Analysis of shopping walking activities and influential factors in neighborhoods. Case study of 21 neighborhoods in Shanghai

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POLITECNICO DI MILANO

October, 2014

Author: LIU Minghao

Student Number: 803583

Faculty:

Architecture and Society

Course of degree:

Architecture

Supervisor: Prof. Corinna MORANDI

Analysis of Shopping Walking Activities and

Influential Factors in Neighborhoods

—Case Study of 21 Neighborhoods in

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Acknowledgements

This work was carried out at Politecnico di Milano and Tongji University. It is my great pleasure to thank all the people who supported me in creating this Master's Thesis.

Special thanks to my supervisor Prof. Corinna Morandi who gave me the great help. Her enthusiastic attitude towards research influenced me a lot. I also wish to express my thanks to my Chinese supervisor Chen Yong, who gave me lots of ideas about the thesis and the guidance of research.

I thank all my friends and colleagues: Huang Kejie, Liu Chang, Chai Zhiping, Chu Qifeng, Chen Weiyi, Bai Xueying and Deng Xiaoxiao, for their valuable comments, advice and encouragement. They have also created a warm and sunny atmosphere also during thesis writing times, making me feel part of a great family.

Finally I would like to thank my parents who trusted and motivated me during my student career. Completion of this work would have been impossible without them.

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List of Charts

Chart 1. 1: Positions of neighborhoods ... 10

Chart 2. 1: Walk Path of neighborhoods with different side length ... 19

Chart 2. 2: Different sections of the node and the walking path of neighborhoods ... 20

Chart 2. 3: Commercial distributions ... 22

Chart 2. 4: Commercial Density ... 22

Chart 2. 5: Purposes of different people travelling on foot ... 25

Chart 2. 6: Proportion of shopping travel on foot ... 26

Chart 2. 7: Proportion of Modes of shopping travel... 27

Chart 2. 8: Shopping destinations of different residents ... 28

Chart 2. 9: Travelling frequency of different supermarket/market perception ... 29

Chart 2. 10: Pedestrian recognition degree of different residents ... 30

Chart 2. 11: Residents’ top 5 reasons of travelling on foot ... 31

Chart 2. 12: Residents’ top 5 Environmental Demands of Walking ... 32

Chart 2. 13: Top 5 walking obstacles of different people ... 33

Chart 2. 14: Overall walking environmental satisfaction of different people ... 35

Chart 2. 15-1: Satisfaction of bus accessibility ... 36

Chart 2. 15-2: Satisfaction of commercial service facilities’ accessibility ... 37

Chart 2. 15-3: Satisfaction of convenience ... 37

Chart 2. 15-4: Satisfaction of traffic safety ... 38

Chart 2. 15-5: Satisfaction of social security ... 38

Chart 2. 15-6: Satisfaction of comfort ... 39

Chart 3. 1: Comparison of Walking and Seldom-walking Shopping Groups’ Social Attributes ... 58

Chart 3. 2: Licheng Road (near Changli road intersection) ... 62

Chart 3. 3: Chengshan Road... 62

Chart 3. 4: Carrefour in Zhenhua road ... 62

Chart 3. 5: Stores along Fuping Road ... 62

Chart 4. 1: Distribution of Businesses in Changli Road... 73

Chart 4. 2: Stores Along Changli Road ... 74

Chart 4. 3: Public Transport Distribution in Tianlin New Town ... 74

Chart 4. 4: Scenes around a Bus Stop in Tianlin Road ... 74

Chart 4. 5: Scene in Front of Carrefour in Zhenhua Road ... 75

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List of Tables

Table 1. 1: Detailed Information of Case Neighborhoods ... 11

Table 2. 1: Neighborhood Questionnaire Distributions ... 16

Table 2. 2: Socio-demographic Attribute Distribution of Residents Researched ... 17

Table 3. 1: Specification of Dependent Variables ... 41

Table 3. 2: Specification of Independent Variables ... 41

Table 3. 3: Correlation between Walking Shopping Travel Frequency and Socio-demographic Attributes. ... 43

Table 3. 4: Correlation between Walking Shopping Frequency and Neighborhood Attributes & Spatial Texture. ... 44

Table 3. 5: Correlation between Walking Shopping Frequency and Commercial Density ... 44

Table 3. 6: Correlation between Walking Shopping Frequency and Density of Other Facilities ... 45

Table 3. 7: Correlation between Walking Shopping Frequency and Public Transport Services. ... 46

Table 3. 8: Correlation between Walking Shopping Frequency and Pedestrian Facilities ... 46

Table 3. 9: Correlation between Walking Shopping Frequency and Interface Form ... 47

Table 3. 10: Fitting Results of Overall Walking Shopping Travel’s Basic Model... 50

Table 3. 11: Parameter Results of Spatial Variables in Three Sub Models of Basic Model-1 51 Table 3. 12: Fitting Results of Walking Shopping Travel’s Basic Model ... 52

Table 3. 13: Parameter Results of Spatial Variables in Three Sub Models of Basic Model-2 52 Table 3. 14: Fitting Results of Seldom-walking Shopping Travel’s Basic Model ... 54

Table 3. 15: Parameter Results of Spatial Variables in Three Sub Models of Basic Model-3. 54 Table 3. 16: Comparison of Pseudo R2’s Added Values of Different Groups Influenced by Spatial Variables ... 56

Table 3. 17: Parameter Results of Spatial Variables in 3 Sub Models of Family Income ... 60

Table 3. 18: Parameter Results of Spatial Variables in 3 Sub Models of Gender ... 63

Table 3. 19: Parameter Results of Spatial Variables in 3 Sub Model of Full-time Workers ... 65

Table 3. 20：Comparison of Spatial Variables to the Increment of Pseudo R2 of Social Attributes Subsamples’ Basic Models... 66

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Abstract

Since the 20th century, the development of China's urbanization and motorization is very fast. The concept of “car-based” urban planning profoundly affects the urban renewal and new district development of many cities in China, and triggers a series of problems, such as long commuting distance, traffic congestion and deterioration of walking environment. However, walking is still the main way to travel in the urban residents’ daily life. It not only puts an important role in the short-distance travel, but also is an indispensable part of all transport modes, especially the green transportation system in most of big cities.

Take 21 neighborhoods of Shanghai as an example. First, analyze residents’ walking characteristics, walking attitude, walk satisfaction, transportation walking frequency and the residents' socio-demographic attributes through the 2861 questionnaires. Second, choose spatial pattern variables affecting transportation walking through the collection of the theoretical literature, and obtain the spatial pattern variables’ data from on-site research. Third, use SPSS to analyze the relationship between shopping walking frequency and the variables with the methods of correlation analysis and basic model simulation with multi-variable logistic regression to find out the most important socio-demographic attributes and spatial pattern variables. Then give the suggesting threshold through scatter diagram.

