Analysis of social networks, social interactions, and out-of-home leisure activity generation: Evidence from Japan

Abstract

This article analyses the connection between social networks, social interactions and out-of-home leisure activity generation in the context of Japanese society. A multilevel structural equation modelling approach is used to account for the hierarchical structure of the data. At the ego-alter (self-other) level, results suggest the existence of a complementary effect between face to face interaction and ICT contact propensity that becomes a substitution effect given increasing distance between egos and alters. Furthermore, a mediating effect by face to face interaction between ICT contact propensity and distance was observed. At the ego (self) level, urbanization level, income, network size and club membership were found to have a direct positive effect on leisure propensity and indirectly on ICT contact propensity, while an extraverted personality was positively associated with higher ICT contact propensity.

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Notes

  1. 1.

    Results from the 2011 Survey on Time Use and Leisure Activities shows that on average, Japanese spend 9% of all their free time explicitly socializing. This figure; however, excludes time spent in hobbies (17%), and sports (7%), or meals (defined as maintenance task), for which no information is provided on companionship).

  2. 2.

    If ego is in the lower half of the cohort, match includes cohort below; if ego is in the upper half of the cohort, match includes cohort above.

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Acknowledgements

This study was supported by JSPS KAKENHI Grant No. 23246091 and The University of Tokyo’s Excellent Graduate Schools (EGS) Support Fund for Young Researchers Grant No. T10027. All spatial data used for the analysis presented in this article were provided by the Center for Spatial Information Science of The University of Tokyo. CSIS joint research No. 479.

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Correspondence to Giancarlos Troncoso Parady.

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Appendix: Built environment sensitivity analysis

Appendix: Built environment sensitivity analysis

A sensitivity analysis on the effect of the built environment was conducted in order to evaluate possible modifiable areal unit problem (MAUP) effects. Although given the way the urbanization level variable was estimated, zoning and scale problems are to some extent controlled for, the optimal scale of analysis is in practice not known. Similar to Guo et al. (2010) Radial network neighbourhoods were operationalized. In addition, a fourth scale of analysis is used where a weight is assigned to surroundings areas as a function of distance from each unit centroid via a kernel density function, so that closer locations are given more importance than more distant ones (See Fig. 6).

Fig. 6
figure6

Diagram of scale definitions used for sensitivity analysis

As shown in Table 7, results are rather stable. At all scales, the direction of the effect is consistent, although the precision of the estimates differ by analysis scale, with the fourth scale having somewhat low t-statistic, suggesting some sensitivity to the analysis unit used.

Table 7 Sensitivity analysis of the built environment effect

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Parady, G., Katayama, G., Yamazaki, H. et al. Analysis of social networks, social interactions, and out-of-home leisure activity generation: Evidence from Japan. Transportation 46, 537–562 (2019). https://doi.org/10.1007/s11116-018-9873-8

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Keywords

  • Social networks
  • Leisure activity generation
  • Social interaction
  • Information and communication technologies
  • Multilevel modelling