An eco-feedback framework for user interface design to support maritime decarbonization

Abstract

Decarbonization of the maritime industry requires fostering habits and conditions that enable operators to make energy-conscious decisions. User interface (UI) design can play a key role in developing strategies to enhance user awareness and motivation. Specifically, UI design can implement feedback mechanisms that help users better understand the consequences of their actions on energy consumption. This approach has demonstrated measurable reductions in energy use in domains such as automotive systems and home appliances. However, research on eco-feedback and its implementation through UI design remains limited in the maritime context. We aimed to address this gap by conducting a systematic review of eco-feedback research and developing an eco-feedback framework (EFF) for UI design. We identified 39 strategies for providing feedback on a UI. These strategies were organized and synthesized into a design framework, the EFF. We illustrate the proof of concept of the EFF with a maritime example: a cruise control system that regulates a ship's speed and power use. Finally, we discuss other potential applications of the EFF in UI design research and conclude by highlighting its importance in fostering habits and conditions for energy-conscious decision-making in the maritime industry.

Keywords

eco-feedback user interface behaviour change sustainable human–computer interaction (HCI)interaction design design framework

1 Introduction

1.1 Supporting energy-conscious choices in maritime decarbonization

Maritime transport plays a crucial role in the global economy. Shipping accounts for 80% to 90% of global trade, transporting over 10 billion tonnes of containers and bulk cargo annually.¹ However, the exponential growth of the global economy and maritime trade is also one of the main drivers of the negative impacts of shipping on the environment, particularly marine life and human health.^2–5 Therefore, the International Maritime Organization aims to fully decarbonize the maritime transportation sector. It targets a 30% reduction in greenhouse gas emissions by 2030 and an 80% reduction by 2040 compared to 2008 levels.⁶

The decarbonization of the maritime sector depends on technological innovation and the everyday decisions made by those who operate and manage ships.⁷ While new fuels, propulsion systems and energy-efficient technologies are vital, they can only reach their full potential when embedded within pro-environmental behaviour that focuses on energy-conscious decision-making (i.e. actions and judgements that consciously prioritize energy efficiency, environmental impact and long-term sustainability) emerge.⁸

Supporting energy-conscious choices through design, specifically through user interface (UI) design, by using eco-feedback as a strategy to achieve energy reduction goals, represents a crucial yet often underestimated dimension of the transition towards sustainable shipping. Eco-feedback is designed to provide users with information about their energy consumption over a specific period to influence individual or group behaviours to reduce environmental impact and encourage pro-environmental actions.^9,10 Eco-feedback interfaces, for example, can transform invisible energy consumption information into tangible signals to which crews can respond.¹¹

Decision-making systems that integrate performance data, environmental conditions and operational constraints into visible and meaningful feedback can help bridge the gap between sustainability goals and real-world operations. Supporting energy-conscious choices in maritime decarbonization bridges technological innovation and human behaviour.^12,13 Through this interplay, decision-making becomes not merely a functional task but a creative and adaptive process, an instance of distributed cognition in action.

1.2 Challenges of supporting energy-conscious choices in maritime decarbonization through UI design

A key challenge in supporting energy-conscious decisions in maritime decarbonization is the design of UIs. Many seafarers rely heavily on intuitive knowledge; however, this alone is insufficient to maintain energy consumption within sustainable targets.

Designing UIs that support energy-conscious decision-making is a complex task that depends on technological advancements and human factors.^12,13 Behavioural change is critical to achieving sustainable goals in any field that involves human interaction.^14,15 Behaviour change refers to the process of altering people's actions and decision-making patterns through targeted interventions.^16,17 We argue that studying human behaviour in context can reveal how individuals interact with equipment and systems, providing insights into how their behaviour can be guided towards more sustainable practices.¹⁸ Consequently, behaviour change as a discipline offers valuable tools for understanding and shaping human behaviour in the maritime sector.

The digital transformation of the maritime sector is one of the most important steps towards improving seafarers’ safety, monitoring equipment usage, making ships more sustainable and keeping maritime companies competitive. Digital transformation is the use of information and communication technologies (ICTs) to improve or change existing business processes or models.^19–21

In the maritime sector, digitalization manifests in several ways, including the improvement of existing equipment, the development of new technologies, process automation, personnel training, the integration of sensors, and the adoption of artificial intelligence.²² However, even with the ongoing digitalization of the sector, challenges persist, such as the lack of integration between the different equipment used by seafarers on the bridge.

According to Nordby et al.,²³ a bridge with equipment from different manufacturers includes various product types, installation methods and UI design specifications and philosophies. This gap between systems forces seafarers to manage inconsistencies across multiple UIs, which can potentially lead to human error, the cause of approximately 80% of maritime incidents and accidents.²⁴ Therefore, it is essential to adapt tasks, equipment, and environments to the user's skills, avoiding situations where seafarers are forced to operate poorly designed or inappropriate systems.²⁵

Inadequately designed UIs, with poor usability and a lack of standardization, can lead to the misuse of equipment, which in turn may result in excessive energy consumption.^23,26 Despite the growing adoption of digital technologies in the maritime domain, there is still no established design precedent for eco-feedback UIs specifically applied to maritime systems. Existing maritime UIs primarily focus on navigation, safety, and operational efficiency, rarely incorporating mechanisms that promote energy awareness or sustainable behaviour among seafarers. Therefore, the development of an eco-feedback design framework represents an important step towards integrating sustainability-driven interaction principles into maritime interface design.

Current maritime UIs are limited to presenting analytical data on energy use, often using highly technical terms such as NOx, SOx, sulphur or CO₂. According to Mäkivierikko et al.,²⁷ these terms can be difficult to translate into clear, actionable insights about real energy use, even for professionals in the field. This raises concerns about the actual understanding of energy information.

Moreover, these UIs tend to display energy consumption data that are not in real time and do not reflect the current operational state. This can hinder decision-making and prevent behavioural adjustments during voyages or operations such as dynamic positioning. However, considering the digitalization of the maritime industry and the growing pressure from regulatory agencies to make the sector more sustainable, there is a strong need to design interfaces that go beyond purely instrumental tasks and help seafarers develop new behaviours and increase their energy consciousness.

1.3 Eco-feedback research and its application in UI design in non-maritime domains

To design an effective eco-feedback UI to encourage sustainable actions, the designer should understand how users process information and make decisions related to energy consumption, considering theories of motivation and behaviour change, such as self-determination theory,²⁸ nudge theory,²⁹ goal setting,³⁰ and persuasive technology.³¹ Understanding these theories is valuable because how information is visualized should guide design decisions. When designing for eco-feedback, many designers employ techniques such as metaphorical representations, comparative feedback, and gamification to enhance users’ understanding of energy consumption and increase engagement.^27,32,33

In human–computer interaction (HCI) design, feedback is used to provide users with information about the results of their actions or the state of a system. This keeps users informed in digital environments and fulfils communication expectations during interaction.³⁴

In HCI, eco-feedback aims to promote environmentally responsible behaviour. According to Froehlich,³⁵^(p1999) ‘eco-feedback is a variation of feedback that describes strategies or technologies that can affect individual or group behaviours to reduce environmental impact and guide people toward pro-environmental behaviour’. By providing users with information about their consumption patterns, eco-feedback helps them become aware of the environmental consequences of their actions, enabling more sustainable choices.³⁶ This awareness, in turn, can foster ‘pro-environmental behaviour (e.g., minimizing resource and energy consumption, using non-toxic substances, and reducing waste production)’.³⁷^(p240)

In the context of energy management for homes and buildings, feedback has proven to be an effective approach for promoting energy conservation and raising awareness.^38,39

Feedback presented on displays such as tablets, computers, or smartphones can save energy by 5% to 20%.⁹ A study by Sanguinetti et al.⁴⁰ showed that prompting drivers with visual cues or tangible feedback can improve fuel efficiency by 6.8% to 18.4%. Similarly, Ahmed et al.⁴¹ showed that in-vehicle feedback provided through dashboard displays can reduce carbon emissions by 5% to 20%.

A meta-analysis by Karlin et al.,⁴² which reviewed 42 studies conducted between 1976 and 2010, found that providing feedback through interactive media (e.g. computers) can influence people's energy consumption behaviour, leading to reductions of 8% to 12%. According to Darby,⁴³ a 25-year study demonstrated that feedback delivered via interactive media, such as smart meters, smartphones, in-home displays, or other digital devices, can reduce energy consumption by up to 20%. These findings illustrate the effectiveness of eco-feedback when provided in a specific setting using appropriate technologies. While data on long-term impacts remain limited, interactive feedback systems consistently demonstrate positive short-term effects on human behaviour, highlighting their value in promoting energy-conscious actions.