Key Words: Neighborhood, Shopping Walking Activities, Spatial Pattern,

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Chapter 1: Introduction

1.1 The Origin of This Study

1.1.1 Research Background

（1）Transformation of Commercial Mode in Residential Districts

Cities in China are now experiencing the transformation from production city to consumption city. With the reform of economic system, the development of the residents' consumption level and the transformation of residents’ ways of shopping,

residents’ shopping behavior is becoming more complex and diverse. Especially since 1990s, new forms of business, with large supermarket and shopping center as their representatives, have risen rapidly in China's large and medium-sized city.Relying on the competitive advantage of large sales, they not only have a great impact on the traditional commercial model and layout, but also bring far-reaching influence on residents shopping travel. Take Shanghai as an example.Shopping centers combined by a variety of retail and service management are developing rapidly. Up to the end of 2007, Shanghai has 54 shopping centers in business, occupying 6262,800 square meters, among which, 24 shopping centers occupy more than 100,000 square meters per unit area.1 Business along the streets in traditional neighborhood is gradually replaced by large centralized commercial center. Residents’ daily shopping travel by walking is decreasing, while shopping travel by car is increasing in the weekend and during the holidays.

(2)Insufficient Vigor in Residential Neighborhood

Differences of the physical environment in different residential neighborhood usually have great influences on the residents’ life style, such as shopping travel mode. People's consumption patterns will also influence the business environment of neighborhood. Streets are the most attractive public space of neighborhood. In addition to the transportation function, they also functions as places for fair trade, shopping, leisure,social communication, entertainment and sightseeing, representing various city life. They are also important places to show regional characteristics. Pedestrian shopping behavior in the streets has complex effects. They are the process of economic operation, bringing consumptions and services as well as creating tremendous economic benefits. At the same time, they are also a driving force and carrier of city life, improving neighborhood life and reflecting the city vigor.However, in the current rapid growth of motorized traffic, more and more streets function just as a traffic channel.A large number of commercial activities along the street are moved to the interior commercial space with constant temperature, humidity and immutable light. Streets become negative and dehumanized.Some even become unsafe areas of the city, leading to a serious decline of the neighborhood vitality.

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(3)Deterioration of Neighborhood Walking Environment

With the rapid development of urbanization and motorization in China nowadays, the construction of suburban residential neighborhood presents more and more characteristics of car driven shopping travel. Motor vehicles occupy more and more street space, worsening the walking environment. From the perspective of the pedestrian safety, traffic accidents remain high, challenging pedestrian safety and comfort of residents, especially children and the elder people. According to the researches in Beijing, Shanghai, Guangzhou, etc. 44% children encountered a very dangerous situation walking to school or home. 60% of the children had difficulty in crossing the street.From the perspective of air quality, the air pollution share rate of motor vehicle emissions in the city has reached 79%.Exhaust gas contains more than one hundred harmful substances. Since it is a source of ground pollution with only 1 meter off the ground, it’s the easiest one to be inhaled. Besides the widening of the road, the cutting down of a large number of trees and the compressing of the green belt make more pedestrian fully exposed to the exhaust and noise. Especially in recent years, with the spreading of the haze weather continues in cities of China, PM2.5, pollutions mainly from vehicle exhaust and more tiny particles pollution has become the focus of public attention. Many scholars therefore have put forward a more Urban-style model of development which advocates that the potential destination should be closer to home, in order to reduce the dependence on the automobile travel. They advocate green travel, the improvement of the walking environment and encourage walking.

(4)The Trend of the Construction of Pedestrian Friendly City

Walking is the main way for people's daily travel. It is also a kind of interaction with the surrounding environment. It satisfies the needs forshopping, leisure, fitness and experiences the city life etc. while walking. Since the latter half of twentieth century, the western developed countries increasingly recognize the importance of walking. It shows the prominent value and significance in alleviating the city traffic pressure, neighborhood revitalization, promoting the city vigor, energy saving, emission reduction and improving individual health etc.It has become the ideal and goal of the society from all walks of life to create a dynamic, secure, sustainable city suitable for walking.Many cities have launched the city pedestrian movement, such as the establishment of walking day, holding the corresponding pedestrian forum, to emphasize the importance of the rights of the pedestrian and the importance of walking activities to city life. This helps weaken the strong position of car travelling and create better conditions for city life and walking activities.

1.1.2 Significance of the Research

Residents’ daily shopping behavior has strong interaction with spatial structure of residential neighborhood, facility and layout of the business environment. Shanghai has having a mature neighborhoods lifestyle for a long time. There are a variety of business activities in the old urban streets. Residents’ daily shopping activities are closely connected with the street life, forming a lot of places with vitality and charm. With the rapid development of urbanization and motorization, the shopping travel

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mode in Shanghai has undergone great changes. Especially under the background of suburbanization development, the construction way and mechanism of residential space are quite different from the traditional construction of residential neighborhood, The car driven city construction has a profound impact on people's daily shopping activities and travel mode. The traditional lively, comfortable street life scene no longer exists.

Therefore, it is necessary to study on the walking environment in the mobilized era from the perspective of neighborhoods in the city to explore the inherent regularity between the neighborhood material space form and residents’ walk shopping activities. This kind of study provides clues and experience for creating suitable walk shopping neighborhoods. Besides, this also provides the basis and reference for our residential construction under the rapid development of motorization, thus, helping people regain pedestrian shopping and promote the sustainable development of residential neighborhoods.

1.2 The Research Object and Content

1.2.1 Research Object

(1) Residential Neighborhood in City

Neighborhood is a community in relatively big cities, the suburbs or towns. It is usually defined as a specific geographical area, which contains a series of social activities and functions.People in the neighborhoods will have face to face communication, seek the common values and maintain effective social control.

From the perspective of leading function differences, neighborhoods can be divided into commercial neighborhood, industrial neighborhood, residential neighborhood, business neighborhood and mixed neighborhood. This paper mainly focus on the residential neighborhood with living as its leading function supplemented by commerce, education, office, entertainment and other basic facilities.They are residential areas composed of city roads or other natural elements, such as rivers, walls, green belt separation etc.

