We all are social beings by nature for ages. Today, the physical world shrinks as information and communication technologies bring us closer together by enabling new ways for socializing. At the same time, these technologies may not only serve as media channels but they can be designed with intent to influence our thoughts and actions.
PERSUASIVE CITIES for SUSTAINABLE WELLBEING
Persuasive Cities research aims at advancing urban spaces to facilitate societal changes. According to social sciences, any well-designed environment can become a strong influencer of what people think and do. There is an endlessly dynamic interaction between a person, a particular behavior, and an environment in which that behavior is performed. This knowledge enables engineering of persuasive environments and interventions for altering human behavior at scale. This research primarily focuses on socially engaging environments for supporting entrepreneurship and innovation, reshaping routines and behavioral patterns in urban spaces, deploying intelligent outdoor sensing for shifting mobility modes, enhancing environmentally friendly behaviors through social norms, introducing interactive public feedback channels to alter attitudes at scale, engaging residents through socially influencing systems, exploring methods for designing persuasive neighborhoods, testing agent-based models and simulations of behavioral interventions, and fostering adoption of novel urban systems.
Future cities will reshape human behavior in countless ways. Persuasive urban systems will play an important role in making cities more livable and resource-efficient by addressing current environmental problems and enabling healthier routines. In the future cities, good urban and building design (to encourage walking, biking, stair-use, etc.) will be combined with socially influencing systems to encourage healthy and sustainable behaviors at scale. The quality of life and the health of the individual and communities will be improved through the design and creation of persuasive cities, streets, buildings, homes, and vehicles.
With support from the Robert Wood Johnson Foundation (RWJF), the Advancing Wellbeing initiative addresses the role of technology in shaping our health, and explores new approaches and solutions to wellbeing. The program is built around education and student mentoring; prototyping tools and technologies that support physical, mental, social, and emotional wellbeing; and community initiatives that will originate at the MIT Media Lab, but be designed to scale.
Dr. Agnis Stibe is a Social Engineer at MIT Media Lab. In his recent TEDx talk and TEDx interview, Agnis envisions future Persuasive Cities that are encouraging healthy and sustainable routines. He believes that our world can become a better place thought purposefully designed urban spaces that successfully blend technological advancements with human nature. His research is built upon socio-psychological theories to design Socially Influencing Systems (SIS) for health behavior change at scale. Agnis is an active member of Persuasive Technology community, frequently speaking at annual conferences and effectively collaborating with industry.
Over more than 20 years, Dr. Stibe has gained professional experience in sales and marketing of IT services and products, development of interactive web solutions, and customer relationship management. He has worked for a number of Fortune 500 companies such as Hewlett-Packard, Oracle, and First Data International. In the course of his career, Dr. Stibe has twice been awarded a recognition from the Minister of Education and Science of Latvia for his long-term creative work. He has also received awards from the Nokia Foundation, Dr. Theo and Friedl Schoeller Research Center for Business and Society, and the Latvian Fund for Education. Dr. Stibe holds a master’s degree in computer science from University of Latvia, an MBA from Riga Business School (in partnership with University of Ottawa and The State University of New York at Buffalo), and a PhD on Socially Influencing Systems from University of Oulu.
ECOSYSTEM OF FUTURE CITIES
Each layer of future cities has its role, character, and supportive technology. Sensitive cities employ sensor networks to read crowd behaviors. In other words, these cities feel human movements. These crowd behaviors further serve as an input for big data analytics that smart cities apply to classify groups of people according to similar behavioral patterns (profiles). When that is accomplished, the groups having better routines can be exemplified to other underperforming groups through intentionally designed Socially Influencing Systems (SIS), which are at the core of persuasive cities.
SOCIALLY INFLUENCING SYSTEMS (SIS)
Earlier research on persuasive technology describes several ways how social dynamics can influence human behavior, which have been further refined and structured as a framework for Socially Influencing Systems (SIS). The SIS framework is a useful tool for scholars and practitioners aiming at improving future cities by introducing persuasive urban interventions targeted to support wellbeing.
The framework describes seven socially influencing principles that can support persuasive urban interventions. The principles are interlinked and have potential to exert stronger effects depending on the context of a particular behavioral challenge. Normative influence and social comparison seem to be more effective to achieve involvement of the target group as the two principles focus on attitudinal changes. Cooperation and social facilitation seem to be more effective to make individuals participate and do the envisioned future behavior even without a formed attitude towards it. Competition and recognition seem to be more effective in engaging the target group to do the future behavior as the principles focus on both attitude and behavior simultaneously.
SUSCEPTIBILITY TO SIS
People generally can fall into one of the three generic categories depending on their susceptibility to socially influencing systems. Self-contained people (the red circle) most likely are not open for changing anything in them. They are fully satisfied with who they are and what they do on daily basis, thus many behavioral interventions might fail in attempts to influence this group of individuals. Self-driven people (the green circle) typically have comparatively high levels of motivation and can achieve everything that they have envisioned. Thus, these people most likely are not looking for additional sources of encouragement, and therefore persuasive technologies might become unnecessary for this group.
However, there is another group of people that oftentimes would like to change their routines, but rarely succeed in doing so. That reminds of New Year’s resolutions that in many cases end around February. Therefore, this group is entitled as January 1st (the yellow circle) and seem to be the most welcoming towards technology supported behavioral interventions designed to help achieving target behaviors. Although, all three groups are presented as equal circles, in reality the size of each group might significantly vary depending on the context and particular behavior.
