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Complexity in daily life – a 3D-visualization showing activity patterns in their contexts

Author

Listed:
  • Kajsa Ellegård

    (Technology and social change, Linköping University)

  • Matthew Cooper

    (Department of Science and Technology, University of Linköping, Campus Norrköping)

Abstract

This article attacks the difficulties to make well informed empirically grounded descriptions and analyses of everyday life activity patterns. At a first glance, everyday life seems to be very simple and everybody has experiences from it, but when we try to investigate it from a scientific perspective, its complexity is overwhelming. There are enormous variations in interests and activity patterns among individuals, between households and socio-economic groups in the population. Therefore, and in spite of good intentions, traditional methods and means to visualize and analyze often lead to over-simplifications. The aim of this article is to present a visualization method that might inspire social scientists to tackle the complexity of everyday life from a new angle, starting with a visual overview of the individual's time use in her daily life, subsequently aggregating to time use in her household, further at group and population levels without leaving the individual out of sight. Thereby variations and complexity might be treated as assets in the interpretation rather than obstacles. To exemplify the method we show how activities in a daily life project are distributed among household members and between men and women in a population.

Suggested Citation

  • Kajsa Ellegård & Matthew Cooper, 2004. "Complexity in daily life – a 3D-visualization showing activity patterns in their contexts," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 1(1), pages 37-59, August.
    • Handle: RePEc:leu:journl:2004:vol1:p37-59
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    References listed on IDEAS

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    1. anonymous, 2003. "Focus on Authors," Marketing Science, INFORMS, vol. 22(3), pages 435-436.
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    Cited by:

    1. Sandels, C. & Widén, J. & Nordström, L., 2014. "Forecasting household consumer electricity load profiles with a combined physical and behavioral approach," Applied Energy, Elsevier, vol. 131(C), pages 267-278.
    2. Ellegård, Kajsa & Palm, Jenny, 2011. "Visualizing energy consumption activities as a tool for making everyday life more sustainable," Applied Energy, Elsevier, vol. 88(5), pages 1920-1926, May.
    3. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
    4. Widén, Joakim & Wäckelgård, Ewa, 2010. "A high-resolution stochastic model of domestic activity patterns and electricity demand," Applied Energy, Elsevier, vol. 87(6), pages 1880-1892, June.
    5. Mattioli, Giulio & Anable, Jillian & Vrotsou, Katerina, 2016. "Car dependent practices: Findings from a sequence pattern mining study of UK time use data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 56-72.

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    More about this item

    Keywords

    household division of labour; time-geography; 3D method; visualization; diaries; everyday life; activity patterns. Complexity in daily life – a 3D-visualization showing activity patterns in their contexts;
    All these keywords.

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • P46 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Consumer Economics; Health; Education and Training; Welfare, Income, Wealth, and Poverty
    • R29 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Other

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