A Theoretical Framework and Methodology for Urban Activity Spatial Structure in E-society: Empirical Evidence for Nanjing City, China

WANG Bo; ZHEN Feng; WEI Zongcai; GUO Shu; CHEN Tingting

doi:10.1007/s11769-015-0751-4

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Article Navigation > Chinese Geographical Science > 2015 > 25(6): 672-683

WANG Bo, ZHEN Feng, WEI Zongcai, GUO Shu, CHEN Tingting. A Theoretical Framework and Methodology for Urban Activity Spatial Structure in E-society: Empirical Evidence for Nanjing City, China[J]. Chinese Geographical Science, 2015, 25(6): 672-683. doi: 10.1007/s11769-015-0751-4

Citation:

WANG Bo, ZHEN Feng, WEI Zongcai, GUO Shu, CHEN Tingting. A Theoretical Framework and Methodology for Urban Activity Spatial Structure in E-society: Empirical Evidence for Nanjing City, China[J]. Chinese Geographical Science, 2015, 25(6): 672-683. doi: 10.1007/s11769-015-0751-4

A Theoretical Framework and Methodology for Urban Activity Spatial Structure in E-society: Empirical Evidence for Nanjing City, China

doi: 10.1007/s11769-015-0751-4

1.
Department of Geography, the University of Hong Kong, Hong Kong 999077, China;
2.
School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China;
3.
Department of Urban Planning and Design, the University of Hong Kong, Hong Kong 999077, China;
4.
Department of Building and Real Estate, the Hong Kong Polytechnic University, Hong Kong 999077, China

Funds: Under the auspices of National Natural Science Foundation of China (No. 40971094)

More Information

Corresponding author: ZHEN Feng. E-mail: zhenfeng@nju.edu.cn
Received Date: 2014-08-04
Rev Recd Date: 2014-11-20
Publish Date: 2015-06-27

Abstract

The existing researches on the influence of information and communication technology (ICT) are mainly focused on human activity, whilst with few efforts on urban space. In the e-society, the widespread adoption of ICT devices not only affects almost every aspect of people's daily life and thereby reshapes the spatial development of regions and cities, but also generates a large amount of real-time activity data with location information. These georeferenced data, however, have relatively recently attracted attention from geographers. Adapted from Lynch's framework based on people's perceptions, this paper proposes a framework of urban spatial structure based on people's actual activity, including five elements, namely activity path, activity node, central activity zone (CAZ), activity district, and activity edge. In the empirical study, by using one week's check-in tweets (from February 25 to March 3 in 2013) collected in Nanjing City, the five elements are recognized and analyzed. Through the comparison between our results and urban spatial structure based on population (and land use), we argue that ICT uses: 1) lead to polarize, rather than to smooth, the urban structural hierarchy, due to the dual role of distance; 2) enable a partial decoupling of activity and activity space node, which challenges our conventional understanding of the role of home and the utility of travel; 3) blur the boundaries of activity districts and hence may play a positive role in enriching districts' functions, which should not be overlooked in the current urban transformation in China.
- information and communication technology (ICT),
- tele-activities,
- activity space,
- big data,
- e-society,
- Nanjing City