(2) Shopping Travel Activities

Shopping refers to a behavior of choosing and buying goods or service from retailers. It can be regarded as a kind of economic and leisure activity, which can occur in the streets, plazas, shopping centers or flea markets. Shopping travel activities are activities in which people from home, work places and leisure venues go to shopping places and shopping. As the research object of this paper is neighborhood, the shopping travel activity refers to the activities from home to shopping places specifically. Neighborhood shoppingis an important form of residents’ daily shopping. people for convenience's demand tend to go to street shops near home in the neighborhood for shopping. Neighborhood shopping with the corner stores as its representative was everywhere once.This paper focuses on shopping travel activity of which walking is its main way of travelling. This includes walking to shop inside and

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around the neighborhood as well as shopping travel to a distant destination using public transport and walking.

1.2.2 Research Content

The focus of this paper is to analyze what neighborhood spatial morphology can make people prefer pedestrian shopping travel through surveying characteristics of spatial morphology, residents’ walk shopping travel activities and problems. The concrete research contents are as follows:

(1) Analyzing street pedestrian shopping travel characteristics and needs, including different demographic residents’ walk shopping travel purpose, the proportion of walking, pedestrian recognition, reasons of walking, requirements of walking environment , walking obstacles and other aspects of the data.

(2) Extracting residential space form variables related to pedestrian shopping activities and analyzing the impact of demographic attributes and spatial variables on pedestrian shopping travel activities by using statistical software SPSS to do the correlation analysis, base model simulation and key variables screening. This paper also explores the relationship between the pedestrian shopping travels and neighborhood material and environmental factors. Then, from the perspective of neighborhood space form, an optimum proposal of pedestrian shopping friendly neighborhoods is put forward through the plot analysis for estimation.

1.3 Current State of Research

There has been a long history studying the neighborhood form and walking activities both in China and other countries. Especially after the publication of Jane Jacobs’ The Death a Life of Great American Cities in 1961, more and more attention has been paid to the value of neighborhood form for city life.

1.3.1 Neighborhood Form and Walking Activities

1.3.1.1 Studies on Neighborhood Form and Walking Activities in Developed Countries

Early studies on neighborhood form and walking activities draw on psychology, behavior science, graphics and typology. The main concern at that time is the cognition of walk space. Most studies are empirical evaluations. Kevin Lynch in his The Image of the City published in 1960 studied memories of the city landscape and summarized 5 elements of space design, which are path, edge, region, node and landmark, while exploring how to form the city's quality of easy identification and image representation; Colin Rowe in his Collage City published in 1978 conducted an analysis of traditional and modern city street network from the whole shape; Allan B. Jacobs analyzed 200 streets from the aspects of scale, plane, section and ways of usage in the Great Street published in 1993 and put forward how to create beautiful streets by designing strategies.

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more profound, the research on the built environment and the walking activities switches from qualitative to quantitative. The content and method of space improvement are mainly acquired through the calculation on land use and spatial index, the comprehensive test of actual usage of people, and analysis of activities and space. From 1970-1980, a new method was put forward for analysis of city space, the space syntax theory, by Bill Hillier and Julienne Hanson and other scholars. This method uses quantitative way to explain the properties of different spatial structure so as to give explanations of spatial structure’s potential functions to human activities. By the late 1990s, some relative methods have been commonly used. For example, the regression model and other statistical methods used discrete data which are quite popular nowadays instead of centralized data to analyze the physical environment, personal factors and travel conditions.

Based on those previous theories, researches about different walking activities are carried out by more and more scholars. Land use, urban design and non-work travel: reproducing other urban areas empirical test results in Portland, Oregon written by Oarnet M. G. and Greenwald M. studies the influence of social and economic attributes of residents, land use and accessibility to residents’ travel frequency, distance and transportation modes through quantitative model under the extensive definition of non-work travel. Robert Cervero in his Mixed Land-use and Commuting：Evidence From The American House Survey (1996) used 300 feet (91.44m) as the radius of influence to measure residential density and mixed degree of land of different blocks and discovered that the increase of residential density and the improvement of the existing community shops and other non-residential type would help increasing the possibility of non-motorized travel based on the data of residents commuting trip, land formation of community and family characteristics through American Housing Survey.

1.3.1.2 Studies on Neighborhood Form and Walking Activities in China

Along with the development of the techniques of foreign statistics and analysis software, some Chinese researchers are starting to study the relationship between the space form of city district and the residents travel.

In Impacts of Urban Forms on Travel Behavior: Case Studies in Shanghai, Pan Hai-xiao, Shen Qing and Zhang Ming discussed the relations between neighborhoods design characteristics and travel based on the data of residents' travel behaviors, social and economic characteristics, and urban form characteristics and by using multi-linear regression theory and logistic mode. The authors find out that traditional neighborhoods are more feasible for non-distance and non-motorized travel and that planning professionals should pay more attention on traditional neighborhoods pattern design which is favorable to biking and walking.

In Attributes and Travel Behavior of Residents in Large Communities at Peripheral Shanghai: A Case Study On Jinhe New Town, Jiadingjiang Bridge written by Zhang Ping and Yang Dongyuan, the authors apply investigation on random samples, together with the interview on neighborhood committees. From the perspectives of the actual living population, travel purpose, and travel direction, the

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authors find that Jinhe Community has the characteristics of low regional mobility, low personal mobility, and low accessibility.

In Public Service Related Outgoing Transportation Characters and Planning Measures Of Large Suburban Neighborhoods written by Zhang Ping, Li Suyan and other authors, they analyze outgoing frequency, method, time, and satisfaction of retired people and commuters to grocery market, supermarket, hospital, bank, and post office. The paper suggests that daily life outgoing needs be put priority at elementary period of large neighborhood development, and puts forward spatial layout methods based on life circle.

According to Analysis of leisure walking activities and influential factors in neighborhoods – Case study of central city area in Shanghai written by Mao Jie, by using statistical software to test the material factors, the individual factors, and pedestrian characteristics of neighborhoods and building a mathematical model, the author discovers that residents' subjective environment perception influence the duration time of leisure activities and walking and physical environment has an impact on the frequency of residents’ leisure activities and walking, then he gives a detailed analysis on the factors of physical environment.

To sum up, studies on neighborhood form and walking activities in developed countries are more mature than in China. However, scholars have not reached a consensus and there are differences in the studying methods. With the differences of city development, construction mode and residents’ lifestyle, those research methods and conclusions are not necessarily suitable for domestic city neighborhoods with high density. Thus, more clear divisions of types of activities and more detailed analysis, especially the study on the relationship between shopping trip and block form, are needed.

1.3.2 Consumer Shopping Behavior

Studies on shopping behavior all experienced shifts from the macro demand level to the micro supply level. Researches in developed countries mainly focus on the studies of basic theories, characteristics of shopping behaviors and its influencing factors, simulation and prediction model. While, researches in China mainly concern about commercial space research, the temporal and spatial characteristics of shopping behavior, influencing factors and decision-making mechanism on the macro level.