1.4 Scope and goal of this paper

While research shows that eco-feedback can be effective in helping users reduce their environmental footprint and energy consumption in various industries, its applicability in the maritime sector remains unexplored; guidelines for designing a UI for eco-feedback are lacking.

The goal of this paper is twofold. First, to conduct an extensive literature review to identify eco-feedback strategies across academic fields related to interaction design, HCI, environmental psychology, ubiquitous computing, behaviour change, persuasive technology, sustainable design, and the environment. Second, to develop a design framework that can serve as a practical and creative tool for practitioners and researchers to design more effective eco-feedback UIs that help users change their behaviour and reduce energy consumption. We present this framework and proof of concept before discussing potential other ways to use the framework.

1.5 Current maritime user interfaces

The ongoing digitalization of the maritime sector has introduced a growing variety of technologies and systems on board vessels. However, this proliferation of equipment has not been accompanied by consistent design standards, particularly at the level of the ship's bridge. In multivendor bridge systems, navigators are required to interact with equipment that presents multiple design languages across physical and digital inputs and outputs, increasing cognitive demands and the potential for operational errors.^26,44

Studies have found that a significant number of seafarers report being confused by information presented across bridge systems, a problem directly linked to the coexistence of multiple equipment types on the bridge.⁴⁵ Despite the recognized need for consistency, current maritime regulations and design guidelines have not provided a clear path to user interface consistency across all bridge systems.^²³

Given this fragmentation, current maritime UIs mainly focus on displaying operational data or supporting voyage planning and navigation tasks. Although such interfaces are essential for these purposes, they do not enable seafarers to make informed decisions regarding energy consumption. The information presented tends to be static and retrospective, offering little support for real-time behavioural adjustments during voyages or operations. As a result, there remains a significant gap between the data these systems provide and the energy-conscious decision-making that sustainable maritime operations increasingly require.

2 Research methodology

We applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology to conduct the systematic literature review^46,47 as follows: (1) establish the search strategy, (2) initial screening, (3) eligibility, (4) explore the resulting dataset, and (5) extract data from the dataset to build the eco-feedback framework (EFF).

Figure 1 summarizes the search process and the resulting dataset.

Figure 1.

Flow diagram of the systematic review.

Eco-feedback was the primary focus of this review, and we also considered related concepts such as eco-driving and energy feedback. This strategy ensured that relevant studies were not overlooked due to variations in terminology. We conducted the literature search across five academic databases to maximize coverage and minimize bias. The search string was adapted to each database to decrease the risk of missing eligible studies. We used a comprehensive search string with core eco-feedback and related terms, employing customized, case-sensitive queries across the different databases.

The specific search queries and their results are as follows:

ACM Digital Library: [Title: eco-feedback] AND [Abstract: eco-feedback] AND [Keywords: eco-feedback] yielded over 756,990 records. When we restricted the search to articles published between 1980 and 2023 [AND E-Publication Date: (01/01/1980 TO 31/12/2023)], this resulted in 22 articles.

ScienceDirect: [Title, abstract, keywords: Eco-feedback, energy feedback, Eco-driving] resulted in 12 records.

IEEE Xplore Digital Library: (‘Publication Title’: Eco-feedback) OR (‘Abstract’: eco-feedback) OR (‘Author Keywords’: Ecofeedback) OR (‘Author Keywords’: Eco-Feedback) OR (‘Publication Title’: ECO FEEDBACK) AND (‘Author Keywords’: Energy-Feedback) OR (‘Publication Title’: energy feedback) OR (‘Abstract’: ENERGY-FEEDBACK) AND (‘Publication Title’: Eco-driving) OR (‘Author Keywords’: Eco-Driving) OR (‘Publication Title’: ECO-DRIVING) returned 244 records.

ResearchGate: (‘Publication Title’: Eco-feedback) OR (‘Abstract’: eco-feedback) OR (‘Author Keywords’: Ecofeedback) OR (‘Author Keywords’: Eco-Feedback) OR (‘Publication Title’: ECO FEEDBACK) AND (‘Author Keywords’: Energy-Feedback) OR (‘Publication Title’: energy feedback) OR (‘Abstract’: ENERGY-FEEDBACK) AND (‘Publication Title’: Eco-driving) OR (‘Author Keywords’: Eco-Driving) OR (‘Publication Title’: ECO-DRIVING) retrieved 100 articles.

Academia: We performed the following query: ‘Eco-feedback’, ‘eco-feedback’, ‘ecofeedback’, ‘Eco-Feedback’, ‘ECO FEEDBACK’, ‘Energy-Feedback’, ‘energy feedback’, ‘ENERGY-FEEDBACK’, ‘Eco-driving’, ‘Eco-Driving’, ‘ECO-DRIVING’. This search returned 1539 results. After filtering the time span of 1980 to 2023, the results narrowed down to 111 journal articles and 45 conference articles in English, totalling 156 articles.

After removing duplicates, we screened the titles and abstracts to exclude articles that did not reference the concept of eco-feedback and were not related to HCI/interaction design, UI design, or ubiquitous computing.

Then, we screened the full text of the remaining articles and used the JBI checklist to assess the relevance of the articles.⁴⁸ We excluded any articles that did not meet all the criteria of the JBI checklist.

2.1 Step 4: Exploring the resulting dataset

We examined key information contained in the dataset, such as the distribution of publication years and countries. Analysing these distributions provides valuable insights into the temporal and geographical trends of research within the field. The year distribution reveals how interest in the topic has evolved, for example, whether research on eco-feedback or energy-conscious design has increased in recent years, indicating growing academic and industrial relevance. Similarly, analysing the countries of publication highlights where research efforts are concentrated, revealing regional leadership, policy influence, or cultural emphasis on sustainability and design practices.

Subsequently, we explored how each article approached eco-feedback and how it was applied within design processes, particularly from the perspective of designers.

We analysed each article and identified the individual descriptions and categorizations of eco-feedback. From this process, we created a cluster of all the identified eco-feedback types. Next, we compiled a comprehensive list of these eco-feedback strategies, along with their definitions. In the second iteration, we began grouping each feedback type into affinity categories based on similarities and shared characteristics. In the third iteration, these feedback groups were organized into distinct design patterns. This structured process resulted in the development of the EFF (see Figure 2).

Figure 2.

Flow of the development process of the eco-feedback framework.

3 Results

We first present the obtained dataset (i.e. the list of articles that resulted from the systematic search and screening). Then, we look at the dataset itself, and finally, we present the EFF.

3.1 The dataset

The initial search yielded 534 articles, of which 41 were eligible for inclusion in the study. Of these, 14 are journal articles and 27 are conference papers. Table 1 provides an overview of the selected studies.

Table 1.
List of included articles.

Title Authors Year Application domain

Sustainability by design. How to encourage users to choose energy-saving programs and settings when washing laundry Laura Grönewald et al. https://doi.org/10.1145/3544548.3581150 2023 Household⁴⁹

The character of eco-feedback systems for energy communities Èlia Gil Peña et al. https://doi.org/10.1145/3593743.3593783 2023 Household⁵⁰

Visualisation in energy eco-feedback systems: a systematic review of good practice M.L. Chalal et al. https://doi.org/10.1016/j.rser.2022.112447 2022 Household⁵¹

Designing eco-feedback systems for communities: interrogating a techno-solutionist vision for sustainable communal energy Rikke Jensen et al. https://doi.org/10.1145/3461564.3461581 2021 Household⁵²

Designing energy feedback for a local social network Aram Mäkivierikko et al. https://doi.org/10.1016/j.enbuild.2019.06.038 2019 Household²⁷

Effective design of domestic energy efficiency displays: a proposed architecture based on empirical evidence Carmen Valor et al. https://doi.org/10.1016/j.rser.2019.109301 2019 Household⁵³

Promoting sustainable energy consumption behavior through interactive data visualizations Thomas Rist et al. https://doi.org/10.3390/mti3030056 2019 Household⁵⁴

Investigating user emotional responses to eco-feedback designs Qifang Bao et al. https://doi.org/10.1115/1.4042007 2019 Household⁵⁵

A priori acceptability of various types of digital display feedback on electricity consumption Sylvain Fleury et al. https://doi.org/10.3917/th.813.0247 2018 Household³⁸

In-situ evaluation of a ‘what if’ approach for eco-feedback Jérémy Wambecke et al. https://doi.org/10.1145/3286689.3286690 2018 Household³⁹