References

[1]	Aguilera A, 2008. Business travel and mobile workers. Transportation Research Part A: Policy and Practice, 42(8): 1109-1116. doi: 10.1016/j.tra.2008.03.005
[2]	Ahas R, Aasa A, Silm S et al., 2007. Mobile positioning in space-time behavior studies: Social positioning method experiments in Estonia. Cartography and Geographic Information Science, 34(4): 259-273. doi: 10.1559/1523040077823 82918
[3]	Alter A, 2012. Your E-Book Is Reading You. The Wall Street Journal, 19.
[4]	Andreev P, Salomon I, Pliskin N, 2010. Review: state of teleactivities. Transportation Research Part C: Emerging Technologies, 18(1): 3-20. doi: 10.1016/j.trc.2009.04.017
[5]	Atsmon Y, Magni M, 2010. China's Internet obsession. McKinsey Quarterly, 3: 1-3
[6]	Barabási A L, Albert R, 1999. Emergence of scaling in random networks. Science, 286(5439): 509-512. doi: 10.1126/science. 286.5439.509
[7]	Berk R, 2009. The role of race in forecasts of violent crime. Race and Social Problems, 1(4): 231-242. doi: 10.1007/s12552-009-9017-z
[8]	Cairncross F, 2001. The Death of Distance: How the Communications Revolution Will Change Our Lives. Boston: Harvard Business Press
[9]	Chai Yanwei, Zhao Ying, 2009. Recent development in Time Geography. Scientia Geographica Sinica, 29(4): 593-600. (in Chinese)
[10]	Clark C, 1951. Urban population densities. Journal of the Royal Statistical Society: Series A (General), 114(4): 490-496. doi: 10.2307/2981088
[11]	CNNIC (China Internet Network Information Center), 2013. The 31th Survey Report on Internet Development in China. Beijing: China Internet Network Information Center. Available at: http://www.cnnic.net.cn/ Retrieved June 20, 2013
[12]	Corbusier L, 1973. The Athens Charter. New York: Grossman publishers.
[13]	Couclelis H, 2009. Rethinking time geography in the information age. Environment and planning A, 41(7): 1556. doi: 10.1068/ a4151
[14]	Cui Gonghao, Wu Jin, 1990. The spatial structure and development of Chinese urban fringe. Acta Geographica Sinica, 45(4): 399-411. (in Chinese)
[15]	de Castro E A, Jensen-Butler C, 2003. Demand for information and communication technology-based services and regional economic development. Papers in Regional Science, 82(1): 27-50. doi: 10.1007/s101100200115
[16]	Dijst M, 2009. ICT and social networks: Towards a situational perspective on the interaction between corporeal and connected presence. The Expanding Sphere of Travel Behaviour Research. Bingley: Emerald Group Publishing Limited, pp. 45-75.
[17]	Ginsberg J, Mohebbi M H, Patel R S et al., 2008. Detecting influenza epidemics using search engine query data. Nature, 457(7232): 1012-1014. doi: 10.1038/nature07634
[18]	Graham S, Marvin S, 1996. Telecommunications and the City: Electronic Spaces, Urban Places. London: Routledge.
[19]	Graham M, Stephens M, Hale S, 2013. Featured graphic. Mapping the geoweb: a geography of Twitter. Environment and Planning A, 44(1): 100-102. doi: 10.1068/a45349
[20]	Hagerstrand T, 1970. What about people in regional science? Papers in Regional Science, 24(1): 7-24. doi: 10.1111/ j.1435-5597.1970.tb01464.x
[21]	Hilbert M, López P, 2011. The world's technological capacity to store, communicate, and compute information. Science, 332(6025): 60-65. doi: 10.1126/science.1200970
[22]	Hollenstein L, Purves R, 2013. Exploring place through user-generated content: Using Flickr tags to describe city cores. Journal of Spatial Information Science, (1): 21-48. doi: 10.5311/JOSIS.2010.1.3
[23]	Hsiao M H, 2009. Shopping mode choice: physical store shopping versus e-shopping. Transportation Research Part E: Logistics and Transportation Review, 45(1): 86-95. doi: 10. 1016/j.tre.2008.06.002
[24]	Johnston R J, Taylor P J, Watts M J, 2002. Geographies of Global Change: Remapping the World. Oxford: Blackwell Publishers.
[25]	Kenyon S, Lyons G, 2007. Introducing multitasking to the study of travel and ICT: examining its extent and assessing its potential importance. Transportation Research Part A: Policy and Practice, 41(2): 161-175. doi: 10.1016/j.tra.2006.02.004
[26]	Krings G, Calabrese F, Ratti C et al., 2009. Urban gravity: a model for inter-city telecommunication flows. Journal of Statistical Mechanics: Theory and Experiment, 2009(7): L07003. doi: 10.1088/1742-5468/2009/07/L07003
[27]	Kwan M P, 2006. Transport geography in the age of mobile communications. Journal of Transport Geography, 14(5): 384-385. doi: 10.1111/j.1467-9272.2007.00633.x
[28]	Kwan M P, 2007. Mobile communications, social networks, and urban travel: hypertext as a new metaphor for conceptualizing spatial interaction. The Professional Geographer, 59(4): 434-446. doi: 10.1111/j.1467-9272.2007.00633.x