1.3.2.1 Studies on Basic Theories

Studies on shopping behaviors stem from city commercial space research. Dynamic balance between supply and demand interactions is its major concern. Reilly is the first one using retail gravitation to define the scope of shopping district. Retail gravitation is an invariant concept of rational economy and space, that is, consumer behaviors are supposed to be rational which is invariant in space. Then, Christller put forward central place theory which combines the assumptions of neo-classical economics, according to which, both economic behavior of producers and consumers are part of the concept of “rational person” and tend to go consciously to the nearest

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shopping center to buy goods or services. These studies focus on commercial format’s own physical space, including the combination of business forms and the type, succession, grade and structure of business in different regions.

Since 1950s, some scholars have explained the establishment and development of the physical space of business through consumer behavior which provides supplements to the central place theory. For example, in The functional bases of the central place hierarchy (1958), Berry J. L. and Garrison W. L. first study consumer behavior theoretically and challenge the assumption that consumers tend to shop at the nearest shopping center. Based on spatial elastic consumer shopping trip mode, Golledge (1966) and other scholars classify business functions and conclude that there are mainly two kinds of goods based on the "elastic space" and the "non-elastic space" respectively. They believe that the functional hierarchy of commercial activities does not necessarily coincide with the center level, but also depends on the consumer shopping behavior and space capacity.

From 1980s, studies on shopping behavior have paid more and more attention in the field of personal preference, attitude, information and other more microscopic sphere. Scholars also start to analyze residents' living space, city commercial space structure and its evolution mechanism from the perspective of consumer behavior. The study of relationship between "people vs. region" has shifted to the research of relationship between "people vs. social relations". The perspective based on individual spatial behavior is becoming the key to understand city space and city society. Huff put forward probability model based on his amendment to Reilly's law of retail gravitation, focusing on consumers instead of retailers. Studies on consumer behavior studies with consumers as research subjects begin since then. Rushton put forward a method of displaying spatial preference, advocating that place preference have more influence to the main consumers than the location.

1.3.2.2 Influencing Factors of the Micro Consumer Behavior

With the development of the consumer behavior theories, it gradually turns to consumer behavior itself as the research object. Scholars start to describe characteristics of consumer behavior and explore economic and social attributes of consumers themselves or families as well as influences of changes in regional business environment on shopping behavior. Besides, residential neighborhoods are the most frequently used places and the overlapped places of many outdoor activities. Through researches of neighborhood forms’ influences on shopping and travelling, an issue about whether residents living in places with rich commercial facilities and good accessibility shops travel more than the residents who live in places with the opposite conditions can be addressed. This therefore means a lot to the evaluation of the adjustment of land use, street space and transportation integration policy.

Therefore, in addition to personal and family situations, the neighborhood space will also influence the decision making process of shopping behavior. Micro consumption behavior will be influenced by two aspects, the personal attributes and environmental factors.

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Researches of consumer behavior in developed countries mainly focus on the studies of quantitative analysis and construction of statistical models. Its major concerns are basic theories of consumer behavior, characteristics of shopping behaviors, prediction and simulation of consumer behavior etc.

Based on those researches, Tilman designed two shopping models, daily commodity and fashion commodity, and simulated consumer shopping behavior, special decision-making in district grocery stores to predict the consumer behavior and turnover. Kapil B.’s A model of household grocery shopping behavior and Robinson R. V. F. & Vickerman R. W.’s The demand for shopping travel: a theoretical and empirical study used models to analyze household consumption and shopping travel frequency as well as the relationship between land use, shopping travel frequency and distance from the perspective of shopping travel.

Susan L. Handy conducted series of studies on shopping travel: In Regional versus local accessibility: Implications for non-work travel (1993), Susan discovered that spatial variables, like types and positions of land use, have no significant effect on residents’ non-living travel based on regional unit summary; In Urban form and pedestrian choices: studies of Austin neighborhoods (1996), Susan found out that modes of transportation of shopping travel are decided by the distance between home and stores; In Local shopping as a strategy for reducing automobile travel (2001) , Susan and Kelly J. Clifton shows that the commercial density has no significant effect on shopping travel distance and modes of transportation of residents. Besides, the traditional belief that the land use policy of the living space can reduce the use of the car shopping trip which can’t be proved.

Effects of space index, such as density, position and accessibility, on the frequency and time utilization of non-work activity travel was examined in Trip generation for shopping travel written by Agyemang-Duah K., Anderson W. P. and other scholars and Zhang M.’s Exploring the relationship between urban form and nonwork travel through time use analysis , receiving a significant causal relationship. Limanond T. & Niemeier D.’s Effect of land use on decisions of shopping tour generation: A case study of three traditional neighborhoods in WA studied the residents’ decisions of shopping tour in traditional neighborhoods in WA and found that types of land use have no significant effects on the frequency of shopping travel, either. However, land use affects shopping travel through other aspects of decision making.

(2) Relative Studies in China

Studies on characteristics of shopping behavior develop rather late in China. Microscopic study concerning neighborhood form and shopping activities is rare. Most researches focus on the macroscopic shopping behavior with descriptive analysis of overall behavior characteristics and spatial structure as its major concern. It lacks studies on land use and special environment to some degree. Current studies on this aspect are as follows:

In The Relationship among Consumer 's Travel Behavior , Urban Commercial and Residential Spatial Structure in Guangzhou, China, Zhou Suhong, Lin Geng and Yan Xiaopei studied the characteristics of and relationship between urban commercial

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and residential space through consumer behavior itself and found out: Firstly, there is a close relationship between people's travel mode, trip distance and multi-objective traveling and type of communities, location, services around, and urban commercial space; The sub-centers and service area around the neighborhoods play an important role in daily shopping service. The weaknesses of daily life supporting service area in service ability and business types will lead to excessive dependence on the old central business district of the city, thus, increasing the daily travel costs.

In Influence of Land use and Traffic supply on travel pattern of Shopping mall in nine sub-districts of Hangzhou, China, Dong Yi-ming, Pan Conglin, Wei Ya-ping used the explanatory variables of individual attributes, commuting distance and land-use characteristics to examine the effects of the urban land-use on travel pattern of shopping mall. The results show that, accessibility improvement and mixed land-use of commercial and residential land can encourage more walk and bicycle trips to shopping mall; while the raise of transit service level encourages more non-motorized travels.

