Preferred citation style Axhausen, K.W. (2006) Social network geographies, activity spaces and travel: Initial hypotheses and empirical results, Department of Sociology, University of Stockholm, Stockholm, September 2006. 1
Social network geographies, activity spaces and travel: Initial hypotheses and empirical results KW Axhausen IVT ETH Zürich September 2006
Part 1: Hypotheses 3
Markets: Time-scaled road -Switzerland (1950 & 2000) Axhausen and Hurni, 2005 4
Markets: Price deflation for cars 1400 Qualitätsbereinigter Preisindex (2004 = 100) [%] 1200 1000 800 600 400 200 Frei, 2004 Raff und Trajtenberg, 1990 Frei, 2005 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 Jahr 5
Markets: Price deflation for telecommunication 2000 1750 US International and interstate average revenue per minute Index [1995 = 100] 1500 1250 1000 750 500 250 FCC (2001) 0 1930 1940 1950 1960 1970 1980 1990 2000 Year 6
Example: Commuter sheds of the 10 largest Swiss towns Botte, 2003 7
Example of a local activity space Schönfelder 12000761 Female, 24 Full time Single 216 trips / 6 weeks 8
Example of a social network geography Ohnmacht, 2004 Female, 28, 4 moves, Public transport user 9
Example: Biography of an architect 10 Larsen, Urry and Axhausen, 2006
How to explain travel? Budget constraints Capability constraints Generalised costs of the schedule Generalised cost of travel Generalised cost of activity participation Risk and comfort-adjusted weighted sums of time, expenditure and social content 11
Number of accompanying travellers (2003 Thurgau) Short vacation Excursion: nature Other Excursion: culture Meeting friends Further education (leisure) Garden/ cottage Voluntary work Disco, pub, restaurant, cinema Meeting relatives/family Window shopping Pick up/drop off/attendance Group/club meeting Family duty Cemetery Active sports Education Long-term shopping Walk or stroll Daily shopping Private business Private business (doctor,... Work Household members travelling along Other persons travelling along Dog travelling along 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Mean 12
How to understand the traveller? Personal worlds of others Social captial: stock of joint abilities, shared histories and commitments Personal world Biography Projects Learning Household locations Social network geography Mobility tools 13
Size of activity spaces: A hypothesis Specialisation Migration Wages - Activities Fleet comfort Housing consumption - vtts et al. Tours - vkm pkm - k - Energy costs Activity space - Elasticity > 0 Elasticity < 0 k: personal short term generalised costs of travel 14
Definition of a social network The topology of a social network describes Which person/firm (node) is linked to which other persons/firms By contacts (links) of a certain quality (impedance or cost) Closeness ~ 1/Impedance 15
Travel and social networks Maintenance of the network requires: Face to face contacts Balanced by other forms of contacts Travel ~ Physical spread of the contacts Trade-off between loosing contacts and social capital and investing in new contacts closer to home 16
Hypotheses Message costs - - k - - - Number of networks Migration - - - Network geography Professional activity space Personal activity space Left skew of intensity distribution Network overlap - Local anomie - Elasticity > 0 Elasticity < 0 17
Expected impacts: Spare versus dense networks 18
Expected impacts: Spare versus dense networks Scales could be different! 19
Expected impacts: Improved welfare The social networks should be more homogeneous and therefore more productive for their members But, the selectivity excludes the less attractive persons who are disadvantaged through a reduced ability to travel or a reduced ability to participate in activities But, the dependence on commercial or state-provided services for care increases 20
Data needs Measurement of the activity spaces (geographies, markets) Estimate of historical activity spaces (Local) level of trust Strength and object of attachment to a locality 21
Part 2: Survey work 22
