Promoting sustainable travel behaviour through the use of smartphone applications: A review and development of a conceptual model

Abstract The negative effects of transport in terms of pollution, congestion and climate change has urged the need for higher shares of cleaner and more efficient modes of transport, especially in urban settings. While new technology can solve some of these issues, behaviour changes has also been identified as an important factor to achieve a modal shift from cars to walking, cycling or public transport. This study investigates how ICT has been used to influence behaviour change and synthesizes key aspects into a conceptual model for creating a behaviour change support system (BCSS) for smartphone applications. A literature review concerning behaviour change and ICT in the fields of transport, health, energy and climate was conducted to gather empirical evidence which forms the foundation of the conceptual model. The empirical findings were tested and verified against a theoretical framework consisted of The Transtheoretical Model, Theory of Planned Behaviour, Diffusion of Innovations and the concept of Gamification. The results suggest that customization to the user, relevant and contextualised information and feedback, commitment, and appealing design are important aspects when influencing users to behaviour change through smartphone applications. The conceptual model provides further knowledge of key aspects to consider when developing persuasive tools that aims to encourage more sustainable modes of transport.

[1]  Peter Fröhlich,et al.  Where are we bound for? Persuasion in transport applications , 2016 .

[2]  David Banister,et al.  How to Write a Literature Review Paper? , 2016 .

[3]  Hsiu-Fang Hsieh,et al.  Three Approaches to Qualitative Content Analysis , 2005, Qualitative health research.

[4]  D. Banister Cities, mobility and climate change , 2011 .

[5]  J. Prochaska,et al.  Transtheoretical therapy: Toward a more integrative model of change. , 1982 .

[6]  S. Michie,et al.  Using the Internet to Promote Health Behavior Change: A Systematic Review and Meta-analysis of the Impact of Theoretical Basis, Use of Behavior Change Techniques, and Mode of Delivery on Efficacy , 2010, Journal of medical Internet research.

[7]  L. Kayler,et al.  Describing barriers and facilitators for medication adherence and self‐management among kidney transplant recipients using the information‐motivation‐behavioral skills model , 2020, Clinical transplantation.

[8]  Dean Eckles,et al.  Mobile Persuasion: 20 Perspectives on the Future of Behavior Change , 2007 .

[9]  William Brown,et al.  Using the Information-Motivation-Behavioral Skills Model to Guide the Development of an HIV Prevention Smartphone Application for High-Risk MSM. , 2015, AIDS education and prevention : official publication of the International Society for AIDS Education.

[10]  I. Ajzen,et al.  Choice of Travel Mode in the Theory of Planned Behavior: The Roles of Past Behavior, Habit, and Reasoned Action , 2003 .

[11]  Andy P. Jones,et al.  Gamification of active travel to school: A pilot evaluation of the Beat the Street physical activity intervention , 2016, Health & place.

[12]  Lucy Yardley,et al.  Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study , 2013, Journal of medical Internet research.

[13]  Sidharta Gautama,et al.  Policy 2.0 Platform for Mobile Sensing and Incentivized Targeted Shifts in Mobility Behavior , 2016, Sensors.

[14]  Pål Kraft,et al.  Current issues and new directions in Psychology and Health: What is the future of digital interventions for health behaviour change? , 2009, Psychology & health.

[15]  Jerald Jariyasunant,et al.  Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior , 2013, J. Intell. Transp. Syst..

[16]  Sebastian Bamberg,et al.  Is a Stage Model a Useful Approach to Explain Car Drivers' Willingness to Use Public Transportation? , 2007 .

[17]  Jason Tang,et al.  How can weight-loss app designers' best engage and support users? A qualitative investigation. , 2015, British journal of health psychology.

[18]  Harri Oinas-Kukkonen,et al.  Social interaction and reflection for behaviour change , 2014, Personal and Ubiquitous Computing.

[19]  S. Forward Exploring people's willingness to bike using a combination of the theory of planned behavioural and the transtheoretical model , 2014 .

[20]  Summary-PASTA ( PHYSICAL ACTIVITY THROUGH SUSTAINABLE TRANSPORT APPROACHES ) , 2019 .

[21]  F. Sniehotta,et al.  Efficacy of behavioural interventions for transport behaviour change: systematic review, meta-analysis and intervention coding , 2014, International Journal of Behavioral Nutrition and Physical Activity.

[22]  Harri Oinas-Kukkonen,et al.  Behavior Change Support Systems: A Research Model and Agenda , 2010, PERSUASIVE.

[23]  Michel C. A. Klein,et al.  Intelligent mobile support for therapy adherence and behavior change , 2014, J. Biomed. Informatics.

[24]  Hjp Harry Timmermans,et al.  A stated adaptation approach to assess changes in individuals’ activity-travel behavior in presence of personalized travel information , 2014 .

[25]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement , 2009, BMJ.

[26]  Francesco Gianni,et al.  Designing for Sustainable Urban Mobility Behaviour: A Systematic Review of the Literature , 2017 .

[27]  Mari Martiskainen,et al.  The role of information and communication technologies (ICTs) in household energy consumption—prospects for the UK , 2011 .

[28]  Wen-Hao Huang,et al.  The use of mobile apps to improve nutrition outcomes: A systematic literature review , 2015, Journal of telemedicine and telecare.

[29]  L. Hiselius,et al.  Mobility Management campaigns as part of the transition towards changing social norms on sustainable travel behaviour , 2016 .

[30]  Todd Litman,et al.  Quantifying the Benefits of Nonmotorized Transportation For Achieving Mobility Management Objectives , 2007 .