In A Study on Activity Space of Shopping of Shanghai Residents: Temporal and Spatial Characteristics and Relative Influencing Factors (Chai Yanwei, Shen Jie & Weng Guilan, 2004) and A study on Commercial Structure of Shanghai Based on Residents’ Shopping Behavior (Chai Yanwei, Shen Jie & Weng Guilan, 2008), the time and spatial characteristics of residents’ shopping behavior are examined based on the results of questionnaire surveys. Further research on its relative influencing factors is carried out from views of individual choice and urban space. The results show that the characteristics of shopping behavior of residents is Shanghai can be summed up as an typical activity of low-frequency, close-travel distance, non-motor-oriented mode as well as night timing. The travel mode, range of the space and the concentrated extent mostly rest on the physical space of retailing of the city.

In A Study on Shopping Behavior of Beijing Residents: the Spatial Differentiation OF Influencing Factors (2009), Ma Jing, Chai Yanwei and Zhang Wenjia consider the travel distance from home to the most frequently shopping sites as dependent variable while considering a series of factors about personal social-economic attributes, family attributes, spatial attributes and shopping activities as independent variables. The authors formulate many regression models based on different locations. The results indicate: firstly, certain factors affect the shopping distance of residents in various locations distinctively. Secondly, the major influencing factors are different, for example, the major factors are commercial density and age in inner city, but shopping frequency and age in suburbs. Besides, factors, such as the education level of residents of different location, influence shopping behavior in intensity and direction of functions to different degrees.

In The Study on Temporal and Spatial Characteristics of Shopping Behavior of Wuhu Residents, Han Hui-ran and Song Jin-ping analyzed the temporal and spatial characteristics of residents’ shopping behavior in terms of shopping frequency, shopping time, travel distance, the spatial hierarchy of shopping trip space and compared with other metropolitan cities based on the questionnaire survey and interviews on shopping behavior of Wuhu residents. The results showed that: the

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multi-purpose travel, including shopping travel, is becoming a mainstream trend; The shopping activities of the vegetables food and the daily necessities are focused on community shopping circle; The spatial tour hierarchy of residents purchasing the daily necessities showing the obvious trends near residence and the higher mobility to purchase the high-grade goods than low-grade goods.

To sum up, the theoretical system of shopping behavior is gradually formed in developed countries. The major focus is shifting from commercial space to the shopping behavior. The research in China is primarily based on the empirical research of foreign scholars on the shopping behavior theory and has accumulated some achievements in the consumer behavior and commercial space structure. However, most studies concentrate in the macroscopic shopping travel, leading to the relative lack of specific research on pedestrian shopping travel, the influencing factors, such as land use and space environment of the pedestrian shopping travel.

1.4 Case selection

1.4.1 Neighborhood Sample

This paper chose Shanghai as the city of this case study,mainly because since the modern times, Shanghai has formed a rich and diverse city texture and neighborhood space through the different historical period.Through the investigation and analysis of several residential neighborhoods in the central parts of Shanghai, the following 21 neighborhoods are selected as the objects of this case study.

Considering the different socio demographic attributes of different residents, residents in these 21 neighborhoods are divided into 5 types according to the development and distribution of residents’ income. (Chart 1.1)

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(1) Historical Neighborhood

Construction time: From the end of the nineteenth century to the beginning of the Republic of China. It is an old residential neighborhood of located in the old central parts of Shanghai. The regional situations nowadays are: the old Linong-neighborhood, new Linong-neighborhood, part of shanties together with Worker’s apartments built afterwards. Laoximen neighborhood is selected for this case study.

(2) Old Worker’s Village

Construction time: 1950s. It is a collective residential area for workers constructed in the 1950s. It is located in the peripheral areas of Shanghai at that time and now it’s between the inner ring and outer ring. The government allocated it, commonly known as “Old Worker’s Apartment”, to the workers free of charge. Five neighborhoods, which are Caoyang New Village, Kongjiang New Village, Tianlin New Village, Ganquan New Village, Fengcheng New Village, are selected.

(3) Old Residential Area

Construction time: 1970s and 1980s. It is a residential area with five or six layer structure built since 1973, the partial recovery time of workshop building. It is called “New Worker’s Apartment” at that time to distinguish from “Old Worker’s Apartment”. Six neighborhoods, which are Laoshan New Village, Nanyuan New Village, Shanggang New Village, Shangnan New Village, Zhongyuan Community and Meiyuan New Village, are selected.

(4) Commercial Housing Neighborhood

Construction time: Since 1980s. Since the launching of reform and opening up policy and the economic transition, the government and the work units no longer distribute houses uniformly.Real estate developers now have the power to build and sell houses. Five neighborhoods, which are Wanlicheng (West), Wanlicheng (East), Lvcheng Neighborhood, Lujiazui Garden and Datang Shengshi Garden, are selected.

(5) International Residential Neighborhood

Construction time: Since 1990s. It is constructed during the middle of the reform and opening up. It aims to provide residential places with high-level hardware design for people from overseas coming to work or invest in China. Four neighborhoods, which are Gubei New Area (West), Gubei New Area (East), Lianyang Community (West) and Lianyang Community (East), are selected.(Detailed information can is listed in the following table.)

Table 1.1: Detailed Information of Case Neighborhoods

Neighborhood Types Name Land Area(ha) Population density (person/km2） The District Nearby Subway Stations Historical

Neighborhood Laoximen 49.1 74000 Huangpu

Line 8: Laoximen， Lujiabang Road；Line 10: Xintiandi；Line 9 : Madang Road Old Worker’s Village Caoyang New Village 157.0 55600 Putuo Line 3, 4: Caoyang Road，Jinshajiang Road；Line 11:

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12 Fengqiao Road Kongjiang New Village 63.0 73600 Yangpu Line 8: Huangxing Road Tianlin New Village 115.1 48700 Xuhui

Line 9: Guilin Road； Line 12: Guilin

Garden Ganquan New

Village 55.3 63400 Putuo Line 7: Xincun Road Fengcheng New

Village 74.0 67300 Yangpu Line 8: Jiangpu Road

Old Residential Area Laoshan New Village 76.6 49300 Pudong new district Line 2: Dongchang Road；Line 4: Pudong Avenue Nanyuan New

Village 45.2 23400 Huangpu Line 4: Luban Road Shanggang New Village 42.7 67500 Pudong new district Line 8: Yaohua Road，Chengshan Road；Line 7: Changqing Road Shangnan New Village 69.9 62300 Pudong new district Line 8: Yaohua Road，Chengshan Road；Line 7: Yuntai Road Zhongyuan Community 155.2 53100 Yangpu Line 8: Shiguang Road，Nenjiang Road Meiyuan New Village 99.7 46600 Pudong New District Line 4: Pudong Avenue，Century Avenue；Line 6: Yuanshen Stadium Commercial Housing Neighborhood

Wanlicheng(West) 44.9 47700 Putuo Line 11: Shanghai West Railway Wanlicheng (East) 41.8 45000 Putuo Line 7: Xincun Road

