Designing Conversational Agents for Energy Feedback

Reducing and shifting energy consumption could contribute significantly to a more sustainable use of energy in households. Studies have shown that the provision of feedback can encourage consumers to use energy more sustainably. While there is wide variety of energy feedback solutions ranging from in-home displays to mobile applications, there is a lack of research on whether and how conversational agents can provide energy feedback to promote sustainable energy use. As conversational agents, such as chatbots, promise a natural and intuitive user interface, they may have great potential for energy feedback. This paper explores how to design conversational agents for energy feedback and proposes design principles based on existing literature. The design principles are instantiated in a text-based conversational agent and evaluated in a focus group session with industry experts. We contribute with valuable design knowledge that extends previous research on the design of energy feedback solutions.

[1]  Ruhi Sarikaya An overview of the system architecture and key components The Technology Behind Personal Digital Assistants , 2022 .

[2]  Alan R. Hevner,et al.  The Use of Focus Groups in Design Science Research , 2010 .

[3]  Jon Froehlich,et al.  Promoting Energy Efficient Behaviors in the Home through Feedback : The Role of Human-Computer Interaction , 2009 .

[4]  Ansgar Scherp,et al.  Designing a Process Guidance System to Support User's Business Process Compliance , 2014, ICIS.

[5]  Anna Watson,et al.  Consumer attitudes to utility products: a consumer behaviour perspective , 2002 .

[6]  Elgar Fleisch,et al.  Overcoming Salience Bias: How Real-Time Feedback Fosters Resource Conservation , 2016, Manag. Sci..

[7]  Margot Brereton,et al.  Curiosity to cupboard: self reported disengagement with energy use feedback over time , 2013, OZCHI.

[8]  Wendy Miller,et al.  Social transition from energy consumers to prosumers: Rethinking the purpose and functionality of eco-feedback technologies , 2017 .

[9]  Clifford Nass,et al.  Computers are social actors , 1994, CHI '94.

[10]  Alexander Maedche,et al.  Advanced User Assistance Systems , 2016, Bus. Inf. Syst. Eng..

[11]  Ruth Mugge,et al.  Washing when the sun is shining! How users interact with a household energy management system , 2013, Ergonomics.

[12]  Ansgar Scherp,et al.  A review of the nature and effects of guidance design features , 2017, Decis. Support Syst..

[13]  Jan Krämer,et al.  Towards a User-Centered Feedback Design for Smart Meter Interfaces to Support Efficient Energy-Use Choices , 2016, Bus. Inf. Syst. Eng..

[14]  Martin Bichler,et al.  Design science in information systems research , 2006, Wirtschaftsinf..

[15]  Alan R. Hevner,et al.  Focus Groups for Artifact Refinement and Evaluation in Design Research , 2010, Commun. Assoc. Inf. Syst..

[16]  Alexander Maedche,et al.  Towards Designing Cooperative and Social Conversational Agents for Customer Service , 2017, ICIS.

[17]  Joseph Weizenbaum,et al.  and Machine , 1977 .

[18]  Kim-Phuong L. Vu,et al.  Privacy Concerns for Use of Voice Activated Personal Assistant in the Public Space , 2015, Int. J. Hum. Comput. Interact..

[19]  Rebecca Ford,et al.  Energy feedback technology: a review and taxonomy of products and platforms , 2014 .

[20]  David Griol,et al.  The Conversational Interface: Talking to Smart Devices , 2016 .

[21]  B. J. Fogg,et al.  Computers as persuasive social actors , 2003 .

[22]  Russell Beale,et al.  Affective interaction: How emotional agents affect users , 2009, Int. J. Hum. Comput. Stud..

[23]  Friedemann Mattern,et al.  Leveraging smart meter data to recognize home appliances , 2012, 2012 IEEE International Conference on Pervasive Computing and Communications.

[24]  A. Kluger,et al.  The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. , 1996 .

[25]  Angela Sanguinetti,et al.  Information, timing, and display: A design-behavior framework for improving the effectiveness of eco-feedback , 2018 .

[26]  Janette Webb,et al.  Influencing household energy practices: a critical review of UK smart metering standards and commercial feedback devices , 2014, Technol. Anal. Strateg. Manag..

[27]  Alessandro Bogliolo,et al.  The Rise of Bots: A Survey of Conversational Interfaces, Patterns, and Paradigms , 2017, Conference on Designing Interactive Systems.

[28]  Justine Cassell,et al.  Relational agents: a model and implementation of building user trust , 2001, CHI.

[29]  Nicole C. Krämer,et al.  Does Humanity Matter? Analyzing the Importance of Social Cues and Perceived Agency of a Computer System for the Emergence of Social Reactions during Human-Computer Interaction , 2012, Adv. Hum. Comput. Interact..

[30]  Jaap Ham,et al.  A Persuasive Robot to Stimulate Energy Conservation: The Influence of Positive and Negative Social Feedback and Task Similarity on Energy-Consumption Behavior , 2014, Int. J. Soc. Robotics.

[31]  Vijay K. Vaishnavi,et al.  A Multidimensional Perceptual Map Approach to Project Prioritization and Selection , 2011 .

[32]  Gerd Kortuem,et al.  Conversations with my washing machine: an in-the-wild study of demand shifting with self-generated energy , 2014, UbiComp.

[33]  Jan Pries-Heje,et al.  FEDS: a Framework for Evaluation in Design Science Research , 2016, Eur. J. Inf. Syst..

[34]  Vijay K. Vaishnavi,et al.  Theory Development in Design Science Research: Anatomy of a Research Project , 2008 .

[35]  Elgar Fleisch,et al.  PowerPedia: changing energy usage with the help of a community-based smartphone application , 2011, Personal and Ubiquitous Computing.

[36]  F. Mattern,et al.  PowerPedia-Changing Energy Usage with the Help of a Smartphone Application , 2011 .

[37]  Rebecca Ford,et al.  The effects of feedback on energy conservation: A meta-analysis. , 2015, Psychological bulletin.

[38]  Robert Dale,et al.  The return of the chatbots , 2016, Natural Language Engineering.