[29]	Long Y, Liu X J, 2013. Featured graphic. How fixed is Beijing, China? A visual exploration of mixed land use. Environment and Planning A, 45(12): 2797-2798. doi: 10.1068/a130162g
[30]	Loo B P Y, 2012. The E-society. New York: Nova Science.
[31]	Lynch C, 2008. Big data: How do your data grow? Nature, 455(7209): 28-29. doi: 10.1038/455028a
[32]	Lynch K, 1960. The Image of the City. The MIT Press.
[33]	Lyons G, Jain J, Holley D, 2007. The use of travel time by rail passengers in Great Britain. Transportation Research Part A: Policy and Practice, 41(1): 107-120. doi: 10.1016/j.tra.2006. 05.012
[34]	Lyons G, Urry J, 2005. Travel time use in the information age. Transportation Research Part A: Policy and Practice, 39(2): 257-276. doi: 10.1016/j.tra.2004.09.004
[35]	Mayer-Schönberger V, Cukier K, 2013. Big Data: A Revolution That Will Transform How We Live. Work and Think. London: John Murray.
[36]	Mokhtarian P L, 1990. A typology of relationships between telecommunications and transportation. Transportation Research Part A: General, 24(3): 231-242. doi: 10.1016/0191-2607 (90)90060-J
[37]	Mokhtarian P L, 2004. A conceptual analysis of the transportation impacts of B2C e-commerce. Transportation, 31(3): 257-284. doi: 10.1023/B:PORT.0000025428.64128.d3
[38]	Mokhtarian P L, Salomon I, Handy S L, 2006. The impacts of ICT on leisure activities and travel: a conceptual exploration. Transportation, 33(3): 263-289. doi: 10.1007/s11116-005-2305-6
[39]	O'brien R, 1992. Global Financial Integration: the End of Geography. New York: Council on Foreign Relations Press.
[40]	Pendyala R M, Goulias K G, Kitamura R, 1991. Impact of telecommuting on spatial and temporal patterns of household travel. Transportation, 18(4): 383-409. doi: 10.1007/BF00186566
[41]	Salomon I, 1986. Telecommunications and travel relationships: a review. Transportation Research Part A: General, 20(3): 223-238. doi: 10.1016/0191-2607(86)90096-8
[42]	Schwanen T, Dijst M, KWAN M P, 2008. ICTs and the decoupling of everyday activities, space and time: Introduction. Tijdschrift voor Economische en Sociale Geografie, 99(5): 519-527. doi: 10.1111/j.1467-9663.2008.00489.x
[43]	Schwanen T, Kwan M P, 2008. The Internet, mobile phone and space-time constraints. Geoforum, 39(3): 1362-1377. doi: 10.1016/j.geoforum.2007.11.005
[44]	Shoval N, Isaacson M, 2007. Sequence alignment as a method for human activity analysis in space and time. Annals of the Association of American Geographers, 97(2): 282-297. doi: 10. 1111/j.1467-8306.2007.00536.x
[45]	Storper M, Venables A J, 2004. Buzz: face-to-face contact and the urban economy. Journal of Economic Geography, 4(4): 351-370. doi: 10.1093/jnlecg/lbh027
[46]	Wakamiya S, Lee R, Sumiya K, 2011. Urban area characterization based on semantics of crowd activities in twitter. In: GeoSpatial Semantics. Berlin: Springer Berlin Heidelberg, pp. 108-123.
[47]	Wang Bo, Zhen Feng, Xi Guangliang et al., 2013. A study of cybergeography based on micro-blog users' relationship: With a case of Sina micro-blog. Geographical Research, 32(2): 380-391. (in Chinese)
[48]	Wang Bo, Zhen Feng, Wei Zongcai, 2014. The research on characteristics of urban activity space in Nanjing: An empirical analysis based on big data. Human Geography, 29(3): 14-21, 55. (in Chinese)
[49]	Wang Xingzhong, 2004. China's Urban Living Spatial Structure. Beijing: Sicence Press. (in Chinese)
[50]	Wilson M W, Graham M, 2013. Situating neogeography. Environment and Planning A, 45(1): 3-9. doi: 10.1068/a44482
[51]	Wolch J R, Dear M J, 1989. The Power of Geography: How Territory Shapes Social Life. Boston: Uniwin Hyman.
[52]	Zhao Ying, Chai Yanwei, 2013. Residents' activity-travel behavior variation by communities in Beijing, China. Chinese Geographical Science, 23(4): 492-505. doi: 10.1007/s11769-013-0616-7
[53]	Zhen Feng, 2004. Regional Spatial Structure in the Information Age. Bejing: The Commercial Press. (in Chinese)
[54]	Zhen Feng, Wei Zongcai, 2008. Influence of information technology on social spatial behaviors of urban residents—Case of Nanjing City in China. Chinese Geographical Science, 18(4): 316-322. doi: 10.1007/s11769-008-0316-x
[55]	Zhen Feng, Wang Bo, Chen Yingxue, 2012. China's city network characteristics based on social network space: an empirical analysis of Sina Micro-blog. Acta Geographica Sinica, 67(8): 1031-1043. (in Chinese)
[56]	Zhou Suhong, Yan Xiaopei, 2005. Characteristics of Jobs-housing and organization in Guangzhou. Scientia Geographica Sinica, 25(6): 664-670. (in Chinese)
[57]	Zook M A, 2001. Old hierarchies or new networks of centrality? The global geography of the Internet content market. American Behavioral Scientist, 44(10): 1679-1696. doi: 10.1177/ 00027640121958113