Lvcheng Neighborhood 86.1 18800 Pudong New District Lujiazui Garden 90.0 17100 Pudong New District Line 6: Yuanshen Stadium, Minsheng Road; Line 9: Middle Yanggao Road Datang Shengshi Garden 54.7 16100 Pudong New District

Line 7: Huamu Road

International Residential Neighborhood

Gubei New Area

(West) 53.5 19400 Changning

Line 10: Shuicheng Road

Gubei New Area

(East) 54.3 22400 Changning Line 10: Yili Road Lianyang Community( West) 81.2 18400 Pudong New District Line 9: Middle Yanggao Road Lianyang Community( East) 80.7 23600 Pudong New District

1.4.2 Selection Principle

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(1) Similarities of the Neighborhoods

The principle of similarities of the case neighborhoods can be presented as follows: (1) Clear outer boundaries: These neighborhoods use city road, highways, river, etc. as boundaries, naturally making a relatively independent area for daily walking activities. The environmental characteristics of residents’ travelling have some similarities. (2)Residential function driven: There is no important city business or tourist attractions. People there are mainly residents. (3) Stable population density: Occupancy rate of the selected neighborhood is high, forming the basis of street activities. (4) Good public transportation: These neighborhoods have several bus stops and more than one subway stop to ensure that residents of the region with the prerequisite of walking and public transit travel. (5) Similar neighborhood size:The selected cases have land area of about 1 km2, no more than plus or minus 0.6 km2

(2) Differences of the Neighborhoods

The principle of differences of the neighborhoods can be presented as follows: (1) The multiple geographical location: The selected areas not only include the historical neighborhoods in the central city, but also include work’s new villages in the peripheral areas and commercial housing neighborhoods inside the outer ring. (2) Spatial difference: Linong-neighborhoods’ blocks are relatively small with high mixed land degree while work’s new village’s blocks are relatively large with high mixed land degree. The commercial housing neighborhood has large areas with relatively low mixed land degree. (3) Differences of the residents: Residents in the Linong-neighborhoods are mainly elderly retirees and tenants with lower education and income and almost no one has private cars; Residents in the work’s new villages are mainly office workers and retirees with middle-level education and income. A few have private cars; Residents in the commercial housing neighborhoods are mainly office workers and people living with their parents with high education and income as well as more private cars.

1.5 Research Methodology and Thesis Structure

1.5.1 Research Methodology

(1) Literature Reading and Organizing

Suitable research methods and framework for this paper will be attained through reading materials related to neighborhood space form, residents walk activities, shopping behavior and travel in recent decades and by analyzing and organizing relative theories and practices.

(2) The Questionnaire

A survey has been conducted in the mid-January, 2012 gradually based on related research projects and with the help of planning departments, street committee and residential committee. The content of the questionnaire involves walking trip characteristics, walking attitude, walking environment satisfaction and the pedestrians’ demographic attributes, etc. 3820 questionnaires were handed out, receiving 2861 questionnaires. The effective recovery rate was 74.9%.

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(3)Field Investigation

The field investigation of the environmental conditions and walk travelling activities was conducted in the case neighborhoods with the help of topographic map from GIS database in The Shanghai urban planning design and research institute, the development of research outline and preparation of relative data. The results are recorded through words, pictures, graphics, etc.

(4) Data statistics and Analysis

Correlation analysis is based on the relevant data of pedestrian activities and spatial form elements resulted from questionnaires and field investigation to try to find important elements related to shopping travel activities by using statistical analysis software, such as EXCEL and SPSS. Then, mathematical model is established to analyze relationships between the physical environment and practical activities. Finally, recommended practices and quantitative indicators are put forward.

1.5.2 Thesis Structure

Chapter one is introduction. In this part, the research background and significance will be introduced. The research object and content will be defined. Focus of this research and the case samples will be established according to the related research status in developed countries and in China.

Chapter two is the survey profile. Detailed explanation of research methods and process will be given. According to the survey data of 21 neighborhoods, general characteristics of walking activities in the residential neighborhoods, Shanghai will be analyzed. Those characteristics include walking travel characteristics, walking attitude, pedestrian environment satisfaction. Specific meaning and quantitative standards of walking activity data and spatial shape elements (including spatial texture, land use, road traffic, pedestrian network, and interface form) will be given.

Chapter three is data analysis. First, correlation analysis will be conducted with travel frequency of shopping on foot as the dependent variable, the demographic attributes factors and spatial variables as independent variables by using the statistical software SPSS to establish basic simulation model. Then, extracting variable factors associated with shopping travel on foot and give the suggesting threshold through scatter diagram.

Chapter four is conclusion and solutions. This part pays attention to summarize the research results and put forward the optimal design of the shopping pedestrian travel strategy in order to provide a reference for future new district planning and construction.

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Chapter 1: Introduction

Research Origin, Research Object and Content, Research Status, Case Selection, Research Methodology and Thesis Structure

Chapter 2: Survey Profile

Demand Research Spatial Form

T ra v el Ac ti v it ies De m o g ra p h ic Attri b u tes Ne ig h b o rh o o d Attri b u tes S p ati al Tex tu re Lan d Us e P u b lic T ra n sp o rt S erv ice s P ed estrian F ac il it ies In terfa ce F o rm

Chapter 3: Data Analysis

Pedes tr ian Shoppi n g Spatial Form Demography Characteristi cs Correlation Analysis Basic Model Key Valuable Screening Valuable of Significance Pearson Related

Multivariate Logistic Regression

Key Demographic Attributes Key Spatial Form

Subsample Analysis

Family Income

Chapter 4: Conclusion and Solutions

W alk in g Atti tu d es En v ir o n m en t S ati sfa cti o n

Questionnaire Documents GIS

Shopping Travel Habit

Gender Full-time Workers

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Chapter 2: Research Profile

2

2.1 Sources of Data

2.1.1 Residents Questionnaire of Walking Activities

With the help of the Shanghai municipal planning bureau and related departments of the street, the questionnaire survey of 21 neighborhoods was conducted successively in Shanghai central city from December 2011 to June 2012. Questionnaires were distributed and recycled randomly by office staff of residents' committees. The period between distribution and recovery cycle of each neighborhood is controlled in almost 2 weeks. The number of questionnaires is

determined according to the different construction scale and the population density of neighborhoods. Generally each neighborhood was distributed 100-200 questionnaires. At the same time, the number of questionnaires distributed is controlled effectively within and between different neighborhoods according to the residents’ proportion of each neighborhood’s population in the whole residential neighborhoods to ensure the rationality of the sample distribution. The balance of all ages is also considered.

