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Measuring Interaction in Workplaces

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Architecture and Interaction

Part of the book series: Human–Computer Interaction Series ((HCIS))

Abstract

Interactions in the workplace have long been studied by the architectural research community, however, in the past, the majority of those contributions focused on single case studies. Drawing on a much larger empirical sample of 27 offices, this chapter aims at establishing a baseline of understanding how the physical structure of office buildings shapes human behaviours of interaction. This may form a foundation for the Human-Computer Interaction (HCI) community to investigate the impact of embedded computer technology on human behaviours inside buildings. Methods of data collection included an analysis of floor plans with Space Syntax techniques and direct observations of space usage patterns. Exploring this data, different patterns emerged: interactions appeared unevenly distributed in space; interaction rates as well as preferences for locations varied by industry; spatial configuration appeared to create affordances for interaction, since unplanned interactions outside of meeting rooms tended to cluster in more visually connected areas of the office; in addition, seven different micro-behaviours of interaction were identified, each of them driven by affordances in both the built environment and the presence of other people; last but not least, locations for interactions showed clear time-space routines. The chapter closes with interpretations of the results, reflecting on the problem of predictability and how these insights could be useful for evidence-based design, but also the HCI community. It also gives an outlook on future developments regarding the constant logging of human behaviours in offices with emerging technologies.

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Notes

  1. 1.

    The leaked internal Yahoo memo is documented here: http://allthingsd.com/20130222/physically-together-heres-the-internal-yahoo-no-work-from-home-memo-which-extends-beyond-remote-workers/ (Last accessed: 01 April 2015)

  2. 2.

    It should be noted that, while we have used the categorisation of space based on the organisation’s use of their buildings, an unsupervised analysis would also be possible, and from this, cluster analyses or unsupervised machine learning methods (such as Self Organising Maps, originally detailed in Kohonen 1998) could generate those categories organically; this is a subject of ongoing research.

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Acknowledgments

This research was partially funded by Innovate UK under the Knowledge Transfer Partnership Scheme (KTP8978 ‘Big Data in the Office’ by UCL and Spacelab, February 2013 – February 2015).

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Authors and Affiliations

  1. Space Syntax Laboratory, The Bartlett School of Architecture, University College London, 140 Hampstead Road, London, NW1 2BX, UK

    Kerstin Sailer & Petros Koutsolampros

  2. Centre for Advanced Spatial Analysis (CASA), The Bartlett School of Architecture, University College London, 90 Tottenham Court Road, London, W1T 4TJ, UK

    Martin Zaltz Austwick & Andy Hudson-Smith

  3. The Bartlett School of Architecture, University College London, Gower Street, WC1E 6BT, London, UK

    Tasos Varoudis

Authors
  1. Kerstin Sailer
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  2. Petros Koutsolampros
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  3. Martin Zaltz Austwick
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  4. Tasos Varoudis
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  5. Andy Hudson-Smith
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Corresponding author

Correspondence to Kerstin Sailer .

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Editors and Affiliations

  1. Dept of Comp Sci & Digi Tech, University of Northumbria, Newcastle upon Tyne, United Kingdom

    Nicholas S. Dalton

  2. Mixed Reality Laboratory,Dep of Comp Sc, University of Nottingham, Nottingham, United Kingdom

    Holger Schnädelbach

  3. Department of Informatics, Umeå University, Umeå, Sweden

    Mikael Wiberg

  4. The Bartlett School of Architecture, University College London, London, United Kingdom

    Tasos Varoudis

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Sailer, K., Koutsolampros, P., Zaltz Austwick, M., Varoudis, T., Hudson-Smith, A. (2016). Measuring Interaction in Workplaces. In: Dalton, N., Schnädelbach, H., Wiberg, M., Varoudis, T. (eds) Architecture and Interaction. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-30028-3_7

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  • DOI: https://doi.org/10.1007/978-3-319-30028-3_7

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  • Online ISBN: 978-3-319-30028-3

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