Contributors ifmo, Berlin T. Ohnmacht, A Frei and KW Axhausen UK DfT J Larsen, J Urry and KW Axhausen COST 355/ifmo A. Frei and KW Axhausen 23
Items to capture social content Detailed purpose coding Social purpose and obligations fulfilled with it Beneficiaries of the activity Composition of the party Prior locations Distribution of the travel and activity costs Planning horizon Number of previous visits to that location Secondary activities 24
Items to capture the social network geographies Name generators Name interpreters Type and length of contact Frequency by mode of contact Home location Second homes Detailed descriptions of face-to-face contacts 25
Contact frequencies: E-Mail messages to kwa 26
Items to characterise the mobility biography Home and second home locations Work and school locations Household composition Mobility tools Main mode (to work/school) (Major holidays) Personal income Household income 27
Response burden and response rate Response rate [%] 80.00 60.00 40.00 20.00 No recruitment, but telephone motivation call No recruitment, no telephone motivation call Recruited during a prior CAPI interview 0.00 0 200 400 600 800 1000 1200 Ex-ante estimate of response burden [Points] 28
Zürich experiment: Response behaviour Phase Pretest On-going main study Share of total Sample 150 2 400 100% Share of reached by phone Wrong address 0 28 1.2% Not reachable by phone 36 706 29.4% Reached by phone 113 1 673 69.7% 100% Recruited 14 179 7.5% 10.7% Interviewed 13 172 7.2% 10.3% Post-interview questionnaire returned 13 154 6.4% 9.2% 29
Data available ifmo: Persons with whom you had contact (f-to-f frequency, location, mobility biography) DfT: Family, non-local friends, most important persons (location, frequency by mode, mobility biography) COST 355: Important people, people with leisure contacts (location, frequency by mode, mobility biography) 30
Contacts 31
Poisson regression of the number of social contacts Variable Mean St. dev Beta Standardised beta Sign. Constant - - 3.753-0.000 Age [years] 45.68 19.08-0.051-0.124 0.000 Age 2 /1000 [years 2 /1000] 2.44 0.09 0.401 0.102 0.000 Data_horizon [y/n] 0.19 0.39-0.289-0.015 0.000 Data_COST 355 [y/n] 0.57 0.50-0.256-0.016 0.000 Number of relocations [n] 5.82 2.74 0.037 0.013 0.000 University degree [y/n] 0.28 0.45 0.116 0.007 0.045 N 128 Adjusted R 2 0.16 32
Distance distribution between home locations 80 60 Frequency 40 20 0 0 1 10 100 Distance 1'000 10'000 100'000 33
Distance by type of contact 10'000 Type of contact Others Friends Family Work mates Mean Distance 1'000 100 10 Up to monthly Monthly Biweekly Weekly More then weekly Face to face (grouped) 34
Contact frequency by mode 140 120 Electronic contacts Face-to-face contacts Mean annual frequency 100 80 60 40 20 0 1 10 100 1000 10000 100000 Mean distance in the decile [km] 35
Market share by contact mode Average contacts per year 60% 50% 40% 30% 20% 10% Face-to-face (Female) Email (Female) Face-to-face (Male) Email (Male) Phone (Female) SMS (Female) Phone (Male) SMS (Male) 0% 0 100 200 300 400 500 600 700 800 Median distance of the quartile [km] 36
Probit results Variable Category Age -.004.004.006 -.007 Market shares of contact modes Face-toface Phone Email SMS Sex: Male -.127 -.624 -.526 Educatio Compulsory school -.251.186.306 -.481 Apprenticeship -.171.254 -.278.086 Baccalaureat Reference Reference Reference Reference Professional tertiary -.384.329.106 -.092 University degree -.628.915 - -.587 Type of Others and friends.197 -.625-2.126 -.459 contact Family and partner - -.402-2.344 -.355 Work mates.600-1.055-1.907 -.779 Ln (distance) -.108 -.132 0.31 Income.028 -.048.075 -.053 Income * Male.048 -.021 -.138.106 Adjusted R 2 /Chi 2 10046 10235 13548 11690 N 381 381 381 381 37
Size distribution of the social geographies 20 15 Frequency 10 5 0 1E2 1E3 1E4 1E5 1E6 1E7 1E8 1E9 95% Confidence ellipse of the social network geography Japan: 378; U.S.A: 9 629 [10 3 km 2 ] 38