Table 2.1 Neighborhood Questionnaire Distributions

Number Name of Neighborhood Total Number of Questionnaire Distributed Number of Valid Questionnaire Recycled Recovery Rate of Valid Questionnaire (%) Recorder

1 Laoximen 180 91 50.6 Mao Jie 2 Caoyang New

Village 220 199 90.5 Chai Zhiping 3 Kongjiang New

Village 180 174 96.7

Chai Zhiping 4 Tianlin New

Village 180 139 77.2 Liu Chang 5 Ganquan New

Village 180 110 61.1

Wang Quanyan 6 Fengcheng

New Village 180 174 96.7 Chai Zhiping 7 Laoshan New Village 180 158 87.8 Wang Quanyan 8 Nanyuan New Village 180 109 60.6 He Ning 9 Shanggang

New Village 180 108 60.0 Mao Jie 10 Shangnan New

Village 180 132 73.3 Ma Keyi 11 Zhongyuan

Community 180 152 84.4 Liu Chang 12 Meiyuan New

Village 180 146 81.1 Meng Zhaocai 13 Wanlicheng 180 164 91.1 Liu Minghao

2

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(West) 14 Wanlicheng

(East) 180 122 67.8 Liu Minghao 15 Lvcheng Neighbourhood 180 114 63.3 Liu Minghao 16 Lujiazui Garden 180 148 82.2 Ma Keyi 17 Datang Shengshi Garden 180 133 73.9 Wang Quanyan 18 Gubei(West) 180 114 63.3 Huang Kejie 19 Gubei(East) 180 102 56.7 Huang Kejie 20 Lianyang(West) 180 124 68.9 Huang Kejie 21 Lianyang(East) 180 148 82.2 Huang Kejie

Total Number 3820 2861 74.9

The content of the research contains 4 aspects: (1) Individual attributes, that is, the social characteristics of respondents, involving gender, age, occupation, education, family population, income and number of transportation owned, etc. (2)Travel characteristics, that is, characteristics of residents’ walk activity, involving walk purpose, distance, frequency, time, proportion and so on. (3)Walking attitude, which is the subjective demand of residents themselves, involving walking motivation, needs, and obstacles, etc. (4) Environment satisfaction. This paper makes a research on walking environment satisfaction of the residents of the individual neighborhoods, involving the overall environment satisfaction and six itemized environment satisfaction.

3820 questionnaires were distributed in these 21 neighborhoods. 2940 questionnaires were recycled. After the evaluation of integrity and authenticity of each questionnaire, 2863 questionnaires were picked out and used as the final samples. The recovery rate of valid questionnaire is 74.9%.

Table 2.2 Socio-demographic Attribute Distribution of Residents Researched Items Number Proportion

(%) Items Number Proportion (%) Gender Male 1133 40.4 Family Member 1 48 1.8 Female 1673 59.6 2-3 1931 73.0 Total Number 2806 4 668 25.2 Age 10-29 314 11.2 Total Number 2647 30-39 572 20.4 Family Income (RMB) Less than 3000 559 21.2 40-49 570 20.3 3000-10,000 1308 49.7 50-59 800 28.5 10,000-20,000 468 17.8 60-69 456 16.2 20,000-30,000 206 7.8 70- 97 3.4 More than 30,000 92 3.5 Total Number 2809 Total Number 2633 Occupation Student 57 2.1 Bicycle 0 1251 43.7

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Full-time 1531 55.6 1 1217 42.5 Part-time 174 6.3 2 329 11.5 Unemployed 106 3.8 3 60 2.1

Retirees 887 32.2 4 4 0.1 Total Number 2755 Total Number 2861

Education Junior high school and lower 217 8.5 Motorcycle 0 1921 67.2 High School 989 38.8 1 807 28.2 Junior College 614 24.1 ≥2 132 4.6

College 626 24.5 Total Number 2860 Postgraduates and higher 104 4.1 Private Car 0 2026 70.8 Total Number 2550 1 714 25.0 ≥2 121 4.2 Total Number 2861

Through the Excel software of data collection and sorting, attributes of residents being investigated are shown as follows:

As for the personal information: (1) Female: 59%; Male:41%. (2) Average age of residents investigated is 43, among which, 11% is lower than 29, 21% between 30-39, 20% between 40-49, 28% between 50-59 and 19% is older than 60.Proportion of age is relatively balanced. (3) Occupation: 2% students, 57% full-time workers, 6% part-time workers and 35% unemployed (including retirees). (4) Education: The average education of residents investigated is junior college. 8% of residents investigated are lower or just junior high school, 37% high school, 24% junior college, 25% college and 4% postgraduate or higher.

As for the family information: (1) Family members: The average number is 3. Families with only 1 member occupy 3%, 2-3 members 72%, more than 4 members 26%. (2) Family income: The average income is 9668 yuan. 20% families are lower than 3000 yuan, 50% between 3000-10000 yuan, 18% between 10000-20000 yuan, 8% between 20000-30000 yuan and 4% higher than 30000 yuan. (3) Private cars owned: average is 0.3 per family. 71% have no private car, 24% with 1 car and 4% with 2 or more than 2 cars.

As for the shopping travel, according to the question 6 in the questionnaire (in the appendix), the data of the times of residents shopping on foot (including walking to transfer bus/subway) per week is extracted as the walking shopping frequency.It is approximately divided into less travel (0-2 times/ week, 31.5%), general travel (3 times/week, 19.6%), more travel (4-5 times/week, 24.9% ) and frequent travel ( 6 times/week, 24.0%) in a ratio of around 25%.

2.1.2 Form Factors of Neighborhood Space

In April 2012, 21 neighborhoods field investigation were conducted. The research content includes residents’ pedestrian activities and space form. In November 2012, check and offset of space form were carried on some neighborhoods.

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Through analyzing and summarizing references, it can be seen that space form of neighborhoods has significant influence on the shopping travel. Many scholars discover that density, land use and street connectivity are important factors affecting walking activities. Generally speaking, high density and mixed land use usually means adjacent relationship of travel destinations. Street connectivity affects the convenience degree to the destination. Shopping on foot is mainly affected by the distance and comfort of each shopping destination.

Therefore, in reference to existing research summary of space form variables, specific analysis of influences of space form on pedestrian shopping activities is conducted by combining with the characteristics of Shanghai residential neighborhoods and selecting the six categories of neighborhood space form factors, which are the neighborhood attribute, spatial texture, land use, road traffic, pedestrian network and interface form.

2.1.2.1 Neighborhood Attributes

Land area and population density of neighborhoods may have certain influence on residents' activities on foot. Generally speaking, High density of population and the appropriate neighborhood land area are advantageous to the mixing of land function and the efficiency of public transport facilities, thereby promoting activities on foot.