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通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

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A Theoretical Framework and Methodology for Urban Activity Spatial Structure in E-society: Empirical Evidence for Nanjing City, China

1. Department of Geography, the University of Hong Kong, Hong Kong 999077, China;

2. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China;

3. Department of Urban Planning and Design, the University of Hong Kong, Hong Kong 999077, China;

4. Department of Building and Real Estate, the Hong Kong Polytechnic University, Hong Kong 999077, China

Funds: Under the auspices of National Natural Science Foundation of China (No. 40971094)

Corresponding author: ZHEN Feng. E-mail: zhenfeng@nju.edu.cn

Received Date: 2014-08-04

Rev Recd Date: 2014-11-20

Publish Date: 2015-06-27

Key words:

information and communication technology (ICT) /
tele-activities /
activity space /
big data /
e-society /
Nanjing City

Abstract: The existing researches on the influence of information and communication technology (ICT) are mainly focused on human activity, whilst with few efforts on urban space. In the e-society, the widespread adoption of ICT devices not only affects almost every aspect of people's daily life and thereby reshapes the spatial development of regions and cities, but also generates a large amount of real-time activity data with location information. These georeferenced data, however, have relatively recently attracted attention from geographers. Adapted from Lynch's framework based on people's perceptions, this paper proposes a framework of urban spatial structure based on people's actual activity, including five elements, namely activity path, activity node, central activity zone (CAZ), activity district, and activity edge. In the empirical study, by using one week's check-in tweets (from February 25 to March 3 in 2013) collected in Nanjing City, the five elements are recognized and analyzed. Through the comparison between our results and urban spatial structure based on population (and land use), we argue that ICT uses: 1) lead to polarize, rather than to smooth, the urban structural hierarchy, due to the dual role of distance; 2) enable a partial decoupling of activity and activity space node, which challenges our conventional understanding of the role of home and the utility of travel; 3) blur the boundaries of activity districts and hence may play a positive role in enriching districts' functions, which should not be overlooked in the current urban transformation in China.

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Reference (57)