Information, timing, and display: a design-behavior framework for improving the effectiveness of eco-feedback Angela Sanguinetti et al. https://doi.org/10.1016/j.erss.2017.10.001 2018 Household⁴⁰

Affordances of eco-feedback design in home energy context Marlen Promann et al. https://aisel.aisnet.org/amcis2017/GreenIS/Presentations/7 2017 Household⁵⁶

Analysing eco-feedback appropriation in a smart-home context Anthony Plancoulaine et al. https://doi.org/10.1145/2970930.2970960 2016 Household¹¹

Design challenges and opportunities for eco-feedback in the home Lyn Bartram https://www.doi.org/10.1109/MCG.2015.69 2015 Household⁵⁷

What-a-watt: exploring electricity production literacy through a long term eco-feedback study Filipe Quintal et al. https://www.doi.org/10.1109/SustainIT.2015.7101365 2015 Household⁵⁸

When an eco-feedback system joins the family Stephen Snow et al. https://doi.org/10.1007/s00779-015-0839-y 2015 Household⁵⁹

An effective approach using eco-feedback to motivate energy conservation behaviors Hieu Huynh https://www.doi.org/10.1109/CTS.2014.6867632 2014 Household⁶⁰

Feeding back about eco-feedback: how do consumers use and respond to energy monitors? Kathryn Buchanan et al. https://doi.org/10.1016/j.enpol.2014.05.008 2014 Household⁹

The eco-feedback in the washing machine interface as a design strategy for behavior change Marcelo Forcato et al. https://hdl.handle.net/1884/35538 2014 Household⁶¹

Design of an appliance level eco-feedback display for domestic electricity consumption Jeni Paay et al. https://doi.org/10.1145/2686612.2686663 2014 Household⁶²

Understanding the limitations of eco-feedback: a one-year long-term study Lucas Pereira et al. https://doi.org/10.1007/978-3-642-39146-0_21 2013 Household⁶³

Why don’t families get along with eco-feedback technologies? A longitudinal inquiry Mary Barreto et al. https://doi.org/10.1145/2499149.2499164 2013 Household⁶⁴

Design of eco-feedback technology to motivate sustainable behavior: cultural aspects in a Brazilian context Lara Piccolo et al. https://aisel.aisnet.org/confirm2012/34 2012 Household⁶⁵

Personalised eco-feedback as a design technique for motivating energy saving behaviour at home Petromil Petkov et al. https://doi.org/10.1145/2399016.2399106 2012 Household⁶⁶

Putting the user in charge: end user development for eco-feedback technologies impressions from a living lab based design case study Timo Jakobi et al. https://dl.ifip.org/db/conf/ifip6-3/sustainit2012/JakobiS12.pdf 2012 Household⁶⁷

The design and evaluation of prototype eco-feedback displays for fixture-level water usage data Jon Froehlich et al. https://doi.org/10.1145/2207676.2208397 2012 Household⁶⁸

Eco-feedback on the go: motivating energy awareness Anna Spagnolli et al. https://doi.org/10.1109/MC.2011.125 2011 Household⁶⁹

Designing eco-feedback systems for everyday life Yolande Strengers et al. https://doi.org/10.1145/1978942.1979252 2011 Household⁷⁰

The design of eco-feedback technology Jon Froehlich et al. https://doi.org/10.1145/1753326.1753629 2010 Household³⁵

Promoting energy efficient behaviors in the home through feedback: the role of human–computer interaction Jon Froehlich https://dada.cs.washington.edu/research/tr/2009/02/UW-CSE-09-02-01.PDF 2009 Household³³

Feedback on household electricity consumption: a tool for saving energy? Corinna Fischer https://doi.org/10.1007/s12053-008-9009-7 2008 Household⁷¹

Making it obvious: designing feedback into energy consumption Sarah Darby https://doi.org/10.1007/978-3-642-56531-1_73 2001 Household⁴³

Computer based systems in household appliances: the study of eco-feedback as a tool for increasing conservation behavior L.T. McCalley et al. https://www.doi.org/10.1109/APCHI.1998.704455 1998 Household⁷²

Ecogo: combining eco-feedback and gamification to improve the sustainability of driving style Simone Avolicino et al. https://doi.org/10.1145/3531073.3531127 2022 Automotive³²

A typology of in-vehicle eco-driving feedback Angela Sanguinetti et al. https://doi.org/10.1007/978-3-319-41682-3_80 2016 Automotive⁷³

Obdenergy: Making metrics meaningful in eco-driving feedback Sumayyah Ahmed et al. https://doi.org/10.1007/978-3-319-20886-2_37 2015 Automotive⁴¹

Direct or indirect sensor enabled eco-driving feedback: which preference do corporate car drivers have? Johannes Tulusan et al. https://www.doi.org/10.1109/IOT.2012.6402302 2012 Automotive⁷⁴

Eco-efficient feedback technologies: which eco-feedback types prefer drivers most? Johannes Tulusan et al. https://www.doi.org/10.1109/WoWMoM.2011.5986187 2011 Automotive⁷⁵

Creating environmental awareness using an eco-feedback application at a higher education institution André Calitz et al. https://doi.org/10.4314/sajee.v36i1.8 2020 Building⁷⁶

Eco-feedback performance exploration for eco-feedback design Livier Serna-Mansoux et al. https://univ-tln.hal.science/hal-01723876 2013 Environment⁷⁷

One size does not fit all: applying the transtheoretical model to energy feedback technology design Helenai He et al. https://doi.org/10.1145/1753326.1753464 2010 Environment⁷⁸

Title	Authors	Year	Application domain
Sustainability by design. How to encourage users to choose energy-saving programs and settings when washing laundry	Laura Grönewald et al. https://doi.org/10.1145/3544548.3581150	2023	Household⁴⁹
The character of eco-feedback systems for energy communities	Èlia Gil Peña et al. https://doi.org/10.1145/3593743.3593783	2023	Household⁵⁰
Visualisation in energy eco-feedback systems: a systematic review of good practice	M.L. Chalal et al. https://doi.org/10.1016/j.rser.2022.112447	2022	Household⁵¹
Designing eco-feedback systems for communities: interrogating a techno-solutionist vision for sustainable communal energy	Rikke Jensen et al. https://doi.org/10.1145/3461564.3461581	2021	Household⁵²
Designing energy feedback for a local social network	Aram Mäkivierikko et al. https://doi.org/10.1016/j.enbuild.2019.06.038	2019	Household²⁷
Effective design of domestic energy efficiency displays: a proposed architecture based on empirical evidence	Carmen Valor et al. https://doi.org/10.1016/j.rser.2019.109301	2019	Household⁵³
Promoting sustainable energy consumption behavior through interactive data visualizations	Thomas Rist et al. https://doi.org/10.3390/mti3030056	2019	Household⁵⁴
Investigating user emotional responses to eco-feedback designs	Qifang Bao et al. https://doi.org/10.1115/1.4042007	2019	Household⁵⁵
A priori acceptability of various types of digital display feedback on electricity consumption	Sylvain Fleury et al. https://doi.org/10.3917/th.813.0247	2018	Household³⁸
In-situ evaluation of a ‘what if’ approach for eco-feedback	Jérémy Wambecke et al. https://doi.org/10.1145/3286689.3286690	2018	Household³⁹

Information, timing, and display: a design-behavior framework for improving the effectiveness of eco-feedback	Angela Sanguinetti et al. https://doi.org/10.1016/j.erss.2017.10.001	2018	Household⁴⁰
Affordances of eco-feedback design in home energy context	Marlen Promann et al. https://aisel.aisnet.org/amcis2017/GreenIS/Presentations/7	2017	Household⁵⁶
Analysing eco-feedback appropriation in a smart-home context	Anthony Plancoulaine et al. https://doi.org/10.1145/2970930.2970960	2016	Household¹¹
Design challenges and opportunities for eco-feedback in the home	Lyn Bartram https://www.doi.org/10.1109/MCG.2015.69	2015	Household⁵⁷
What-a-watt: exploring electricity production literacy through a long term eco-feedback study	Filipe Quintal et al. https://www.doi.org/10.1109/SustainIT.2015.7101365	2015	Household⁵⁸
When an eco-feedback system joins the family	Stephen Snow et al. https://doi.org/10.1007/s00779-015-0839-y	2015	Household⁵⁹
An effective approach using eco-feedback to motivate energy conservation behaviors	Hieu Huynh https://www.doi.org/10.1109/CTS.2014.6867632	2014	Household⁶⁰
Feeding back about eco-feedback: how do consumers use and respond to energy monitors?	Kathryn Buchanan et al. https://doi.org/10.1016/j.enpol.2014.05.008	2014	Household⁹
The eco-feedback in the washing machine interface as a design strategy for behavior change	Marcelo Forcato et al. https://hdl.handle.net/1884/35538	2014	Household⁶¹
Design of an appliance level eco-feedback display for domestic electricity consumption	Jeni Paay et al. https://doi.org/10.1145/2686612.2686663	2014	Household⁶²
Understanding the limitations of eco-feedback: a one-year long-term study	Lucas Pereira et al. https://doi.org/10.1007/978-3-642-39146-0_21	2013	Household⁶³

