2019 5th International Conference on Economics and Management (ICEM 2019) ISBN: 978-1-60595-634-3

Research on Urban Quality Development Evaluation Based on ANP—Taking as an Example Shan-Hui WANG Ningbo Institute of Technology, University, Ningbo, Zhejiang, [email protected]

Keywords: Urban Quality, ANP, Indicator System, Ningbo City.

Abstract. The urban development is not only reflected in scale expansion, but also in quality improvement. This paper, taking Ningbo as a sample, structures an indicator system based on ANP to evaluate the quality of Ningbo development. The system covers a set of quality measurements involving economy, society, ecology, urban and rural areas, and government service. The research reveals the obvious spatial differentiation taking place in urban quality development, with higher—level quality of downtown areas versus lower—level quality of non—central areas. Also, the factors affecting the development of urban quality are unbalanced and in disparity, with respective weakness appearing.

Introduction The city in China is the place where all kinds of factors of production and economic and social activities are gathered. To build a moderately prosperous society and accelerate modernization, we must ensure the good quality of city development that is the leading force to drive the country’s advancement. However, promoting the development of cities with Chinese characteristics requires not only the growth momentum but also the quality improvement that is mainly measured by the harmony between man and nature, environmental management, low carbon, ecological civilization, happiness expectation and the overall satisfaction of rational demand. At present, various urban diseases are occurring strikingly in China such as traffic congestion, energy shortage, environmental pollution, and growing supply—demand concentration. Faced with a range of major contradictions in the current urban economic and social development, we must propose a set of policies to solve problems in the quality development. We need to take a holistic approach, seek theoretical innovation, and strive to make breakthroughs in strategic planning to improve the urban development that is accounted on sustainability, livability and the quality of products and services. Based on the analysis of the connotation of urban quality development, this paper constructs an indicator system, and takes Ningbo as an example to measure its quality development by ANP. This has important practical significance for measuring the level of urban quality development and improving the scientific decision-making in this way.

Literature Review The quality of urban development is a new field of quality research and a current research hotspot. Previous researches have always focused on micro-quality, while little attention are paid to macro—quality. There are few theoretical and empirical researches on urban quality development. At present, the definition of macro quality is far from reaching consensus. Lang Zhizheng (2002), Jiang Jiadong (2005), Ma Xiaoping (2009), Cheng Hong (2009, 2010), Zhang Zhengmin (2015) and Song Mingshun (2016) put forward different macro quality concepts, which provides different analytical approaches to the construction of the quality development theory system. Compared with less macro-quality theory research, there are considerable researches on macro-quality development evaluation. Jiang Jiadong (2005), Ma Xiaoping (2009) and Yang Ying (2009), Cheng Hong (2009), Xiao Xiaojing (2009), Wei (2013), Cheng Hong (2013), and Yi Songhua (2016) propose a detailed macro-quality evaluation index system from different perspectives. In terms of evaluation method, the existing method to assess quality is mainly based on the AHP. Jiang Jiadong (2005) 623 combines AHP and Delphi, using the Delphi method for scoring and AHP for determining the weight, which is helpful to study the logical relationship between indicators. Cheng Hong (2009) combines expert opinions and the AHP to conduct an empirical study on the overall quality index of the evaluation of the area. Different from Jiang Jiadong and Cheng Hong's evaluation researches which rely on experts scoring to determine the weight, Ma Xiaoping (2009) believes that the indicators among various quality indicator systems are not independent of each other, and factor analysis is used to do multiple linear regression to determine the weight of indicators. If the cumulative contribution rate of the factor is above 40%, it is defined as the macro quality index. Jin Shenglong (2005) and Xu Xiaomin (2007) propose the BP neural network model based on the product quality index and the construction method of macro-quality index of inbound and outbound goods. But these existing models do not take interactions between evaluation indicators into account. The ANP considers the interaction between the elements within the same layer and different levels of elements, avoiding many of the assumptions required for AHP applications (Sun Hongcai, 2001). The ANP currently has been applied in many fields (Yu Shunkun, 2013; Yu Shunkun, 2015; Sun Hongcai, 2007; Wei Weimei, 2008; Wang Wei, 2008; Chen Kejia, 2012; Liu Lei, 2013; Li Kongqing, 2013; Shu Huan, 2014; Li Xia , 2014).

