Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-26T22:28:44.813Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessing Social Behaviour Towards Near-Body Product Users in the Wild: A Review of Methods

Published online by Cambridge University Press:  26 May 2022

M. De Boeck ,
J. Vleugels ,
D. Van Rooy  and
K. Vaes
M. De Boeck*
Affiliation:
University of Antwerp, Belgium
J. Vleugels
Affiliation:
University of Antwerp, Belgium
D. Van Rooy
Affiliation:
University of Antwerp, Belgium
K. Vaes
Affiliation:
University of Antwerp, Belgium
*
[email protected]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Prior to wide adoption, a product must find social approval, which is especially true for near-body products as they are considered part of the human body. Based on a theoretical foundation, this study aims to provide an overview of methods to assess natural behaviour towards users of visible near-body products in uncontrolled environments, i.e. in the wild. Approaching the matter from a product design perspective, this article is primarily intended for designers of near-body products who wish to gain insights into the social behaviour of people towards users wearing their design proposals.

Keywords

social acceptanceresearch methodologies and methodsnear-body productshuman-centred designhuman behaviour
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 2097 - 2106
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

References

Al-naimi, I. and Wong, C.B. (2017), “Indoor Human Detection and Tracking Using Advanced Smart floor”, ICICS 2017, IEEE.Google Scholar
Andersen, P.A. (2016), “Eye Behavior”, The Int. Encyclopedia of Interpersonal Communication, pp. 1–7, https://dx.doi.org/10.1002/9781118540190.wbeic0152.Google Scholar
Aziz, H. (2017), “Comparison between Field Research and Controlled Laboratory Research”, Archives of Clinical and Biomedical Research, Vol. 01 No. 02, pp. 101–104, https://dx.doi.org/10.26502/acbr.50170011.CrossRefGoogle Scholar
Bakhshian, S. and Lee, Y. (2020), “Influence of Social Acceptability and Product Attributes on Consumers’ Attitude and Intention of Using Smart Apparel”, ITAA Proceedings, pp. 4–7, doi: https://dx.doi.org/10.31274/itaa.11849.Google Scholar
Baumeister, R. and Bushman, B. (2014), Social Psychology and Human Nature, Belmont, Boston USA.Google Scholar
Baumeister, R.F., Vohs, K.D., Nathan DeWall, C. and Zhang, Liqing. (2007), “How Emotion Shapes Behavior: Feedback, Anticipation, and Reflection, Rather Than Direct Causation”, Personality and Social Psychology Review, Vol. 11 No. 2, pp. 167–203, https://dx.doi.org/10.1177/1088868307301033.CrossRefGoogle ScholarPubMed
Belk, R.W. (1988), “Possessions and the Extended Self”, Journal of Consumer Research, Vol. 15 No. September.CrossRefGoogle Scholar
Birdwhistell, R. (1955), “Background to kinesics”, ETC: A Review of General Semantics, Vol. 13 No. 1, pp. 10–18.Google Scholar
Boolani, A., Sur, S., Yang, D., Avolio, A., Goodwin, A., Mondal, S., Fulk, G., et al. . (2021), “Six Minutes of Physical Activity Improves Mood in Older Adults: A Pilot Study”, Journal of Geriatric Physical Therapy, Vol. 44 No. 1, pp. 18–24, https://dx.doi.org/10.1519/JPT.0000000000000233.CrossRefGoogle ScholarPubMed
Carpendale, S. (2008), “Evaluating information visualizations”, Information Visualization, Springer-Verlag, Berlin Heidelberg, pp. 19–45, https://dx.doi.org/10.1007/978-3-540-70956-5.Google Scholar
Cosco, N.G., Moore, R.C. and Islam, M.Z. (2010), “Behavior Mapping: A Method for Linking Preschool Physical Activity and Outdoor Design”, Journal of the American College of Sports Medicine, pp. 513–519, https://dx.doi.org/10.1249/MSS.0b013e3181cea27a.Google ScholarPubMed
Desmet, P. (2003a), “From disgust to desire: how products elicit emotions”, Design and Emotion, No. May, pp. 8–12, https://dx.doi.org/10.1201/9780203608173-c2.CrossRefGoogle Scholar
Desmet, P. (2003b), “Measuring emotion: development and application of an instrument to measure emotional responses to products”, Funology. Human-Computer Interaction Series, Springer, Dordrecht, pp. 111–123, doi: 10.1007/1-4020-2967-5_12.CrossRefGoogle Scholar
