Abstract proposal for 2019 IGU Urban Commission Meeting Luxembourg - 4th -9th August 2019 Abstract proposal for 2019 IGU Urban Commission Meeting Luxembourg – 4th- 9th August 2019 2019 IGU Urban Commission Annual Meeting Urban Challenges in a complex World The urban geographies of the new economy, services industries and financial market places AUTHORS: Jin Li Paper Title: Research on the regularities of distribution of urban productive public service industries: the case of Nanjing city Session: Services industries and financial market places Extended abstract • Theoretical background Urban productive public service industries, including finance, insurance, law, banking, accounting, information and intermediary related industries, are knowledge intensive and specialized customer service industries (Browning, 1975, Howells, 1986). The corresponding types of land use are mainly dominated by trade offices and mixed commercial and office buildings. The distribution of urban productive public service industries in the city is not only related to their own development and the impact of market factors, but also needs to coordinate with other industries and urban functions, in order to be in line with the overall spatial development rules of urban. With the development of economic globalization and the growing depth and breadth of international division of labor among countries, urban productive public service industries are more and more important. What is more, their spatial distribution influences the whole urban structure which makes them one of the significant urban spatial distribution components. From the perspective of self-development of urban productive public service industries, there is a trend of "internalization" or "de-marketization" to "externalization" or "marketization". Its production is based on the deepening of division of labor of cost advantages, and the development of outsourcing activities. With the development of economy, the promotion of marketization and the reduction of market transaction costs, independent market players specialized in providing services such as accounting, marketing, consulting and logistics are emerging in the economic system. The development of externalization, marketization and industrialization of productive public service is the natural extension of specialized division of labor and allocation of resources from the internal enterprise to the internal market. Therefore, the development of productive public service is not only a reflection of the breadth and depth of its own industries, but also relates to the level of development of other industries that serve as its targets. By summarizing the current spatial distribution pattern of industries land for productive service industry, this research will provide support for the planning and layout of land for 1 Abstract proposal for 2019 IGU Urban Commission Meeting Luxembourg - 4th -9th August 2019 productive industries in urban areas in the future, and provide reference and basis for quantitative study of urban spatial distribution. • Research questions What is the regularities of distribution of urban productive public service industries and the forming reason of it. • Methodology This study takes Nanjing city as the research object (including Xuanwu District, Gulou District, Qinhuai District, Jianye District, Yuhuatai District, Qixia District, Jiangning District, Pukou District and Liuhe District). Judging from the distribution of service land in the whole city of Nanjing, the land use of all types of public service industries is decreasing from the urban center to the marginal areas. Among them, the type of land for productive service industries is mainly trade and commercial mixed-use land, with an area of 285.0 hectares, a total construction area of 1,852.80 hectares, an average building density of 0.325, and an average floor area ratio(FAR) of 2.346. To study the coupling relationship between land prices in Nanjing and industries used for productive service industries the benchmark land price of commercial land in Nanjing was selected, and a total of 22 benchmark land price grades for commercial land were used. (Land price information source: Nanjing Municipal Bureau of Land Resources). According to the Nanjing commercial benchmark land price information, the distribution situation map was formed using ArcGIS fitting. The city’s commercial land price is distributed into two district structures, and the overall trend is circular and progressively decreasing. The highest price of the commercial benchmark land price is distributed along the Zhongyang Road- Zhongshan Road. Three peak points are formed and form the north-south axis structure, and these three points are Zhongyang Gate Area, Hunan Road Area and Xinjiekou Area. Secondary land prices are distributed in the form of fingers, with the old city of Nanjing as the center, and extending to Yanziji, the direction of Youfang Bridge on the 2nd subway line, the direction of Nanjing-Hangzhou Expressway, the direction of the airport expressway and Yuantong Station on the 2nd subway line. The