[1]	Aguilera A, 2008. Business travel and mobile workers. Transportation Research Part A: Policy and Practice, 42(8): 1109-1116. doi: 10.1016/j.tra.2008.03.005
[2]	Ahas R, Aasa A, Silm S et al., 2007. Mobile positioning in space-time behavior studies: Social positioning method experiments in Estonia. Cartography and Geographic Information Science, 34(4): 259-273. doi: 10.1559/1523040077823 82918
[3]	Alter A, 2012. Your E-Book Is Reading You. The Wall Street Journal, 19.
[4]	Andreev P, Salomon I, Pliskin N, 2010. Review: state of teleactivities. Transportation Research Part C: Emerging Technologies, 18(1): 3-20. doi: 10.1016/j.trc.2009.04.017
[5]	Atsmon Y, Magni M, 2010. China's Internet obsession. McKinsey Quarterly, 3: 1-3
[6]	Barabási A L, Albert R, 1999. Emergence of scaling in random networks. Science, 286(5439): 509-512. doi: 10.1126/science. 286.5439.509
[7]	Berk R, 2009. The role of race in forecasts of violent crime. Race and Social Problems, 1(4): 231-242. doi: 10.1007/s12552-009-9017-z
[8]	Cairncross F, 2001. The Death of Distance: How the Communications Revolution Will Change Our Lives. Boston: Harvard Business Press
[9]	Chai Yanwei, Zhao Ying, 2009. Recent development in Time Geography. Scientia Geographica Sinica, 29(4): 593-600. (in Chinese)
[10]	Clark C, 1951. Urban population densities. Journal of the Royal Statistical Society: Series A (General), 114(4): 490-496. doi: 10.2307/2981088
[11]	CNNIC (China Internet Network Information Center), 2013. The 31th Survey Report on Internet Development in China. Beijing: China Internet Network Information Center. Available at: http://www.cnnic.net.cn/ Retrieved June 20, 2013
[12]	Corbusier L, 1973. The Athens Charter. New York: Grossman publishers.
[13]	Couclelis H, 2009. Rethinking time geography in the information age. Environment and planning A, 41(7): 1556. doi: 10.1068/ a4151
[14]	Cui Gonghao, Wu Jin, 1990. The spatial structure and development of Chinese urban fringe. Acta Geographica Sinica, 45(4): 399-411. (in Chinese)
[15]	de Castro E A, Jensen-Butler C, 2003. Demand for information and communication technology-based services and regional economic development. Papers in Regional Science, 82(1): 27-50. doi: 10.1007/s101100200115
[16]	Dijst M, 2009. ICT and social networks: Towards a situational perspective on the interaction between corporeal and connected presence. The Expanding Sphere of Travel Behaviour Research. Bingley: Emerald Group Publishing Limited, pp. 45-75.
[17]	Ginsberg J, Mohebbi M H, Patel R S et al., 2008. Detecting influenza epidemics using search engine query data. Nature, 457(7232): 1012-1014. doi: 10.1038/nature07634
[18]	Graham S, Marvin S, 1996. Telecommunications and the City: Electronic Spaces, Urban Places. London: Routledge.
[19]	Graham M, Stephens M, Hale S, 2013. Featured graphic. Mapping the geoweb: a geography of Twitter. Environment and Planning A, 44(1): 100-102. doi: 10.1068/a45349
[20]	Hagerstrand T, 1970. What about people in regional science? Papers in Regional Science, 24(1): 7-24. doi: 10.1111/ j.1435-5597.1970.tb01464.x
[21]	Hilbert M, López P, 2011. The world's technological capacity to store, communicate, and compute information. Science, 332(6025): 60-65. doi: 10.1126/science.1200970
[22]	Hollenstein L, Purves R, 2013. Exploring place through user-generated content: Using Flickr tags to describe city cores. Journal of Spatial Information Science, (1): 21-48. doi: 10.5311/JOSIS.2010.1.3
[23]	Hsiao M H, 2009. Shopping mode choice: physical store shopping versus e-shopping. Transportation Research Part E: Logistics and Transportation Review, 45(1): 86-95. doi: 10. 1016/j.tre.2008.06.002
[24]	Johnston R J, Taylor P J, Watts M J, 2002. Geographies of Global Change: Remapping the World. Oxford: Blackwell Publishers.
[25]	Kenyon S, Lyons G, 2007. Introducing multitasking to the study of travel and ICT: examining its extent and assessing its potential importance. Transportation Research Part A: Policy and Practice, 41(2): 161-175. doi: 10.1016/j.tra.2006.02.004
[26]	Krings G, Calabrese F, Ratti C et al., 2009. Urban gravity: a model for inter-city telecommunication flows. Journal of Statistical Mechanics: Theory and Experiment, 2009(7): L07003. doi: 10.1088/1742-5468/2009/07/L07003
[27]	Kwan M P, 2006. Transport geography in the age of mobile communications. Journal of Transport Geography, 14(5): 384-385. doi: 10.1111/j.1467-9272.2007.00633.x
[28]	Kwan M P, 2007. Mobile communications, social networks, and urban travel: hypertext as a new metaphor for conceptualizing spatial interaction. The Professional Geographer, 59(4): 434-446. doi: 10.1111/j.1467-9272.2007.00633.x
[29]	Long Y, Liu X J, 2013. Featured graphic. How fixed is Beijing, China? A visual exploration of mixed land use. Environment and Planning A, 45(12): 2797-2798. doi: 10.1068/a130162g