DeWall, C.N., Baumeister, R.F., Chester, D.S. and Bushman, B.J. (2016), “How often does currently felt emotion predict social behavior and judgment? A meta-analytic test of two theories”, Emotion Review, Vol. 8 No. 2, pp. 136–143, https://dx.doi.org/10.1177/1754073915572690.Google Scholar
Dharmawan, V. and Rachmaniyah, N. (2019), “Spatial behavior pattern of visitors in City Park Case study: Flora and Bungkul Park, Indonesia”, ICEAT 2019, Vol. 821, https://dx.doi.org/10.1088/1757-899X/821/1/012006.Google Scholar
Dols, J.M.F. and Russell, J.A. (2017), The Science of Facial Expression, Oxford University Press.Google Scholar
Dovidio, J.F., Kawakami, K., Johnson, C., Johnson, B. and Howard, A. (1997), “On the Nature of Prejudice: Automatic and Controlled Processes”, Journal of Experimental Social Psychology, Vol. 540 No. 33, pp. 510–540.CrossRefGoogle Scholar
Fiske, S.T., Cuddy, A.J.C. and Glick, P. (2007), “Universal dimensions of social cognition: warmth and competence”, Trends in Cognitive Sciences, Vol. 11 No. 2, pp. 77–83, https://dx.doi.org/10.1016/j.tics.2006.11.005.CrossRefGoogle ScholarPubMed
Goffman, E. (1959), “Presentation of self in everyday life”, American Journal of Sociology.Google Scholar
Goffman, E. (1963), Behavior in Public Places, The Free Press, New York, USA.Google Scholar
Hall, E.T. (1963), “A system for the notation of proxemic behaviour”, American Anthropologist, Vol. 65 No. 5, pp. 1003–1026.CrossRefGoogle Scholar
Hall, E.T. (1966), The Hidden Dimension, Anchor Books.Google Scholar
Hans, A. and Hans, E. (2015), “Kinesics, Haptics and Proxemics: Aspects of Non -Verbal Communication”, IOSR Journal Of Humanities And Social Science Ver. IV, Vol. 20 No. 2, pp. 47–52, https://dx.doi.org/10.9790/0837-20244752.Google Scholar
Hanzl, M. and Ledwon, S. (2017), “Analyses of human behaviour in public spaces”, ISOCARP, Portland, Oregon, USA.Google Scholar
Huang, S.C.L. (2006), “A study of outdoor interactional spaces in high-rise housing”, Landscape and Urban Planning, Vol. 78 No. 3, pp. 193–204, https://dx.doi.org/10.1016/j.landurbplan.2005.07.008.CrossRefGoogle Scholar
Hutchins, E. (1995), Cognition in the Wild, MIT Press, Cambridge, Massachusetts.Google Scholar
Jansson, L. and Norberg, A. (1995), “Facial Expressions of Patients With Dementia: A Comparison of Two Methods of Interpretation”, International Psychogeriatrics, Vol. 7 No. 4, pp. 527–534, https://dx.doi.org/10.1017/S1041610295002262.Google Scholar
Kelly, N. (2016), The WEAR Scale: Developing a Measure of the Social Acceptability of a Wearable Device, Iowa State University, https://dx.doi.org/10.1145/2851581.2892331.CrossRefGoogle Scholar
Kotanen, A., Hännikäinen, M., Leppäkoski, H. and Hämäläinen, T.D. (2003), “Experiments on Local Positioning with Bluetooth”, ITCC 2003, IEEE, pp. 2–8.Google Scholar
Kouhne, M. and Sieck, J. (2014), “Location-Based Services with iBeacon Technology”, AIMS 2014, pp. 315–321, https://dx.doi.org/10.1109/AIMS.2014.58.Google Scholar
Leroy, J., Rocca, F. and Gosselin, B. (2014), “Proxemics Measurement During Social Anxiety Disorder Therapy Using a RGBD Sensors Network”, Bio-Imaging and Visualization for Patient-Customized Simulations., Springer Cham, pp. 89–101, https://dx.doi.org/10.1007/978-3-319-03590-1_8.Google Scholar
Liu, Y., Wang, Z. and Yu, G. (2021), “The Effectiveness of Facial Expression Recognition in Detecting Emotional Responses to Sound Interventions in Older Adults With Dementia”, Frontiers in Psychology, Vol. 12 No. August, pp. 1–16, https://dx.doi.org/10.3389/fpsyg.2021.707809.Google ScholarPubMed
Maggy. (2021), “Maggy as your Social distancing device”, available at: https://www.maggylife.eu/ (accessed 18 September 2021).Google Scholar
Mccall, C., Blascovich, J., Young, A. and Persky, S. (2009), “Proxemic behaviors as predictors of aggression towards Black (but not White) males in an immersive virtual environment”, Social Influence, Vol. 4 No. 2, pp. 138–154, https://dx.doi.org/10.1080/15534510802517418.Google Scholar
Mccall, C. and Singer, T. (2015), “Facing Off with Unfair Others: Introducing Proxemic Imaging as an Implicit Measure of Approach and Avoidance during Social Interaction”, PLoS ONE, Vol. 10 No. 2, pp. 1–14, https://dx.doi.org/10.1371/journal.pone.0117532.CrossRefGoogle ScholarPubMed
Mehl, M.R. and Conner, T.S. (2012), Handbook of Research Methods for Studying Daily Life, New York, NY: Guilford.Google Scholar