(1) Land area （ hm2） refers to the total land area of the selected case neighborhoods limited by urban roads or other natural boundaries such as rivers, lakes and so on. It is the actual land area of neighborhoods surrounded by peripheral road centerline.

(2) Population density (10,000 people/ km2) refers to the total number of residents per square kilometer, that is, residential population/ total land area of neighborhood.

2.1.2.2 Spatial Texture

Spatial texture reflects the spatial structure features of neighborhoods. It is the skeleton of development of neighborhood form. Under different social and economic background and the concept of planning in different periods, neighborhood form is different.For example, different characteristics in special texture are presented among the old Linong-neighborhoods, the new villages built after the liberation under the collective ownership and commercial

neighborhoods emerged under the system of market economy.

(1)The Average Side Length of Blocks

It uses area or perimeter as evaluation index, which is more beneficial to the operation of land planning, but not an accurate reflection of walking accessibility. As shown in chart 2.13,

3

Jennifer Dill. Measuring Network Connectivity for Bicycling and Walking[C]. TRB 2004 Annual meeting

Chart 2.1 Walk Path of neighborhoods with different side length

Source of chart：Measuring Network Connectivity for Bicycling and Walking

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under the same circumference and area of blocks, the former walking paths (A + B) between blocks are obviously shorter than the latter, and as for walking paths (C + D), the former is much longer than the latter. Therefore, this paper mainly use average side length of blocks to measure the effect of neighborhood division on walking travel. The average side length of blocks (m) refers to the the average length of each block within case neighborhoods, that is, sum of the side length / the sum of the number of sides within neighborhoods.

(2) The Density of Intersection

Intersection density has a profound impact on the convenience and smooth of walking paths. Jan Gehl thinks that good walking environment first requires perfect organic walking system, making people go to wherever they want conveniently. Allan B. Jacobs in Great Street uses figure analysis to compare dozens of city streets form around the world. The influences of the number of intersections on walking activities are expressed intuitively. Venice, the Heaven for walking, has 1500 intersections every square mile, while Los Angeles in America has 150, Irvine in California only has 15, thus a ratio of 100:10: l. Therefore, intensive pedestrian network within different scales of public space should be accomplished first.

This paper selected the intersection density, road node ratio and the entry point density to reflect the influence of intersections on walking activities. Intersection in this paper refers to the intersection between urban road intersections. Community, schools and other end connected with gateway are not included.

(1) Intersection density (/km2) refers to the number of intersections per square

kilometer range within neighborhoods investigated, that is, the number of intersections/ total land area of neighborhoods.

(2) Road node ratio refers to the total number of roads within the scope of

neighborhoods investigated/ total number of nodes of intersections. As shown in chart 2.2, under the same block density, the same intersection density and different node ratio, the path length is different.

(3) Density of road entry point (/km2) refers to the number of urban road intersections per square kilometer range being able to connect with the the external enviroment. It is used to examine connectivity between neighborhoods investigated and the external environment.

2.1.2.3 Land Use

It can be found from the work of researchers from home and abroad that the land use structure has important implications for transportation including walking activities. Some of these implications are direct, some are indirect. For example, the

Chart 2.2 Different sections of the node and the walking path of neighborhoods

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accessibility of community market, convenience stores and cultural and entertainment facilities will also prompt residents’ walk travel; In residents' daily shopping, the large supermarket is becoming more and more important, which is also one of the important factors measuring the richness of life service facilities in neighborhoods.

It is difficult to accurately describe the influence of land use on pedestrian shopping activities if regarding the function multiplicities of land use as the only evaluation factor.Therefore, this paper, drawing on the Chinese planning department for the types of land use in land use planning and combining with the different functions of different types affecting the travel activities on foot, divided index of land use on commercial into: large commercials, street stores, ratio of street stores≥ 15 /100m and ratio of street stores≤5/100m (Chart 2.3, 2.4). Besides, indicators also include educational facilities, medical facilities, cultural facilities, office buildings, community service facilities and public green space, etc.

(1) Density of large commercials (/km2) refers to the total number of large commercials per square kilometer within the scope of neighborhoods investigated, that is, the total number of large commercials with neighborhoods/ the total land area. The large commercials include large supermarkets, shopping malls and commercial streets, etc.

(2) Density of street stores（m/km2）refers to the total length of commercial

shops along the street per square kilometer within neighborhoods investigated, that is, the total length of commercial shops along the street/ the total land area.

(3) Ratio of street stores which ≥15/100m（%）refers to the 15/100m or more stores accounted for the proportion of all the stores down the street within neighborhoods investigated, namely the number of 15/100m or more stores along the street/ total number of stores along the street.

(4) Ratio of street stores which ≤5/100m（%）refers to the 5/100m or less stores accounted for the proportion of all the stores down the street within neighborhoods investigated, namely the number of 5/100m or less stores along the street/ total number of stores along the street.

(5) Density of educational facilities (/km2) refers to the total number of kindergartens, primary schools, secondary schools, mechanic schools, vocational education and other institutions of education per square kilometer within neighborhoods investigated, namely the number of institutions of education/ the total land area.

(6) Density of medical facilities (/km2) refers to the total number of health posts, outpatient clinics, hospitals and nursing stations per square kilometer within neighborhoods investigated, namely the number of medical institutions/ the total land area.

(7) Density of cultural facilities (/km2) refers to the total number of cultral facilities, including cultural centers, residents' fitness rooms and so on per square kilometer within neighborhoods investigated, namely the number of cultral facilities/ the total land area.

(8) Density of office buildings (/km2) refers to the total number of all kinds of business office buildings per square kilometer within neighborhoods investigated,

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namely the number of office buildings/ the total land area.

(9) Density of community service facilities (/km2) refers to the total number of community service facilities, including neighborhood committees, security defense stations, telecommunications, post offices, banks, and municipal administrations such as police stations, fire stations, etc. per square kilometer within neighborhoods investigated, namely the number of community service facilities/ the total land area.

(10) Density of public green space（m2/km2）refers to the total land area of public green space, including open parks, street green space, small gardens as well as the green belt within protective isolations, namely the total land area of public green space/ the total area of neighborhoods investigated.

Chart 2.3 Commercial distributions

Chart 2.4 Commercial Density 2.1.2.4 Public Transport Services

Walking space of motorized era requites the balancing of the needs for motor transport and walk. Motor transport mainly include public transport and private cars. It is easy for public transport and walking to achieve harmony. The higher the proportion of residents choosing bus or metro, the higher walk travel rate is. This also meet the demand of health and environmental protection. Besides, public transport is