혀졌다. 주택을 크기에 따라 분류하였을 때 매매가격증가율을 이용한 분석결과와 전세가격증가율을 이용한 분석결과 간에는 큰 차이를 발견할 수 없었다. 아파트의 경우는 중형 아파트와 소형 아파트 간 상관관계가 가장 큰 것으로 나타났으며, 단독주택의 경우에는 대형 단독주택과 중형 단독주택 간 상관관계가 제일 큰 값을 기록하였다. 일반적으로 사람들이 아파트는 중소형 이하에, 단독주택은 중대형 이상에 관심이 많다는 사실이 본 연구의 분석결과를 간접적으로 뒷받침해주고 있다. 연립주택의 경우에는 매매 가격보다 전세가격의 경우에 중 대형 연립주택과 소형 연립주택 간 상관계수가 더 커지는 현상을 보이고 있는데, 이는 주택을 구입하는 경우와 주택을 임대하는 경우의 의사결정 과정이 서로 상이한데 그 이유가 있는 듯 보인다.

• 대한지리학회지
• /
• 제35권5호
• /
• pp.717-729
• /
• 2000

1997년 말의 경제위기 상황 이후 한국의 부동산 시장에서의 공급 증가 및 수요의 위축으로 부동산 가격이 크게 폭락하였다. 주택 시장에 있어서도 실질소득이 감소와 주택금융의 부족 등에 의한 수요의 감소로 단기간 동안 주택가격이 급격히 하락하였다. 그러나, 부동산 경기 부양을 유도하는 정책적인 기제에 의해 1998년 말 이후 주택가격이 다시 상승하게 되었다. 이 경우 주택 가격 하락기나 그 이후의 회복기에 도시별 격차가 뚜렷하게 나타났다. 각 도시들은 주택 가격의 하락률과 상승률의 차이에 따라 4개 그룹으로 구분될 수 있다. 몇몇 도시들에서는 주택 가격의 하락기에는 급격한 하락을 보인 대신 상승기에는 다시 비교적 빠른 상승세를 보여 경제 위기 이전의 상황으로 그 수준이 거의 회복되었다. 그러나, 반면에 다른 몇몇의 도시들에서는 주택시장이 침체에서 벗어나지 못한 채 회복기 이후에도 계속 하락하는 추세를 보였다. 이러한 격차는 주택 매매 가격뿐만 아니라 주택 전세 가격에도 뚜렷이 나타났다. 특히, 수도권 일대의 전세가격 상승 정도는 주택 시장 침체기에 나타났던 하락을 상회하였고, 일부 지역의 재개발 계획과 그에 대한 기대 심리로 인해 전세 수요의 급증을 초래하기도 하였다. 결과적으로 금융위기에 따른 경제 침체기를 경험하고 극복하는 과정에서 도시간 주택 시장의 격차는 더 크게 벌어지게 되었다.