distribution of land prices is influenced by the Yangtze River as a main and sub-space structure across the Yangtze River, and the relatively high land price centers in Pukou District and Liuhe District have basically taken shape. Based on the circle layer method, this study analyzes the relationship and the law between the floor area ratio of the land use for urban productive public service industries and the commercial benchmark land price, through spatial autocorrelation, significant test and correlation analysis. Specific steps are as follows: 1. Determine the city center. The central area of Nanjing Xinjiekou Area is located in the geometric center of Nanjing city, where east-west and south-north city main roads meet. Meanwhile, from the aspect of urban function, Xinjieko Area is also the center of commercial, business, culture and entertainment etc. Among them, Xinjiekou Square is located at the intersection of four central roads in the central part of Xinjiekou, east to Zhongshan East Road (to Zhongshan Gate), south to Zhongshan South Road (to Zhonghua 2 Abstract proposal for 2019 IGU Urban Commission Meeting Luxembourg - 4th -9th August 2019 Gate), west to Hanzhong Road (to Hanzhong Gate), and north to Zhongshan Road, leading to Gulou Square. Therefore, Xinjiekou Square is chosen as the center of this study. 2. Calculate building density and floor area ratio based on different land properties. According to the site investigation and data entry, the building density and the floor area ratio of each block of different land use types were calculated, and the productive public service industries are selected to obtain the spatial distribution pattern. 3. Calculate in circles. Taking Nanjing Xinjiekou Square as the center, with the radius of li = 1 + 1 ( i – 1 ), (i=1,2,...,19, unit:km ), the Nanjing urban area is divided into 19 circles. The distance Ri from each circle to the city center is calculated as follows: Ri = l ( i – 1 ) + ( li – l ( i – 1 ) ) / 2 , ( i = 1 , 2 , … , 19 ). Due to the reason of data volume, layers 7 to 8, 9 to 10, 11 to 13, 14 to 16 and 17 to 19 are combined to form a new secondary layer. There are a total of 11 secondary circle layers, of which the focus is on layers 1 to 9 in the secondary circle layer. 4. Model fitting. Applying the above model and linear model respectively, a fitting analysis of the building density of public service industries, floor area ratios, and the layout of commercial benchmark land prices in Nanjing was performed, and calculations are made. Correlation rules are then found. Distribution of commercial benchmark land price in each circle of Nanjing • Results/findings Using the mathematical statistical analysis method, the Pearson correlation coefficient of the plot ratio of the land for productive public service industries in Nanjing and the commercial benchmark land price was calculated to be 0.330, corresponding to a p value of 0<0.05, indicating the distribution density of productive public service industries in the main city area of Nanjing remarkably related to benchmark land price. The coupling relationship between the floor area ratio of the land for productive public service industries and the commercial benchmark land price in each circle is significantly different. The above results are summarized to obtain a circle map of the coupling ratio of the floor area ratio of the land for productive public service industries to the commercial benchmark land price. Among them, the floor area ratio of land for productive public service industries in the first circle (0-1000m) is weakly related to the commercial benchmark land price, and 3 Abstract proposal for 2019 IGU Urban Commission Meeting Luxembourg - 4th -9th August 2019 there is no significant correlation in the second circle (1000-2000m). The third circle (2000- 3000m) and the fourth circle (3000-4000m) showed strong correlation and weak correlation in turn. In the fifth and other layers (>4000m), there was no significant correlation, except for the the seventh circle(6000-8000m) with a strong correlation. Corresponding to the core structure of the urban center zone, the floor area ratio of the land for productive public service industries and the commercial benchmark land price are significantly weak correlation in the core circle and the shadow circle in the core structure of the central zone. In the subnuclear circle and the auxiliary circle, there is no significant correlation in the layers. There was a significant correlation in the area among Mochou Lake, the Confucius Temple, the Ming Palace, and Gulou District. There was a significant correlation in the area among Yuhua District Software Park and the Olympic Sports Center, south part of Hexi District. Considering the average value, median value, and normal distribution of the benchmark price of commercial land and floor area ratio of the land for productive public service industries in the city, we define the commercial benchmark land price of more than 20,000 Yuan/ m2 as the high land price region, and the floor area ratio below 2.6 is defined as low floor area ratio area.