The Construction of Urban Quality Development Evaluation Index System The guiding principle for urban quality development is to focus on improving quality and efficiency. Focusing on ecology, urban and rural areas, and government services, the urban development, in two key areas of economy and society, must and adhere to four development principles of science, coordination, sustainability, and inclusiveness, carry out five development ideas of innovation, coordination, green, open, sharing, and overall which will be promoted in balanced and coordinated way, so as to ultimately achieve the goal of building a well-off society in an all-round way. Principles for Designing the Indicator System Guiding Principles. The indicator system should give full play to the guiding and leading role, encourage cities to improve the quality management level, and promote the construction of quality power. Scientific Principles. Indicator selection should be scientific. First, the selection of indicators must be logical and has sufficient representativeness and argumentation. Second, it aims to achieve a wide coverage and a high level of hierarchy. At the same time, it is necessary to exclude the indicators with strong correlation to avoid redundancy and duplication. The Principle of Sustainability. The principle of sustainability requires the appropriate handling of the relationship between man and nature, adherence to the principle of ecological priority, and the focus on resource conservation and intensive use, so that urban development does not exceed the carrying capacity of the resource environment. The Principle of Operability. Indicator selection should be representative and comparable. First, the indicator concept should be clear, intuitive, easy to calculate, easy to collect data, and appropriate in the number of indicators, and give priority to data that are standardized and open in statistical system. Second, the designing of the indicator system is as comparable as possible to the system. Indicators of uniform caliber should be used. The application of per capita, proportion, percentage and the like Should be applied to the comparison between cities to better reflect the level of urban development. Contents of the Evaluation Index System for Urban Quality Development According to the principles of system orientation, science, sustainability and operability, the urban quality development evaluation system covers five major areas of economy society, urban and rural areas, ecology and government services which are also five primary indicators measuring development quality, together with another 12 secondary indicators and 35 third-class indicators, as shown in Table 1:

624 Table 1. Urban Quality Development Evaluation Index System. Primary Secondary Indicator Three-class indicator indicator indicators direction Total social R&D expenditures as a percentage Positive of GDP (%) indicator Innovation Number of talent resources per 10,000 people Positive power (person) indicator (C11) Output value of new industrial products above Positive designated size (%) indicator The added value of the tertiary industry as a Positive Economic percentage of GDP (%) indicator Structural development The added value of high-tech industries accounts Positive optimization quality for the added value of industrial enterprises (%) indicator (C12) (B1) The proportion of exports of high-tech products Positive to the value of exports of goods (%) indicator Profit growth rate of industrial enterprises above Positive designated size (%) indicator Development Positive benefit Full labor productivity (10,000 yuan / person) indicator (C13) Positive Tax as a percentage of GDP (%) indicator Positive Disposable income of urban residents (yuan) indicator Quality of life Positive Per capita consumption expenditure (yuan) (C21) indicator Positive Per capita living area (m2) indicator Positive Food and drug sampling pass rate (%) indicator Quality of Number of deaths in production safety accidents social Social security Inverse of 100 million yuan of GDP (person/100 million development (C22) indicator yuan) (B2) Inverse Number of criminal cases per 10,000 people (a) indicator Per capita public cultural and sports facilities Positive (square meters) indicator Cultural Positive Per capita cultural undertaking fee (yuan) support (C23) indicator The added value of culture and related industries Positive accounts for the proportion of GDP (%) indicator Positive Drainage pipe density in built-up area (km/km2) indicator Functional 10,000 people public transport vehicle Positive construction ownership (standard / 10,000 people) indicator Urban and (C31) Thousands of international Internet users Positive rural (households / thousand people) indicator development Positive quality Household registration rate (%) indicator (B3) Urban and Rural Multiplier of per capita income of urban and Inverse Coordination rural residents (times) indicator (C32) Proportion of urban and rural per capita Positive education expenses (%) indicator Positive Ecological Air quality compliance rate (%) Ecological indicator development environment Water quality compliance rate of surface water Positive quality (C41) functional area (%) indicator (B4) Green coverage rate in built-up areas (%) Positive

