Persuasive Cities for Sustainable Wellbeing: Quantified Communities
Abstract
Can you imagine a city that feels, understands, and cares about your wellbeing? Future cities will reshape human behavior in countless ways. New strategies and models are required for future urban spaces to properly respond to human activity, environmental conditions, and market dynamics. Persuasive urban systems will play an important role in making cities more livable and resource-efficient by addressing current environmental challenges and enabling healthier routines. Persuasive cities research aims at improving wellbeing across societies through applications of socio-psychological theories and their integration with conceptually new urban designs. This research presents an ecosystem of future cities, describes three generic groups of people depending on their susceptibility to persuasive technology, explains the process of defining behavior change, and provides tools for social engineering of persuasive cities. Advancing this research is important as it scaffolds scientific knowledge on how to design persuasive cities and refines guidelines for practical applications in achieving their emergence.
Keywords
Persuasive technology Socially influencing systems Wellbeing Sustainability Urban design Health behavior change Quantified communitiesNotes
Acknowledgements
We gratefully acknowledge Matthias Wunsch, Alexandra Millonig, Katja Schechtner, Ryan C.C. Chin, Stefan Seer, Chengzen Dai, Felipe Lozano-Landinez, Francesco Pilla, Rosalind Picard, Pattie Maes, Kevin Slavin, Liz Voeller, Christiana von Hippel, Leo Brown, Shin Bin Tan, Austrian Institute of Technology, and the Schoeller Research Center, for their support and contribution to this research.
References
- 1.Axelrod, R.: On six advances in cooperation theory. Anal. Krit. 22(1), 130–151 (2000)Google Scholar
- 2.Bandura, A.: Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice Hall, Englewood Cliffs (1986)Google Scholar
- 3.Batty, M., Axhausen, K.W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., Ouzounis, G., Portugali, Y.: Smart cities of the future. Eur. Phys. J. Spec. Top. 214(1), 481–518 (2012)CrossRefGoogle Scholar
- 4.Cacioppo, J.T., Petty, R.E., Stoltenberg, C.D.: Processes of social influence: the elaboration likelihood model of persuasion. In: Kendall, P.C. (ed.) Advances in Cognitive-Behavioral Research and Therapy, pp. 215–274. Academic Press, San Diego (1985)CrossRefGoogle Scholar
- 5.Caragliu, A., Del Bo, C., Nijkamp, P.: Smart cities in Europe. J. Urban Technol. 18(2), 65–82 (2011)CrossRefGoogle Scholar
- 6.Chatterjee, S., Price, A.: Healthy living with persuasive technologies: framework, issues, and challenges. J. Am. Med. Inform. Assoc. (JAMIA) 16, 171–178 (2009)CrossRefGoogle Scholar
- 7.Deutsch, M.: A theory of cooperation-competition and beyond. Handb. Theor. Soc. Psychol. 2, 275 (2011)MathSciNetGoogle Scholar
- 8.Fogg, B.J.: Persuasive Technology: Using Computers to Change What We Think and Do. Morgan Kaufmann, San Francisco (2003)Google Scholar
- 9.Forester, J.: Bicycle Transportation: A Handbook for Cycling Transportation Engineers. MIT Press, Cambridge (1994)Google Scholar
- 10.Guerin, B., Innes, J.: Social Facilitation. Cambridge University Press, Cambridge, England (2009)Google Scholar
- 11.Ham, J., McCalley, T., Midden, C., Zaalberg, R.: Using persuasive technology to encourage sustainable behavior. In: 6th IEEE International Conference on Pervasive Computing, Sydney, pp. 83–86. IEEE (2008)Google Scholar
- 12.Hancke, G.P., Hancke Jr., G.P.: The role of advanced sensing in smart cities. Sensors 13(1), 393–425 (2012)CrossRefGoogle Scholar
- 13.Kock, N.: WarpPLS 5.0 User Manual. ScriptWarp Systems, Laredo, TX (2013)Google Scholar
- 14.Lapinski, M.K., Rimal, R.N.: An explication of social norms. Commun. Theory 15(2), 127–147 (2005)CrossRefGoogle Scholar
- 15.Malone, T.W., Lepper, M.: Making learning fun: a taxonomy of intrinsic motivations for learning. In: Snow, R.E., Farr, M.J. (eds.) Aptitude, Learning and Instruction: III. Conative and Affective Process Analyses, pp. 223–253. Erlbaum, Hillsdale (1987)Google Scholar
- 16.Mumford, E.: A socio-technical approach to systems design. Requir. Eng. 5(2), 125–133 (2000)CrossRefGoogle Scholar
- 17.Ogilvie, D.: Promoting walking and cycling as an alternative to using cars: systematic review. BMJ 329, 763 (2004)CrossRefGoogle Scholar
- 18.O’Keefe, D.J.: Theories of persuasion. In: Nabi, R., Oliver, M.B. (eds.) Handbook of Media Processes and Effects. Sage Publications, Thousand Oaks (2009)Google Scholar
- 19.Richter, J., Friman, M., Gärling, T.: Soft transport policy measures: gaps in knowledge. Int. J. Sustain. Transp. 5, 199–215 (2011)CrossRefGoogle Scholar
- 20.Stibe, A.: Socially influencing systems: persuading people to engage with publicly displayed Twitter-based systems. Acta Universitatis Ouluensis (2014)Google Scholar
- 21.Stibe, A.: Towards a framework for socially influencing systems: meta-analysis of four PLS-SEM based studies. In: MacTavish, T., Basapur, S. (eds.) PERSUASIVE 2015. LNCS, vol. 9072, pp. 172–183. Springer, Heidelberg (2015)CrossRefGoogle Scholar
- 22.Wood, J.V.: What is social comparison and how should we study it? Pers. Soc. Psychol. Bull. 22(5), 520–537 (1996)CrossRefGoogle Scholar
- 23.Wunsch, M., Stibe, A., Millonig, A., Seer, S., Chin, R.C.C., Schechtner, K.: Gamification and social dynamics: insights from a corporate cycling campaign. In: Streitz, N., Markopoulos, P. (eds.) DAPI 2016. LNCS, vol. 9749, pp. 494–503. Springer, Heidelberg (2016). doi: 10.1007/978-3-319-39862-4_45 CrossRefGoogle Scholar
- 24.Wunsch, M., Stibe, A., Millonig, A., Seer, S., Dai, C., Schechtner, K., Chin, R.C.: What makes you bike? Exploring persuasive strategies to encourage low-energy mobility. In: MacTavish, T., Basapur, S. (eds.) PERSUASIVE 2015. LNCS, vol. 9072, pp. 53–64. Springer, Heidelberg (2015)CrossRefGoogle Scholar