Data-driven approach to site selection in Shanghai

September 30, 2019 / By  

In Shanghai, Grade A office decentralization has become the new norm. Facing more relocation and consolidation options than ever, large space occupiers frequently ask where will the next CBD in Shanghai likely be.  To answer this question, JLL Research adopted a data-driven approach using Geographic Information System (GIS) software to rate decentralized submarkets with the highest business atmosphere by integrating various types of research data.

As described in the JLL white paper titled Shanghai’s Decentralized Office Market: At a tipping point, metro expansion, retail amenities, higher–spec buildings, higher tenant profile, ownership opportunity, and formation of CBD-like clusters are the most significant factors in attracting tenants to decentralized Grade A offices. On this basis, we classified the main factors and set four criteria that can be quantitatively weighted to evaluate the future business atmosphere in a specific decentralized area. The four criteria are: size of Grade A office future supply, size of retail future supply, accessibility of surrounding metro services (both existing and future) and a comprehensive index scored by JLL Research.

Figure 1: Business Atmosphere Index Methodology

Source: JLL Research

In conducting the analysis, the decentralized area in Shanghai was divided into a mesh of regular 1/16-km2 hexagons and each hexagon was assigned with four different criteria values extracted from the data layers. The layers were attributed weights based on their importance determined by JLL Research and the overall future business atmosphere index was achieved by adding the weighted values together.

Figure 2: Shanghai Future Business Atmosphere Index 3D MapSource: JLL Research

The map above shows the final result of the analysis visualized by 3D Scene Viewer on MapIT. Each column is stretched and color-coded representing the corresponding value of the business atmosphere index. Looking at the map, the top-tier submarkets highlighted include Qiantan, North Bund, Shanghai Railway Station and Xuhui Bund, which have also been identified as optimal locations for office site selection in decentralized Shanghai.

Moving forward, we will adopt this data-driven approach in different types of scenarios to enhance our analysis capability and provide more customized services. We believe that in the future,  key decisions in commercial real estate will increasingly be made based on quality data and a scientific approach.

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