Why don’t families get along with eco-feedback technologies? A longitudinal inquiry	Mary Barreto et al. https://doi.org/10.1145/2499149.2499164	2013	Household⁶⁴
Design of eco-feedback technology to motivate sustainable behavior: cultural aspects in a Brazilian context	Lara Piccolo et al. https://aisel.aisnet.org/confirm2012/34	2012	Household⁶⁵
Personalised eco-feedback as a design technique for motivating energy saving behaviour at home	Petromil Petkov et al. https://doi.org/10.1145/2399016.2399106	2012	Household⁶⁶
Putting the user in charge: end user development for eco-feedback technologies impressions from a living lab based design case study	Timo Jakobi et al. https://dl.ifip.org/db/conf/ifip6-3/sustainit2012/JakobiS12.pdf	2012	Household⁶⁷
The design and evaluation of prototype eco-feedback displays for fixture-level water usage data	Jon Froehlich et al. https://doi.org/10.1145/2207676.2208397	2012	Household⁶⁸
Eco-feedback on the go: motivating energy awareness	Anna Spagnolli et al. https://doi.org/10.1109/MC.2011.125	2011	Household⁶⁹
Designing eco-feedback systems for everyday life	Yolande Strengers et al. https://doi.org/10.1145/1978942.1979252	2011	Household⁷⁰
The design of eco-feedback technology	Jon Froehlich et al. https://doi.org/10.1145/1753326.1753629	2010	Household³⁵
Promoting energy efficient behaviors in the home through feedback: the role of human–computer interaction	Jon Froehlich https://dada.cs.washington.edu/research/tr/2009/02/UW-CSE-09-02-01.PDF	2009	Household³³
Feedback on household electricity consumption: a tool for saving energy?	Corinna Fischer https://doi.org/10.1007/s12053-008-9009-7	2008	Household⁷¹

Making it obvious: designing feedback into energy consumption	Sarah Darby https://doi.org/10.1007/978-3-642-56531-1_73	2001	Household⁴³
Computer based systems in household appliances: the study of eco-feedback as a tool for increasing conservation behavior	L.T. McCalley et al. https://www.doi.org/10.1109/APCHI.1998.704455	1998	Household⁷²
Ecogo: combining eco-feedback and gamification to improve the sustainability of driving style	Simone Avolicino et al. https://doi.org/10.1145/3531073.3531127	2022	Automotive³²
A typology of in-vehicle eco-driving feedback	Angela Sanguinetti et al. https://doi.org/10.1007/978-3-319-41682-3_80	2016	Automotive⁷³
Obdenergy: Making metrics meaningful in eco-driving feedback	Sumayyah Ahmed et al. https://doi.org/10.1007/978-3-319-20886-2_37	2015	Automotive⁴¹
Direct or indirect sensor enabled eco-driving feedback: which preference do corporate car drivers have?	Johannes Tulusan et al. https://www.doi.org/10.1109/IOT.2012.6402302	2012	Automotive⁷⁴
Eco-efficient feedback technologies: which eco-feedback types prefer drivers most?	Johannes Tulusan et al. https://www.doi.org/10.1109/WoWMoM.2011.5986187	2011	Automotive⁷⁵
Creating environmental awareness using an eco-feedback application at a higher education institution	André Calitz et al. https://doi.org/10.4314/sajee.v36i1.8	2020	Building⁷⁶
Eco-feedback performance exploration for eco-feedback design	Livier Serna-Mansoux et al. https://univ-tln.hal.science/hal-01723876	2013	Environment⁷⁷
One size does not fit all: applying the transtheoretical model to energy feedback technology design	Helenai He et al. https://doi.org/10.1145/1753326.1753464	2010	Environment⁷⁸

The selected articles for this study came from various domains. The most prevalent domain for the application of eco-feedback strategies was the household, where eco-feedback was used to reduce energy and water consumption, monitor household waste, and promote behaviour change. Although fewer in number, other studies demonstrated the application of eco-feedback in domains such as the automotive industry, buildings, and environmental monitoring.

The following list is organized by descending year of publication and application domain.

4 The EFF

The EFF is a design framework encompassing 39 eco-feedback strategies categorized into five main types: direct, indirect, offline, real-time, and accumulated. Additionally, the framework incorporates five design patterns: self-evaluation, comparison, temporal, metaphorical, style, and visual design. The eco-feedback strategies and design patterns presented in this framework can be applied either individually or in combination, depending on the goals of the practitioners or the project. Their applicability is not limited to specific contexts or domains.

Our aim with this framework is to offer practitioners a set of actionable strategies for designing more effective eco-feedback UIs. These strategies are considered eco-feedback strategies because they represent planned, systematic approaches intended to influence behaviour to achieve specific environmental goals, such as reducing energy consumption, water use, or emissions.⁶⁸

The EFF provides designers and researchers with a theoretical and practical basis for creating more engaging and effective eco-feedback systems. The framework integrates several aspects of eco-feedback previously treated in isolation in the academic literature. Figure 3 depicts how the framework is structured.

Figure 3.

Eco-feedback framework structure.

In the next sections, we introduce the main components of the EFF, starting with the type of feedback.

4.1 Types of feedback

We identify five types of feedback: direct, indirect, offline, real-time, and accumulated. Each type of feedback can function independently or be combined with other eco-feedback strategies to enhance the user experience regarding energy consumption and decision-making processes. Each type can target different behaviours. For instance, they can inform users about energy consumption, nudge them towards better energy management or raise awareness about ecological impacts or economic waste, such as leaving appliances in standby mode, excessive use of air conditioning and heating or inefficient water heaters. Tables 2 –6 summarize the different eco-feedback strategies, which total 39 strategies.

Table 2.
Direct feedback.

Direct feedback Definition How it can be used to reduce energy consumption

Context-sensitive Information or guidance tailored to specific situational or environmental factors. To characterize the situation of entities, it is often presented as a reminder, whereby individuals are prompted with contextual information related to their behaviour. This could include suggestions on appropriate driving techniques (e.g. avoiding high speeds to save energy and improve safety) or energy-saving practices (e.g. switching off an appliance).

Negative Identifies areas where performance, behaviour or outcomes fall short of expectations or established standards. To provide negative information related to the user's behaviour, highlighting undesirable actions or outcomes and signalling that current practices are inefficient or environmentally harmful (e.g. ‘Your energy use is 20% above the recommended level’ or ‘This voyage consumed more fuel than the previous week’).

Positive Highlights areas where performance, behaviour or outcomes are perceived as strong and well-executed by the user in a specific context. To reinforce desirable behaviours by acknowledging or rewarding actions that align with energy efficiency or environmental goals. It highlights successful outcomes (e.g. ‘Your energy consumption is 15% below the recommended level’).

Consumption Information is provided to users to understand their energy consumption patterns. To provide information about energy or fuel consumption and encourage energy savings. In certain contexts, it can also represent the associated environmental consequences or monetary costs related to the energy consumed by the user (e.g. ‘This voyage will consume more than 15% more fuel than your previous voyage’).

Hybrid system indicator Visual cues or displays on a hybrid vehicle's dashboard that provide real-time information about the vehicle's hybrid powertrain. To provide users with information about the status and performance of combined energy systems, such as engines, batteries or renewable sources (e.g. a panel shows when engines or batteries are operating optimally versus when energy is being wasted).

Eco-mode Information or visual cues are provided to a driver when a vehicle is operating in eco-mode, indicating that the car is in a sustainable or ecological setting, which is designed to produce lower emissions. To indicate that the user is operating in an ecological or economic mode. It keeps the user aware of their current energy consumption patterns. When this feedback is provided, the user receives a visual indicator showing that the operation is efficient and eco-friendly.

Eco-driving coach System built into a vehicle that provides real-time feedback and tips to guide drivers toward more fuel-efficient and environmentally friendly driving habits. To advise the user during a trip and encourage energy-efficient driving by providing notifications about driving behaviour (e.g. ‘Smooth acceleration saves fuel!’ or ‘Optimize gear shifts’). It is often accompanied by visual content.