625 indicator 10,000 yuan GDP energy consumption (tons of Inverse standard coal / 10,000 yuan) indicator Resource 10,000 yuan GDP water consumption (ton / Inverse conservation 10,000 yuan) indicator (C42) General industrial solid waste comprehensive Positive utilization rate (%) indicator Per capita general public budget expenditure Positive Service ability (yuan) indicator (C51) Household registration, pension and medical Positive insurance participation rate (%) indicator Government Administrative approval service public Positive service quality satisfaction (minutes) indicator Service (B5) Positive efficiency Government website performance (minutes) indicator (C52) Positive Service quality public satisfaction (minutes) indicator

Evaluation Methods and Data Sources Introduction to ANP The ANP is proposed by Professor Thoms L. Saaty of the University of Pittsburgh in 1996 to solve the nonlinear problem of complex systems based on the AHP. ANP describes the relationship of each element within the system with a similar network structure, instead of a simple hierarchical structure. The elements in the network layer may influence and dominate each other. Given that ANP considers the information feedback among the levels and the interdependence of the internal elements of the hierarchy, the credibility and accuracy of the evaluation results will be higher. A typical ANP structure is shown in Figure 1. The evaluation of urban quality development involves multiple indicators, relationships and multi-layer systems. Although the indicator system presents a certain hierarchical structure, the levels are not isolated, so are the indicators and programs. There exist many complex relationships such as interdependence and feedback. Hence, this paper chooses the ANP as the calculation method.

Figure 1. Typical ANP Structure.

The ANP application software is SD software. Super Decisions (SD) software is based on ANP theory and is a specialized calculation tool for ANP. The basic steps of the calculation are as follows:

626 1) Input. Breaking a complex problem into individual element groups and elements. There are 3 input methods: 3 layer structure template, 2 layer structure template or no template, and design by yourself. 2) Determining the relationship among the element groups and the elements to determine whether the element level is internally independent, and whether there is a dependency and feedback relationship. When the elements in the same layer are dependent of each other and are not compared in pairs, they are transformed into an AHP model. 3) Calculating the analysis section. According to the above input, the SD software can construct various matrices, and finally the comprehensive advantage can be obtained. Urban Quality Development Evaluation Model Based on ANP Method According to the evaluation index system established above, the analysis shows that the index system not only has a hierarchical structure, but also the five primary indicators and 14 secondary indicators constructed in the evaluation index system interact with each other in the hierarchy. And each element inside the structure is influenced and dominated by other elements. Therefore, according to the principle and characteristics of ANP, the urban quality evaluation refers to the network structure model using the ANP to construct the evaluation index, as shown in Figure 1.

Urban Quality Development Evaluation A

B1.economyn B2.society B3.urban/rural B4.ecology B5.gov.service

C2 C2 C1 C1 1 2 C3 C3 C4 C4 Q5 C5 1 2 1 2 1 2 1 2

C2 C1 3 3

area area area area area

Figure 2. ANP Structural Model for Urban Quality Development Evaluation.

Through ANP model construction and SD software operation, the weights of each indicator factor layer are obtained, and the comprehensive evaluation results of Ningbo quality development are calculated. Data Source This paper takes counties (cities) of Ningbo as samples, and the original data used is from Ningbo Statistical Yearbook (2018). Some of the data are from the statistics of relevant departments in Ningbo. The missing data are regained based on the processing of data of previous years.