[30]	Loo B P Y, 2012. The E-society. New York: Nova Science.
[31]	Lynch C, 2008. Big data: How do your data grow? Nature, 455(7209): 28-29. doi: 10.1038/455028a
[32]	Lynch K, 1960. The Image of the City. The MIT Press.
[33]	Lyons G, Jain J, Holley D, 2007. The use of travel time by rail passengers in Great Britain. Transportation Research Part A: Policy and Practice, 41(1): 107-120. doi: 10.1016/j.tra.2006. 05.012
[34]	Lyons G, Urry J, 2005. Travel time use in the information age. Transportation Research Part A: Policy and Practice, 39(2): 257-276. doi: 10.1016/j.tra.2004.09.004
[35]	Mayer-Schönberger V, Cukier K, 2013. Big Data: A Revolution That Will Transform How We Live. Work and Think. London: John Murray.
[36]	Mokhtarian P L, 1990. A typology of relationships between telecommunications and transportation. Transportation Research Part A: General, 24(3): 231-242. doi: 10.1016/0191-2607 (90)90060-J
[37]	Mokhtarian P L, 2004. A conceptual analysis of the transportation impacts of B2C e-commerce. Transportation, 31(3): 257-284. doi: 10.1023/B:PORT.0000025428.64128.d3
[38]	Mokhtarian P L, Salomon I, Handy S L, 2006. The impacts of ICT on leisure activities and travel: a conceptual exploration. Transportation, 33(3): 263-289. doi: 10.1007/s11116-005-2305-6
[39]	O'brien R, 1992. Global Financial Integration: the End of Geography. New York: Council on Foreign Relations Press.
[40]	Pendyala R M, Goulias K G, Kitamura R, 1991. Impact of telecommuting on spatial and temporal patterns of household travel. Transportation, 18(4): 383-409. doi: 10.1007/BF00186566
[41]	Salomon I, 1986. Telecommunications and travel relationships: a review. Transportation Research Part A: General, 20(3): 223-238. doi: 10.1016/0191-2607(86)90096-8
[42]	Schwanen T, Dijst M, KWAN M P, 2008. ICTs and the decoupling of everyday activities, space and time: Introduction. Tijdschrift voor Economische en Sociale Geografie, 99(5): 519-527. doi: 10.1111/j.1467-9663.2008.00489.x
[43]	Schwanen T, Kwan M P, 2008. The Internet, mobile phone and space-time constraints. Geoforum, 39(3): 1362-1377. doi: 10.1016/j.geoforum.2007.11.005
[44]	Shoval N, Isaacson M, 2007. Sequence alignment as a method for human activity analysis in space and time. Annals of the Association of American Geographers, 97(2): 282-297. doi: 10. 1111/j.1467-8306.2007.00536.x
[45]	Storper M, Venables A J, 2004. Buzz: face-to-face contact and the urban economy. Journal of Economic Geography, 4(4): 351-370. doi: 10.1093/jnlecg/lbh027
[46]	Wakamiya S, Lee R, Sumiya K, 2011. Urban area characterization based on semantics of crowd activities in twitter. In: GeoSpatial Semantics. Berlin: Springer Berlin Heidelberg, pp. 108-123.
[47]	Wang Bo, Zhen Feng, Xi Guangliang et al., 2013. A study of cybergeography based on micro-blog users' relationship: With a case of Sina micro-blog. Geographical Research, 32(2): 380-391. (in Chinese)
[48]	Wang Bo, Zhen Feng, Wei Zongcai, 2014. The research on characteristics of urban activity space in Nanjing: An empirical analysis based on big data. Human Geography, 29(3): 14-21, 55. (in Chinese)
[49]	Wang Xingzhong, 2004. China's Urban Living Spatial Structure. Beijing: Sicence Press. (in Chinese)
[50]	Wilson M W, Graham M, 2013. Situating neogeography. Environment and Planning A, 45(1): 3-9. doi: 10.1068/a44482
[51]	Wolch J R, Dear M J, 1989. The Power of Geography: How Territory Shapes Social Life. Boston: Uniwin Hyman.
[52]	Zhao Ying, Chai Yanwei, 2013. Residents' activity-travel behavior variation by communities in Beijing, China. Chinese Geographical Science, 23(4): 492-505. doi: 10.1007/s11769-013-0616-7
[53]	Zhen Feng, 2004. Regional Spatial Structure in the Information Age. Bejing: The Commercial Press. (in Chinese)
[54]	Zhen Feng, Wei Zongcai, 2008. Influence of information technology on social spatial behaviors of urban residents—Case of Nanjing City in China. Chinese Geographical Science, 18(4): 316-322. doi: 10.1007/s11769-008-0316-x
[55]	Zhen Feng, Wang Bo, Chen Yingxue, 2012. China's city network characteristics based on social network space: an empirical analysis of Sina Micro-blog. Acta Geographica Sinica, 67(8): 1031-1043. (in Chinese)
[56]	Zhou Suhong, Yan Xiaopei, 2005. Characteristics of Jobs-housing and organization in Guangzhou. Scientia Geographica Sinica, 25(6): 664-670. (in Chinese)
[57]	Zook M A, 2001. Old hierarchies or new networks of centrality? The global geography of the Internet content market. American Behavioral Scientist, 44(10): 1679-1696. doi: 10.1177/ 00027640121958113

A Theoretical Framework and Methodology for Urban Activity Spatial Structure in E-society: Empirical Evidence for Nanjing City, China

doi: 10.1007/s11769-015-0751-4

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