[31]  Sidharta Gautama,et al.  Crowdsourcing mobility insights: reflection of attitude based segments on high resolution mobility behaviour data , 2016 .

[32]  Martin Anda,et al.  Smart metering for residential energy efficiency: The use of community based social marketing for behavioural change and smart grid introduction , 2014 .

[33]  Raja Sengupta,et al.  The Quantified Traveler: Changing Transport Behavior with Personalized Travel Data Feedback , 2012 .

[34]  Luc Int Panis,et al.  Physical Activity through Sustainable Transport Approaches (PASTA): a study protocol for a multicentre project , 2016, BMJ Open.

[35]  M. Milczarek,et al.  Using a Smartphone Application to Promote Healthy Dietary Behaviours and Local Food Consumption , 2015, BioMed research international.

[36]  Sean P Mullen,et al.  Increasing Physical Activity With Mobile Devices: A Meta-Analysis , 2012, Journal of medical Internet research.

[37]  J. Anable,et al.  Smarter Choices: Assessing the Potential to Achieve Traffic Reduction Using ‘Soft Measures’ , 2008 .

[38]  M. Conner,et al.  Efficacy of the Theory of Planned Behaviour: a meta-analytic review. , 2001, The British journal of social psychology.

[39]  Johann Schrammel,et al.  Persuasive Technologies for Sustainable Urban Mobility , 2016, ArXiv.

[40]  Stefan Poslad,et al.  Using a Smart City IoT to Incentivise and Target Shifts in Mobility Behaviour—Is It a Piece of Pie? , 2015, Sensors.

[41]  J. Anable,et al.  AN EVIDENCE BASE REVIEW OF PUBLIC ATTITUDES TO CLIMATE CHANGE AND TRANSPORT BEHAVIOUR , 2006 .

[42]  I FelsDeborah,et al.  Gamification in theory and action , 2015 .

[43]  I. Ajzen The theory of planned behavior , 1991 .

[44]  Antti Jylhä,et al.  Towards an Applied Gamification Model for Tracking, Managing, & Encouraging Sustainable Travel Behaviours , 2014, EAI Endorsed Trans. Ambient Syst..

[45]  Sebastián Castellanos Delivering modal-shift incentives by using gamification and smartphones: A field study example in Bogota, Colombia , 2016 .

[46]  Tom Baranowski,et al.  Let's get technical! Gaming and technology for weight control and health promotion in children. , 2012, Childhood obesity.

[47]  Cristina Pronello,et al.  The effects of the multimodal real time information systems on the travel behaviour , 2017 .

[48]  Michael Nye,et al.  Making energy visible: A qualitative field study of how householders interact with feedback from smart energy monitors , 2010 .

[49]  Harri Oinas-Kukkonen,et al.  Persuasive Systems Design: Key Issues, Process Model, and System Features , 2009, Commun. Assoc. Inf. Syst..

[50]  C. Abraham,et al.  A taxonomy of behavior change techniques used in interventions. , 2008, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[51]  Deborah I. Fels,et al.  Gamification in theory and action: A survey , 2015, Int. J. Hum. Comput. Stud..

[52]  A. Colorni,et al.  Behavioral Change and Social Innovation Through Reward: An Integrated Engagement System for Personal Mobility, Urban Logistics and Housing Efficiency , 2016 .

[53]  Christina Cheng,et al.  Evaluating mobile phone applications for health behaviour change: A systematic review , 2018, Journal of telemedicine and telecare.

[54]  Kenton O'Hara,et al.  Gamification. using game-design elements in non-gaming contexts , 2011, CHI Extended Abstracts.

[55]  Geraldine Naughton,et al.  Smartphone Interventions for Weight Treatment and Behavioral Change in Pediatric Obesity: A Systematic Review. , 2015, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[56]  Mario Platzer,et al.  Field Evaluation of the Smartphone-based Travel Behaviour Data Collection App “SmartMo”☆ , 2015 .

[57]  Johann Schrammel,et al.  Watch your Emissions: Persuasive Strategies and Choice Architecture for Sustainable Decisions in Urban Mobility , 2014, PsychNology J..

[58]  Frank Witlox,et al.  MaxSUMO: A New Expert Approach for Evaluating Mobility Management Projects , 2013 .

[59]  L. Yardley,et al.  Current issues and new directions in Psychology and Health : Contributions to translational research , 2008, Psychology & health.

[60]  Alistair Woodward,et al.  Smartphone Apps for Measuring Human Health and Climate Change Co-Benefits: A Comparison and Quality Rating of Available Apps , 2016, JMIR mHealth and uHealth.

[61]  Aykut Coşkun,et al.  Designing For Behaviour Change: Smart Phone Applications As Persuaders Of Pro-Environmental Behaviours , 2014 .

[62]  Jan-Dirk Schmöcker,et al.  Can we promote sustainable travel behavior through mobile apps? Evaluation and review of evidence , 2017 .

[63]  Brian Caulfield,et al.  Does green make a difference: The potential role of smartphone technology in transport behaviour , 2013 .

[64]  Juliana Chen,et al.  The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment , 2015, JMIR mHealth and uHealth.

[65]  Kenneth A. Small,et al.  Research Policy and Review 25. Modeling Land Use and Transportation: An Interpretive Review for Growth Areas , 1987, Environment and Planning A: Economy and Space.

[66]  W. James Potter,et al.  Rethinking validity and reliability in content analysis , 1999 .

[67]  Italo Meloni,et al.  Lessons learned from a personalized travel planning (PTP) research program to reduce car dependence , 2017 .

[68]  Gavin T. Colquitt,et al.  Increasing Physical Activity During Skill Practice , 2011 .