Biophilic rewards Incorporates nature-related elements (plants, animals, and materials) or gamification into the UI. To encourage energy-efficient behaviour by providing positive feedback through visual representations to enhance the user experience or through visual metaphors (e.g. growing leaves, trees, or butterflies) that symbolize the user's positive actions and reinforce energy-saving behaviour.

Frequency How often feedback is prompted; regular feedback can help users develop habits and make informed decisions over time. To inform users about how often a specific energy-related behaviour occurs, helping them become aware of patterns that may lead to excessive consumption (e.g. a dashboard might show how many times a device was left running or how frequently a driver exceeded the optimal speed).

Direct feedback	Definition	How it can be used to reduce energy consumption
Context-sensitive	Information or guidance tailored to specific situational or environmental factors.	To characterize the situation of entities, it is often presented as a reminder, whereby individuals are prompted with contextual information related to their behaviour. This could include suggestions on appropriate driving techniques (e.g. avoiding high speeds to save energy and improve safety) or energy-saving practices (e.g. switching off an appliance).
Negative	Identifies areas where performance, behaviour or outcomes fall short of expectations or established standards.	To provide negative information related to the user's behaviour, highlighting undesirable actions or outcomes and signalling that current practices are inefficient or environmentally harmful (e.g. ‘Your energy use is 20% above the recommended level’ or ‘This voyage consumed more fuel than the previous week’).
Positive	Highlights areas where performance, behaviour or outcomes are perceived as strong and well-executed by the user in a specific context.	To reinforce desirable behaviours by acknowledging or rewarding actions that align with energy efficiency or environmental goals. It highlights successful outcomes (e.g. ‘Your energy consumption is 15% below the recommended level’).
Consumption	Information is provided to users to understand their energy consumption patterns.	To provide information about energy or fuel consumption and encourage energy savings. In certain contexts, it can also represent the associated environmental consequences or monetary costs related to the energy consumed by the user (e.g. ‘This voyage will consume more than 15% more fuel than your previous voyage’).
Hybrid system indicator	Visual cues or displays on a hybrid vehicle's dashboard that provide real-time information about the vehicle's hybrid powertrain.	To provide users with information about the status and performance of combined energy systems, such as engines, batteries or renewable sources (e.g. a panel shows when engines or batteries are operating optimally versus when energy is being wasted).
Eco-mode	Information or visual cues are provided to a driver when a vehicle is operating in eco-mode, indicating that the car is in a sustainable or ecological setting, which is designed to produce lower emissions.	To indicate that the user is operating in an ecological or economic mode. It keeps the user aware of their current energy consumption patterns. When this feedback is provided, the user receives a visual indicator showing that the operation is efficient and eco-friendly.
Eco-driving coach	System built into a vehicle that provides real-time feedback and tips to guide drivers toward more fuel-efficient and environmentally friendly driving habits.	To advise the user during a trip and encourage energy-efficient driving by providing notifications about driving behaviour (e.g. ‘Smooth acceleration saves fuel!’ or ‘Optimize gear shifts’). It is often accompanied by visual content.
Biophilic rewards	Incorporates nature-related elements (plants, animals, and materials) or gamification into the UI.	To encourage energy-efficient behaviour by providing positive feedback through visual representations to enhance the user experience or through visual metaphors (e.g. growing leaves, trees, or butterflies) that symbolize the user's positive actions and reinforce energy-saving behaviour.
Frequency	How often feedback is prompted; regular feedback can help users develop habits and make informed decisions over time.	To inform users about how often a specific energy-related behaviour occurs, helping them become aware of patterns that may lead to excessive consumption (e.g. a dashboard might show how many times a device was left running or how frequently a driver exceeded the optimal speed).

Table 3.

Indirect feedback.

Indirect feedback	Definition	How it can be used to reduce energy consumption
Goal-based	Offers individuals information that compares their current performance or behaviour against predefined objectives.	To inform users about their progress toward specific energy-related targets or goals (e.g. ‘keep your eco-score at 3.0 to save the environment’). This encourages behaviours that align with system objectives, aiming to reduce energy consumption and promote ecological actions.
Recommending action	Suggests specific actions users can take based on the information provided. This dimension aims to encourage users to take practical steps towards behaviour change in response to the feedback they receive.	To provide users with suggestions or guidance on specific behaviours that can improve energy efficiency (e.g. ‘reduce speed by 1 knot to save fuel’ or ‘turn off unused equipment during the voyage’). This encourages users to take practical steps that directly contribute to reducing energy consumption.
Pecuniary	Emphasizes the monetary implications of energy use, helping users recognize the cost benefits and savings associated with their consumption patterns.	To inform users about the monetary consequences of their energy consumption, helping them understand the financial impact of their behaviour. This can provide comparisons of monthly or yearly energy costs and potential savings (e.g. ‘this voyage has cost $150 in fuel’ or ‘leaving lights on overnight costs $5 per day’). This encourages users to adopt energy-saving actions and enhances energy awareness.
Social sharing	Information and cues individuals about users’ environmental behaviours, concerning those of others.	To nudge users through peer-to-peer comparison in a social context. This encourages energy-efficient behaviour by allowing users to share their performance or achievements with others. Such social visibility can create a sense of accountability or friendly competition that motivates sustainable actions (e.g. ‘beat your friend by reducing 10% of energy use this week’ or ‘you’re among the top 5 energy savers in the country’).
Intergroup	Information is provided to a group that the participant is part of.	To foster energy-efficient behaviour by comparing the performance of different groups or teams (e.g. ‘Group A is leading the chart and has reduced consumption by 8% this week’). This generates a climate of competition between groups of consumers, leveraging social dynamics and collective motivation to encourage sustainable practices and fostering collaboration and healthy competition towards energy-saving goals.
Interpersonal	Exchange of information or evaluations between individuals in a social context.	To provide energy-saving- or consumption-related feedback to individuals in the same social context (e.g. ‘your colleague has saved 50 h of energy, equivalent to 5 wind turbine miles’). This helps increase energy awareness and highlights consumption patterns among individuals in the same social setting.
Production	Information provided to individuals or community regarding their energy production activities.	To provide information related to energy production, such as the resources used to generate electricity or the associated environmental impact (e.g. ‘your city produced 30% of its energy using solar panels’). In vehicles, this can show how energy is being generated or recovered (e.g. through regenerative braking). This helps users develop an awareness of energy generation processes and their connection to overall consumption.

Table 4.

Offline feedback.

Offline feedback	Definition	How it can be used to reduce energy consumption
Social	Based on social norms theory, messages, or advice to nudge the user towards pro-environmental behaviours.	To compare an individual's energy use to that of their peers (e.g. ‘this week you saved more energy than your neighbour’). This can motivate users to adopt more efficient behaviours through competition or social pressure, further encouraging them to reduce their usage and align with more sustainable practices.
Inadvertent	Information or cues that users receive unintentionally as a by-product of their actions or interactions with a system or environment.	To help users learn by association through unintentional or indirect information about energy use (e.g. a more energy-efficient appliance may reduce electricity consumption, or a driver may notice higher fuel use when driving aggressively). This raises awareness of inefficient behaviours and encourages energy-conscious actions.
Additional information	Additional contextual data that help the user understand the impact of their actions in comparison to other behaviours or environmental goals.	To provide users with supplementary information to guide energy-efficient behaviour. This can include estimated carbon footprint reduction, potential energy or fuel savings or the environmental impact of specific actions (e.g. choosing a lower-speed setting). These insights can be presented visually through metaphors, icons, or other visual cues.

Table 5.

Real-time (just-in-time) feedback.

