|Mohammed Ali Berawi||Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia|
|Nyoman Suwartha||Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia|
|Fathiya Salsabila||Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia|
|Roy Woodhead||Business Operation Systems, Sheffield Business School, Sheffield Hallam University, 38 - 40 Howard Street, Sheffield S1 1WB, United Kingdom|
Infrastructure development in Indonesia creates massive impacts on the economy. The Light Rail Transit (LRT) of the greater Jakarta (Jabodebek) project has an estimated cost of more than 29 trillion rupiahs due to land acquisition and route planning. The urban transit development may impact to the price of property including residential, commercial and offices along the route. This research aims to determine variables affecting the price elasticity of property and the correlation to station proximity. Data mining through web scrapping was used to assess the degree of correlation between price elasticity and station location. The result shows that approximately 13% of commercial property was spread over a distance of 1 km from the LRT station. The closer a property to transit station, the more likely a price will be twice as cheap compared to those further away. The findings also show variables that highly contribute to property prices, including schools and hospitals, linked to proximity of some transit stations located in city center of Jakarta and building density.
Commercial property; Data mining; Land value capture; LRT; Transit-oriented development
Various types of infrastructure are included in the government’s long-term projects to create investments and equitable development in Indonesia, increasing demand on the state budget. Infrastructure development recently intensified by the government has been in the rail-based public transportation sector (Berawi et al., 2018a; Rahman et al., 2018). The existing modes of rail transportation in Indonesia are still quite limited, so to expand the network, Mass Rapid Transit (MRT) and Light Rail Transit (LRT) systems have been designed. This paper discusses the LRT project and its construction phases, which have required a total of 29.9 trillion rupiahs originating from the state budget and PT Adhi Karya, an infrastructure development company. Presently, phase A of the construction process is being carried out by Adhi Karya and is expected to be completed in the middle of 2019. In this first phase, the project financing is fully provided by the government. Primary and secondary data are taken to calculate the effects of development on property values around the available stations along the route. This calculation is intended to determine how much the construction of LRT infrastructure influences property price increases in the catchment area, thereby creating valuable insights for the government. Value capture is considered in the affected areas by constructing an LRT station as part of the project, and estimating resultant property values.
Land value capture is a public financing technique that captures a fraction of price increases from new public investments and taxes on property or required contributions for repairs. Several cities in the world have used Transit Oriented Development (TOD) to formulate policies and strategies for urban development (Suzuki et al., 2015; Berawi et al., 2019). To carry out value capture, several implementation methods are used, such as property-based developments and others relying on taxes or fees charged on property affected by TOD (Zhang & Xu, 2017; Cordera et al., 2019). Property values are affected by infrastructure development, especially rail and its characteristics including physical attributes, location, and environment. The impacts from rail infrastructure are diverse and range from insignificant and negative influences to significant and positive attributes (Debrezion et al., 2007; Fahirah 2010). Railway investment is expected to support more compact urban structures and, therefore, serves planning purposes (Fejarang 1993; Mu & de Jong, 2012).
Physical attributes are among the most influential factors in increasing property values and include factors that directly affect land values. Generally, the physical attributes that affect property prices are divided into four categories: accommodation, materials used, age, and structural conditions (Goldberg, 1981; Zhang & Xu, 2017). Accommodation further affects the value of land prices due to variations in land uses. Based on various studies conducted, therefore, the number of rooms positively and significantly affects property prices, and prices rise with an increasing number of rooms (Listiyarko & Ennoch, 2014).
According to Fejarang (1993), property prices are strongly influenced by the characteristics of attractive locations. In other cases, the Central Business District (CBD), which is the center of many urban activities, is also considered to be an attractive quality capable of increasing property prices (Berawi et al., 2018b; Malaitham et al., 2018). Environmental attributes also affect the quality of life of the people utilizing property. However, the quality of life usually depends on the level of comfort of the persons inside and is measured based on land used for commercial or residential purposes with varying results (Medda, 2012).
Several studies have shown that the facilities around properties impact the growth of property values. Zhang and Xu (2017) carried out research in Wuhan, China with data collected in 2015 on two MRT corridor lines, 1,604 houses, 678 commercial units, and 844 office units. By taking such variables, this research considers commercial roadsides, streets, shopping malls, and different areas. The research will also take into account three types of property based on its proximity location. However, the catchment area for commercial property was only cover 300 m from transit station (Haider & Miller, 2000).
Property characteristics have varied impacts on property prices. Based on the benchmarking process taking into account similar TOD project in Wuhan, China, several variables had significant impacts on property prices including the CBD, main road, and schools. However, TOD in Bangkok, Thailand, indicated that distance from public transportation had no significant impacts on property prices and was replaced by job access, density of commercial properties, distance from main roads, distance from the station, time to the CBD, and percentage of vacant building-space. TOD in Rome shows similar result to Wuhan where the location had more positive impacts on property prices than access to transportation, while building-age had negative impacts.