DEFINING BEHAVIOR CHANGE
To achieve an envisioned target behavior, the process and components of behavior change have to be well understood and clearly defined. In the process of defining behavior change, there are three main components, namely the selected target group, their present behavior, and their envisioned future behavior.
Target group. A group of people currently having an unsatisfactory behavior. It is important to narrow down the target group as precise as possible. Present behavior. A certain behavior of the target group that currently is not in line with an envisioned future behavior in a given context. Future behavior. An ultimate future behavior of the target group that is envisioned to be more beneficial for everyone.
Here is a helpful template to define your case:
— There is [this group of people] who currently [do this unsatisfactory behavior]. In the future, they need to [do this new behavior]. —
Stibe, A. & Larson, K. (2016). Persuasive Cities for Sustainable Wellbeing: Quantified Communities. In M. Younas et al. (eds.): Mobile Web and Intelligent Information Systems (MobiWIS 2016), LNCS 9847 (pp. 271–282) [PDF]
Stibe, A. (2016). Persuasive Cities: Health Behavior Change at Scale. Adjunct Proceedings of the 11th International Conference on Persuasive Technology (pp. 42–45) [PDF]
Stibe, A., Chatterjee, S., Schechtner, K., Wunsch, M., Millonig, A., Seer, S., Chin, R.C.C., & Larson, K. (2016). Empowering Cities for Sustainable Wellbeing. Adjunct Proceedings of the 11th International Conference on Persuasive Technology (pp. 76–79) [PDF]
Stibe, A., & Cugelman, B. (2016). Persuasive Backfiring: When Behavior Change Interventions Trigger Unintended Negative Outcomes. In Persuasive Technology (pp. 65–77). Springer International Publishing [PDF]
Wunsch, M., Stibe, A., Millonig, A., Seer, S., Chin, R.C.C. & Schechtner, K. (2016) Gamification and Social Dynamics: Insights from a Corporate Cycling Campaign. In: Streitz, N., Markopoulos, P. (eds.) DAPI 2016. LNCS 9749, (pp. 494–503) [PDF]
Wunsch, M., Millonig, A., Seer, S., Schechtner, K., Stibe, A., & Chin, R.C.C. (2016). Challenged to Bike: Assessing the Potential Impact of Gamified Cycling Initiatives. Transportation Research Board (TRB) 95th Annual Meeting, January 10–14, 2016, Washington D.C., USA.
Stibe, A. (2015). Advancing Typology of Computer-Supported Influence: Moderation Effects in Socially Influencing Systems. In Persuasive Technology (pp. 253–264). Springer International Publishing [PDF]
Stibe, A. (2015). Towards a Framework for Socially Influencing Systems: Meta-Analysis of Four PLS-SEM Based Studies. In Persuasive Technology (pp. 172–183). Springer International Publishing [PDF]
Cyr, D., Head, M., Lim, E., & Stibe, A. (2015). The Art of Online Persuasion through Design: The Role of Issue Involvement as it Influences Users based on Prior Knowledge. International Conference on Information Systems (ICIS), Proceedings of the Fourteenth Annual Workshop on HCI Research in MIS, Fort Worth, Texas, USA. (Received the best paper award.) [PDF]
Wunsch, M., Stibe, A., Millonig, A., Seer, S., Dai, C., Schechtner, K., & Chin, R. C. C. (2015). What Makes You Bike? Exploring Persuasive Strategies to Encourage Low-Energy Mobility. In Persuasive Technology (pp. 53–64). Springer International Publishing [PDF]
Stibe, A. (2014). Socially Influencing Systems: Persuading People to Engage with Publicly Displayed Twitter-based Systems. Acta Universitatis Ouluensis. PhD thesis [PDF]
Stibe, A. (2014). Exploring Social Influence and Incremental Online Persuasion on Twitter: A Longitudinal Study. In Mobile Web Information Systems (pp. 286–300). Springer International Publishing [PDF]
Stibe, A. & Oinas-Kukkonen, H. (2014). User Engagement in Feedback Sharing through Social Influence. The Evolution of the Internet in the Business Sector: Web 1.0 to Web 3.0 (pp. 234–257). IGI Global book series Advances in E-Business Research [PDF]
Stibe, A. & Oinas-Kukkonen, H. (2014). Designing Persuasive Systems for User Engagement in Collaborative Interaction. Proceedings of the European Conference on Information Systems (ECIS) [PDF]
Stibe, A., & Oinas-Kukkonen, H. (2014). Using Social Influence for Motivating Customers to Generate and Share Feedback. In Persuasive Technology (pp. 224–235). Springer International Publishing (Received the 3rd best paper award.) [PDF]
Stibe, A., Oinas-Kukkonen, H., & Lehto, T. (2013). Exploring Social Influence on Customer Engagement: A Pilot Study on the Effects of Social Learning, Social Comparison, and Normative Influence. In Proceedings of the 46th Hawaii International Conference on System Sciences (HICSS) (pp. 2735–2744). IEEE [PDF]
Stibe, A., Oinas-Kukkonen, H., Bērziņa, I., & Pahnila, S. (2011). Incremental Persuasion through Microblogging: A Survey of Twitter Users in Latvia. In Proceedings of the 6th International Conference on Persuasive Technology: Persuasive Technology and Design: Enhancing Sustainability and Health (p. 8). ACM [PDF]
Stibe, A., & Bicevskis, J. (2009). Web Site Modeling and Prototyping Based on a Domain-Specific Language. Computers Science and Information Technologies, vol.751 (pp. 7–21). University of Latvia [PDF]