著者
小松 広明
出版者
公益社団法人 日本不動産学会
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.32, no.2, pp.127-134, 2018-09-28 (Released:2019-09-28)
参考文献数
8

In the current empirical study, I verified whether a size difference in square meters affects rental rate reduction based on comments received from tenants occupying the rental units. In apartments under 25 square meters, tenants displayed a sense of antipathy, which affected their recognition of unit depreciation. In contrast, for units larger than 65 square meters, depreciation had a major impact on the perceptions of functional depreciation for tenants.
著者
清田 陽司
出版者
公益社団法人 日本不動産学会
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.31, no.1, pp.64-71, 2017-06-29 (Released:2018-06-29)
参考文献数
15
被引用文献数
1

This article describes frontier efforts to apply deep learning technologies, which is the greatest innovation of research on artificial intelligence and computer vision, to image data such as real estate property photos and floor plans. Specifically, attempts to detect property photos that violate regulations or were misclassified, and to extract information that can be used as new recommendation features from property photos, were mentioned. In addition, this article introduces an innovation created by providing datasets for academic communities.
著者
清水 千弘
出版者
公益社団法人 日本不動産学会
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.31, no.1, pp.45-51, 2017-06-29 (Released:2018-06-29)
参考文献数
6
被引用文献数
2

What effect might the development of big data and AI have on the work of real estate professionals ? This paper focuses on the degree to which AI and machine learning may be able to correctly determine real estate prices - a task which occupies a central position in the work of real estate appraisers and brokers. Real estate price determination requires a process where real estate data of varying quality is utilized in the analysis of price formation structures. Furthermore, as the market is in a constant state of flux prices must be determined in response to changes over time. Big data and AI are terms that are commonly used in general conversation. While they do have a complementary relationship they have developed, fundamentally, as diff erent technologies. Recent developments in this area have garnered attention, with a particular focus on advances in big data, and in the context of the development of such an information base the significant improvements in the methods of analysis known as AI and machine learning indicate that such techniques will eventually be able to perform the task of real estate price determination that is currently carried out by appraisers and brokers.
著者
大和 大祐 野村 眞平
出版者
公益社団法人 日本不動産学会
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.31, no.1, pp.78-83, 2017-06-29 (Released:2018-06-29)
参考文献数
6
被引用文献数
1

This paper introduces the market price of house rent in SUUMO as an example of applications for big data utilization. The market price using average or median of house rent may not be appropriate with respect to the stabilization. This paper investigates the possibility of the market price using statistical models using linear regression or random forests to make the market price to be stabilized. This analysis uses the data of houses listed in SUUMO from August 2016 to October 2016 and the number of houses are about three million. The result shows that the market price using random forest with smoothing is the most appropriate in our case.
著者
吉田 修平
出版者
公益社団法人 日本不動産学会
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.27, no.2, pp.41-46, 2013-09-20 (Released:2017-01-18)

Under the revision of the Civil Code(law of claims), provisions for the assignment of claims which may arise in future are newly provided and it is espected that the assignment of claims which may arise in future will be accelerated in combined with the reconsideration of requirement for perfection. Particularly, the assignment of rent which may arise in future from the lease contract is instrumental in a means of collateral and supportable by fi nancial industry. Among this trend, I refl ect on the essential of the lease contract and point out the problem fromthe view point of the practical real property leasing, which can be occurred by the separation of the status of a lessor and of a rent creditor.
著者
明野 斉史
出版者
日本不動産学会誌
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.19, no.1, pp.66-71, 2005

The business improvement district (BID) is the new concept of utilizing private sector, in order for public administration to make a central city area revitalization. The approach is one in which a geographically defined majority of property owners and/or merchant agrees to provide an extra level of public service in a specific area by imposing an added tax or fee on all of the properties and/or businesses in the area. Examples of services include supplementary security, additional street cleaning, and the unique marketing of events.<BR>The impetus for creating a BID may come from real estate developers, property owners, merchants downtown associations, or from within local government itself. In most jurisdictions, local government legally establishes the district pursuant to state law, collects the special tax assessments or fees, and then transfers the revenues over to the BID to use as it sees fit. In communities across the county, BIDs have used their funds to transform downtown areas into exciting, interesting places where businesses want to relocate and people want to work, shop, live, and have fun.
著者
宮下 量久
出版者
公益社団法人 日本不動産学会
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.30, no.4, pp.47-53, 2017-03-28 (Released:2018-03-28)
参考文献数
4
著者
青山 貞一
出版者
Japan Association for Real Estate Sciences
雑誌
日本不動産学会誌 (ISSN:21859531)
巻号頁・発行日
vol.17, no.2, pp.68-73, 2003

Now, in Tokyo, the so-called "2003 problem" has become the big center of attention. It came to the urban redevelopment last in the Yamanote Line inner side which became the forerunner of the "2003 Problem" of the 20th century, and the environmental load by which the major urban redevelopment in the Tokyo newly emerging city center brings Yebisu Garden Place in an area to an example by thispaper, and quantitive consideration was tried in it. For the environmental load which a major urban redevelopment brings about, various things, such as air pollution, noise, vibration, water pollution, greenhouse gas, a wind damage, sunshine prevention and so on can be considered. This paper considered environmental load by making air pollution (nitrogen dioxide, nitrogen oxide) into a representation index. Consequently, it is before and after enforcement of a redevelopment project, and it turns out that automobile traffic increases twice and the environmental load of the air pollution resulting from an automobile exhaust gas increases 1.8 times. Furthermore, it also turns out the influence area of high concentration air pollution, and that it increases centering on a place along the route more sharply than development before.
著者
瀬下 博之
出版者
公益社団法人 日本不動産学会
雑誌
日本不動産学会誌 (ISSN:09113576)
巻号頁・発行日
vol.24, no.4, pp.86-93, 2011-04-08 (Released:2015-10-15)
参考文献数
14