This indicates that property prices depend on the location of TOD and variables included on the hedonic price modeling should be adjusted based on the context of case study. This research has identified significant property characteristics based on case studies in Jakarta, Indonesia. High-density property and proximity a station of Dukuh Atas were positively correlated to property prices.
This research was supported by research grants from the Universitas Indonesia and the Ministry of Research, Technology and Higher Education, Republic of Indonesia through Hibah Penelitian Dasar Unggulan Perguruan Tinggi (PDUPT) 2019 (No. NKB-1656/UN2.R3.1/HKP.05.00/2019).
Berawi, M.A., Nabila, A., Miraj, P., Rahman, H.A., Berawi, A.RB., 2018a. Analysis of Life Cycle Cost and Public-Private Partnership in the Development of Walini City as Technology Park. International Journal of Technology, Volume 9(7), pp. 1469–1479
Berawi, M.A., Suwartha, N., Kurnia, K., Miraj, P., Berawi, A.RB., 2018b. Forecasting the Land Value around Commuter Rail Stations using Hedonic Price Modeling. International Journal of Technology, Volume 9(7), pp. 1329–1337
Berawi, M.A., Ibrahim, B.E., Miraj, P., 2019. Developing a Conceptual Design of Transit-Oriented Development to Improve Urban Land Use Planning. Journal of Design and Built Environment, Volume 19(1), pp. 40–48
Cordera, R., Coppola, P., dell'Olio, L., Ibeas, Á., 2019. The Impact of Accessibility by Public Transport on Real Estate Values: A Comparison between the Cities of Rome and Santander. Transportation Research Part A: Policy and Practice, Volume 125, pp. 308–319
Debrezion, G., Pels, E., Rietveld., P., 2007. The Impact of Railway Stations on Residential and Commercial Property Value: A Meta-Analysis. The Journal of Real Estate Finance and Economics, Volume 35(2), pp. 161–180
Fahirah, F., 2010. Identifikasi Faktor yang Mempengaruhi Nilai Jual Lahan dan Bangunan Pada Perumahan Tipe Sederhana (Identification of Factors Affecting the Sale Value of Land and Buildings in Simple Type of Housing). SMARTek, Volume 8(4), pp. 251–269
Fejarang, R.A., 1993. Impact on Property Values: A Study of the Los Angeles Metro Rail. In: Public Transport Planning and Operations. Proceedings of Seminar Held at the European Transport, Highways and Planning 21st Summer Annual Meeting (September 13–17, 1993), UMIST, Volume P370, pp. 27–41
Goldberg, M.A., 1981. Transportation Systems and Urban Forms: Performance Measurement and Data Requirements. In: Proceedings of the International Symposium on Surface Transportation Performance, Volume 259
Haider, M., Miller, E.J., 2000. Effects of Transportation Infrastructure and Location on Residential Real Estate Values: Application of Spatial Autoregressive Techniques. Transportation Research Record, Volume 1722(1), pp. 1–8
Listiyarko, W., Ennoch, S., 2014. Penerapan Model Hedonic dalam Penentuan Nilai Tanah sebagai Referensi dalam Penilaian Barang Milik Negara dan Harga Limit Lelang (Application of the Hedonic Model in Determining Land Value as a Reference in Valuation of State Property and Auction Limit Prices). Avaliable Online at https://bppk.kemenkeu.go.id › publikasi › kajian-akademis, Accessed on August 10, 2019
Malaitham, S., Fukuda, A., Vichiensan, V., Wasuntarasook, V., 2018. Hedonic Pricing Model of Assessed and Market Land Values: A Case Study in Bangkok Metropolitan Area, Thailand. Case Studies on Transport Policy. In Press, Corrected Proof. DOI: 10.1016/j.cstp.2018.09.008
Medda, F., 2012. Land Value Capture Finance for Transport Accessibility: A Review. Journal of Transport Geography, Volume 25, pp. 154–161
Mu, R., de Jong, M., 2012. Establishing the Conditions for Effective Transit-Oriented Development in China: The Case of Dalian. Journal of Transport Geography, Volume 24, pp. 234–249
Rahman, H.Z., Berawi, M.A., Susantono, B., Miraj, P., Petroceany, J.S., Maya, R., 2018. Investigation of an Operation and Maintenance Framework in the railway Industry: A Case Study of the Makassar-Parepare. International Journal of Technology, Volume 9(3), pp. 549–557
Suzuki, H., Murakami, J., Hong, Y.-H., Tamayose, B., 2015. Financing Transit-Oriented Development with Land Values: Adapting Land Value Capture in Developing Countries. World Bank. Washington, United States
Zhang, M., Xu, T., 2017. Uncovering the Potential for Value Capture from Rail Transit Services. Journal of Urban Planning and Development, Volume 143(3), pp. 1–13