Real-time feedback	Definition	How it can be used to reduce energy consumption
Eco-accelerometer	Provides drivers with real-time information about their driving habits in relation to eco-friendly practices.	To present eco-gauges with feedback on acceleration behaviour. The gauge has an eco-range of acceleration (e.g. a dashboard might display a visual cue or alert when rapid acceleration occurs). This encourages energy-efficient driving or navigation by prompting the user to adopt smoother driving habits to save energy.
Eco-indicator	A visual indicator displayed on the vehicle's dashboard that provides real-time feedback to show the driver how efficiently they are driving.	To provide feedback on environmental data in an easily interpretable visual form (e.g. a colour-coded gauge, visual indicator, or symbolic metaphor). This type of feedback helps users understand the impact of their actions or system performance, enabling them to make more energy-conscious decisions.
Haptic pedal	Information is provided through touch and vibration to communicate sensations or feelings.	To deliver feedback through haptic responses (e.g. vibrations, resistance, counter pressure, or pulses). This warns the driver to make immediate adjustments to maintain smoother pedal control, thereby promoting more energy-efficient driving behaviour.
Regenerative (energy recovery)	Real-time information is provided through visual indicators or data on the vehicle's dashboard, informing the driver about how efficiently the regenerative braking system is functioning.	To provide feedback about energy recovery through visual representations (e.g. animations showing the energy flow between the battery and the engine). This helps users understand how energy is regenerated during operation, enhancing energy awareness and promoting more efficient behaviour.
Measurement unit	A standard quantity used to express and quantify physical properties, often displayed as units of measurement such as miles per gallon (MPG), kilometres per litre (km/L), kilowatt-hours (kWh) or carbon footprint equivalents (e.g. CO₂ emissions).	To deliver analytical or numeric indicators that display fuel or energy consumption values on dashboards or screens (e.g. ‘your motor is running at 30 MPG’ or ‘you have consumed 15 kWh this morning’). This provides users with precise and quantifiable information about their consumption, allowing them to monitor efficiency levels and identify opportunities to reduce energy use.
Utility-controlled	Mechanisms implemented and managed by utility companies to provide information to consumers about their energy usage.	To reduce energy consumption by providing signals from an external system (e.g. an energy provider or fleet manager) about demand peaks or energy availability. (e.g. ‘high demand; reduce consumption temporarily’). This promotes adaptive behaviour and alignment with broader efficiency goals.
Pull/push	Push feedback involves real-time notifications or alerts to encourage immediate action. Pull feedback allows users to access information voluntarily.	To reduce energy consumption by delivering information in complementary ways. Push feedback prompts immediate energy-saving actions (e.g. ‘reduce energy usage during peak hours’). Pull feedback allows users to request information (e.g. by checking energy dashboards or reports). Push/pull strategies increase awareness and encourage timely, informed decisions that promote more efficient energy use.
Duration	The length of time over which feedback is provided or monitored indicates how frequently or continuously users receive information regarding their energy consumption.	To reduce energy consumption by allowing users to monitor their energy use continuously or at regular intervals (e.g. a system may display daily, weekly or monthly energy consumption trends). This can help users identify patterns, track progress, and adjust behaviour to save energy.
Content	Information shown to the user about their energy use, which can vary based on detail, relevance or context.	To reduce energy consumption by providing users with relevant and contextual information about their energy use (e.g. ‘you’re using more energy in the evenings’). This helps users understand where energy is being wasted and make informed decisions to adopt more efficient behaviours.
Power meter	Information provided in real time through a power meter display, typically found in hybrid or electric vehicles, shows the vehicle's power consumption and energy flow.	To reduce energy consumption by providing real-time or aggregated measurements of electricity or fuel usage (e.g. a dashboard may display the current power draw of devices, total energy consumed during a voyage or carbon footprint in g CO₂ or kWh). This helps users identify high-consumption behaviours and adjust their operations to use energy more efficiently.
Mileage feedback	Information on the distance a vehicle has travelled and its fuel or energy consumption efficiency.	To reduce energy consumption by providing users with real-time numerical information about their energy use (e.g. MPG or km/L). This helps raise energy awareness by linking driving performance to environmental impact or cost savings, encouraging eco-driving habits.

Table 6.

Accumulated feedback.

Accumulated feedback	Definition	How it can be used to reduce energy consumption
Relative range	The distance a vehicle can travel on its current fuel or energy level compared to a reference point, such as past performance, average usage, or the expected range under similar conditions.	To inform users how far the vehicle can travel based on current fuel or energy levels compared to past performance or expected efficiency (e.g. a display might show ‘range reduced by 10% due to high speed’). This enhances energy awareness by prompting the user to adjust driving behaviour to extend the range and optimize energy use.
Historical comparison	Compares current energy consumption with the user's past usage over different time intervals (e.g. daily, weekly, monthly, or yearly).	To help users recognize changes and trends in their energy use over time (e.g. ‘you used 12% more energy this week compared to last week’). This enables users to quickly gain an overview of their energy usage patterns, facilitating a deeper understanding of their consumption behaviours and motivating them to adopt more efficient habits to maintain or improve past performance.
Summary statistics data	A summary of key metrics and insights into how energy has been used over a specified period, typically displayed on the vehicle's dashboard.	To provide users with a concise overview of their performance and efficiency trends over time (e.g. ‘average fuel efficiency this week: 5.8 km/L; average CO₂ emitted: 2.4 kg’). This helps users identify inefficiencies, set improvement goals and stay motivated to adopt more sustainable driving or operational habits, which can ultimately lead to long-term behaviour change.
Data granularity	Level of detail at which energy consumption information is provided to the user. It can range from broad summaries (e.g. total energy used per week) to fine-grained data (e.g. energy consumed by each device or during specific trips).	To provide users with feedback at different levels of detail, from high-level summaries to fine-grained, device- or trip-specific information. For example, a system might show energy consumption per device, hour, or journey. This helps users identify specific inefficiencies and adjust their behaviour to optimize energy use.
End-use analysis	Information is provided to the user after a certain period of interaction with the product that sums up their pattern.	To provide graphical representations of energy usage (e.g. bar charts, pie charts, and cumulative graphs) to visually convey energy information. This enhances users’ energy awareness by illustrating end-use analysis for each appliance or piece of equipment, highlighting peak consumption periods, usage duration, and other variables that help users better understand their energy use patterns.

Energy audits	Audit data that present individuals or building occupants with detailed information about their energy consumption, along with recommendations for improving energy efficiency.	To provide energy information through visual infographics or reports, illustrating the breakdown of energy use (e.g. ‘your yearly consumption is equivalent to 3500 kWh’ or ‘this year, you charged your car 500 times, consuming 1000 kWh’). This feedback can be accompanied by recommendations (e.g. upgrading to energy-efficient appliances to reduce costs). This helps users understand their energy consumption over a year, which can increase energy awareness and promote pro-environmental behaviour.
Comparison	Information that evaluates the user's performance at various points in time.	To provide self-comparison feedback (e.g. ‘This month your consumption is 30% lower than last month – keep it up!’). This helps users understand their energy consumption patterns, which can encourage behaviour change and consequently reduce energy use.
Normative comparison	Feedback is based on social or normative norms, which relate to social rules and how people perceive themselves and others in their social group.	To provide users with information about their energy use relative to social or group norms (e.g. ‘your consumption is above the city average’ or ‘keep your consumption below the recommended limit’). This uses group or social norms as a reference to nudge users towards reducing energy by comparing their performance with that of their peers, group or established norms. By showing users how their behaviour differs from the norm, this feedback can encourage behaviour change and ultimately decrease energy consumption. It can be used to influence individuals belonging to the same social context or community.
Breakdown	The process of dividing and detailing energy consumption into specific components makes it easier for users to identify which factors or areas contribute most to their overall usage. This can include analysing consumption by appliance, room, time of day or type of energy use.	To present feedback through graphical representations (e.g. pie charts, bar charts, and stacked graphs) that display consumption from multiple sources over time. This helps users gain a comprehensive view of their energy breakdown, highlighting high- or low-consuming appliances for quick identification, which can lead to more informed decisions and energy-saving behaviour.

4.1.1 Direct feedback

This type of feedback explicitly communicates information about the impact of an action in a clear and understandable way, directly linking the user's behaviour to its environmental consequences. Typically provided shortly after the behaviour occurs, it ensures that users can easily associate their actions with the resulting outcomes (see Table 2).

4.1.2 Indirect feedback

This refers to information or cues given to individuals that indirectly communicate evaluation, guidance, or suggestions about their actions, behaviours, or performance (see Table 3).

4.1.3 Offline feedback

This refers to information, evaluation, or comments provided to individuals outside of real-time or immediate interaction (see Table 4).

4.1.4 Real-time (just-in-time) feedback

This feedback is delivered immediately after an action is taken, allowing for immediate awareness and response (see Table 5).

4.1.5 Accumulated feedback

This refers to the results from aggregating multiple sources or instances of feedback, such as evaluations, assessments or comments collected over days, weeks or months (see Table 6).

4.2 Design patterns

According to Bosch,⁷⁹^(p1) ‘design patterns provide solutions to general design problems that can be customized for particular applications’. We categorize these patterns into self-evaluation and comparative, temporal, style (pragmatic or hedonic), metaphorical, and visual design to guide designers and researchers in creating an eco-feedback UI that meets different needs. For example, feedback can focus on practical actions (pragmatic), use metaphors to convey ideas or compare a user's performance to themselves or others. Each approach helps users achieve their sustainability goals in unique ways.