Tobit results Variable Mean St. dev Beta Standardised beta Sign. Data_ifmo [y/n] 0.26 0.43 2.309 0.184 0.048 Male [y/n] 0.57 0.50 2.293 0.212 0.021 Age [years] 44.72 18.92-0.078-0.277 0.002 University degree [y/n] 0.28 0.45 2.286 0.192 0.047 Car ownership [y/n] 0.52 0.50 3.842 0.358 0.000 Annual or monthly public transport ticket [y/n] 0.90 0.32 6.585 0.398 0.000 Number of relocations [n] 5.87 2.74 0.634 0.325 0.000 N 117 Adjusted R 2 0.48 39
Assessment: Survey work Combined face-to-face interviews and self administered questionnaire an expensive but practicable survey method Respondents participation is very selective Small number of contacts (See Connected Lives Study in Toronto for larger numbers) Detailed information on meetings still missing in this protocol 40
Results from the initial models Biography has an impact on the number of contacts given Strong distance decay of contact frequency Strong distance and income effects on contact mode share Biography affects the size of network geography 41
Part 3 42
Research issues Measurement of the activity spaces (geographies, markets) Number and kind of contacts Measurement methods Estimate of historical activity spaces Use of written or electronic records Taste differences in network form and geography Social/cultural preferences for network form and geography Stability of the geographies under pressure Elasticities to policy (or environmental) change 43
Policy questions Is happiness still growing? How large are the social externalities? How stable is the overall system under pressure? 44
Appendix 45
References Axhausen, K.W. (2003) Social networks and travel: Some hypotheses, Arbeitsberichte Verkehr- und Raumplanung, 197, Institut für Verkehrsplanung und Transportsysteme (IVT), ETH Zürich, Zürich. Axhausen, K.W., A. Frei and T. Ohnmacht (2006) Networks, biographies and travel: First empirical and methodological results, Vortrag, 11th International Conference on Travel Behaviour Research, Kyoto, August 2006. Axhausen, K.W. and L. Hurni (eds.)(2005) Zeitkarten Schweiz 1950-2000, IVT and IKA, ETH Zürich, Zürich. Botte, M. (2003) Strukturen des Pendelns in der Schweiz, Diplomarbeit, Fakultät für Bauingenieurwesen, TU Dresden, August 2003. FCC (2001) Long distance telecommunication industry, FCC, Washington, D.C. Larsen, J., J. Urry and K.W. Axhausen (2006) Mobilities, Networks, Geographies, Ashgate, Aldershot. Ohnmacht, T. (2004) Soziale Netze und persönliche Mobilität: Grundlagen für eine empirische Erhebung, Arbeitsbericht Verkehrs- und Raumplanung, 250, IVT, ETH Zürich, Zürich. Rai, R.K., M. Balmer, M. Rieser, V.S. Vaze, S. Schönfelder and K.W. Axhausen (2006) Capturing human activity spaces: New geometries, Arbeitsberichte Verkehrs- und Raumplanung, 378, IVT, ETH Zürich, Zürich. 46
Social networks: Hypotheses [1] The size of the social network geography is inversely proportional to the generalised costs of travel and communication [2] The number of contacts individuals maintain is inversely proportional to the generalised costs of travel and communication [3] The probability of being linked to a member of one s network through multiple networks increases with the spatial density of one s contacts [4] The distribution of effort on non-household members will become more left skewed as the spatial social network tightness decreases [5] The knowledge about the contacts of contacts in a social network is proportional to the generalised costs of travel and communication 47
Social networks: Hypotheses (2) [6] The activity space of an individual is proportional to its social network geography [7a] The size of the local activity space of an individual stabilises after an initial exploration. [7b] The size of the total activity space will grow in line with the growth of social network geographies. [8] The reliance on commercial or publicly funded personal services increases proportionally with the geography of social networks [9] The welfare of the individuals should increase inversely proportional to the generalised costs of travel 48
Measurement approaches: Inclusion geometries 280000 home location shop location shop cassini shop bean shop superellipse shop ellipse y coordinate 275000 270000 Rai et al., 2006 265000 700000 705000 710000 715000 720000 x coordinate 49