627 The Analysis of Empirical Results Through the application of ANP, after the calculation and summary based on the evaluation index system, data being fitted and standardized, the comprehensive score of Ningbo urban development quality is obtained, as shown in Table 2:

Table 2. 2017 Ningbo City Quality Development Scores. Urban and economic Social Ecological Governmen rural area Total Score development development development t service development quality quality quality quality quality Haishu 95.66 88.39 104.44 90.67 97.23 97.73 Yinzhou 95.55 94.29 104.65 84.05 92.62 98.29 Beilun 95.40 96.79 97.27 84.88 94.25 101.58 Jiangbei 95.37 95.77 100.07 87.29 92.93 98.26 Cixi City 93.01 93.20 101.44 80.04 90.92 93.87 County 92.86 89.14 100.65 80.99 96.56 92.33 Zhenhai 92.43 90.36 102.83 82.62 87.23 96.75 92.01 90.64 100.04 79.22 91.50 94.10 Xiangshan 90.70 84.89 95.91 79.67 96.62 94.86 Fenghua 90.62 84.59 99.64 81.71 92.40 93.19 It can be seen from Table 2: (1) It can be seen from the ranking of the comprehensive evaluation scores of the development quality of 10 districts and counties (cities) in Ningbo, that the highest score is Haishu , ranking first with 95.66, followed by Yinzhou District, ranked second with 95.55. , Jiangbei District and Cixi City are ranked the third, the fourth and the fifth, respectively. The sixth to tenth are , , Yuyao City, Xiangshan County and Fenghua District. The average score of the 10 districts (counties) is 93.32 points. The top four scores are higher than the average score, and the districts (cities) ranked fifth to tenth are lower than the average. Judging from the scores, the scores of neighboring districts (counties) are relatively small, indicating that the development of each district (county) is relatively balanced. (2) There is a regional imbalance in the development quality of counties (cities) in various districts and counties in Ningbo. The improvement of the comprehensive level of regional development quality depends not only on the efforts of individual regions, but also on the level of regional economic and social development and the development linkage among regions. For example, for downtown areas like Haishu, Zhangzhou, Beilun, Jiangbei, their quality development is pretty good, with higher level of regional coordinated development. And they have natural advantages in the improvement of quality in various fields. As to non-central areas, due to the relative backwardness of regional economic and social development, regional cooperation development is not strong enough, resulting in relatively lower level of development quality in this region. (3) The quality improvement of Ningbo development needs to take into account the quality improvement in various fields. The regional development quality is a comprehensive system, so the healthy and coordinated development relies a benign and balanced development of all aspects of the system. From the perspective of the development balance of various districts (counties), the districts and counties with development quality above the city's average level are ranked upstream in the development quality of various fields. For example, Haishu ranks within the top three in five fields of society, urban and rural areas, ecology, and government service. It is clear that balanced development leads to an improvement in the overall development quality.

Conclusion Based on the connotation of urban high-quality development, this paper selects 35 indicators from five dimensions: economy, society, ecology, urban and rural areas, and government services to

628 establish an evaluation index system for urban quality development. The paper takes Ningbo as an example, and uses ANP to measure the quality of Ningbo city. The evaluation shows that the urban development quality of various regions in Ningbo shows relatively obvious spatial distribution, with higher quality development level of the central urban areas, and lower scores of the remote suburbs. The quality of urban development is not balanced, and there are still many fields that need to be improved. It is necessary to pay attention to make up for the shortage in the future development and achieve an overall improvement in the quality of urban development.

Acknowledgement This work is supported by Major projects of the National Social Science Fund(No. 17ZDA070), Natural Science Foundation of Zhejiang Province (No. LQ18G030001), Natural Science Foundation of Zhejiang Province (No. LY18G030001), the Ministry of Education Humanities and Social Sciences Research foundation (No. 18YJA630081) , he Fifth Round of Ningbo Philosophy and Social Sciences Leader Cultivation Project (Research on the Construction of Ningbo Public Service Supply Model Based on Synergy Theory) and Campus Fund of Ningbo Institute of Technology, Zhejiang University (NBLGXNXM0259).

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