4.2.1 Self-evaluation and comparative design pattern

Self-evaluation and comparative patterns are often influenced by the context in which feedback is presented. For example, the eco-score can serve as individual feedback reflecting personal progress. However, if the presentation includes an average score from other users, it becomes a comparison. Likewise, self-comparisons can be an assessment of the user's behaviour over time and an indirect comparison when aligned with standardized goals.

4.2.2 Temporal design pattern

The temporal perspective differentiates between immediate feedback (real-time data for instant behavioural adjustments) and long-term cumulative feedback (data that encourage reflection and gradual adjustments over time). The distinctions based on temporal perspective illustrate how feedback can be tailored to meet immediate needs (e.g. adjusting behaviour while driving) or foster long-term reflections on consumption habits.

4.2.3 Style design pattern

The style perspective refers to how eco-feedback is presented to the user. We identify two distinct presentation styles of eco-feedback: pragmatic and hedonic.

4.2.3.1 Pragmatic

The pragmatic style focuses on efficiency, measurable outcomes, and observable behaviours. This style is essential for optimizing actions and promoting better resource utilization because it emphasizes numerical or analytical data. It provides users with concrete feedback to drive immediate improvements in their behaviour.

4.2.3.2 Hedonic

The hedonic style focuses on user experience, emotional responses, and personal satisfaction. This approach examines how individuals perceive their actions and the influence of social dynamics on their behaviour. The emphasis is on subjective experiences, enjoyment, and social context rather than strictly on performance metrics. Such a focus is important for reflecting on and understanding behaviour over time.

4.2.4 Metaphorical

Eco-feedback elements can use visual or conceptual metaphors to represent consumption and encourage sustainable behaviours, often manifesting through symbols or visual representations that evoke natural or behavioural concepts. These elements facilitate comprehension and foster engagement, making abstract ideas about energy use and conservation more relatable and intuitively understandable. By connecting environmental actions with familiar metaphors, such feedback helps users internalize sustainable practices on an emotional and cognitive level, ultimately promoting lasting behavioural change.

4.2.5 Visual design

The visual design perspective encompasses various visual strategies and concepts employed to convey environmental information to users. The components are summarized in Table 7.

Table 7.
Visual design pattern.

Charts and graphs Bar charts

Pie charts

Line graphs

Heat maps

Trend graphs

Cumulative graphs

Historical graphs

Numbers

Icons and symbols Emoji representations (happy/sad faces)

Leaves

Trees

Butterflies

Green checkmark

Green globe

Liquid drop

Colour coding Status indicators (e.g. red for high consumption)

Efficiency levels

Performance indicators

Usage patterns

Warning signals (e.g. yellow)

Glow light

Positive performance (e.g. green or blue)

Progress indicators Growing elements (e.g. trees and leaves)

Progress bars

Timers

Performance tracking visualizations

Gamification elements Badges

Trophies

Leader boards

Shared progress bars

Achievement indicators

Group comparisons

Neighbour usage comparisons

Community benchmarks

Scores or points

Progress bar

Animation Tutorial animations

Instructional icons

Best practice demonstrations

Tips and recommendations graphics

Animated icons

Charts and graphs relate to self-evaluating and temporal feedback by providing visual representations of energy consumption data over time, enabling individuals to assess their energy consumption patterns.

Icons and symbols relate to metaphorical feedback by providing a meaningful representation of energy consumption over time, enabling individuals to grasp abstract or technical data about their energy consumption impacts and encouraging them to think about how their actions affect the environment.

Colour coding provides a semiotic language representation that the user can easily internalize. The use of colours allows for easy identification of patterns or trends in energy consumption, helping users recognize when their energy consumption is high, low, or within desired thresholds.

Progress indicators relate to self-evaluation, metaphorical, and comparison feedback by displaying a visual representation of energy consumption and performance compared to themselves or their peers, enabling individuals to assess their progress towards a goal and compare their performance against a target or previous achievements.

Gamification elements relate to metaphorical and hedonic styles by providing a fun or playful presentation of energy consumption data and patterns, enabling individuals to explore their energy consumption information in an engaging manner.

Animation relates to different visual design patterns, and it can be pragmatic, temporal, hedonic, or metaphorical, providing animated and dynamic visual presentations of energy consumption data or a way to read energy data, providing users with the ability to track their progress, stay engaged with the information, and gain an understanding of their consumption habits.

5 How to use the framework

In the following section, we present a case study that illustrates the practical application of the EFF. It is important to note that the eco-feedback strategies and design patterns presented in the framework can be applied either individually or in combination, depending on the goals of the practitioners or the specific project. In this case study, we combined them to communicate information related to energy consumption in a more meaningful and engaging way.

5.1 Case study: EFF applied in practice

This case study was limited to the conceptual phase and did not include user testing. For this study, we focused on a fuel control system, a digital panel designed to monitor and optimize energy consumption on ships, similar to a cruise control system in a car. The interface displays key parameters such as vessel speed and fuel usage, giving mariners a clear overview of consumption throughout the voyage (see Figure 4).

Figure 4.

Fuel control digital instrument cluster.

To promote energy-efficient operations, we designed three eco-feedback UI concepts for the digital panel (average fuel consumption, summary information, and real-time fuel consumption). These concepts aim to enhance mariners’ energy awareness and encourage behavioural change. To develop the interfaces, we selected 12 eco-feedback strategies from the EFF (see Table 8).

Table 8.

Selected eco-feedback strategies.

Eco-feedback strategies	Type of feedback/pattern	Type of pattern
Historical comparison	Accumulated
Recommending action	Indirect
Bar graph visualization		Visual design
High-consumption zone		Visual design
Eco-zone		Visual design
Mileage feedback	Real-time
Line graph visualization	Visual design
Eco-score	Accumulated
Comparison feedback	Accumulated feedback
Summary statistics data	Accumulated
Eco-indicator	Real-time
Biophilic rewards (leaves)		Metaphorical

From this selected list of strategies, we started the conceptual phase of the UI. These feedback strategies were applied in combination rather than individually. This approach was intended to enhance the presentation of energy-related information, allowing users to reflect more effectively on their consumption patterns and actions.

5.2 Average fuel consumption

The average fuel consumption concept is a UI modal (i.e. a secondary interface window that overlays the main display) (see Figure 5). It is accessible to the captain or crew members to visualize energy consumption data over a specified period. Here, multiple eco-feedback strategies are integrated to help users understand and reflect on their energy performance.

Figure 5.

Average fuel consumption user interface (UI) modal.

5.2.1 Recommending action

The first strategy is recommending action, which suggests specific actions users can take based on the information provided. This feedback is mostly delivered as text. Here, it indicates that fuel consumption in January exceeds the eco-zone, which represents the recommended limit or threshold.

5.2.2 Historical comparison

The second strategy is historical comparison, which is categorized as accumulated feedback. This feedback results from the aggregation of multiple instances of data over time. It compares current consumption with past consumption by the same user over short periods (daily or weekly) or long periods (monthly or yearly). This strategy increases the captain's awareness of the vessel's energy consumption and promotes more efficient and informed operation.

5.2.3 Bar graph visualization

The interface also includes a bar graph visualization, using the charts and graphs’ visual design pattern. This type of visual feedback helps users understand overall energy consumption trends by showing how much energy they have consumed each day.

5.2.4 Eco-zone and high-consumption zone

Finally, the interface incorporates eco-zone and high-consumption zone indicators, both of which are based on colour coding, a component of the visual design pattern. The first uses green to represent positive performance, helping users maintain energy use within a sustainable range, while the second uses yellow as a warning signal to alert users when consumption exceeds the recommended limit.

5.3 Summary information

Summary information is a UI modal that can be accessed by the captain or crew members to visualize summary statistical data on energy consumption.

5.3.1 Summary statistical data

These present key metrics and insights into energy usage during a completed voyage. Here, we use it to communicate voyage-related information by combining several eco-feedback strategies to present energy consumption data in a comprehensible way (see Figure 6).

Figure 6.

Summary statistical data.

5.3.2 Eco-score

The eco-score represents an efficiency metric based on energy consumption during a voyage. This feedback is less technical and easier for users to interpret: A low score indicates higher energy consumption, whereas a high score reflects greater efficiency. By translating complex fuel data into a simple score, users can quickly understand their performance and are encouraged to adopt more energy-efficient behaviours.

5.3.3 Recommending action

We also include recommending action, which represents indirect feedback. This type of feedback provides information or cues that convey evaluation, guidance, or suggestions regarding users’ actions. In this case, the UI offers advice for the next voyage to help reduce energy consumption.