Millonig, A., Ray, M. and Bauer, D. (2009), “Pedestrian behaviour monitoring: methods and experiences”, Behaviour Monitoring and Interpretation, https://dx.doi.org/10.3233/978-1-60750-048-3-11.Google Scholar
Mittal, B. (2006), “I, me, and mine - how products become consumers’ extended selves”, Journal of Consumer Behaviour, Vol. 5 No. November, pp. 550–562, https://dx.doi.org/10.1002/cb.CrossRefGoogle Scholar
Mogilner, C., Aaker, J. and Kamvar, S.D. (2012), “How happiness affects choice”, Journal of Consumer Research, Vol. 39 No. 2, pp. 429–443, https://dx.doi.org/10.1086/663774.CrossRefGoogle Scholar
Mu, B., Liu, C., Mu, T., Xu, X., Tian, G., Zhang, Y. and Kim, G. (2021), “Spatiotemporal fluctuations in urban park spatial vitality determined by on-site observation and behavior mapping: A case study of three parks in Zhengzhou City, China”, Urban Forestry and Urban Greening, Vol. 64 No. January, https://dx.doi.org/10.1016/j.ufug.2021.127246.Google Scholar
Nakamura, K., Zhao, H., Shao, X. and Shibasaki, R. (2012), “Human sensing in crowd using laser scanners”, Laser Scanner Technology, No. May 2014, https://dx.doi.org/10.5772/33276.Google Scholar
Namba, S., Sato, W., Osumi, M. and Shimokawa, K. (2021), “Assessing automated facial action unit detection systems for analyzing cross-domain facial expression databases”, Sensors, Vol. 21 No. 12, https://dx.doi.org/10.3390/s21124222.CrossRefGoogle ScholarPubMed
Nanda, P., Bos, J., Kramer, K.L., Hay, C. and Ignacz, J. (2008), “Effect of smartphone aesthetic design on users’ emotional reaction: an empirical study”, TQM Journal, Vol. 20 No. 4, pp. 348–355, https://dx.doi.org/10.1108/17542730810881339.CrossRefGoogle Scholar
Overgaard, K.D. (2019), Student's Explicit and Implicit Attitudes Regarding Breastfeeding in Public: Analyzed Through FaceReaderTM Technology, Montclair State University.Google Scholar
Park, J., Morris, K., Stannard, C. and Hamilton, W. (2014), “Design for many, design for me: Universal design for apparel products”, Design Journal, Vol. 17 No. 2, pp. 267–290, https://dx.doi.org/10.2752/175630614X13915240576103.CrossRefGoogle Scholar
Pryor, J.B., Reeder, G.D., Yeadon, C. and Hesson-McInnis, M. (2004), “A dual-process model of reactions to perceived stigma”, Journal of Personality and Social Psychology, Vol. 87 No. 4, pp. 436–452, https://dx.doi.org/10.1037/0022-3514.87.4.436.CrossRefGoogle ScholarPubMed
Soares, F. and Santos, C.P. (2021), “Fostering Emotion Recognition in Children with Autism Spectrum Disorder”, Multimodal Technol. Interact., Vol. 5 No. 57, https://dx.doi.org/10.3390/mti5100057.Google Scholar
Sousa, M., Techmer, A., Steinhage, A., Lauterbach, C. and Lukowicz, P. (2013), “Human tracking and identification using a sensitive floor and wearable accelerometers”, PerCom 2013, IEEE, pp. 166–171, https://dx.doi.org/10.1109/PerCom.2013.6526728.Google Scholar
De, Stefani, E. and Mondada, L. (2018), “Encounters in public space: how acquainted versus unacquainted persons establish social and spatial arrangements”, Research on Language and Social Interaction, Routledge, Vol. 51 No. 3, pp. 248–270, https://dx.doi.org/10.1080/08351813.2018.1485230.Google Scholar
Vaes, K., Jan Stappers, P. and Standaert, A. (2016), “Measuring Product - Related Stigma in Design”, DRS2016: Future-Focused Thinking, Vol. 8 No. June, https://dx.doi.org/10.21606/drs.2016.444.CrossRefGoogle Scholar
Vaes, K., Standaert, A. and Jan, P. (2012), “Masked Aversion - Walking and Staring Behavior towards Stigmatizing Products”, pp. 1–4, https://dx.doi.org/10.13140/2.1.3542.2722.Google Scholar
Wohlin, C. (2014), “Guidelines for snowballing in systematic literature studies and a replication in software engineering”, ACM 2014, https://dx.doi.org/10.1145/2601248.2601268.Google Scholar
Yoshimura, Y., Sobolevsky, S., Ratti, C., Girardin, F., Carrascal, J.P., Blat, J. and Sinatra, R. (2014), “An analysis of visitors’ behavior in the louvre museum: A study using bluetooth data”, Environment and Planning B: Planning and Design, Vol. 41 No. 6, pp. 1113–1131, https://dx.doi.org/10.1068/b130047p.CrossRefGoogle Scholar
Zhang, Z. (2014), “Microsoft Kinect Sensor and Its Effect”, Computer Society, No. June, https://dx.doi.org/10.1109/MMUL.2012.24.Google Scholar