5.3.4 Eco-indicator

Additionally, the UI features an eco-indicator, a real-time visual indicator displayed on the dashboard to show the captain how efficiently and sustainably the voyage is proceeding. This visual indicator is associated with the metaphorical design pattern using icons and symbols.

Metaphors to represent consumption or encourage sustainable behaviours often use symbols or visual representations that evoke natural concepts. Furthermore, metaphors facilitate the comprehension of energy consumption by making abstract or technical units more relatable and intuitively understandable, thereby fostering engagement.

5.3.5 Comparison

Finally, we added comparison feedback, which assesses the user's current performance against past performance. This can increase energy awareness and encourage pro-environmental behaviour.

5.4 Real-time fuel consumption

5.4.1 Real-time feedback

In the third UI concept, we applied a real-time feedback strategy, which allows for instant awareness and response (see Figure 7). This enhances the understanding of the ship's energy dynamics and encourages more informed sailing behaviours.

Figure 7.

Real-time fuel consumption.

5.4.2 Line graph visualization

The use of a line graph to visualize energy consumption in real time is particularly important for decision-making during ship operations. This visual feedback can help the captain optimize sailing techniques to maximize efficiency and minimize energy waste.

5.4.3 Mileage feedback

In this concept, two-line graphs are used to represent fuel consumption and speed. These two types of information are expressed through mileage feedback, a form of real-time feedback that provides operators with information about the distance travelled and the efficiency of fuel or energy consumption.

5.4.4 Eco-zone and high-consumption zone

Finally, the interface incorporates eco-zone and high-consumption zone indicators, both based on colour coding, a component of the visual design pattern. The first uses green to represent positive performance, helping users maintain energy use within a sustainable range, while the second uses yellow as a warning signal to alert users when consumption exceeds the recommended limit. These visual cues play a crucial role in supporting decision-making during a voyage.

6 Discussion

In our systematic literature review, we identified key eco-feedback strategies and design patterns to inform UI development for energy management systems. Based on our review, we developed the EFF to provide a structured approach to designing and evaluating eco-feedback mechanisms. However, several opportunities and considerations remain.

6.1 Opportunities for applying the EFF in design research

The EFF is intended as a practical resource for researchers and practitioners in HCI and related fields. It can serve multiple purposes across different stages of the design research process, as follows:

Qualifying eco-feedback in empirical studies: The EFF structure and categories can be used to describe in detail how different feedback mechanisms may influence user behaviour in experimental settings.

Supporting explorative design: The EFF can serve as a guide when exploring the solution space for designing energy-efficient UIs. The eco-feedback design patterns can provide researchers with interaction techniques and visual metaphors.

Developing design guidelines: The EFF can also be used to develop guidelines for designing eco-feedback interfaces. It provides a structured approach to analysing design precedence, which involves examining previous design solutions to inform current decisions, and links eco-feedback strategies to the core design patterns for eco-feedback UI design.

Supporting co-design processes: The EFF can be integrated into design workshops and participatory design sessions to frame discussions and generate design ideas.

Helping to bridge theory and practice in HCI: The EFF contributes to linking theoretical perspectives on behavioural change with practical UI design strategies.

6.2 Key considerations for eco-feedback design

6.2.1 Aesthetic considerations

The EFF addresses aesthetics through visual design patterns, providing designers with UI content examples for eco-feedback systems. Topics such as how perceived attractiveness and emotional responses influence motivation and trust are not yet well covered by the framework. This is important because the aesthetic dimension of UIs should not focus only on the visual appeal of a representation but also on the effect they evoke (see, e.g. Bartram⁸⁰).

6.2.2 Alignment with user goals

Effective eco-feedback must align with users’ motivations and contextual needs. The EFF incorporates self-evaluation, comparison, temporal and metaphorical patterns to support this alignment. Topics such as how eco-feedback interfaces resonate with user perspectives to foster trust and long-term behavioural change are not yet well covered by the framework. This is important because feedback is more effective when it aligns with users’ goals (see, e.g. Sanguinetti et al.⁴⁰).

Moreover, metrics such as carbon footprints or kilowatt-hours often create barriers for users in understanding energy information.³³ From a user perspective, technical units are difficult to interpret and demand greater cognitive effort, which can reduce the overall effectiveness of feedback.^41,65 Therefore, using metaphors to convey energy consumption information tends to be more effective and easier for users to comprehend.⁵⁵

6.2.3 Presentation modes and feedback saliency

How eco-feedback is presented plays a key role in user comprehension and engagement. The EFF includes metaphorical and hedonic style patterns to enhance saliency. Other topics not yet well covered by the EFF include the impact of gamification, storytelling and immersive feedback (e.g. ambient and auditory cues) on supporting knowledge internalization and behavioural change.

Calitz et al.⁷⁶ argue that using metaphors can simplify feedback by transforming complex energy metrics into more accessible and relatable representations. Similarly, Avolicino et al.³² found that providing eco-feedback in the form of metaphors, rather than raw data, can enhance users’ understanding and attention to the feedback received. Bartram⁸⁰ also emphasizes that people tend to prefer receiving information in artistic or metaphorical forms that demand less cognitive effort. For example, representing energy usage through a metaphor such as a ‘dying tree’ can engage users more effectively than presenting numerical data alone. This approach not only reduces users’ cognitive load but also provides a more visual and emotionally engaging form of feedback.^55,76.

6.2.4 Long-term impact of eco-feedback

The EFF integrates self-evaluation and hedonic design patterns to support long-term engagement. Topics such as how pecuniary feedback, self-monitoring, and social comparison contribute to sustained energy-saving behaviours are not yet well covered by the EFF.

6.2.5 An interaction design perspective on eco-feedback

In addition to research focusing on eco-feedback as a technological tool for reducing energy consumption, we propose that eco-feedback research should also adopt an interaction design perspective, focusing, for example, on how to apply eco-feedback strategies across delivery platforms, including mobile, desktop, and ambient interfaces, and across physical interactions and modalities, such as ambient audio or haptic feedback. In future research, we will apply this framework in the maritime setting to explore how people interact with eco-feedback and make decisions that impact energy consumption and emissions reduction.

7 Conclusion

The EFF contributes to HCI, interaction design, and related research fields for both practitioners and researchers. For practitioners, it offers actionable guidance for designing UIs for energy consumption management and the promotion of sustainable behaviours. For researchers, the EFF serves as a tool for better understanding how eco-feedback strategies and design patterns can drive energy conservation. This study contributes to maritime decarbonization as a baseline for designing better feedback systems aimed at reducing energy consumption within maritime settings.

We argue that the EFF can serve as a creative and practical tool to help practitioners and researchers design better eco-feedback UIs for maritime equipment. These UIs aim to reduce energy consumption by raising energy awareness and promoting behavioural change among seafarers, encouraging the optimal use of equipment and energy and, from a cognitive perspective, guiding seafarers towards pro-environmental behaviour that ultimately benefits both the crew and the environment.

Footnotes

Acknowledgements

We would like to thank the Maritime Group at the Technical University of Denmark (DTU) and DNV for organizing the 25th DNV Nordic Maritime Universities Workshop. We were able to present this study at the workshop and received useful feedback. Special thanks to Mostafa Amini for leading the event and providing important information for the submission.

ORCID iDs

Filipe Landu Nzongo

Etienne Gernez

Kjetil Nordby

Author contributions

Filipe Landu Nzongo: Conceptualization; Formal analysis; Methodology; Writing – original draft.

Etienne Gernez: Writing – review & editing.

Kjetil Nordby: Conceptualization; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by the Norwegian Research Council – project number 344160: OpenZero – Digital UI design for energy-conscious and safe maritime operations.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Charts and graphs	Bar charts
	Pie charts
	Line graphs
	Heat maps
	Trend graphs
	Cumulative graphs
	Historical graphs
	Numbers
Icons and symbols	Emoji representations (happy/sad faces)
	Leaves
	Trees
	Butterflies
	Green checkmark
	Green globe
	Liquid drop
Colour coding	Status indicators (e.g. red for high consumption)
	Efficiency levels
	Performance indicators
	Usage patterns
	Warning signals (e.g. yellow)
	Glow light
	Positive performance (e.g. green or blue)
Progress indicators	Growing elements (e.g. trees and leaves)
	Progress bars
	Timers
	Performance tracking visualizations
Gamification elements	Badges
	Trophies
	Leader boards
	Shared progress bars
	Achievement indicators
	Group comparisons
	Neighbour usage comparisons
	Community benchmarks
	Scores or points
	Progress bar
Animation	Tutorial animations
	Instructional icons
	Best practice demonstrations
	Tips and recommendations graphics
	Animated icons