Gamification Approaches and Assessment Methodologies for Occupants’ Energy Behavior Change in Buildings: A Systematic Review
Abstract
:1. Introduction
1.1. Building Energy Solution and Human Disruption
1.2. Gamification and Serious Games in Behavioral Transformation
1.3. Previous Literature Studies
1.4. Scope, Research Questions and Novelty of This Systematic Review
2. Materials and Methods
2.1. Searching Strategy
2.2. Data Collection
2.3. Data Analysis
3. Results
3.1. Gamification Integration into Building Systems
3.1.1. Gamification in Different Building Types
3.1.2. Gamification Techniques Utilization and Their Performance
3.1.3. Gamification Interface Integration and Design of Gamifying Elements
3.1.4. Gamification Mechanism and User Engagement
3.2. Assessment Methodologies of Gamification Performance for Driving Users’ Energy Behavior Change
4. Discussion
4.1. Relationships and Challenges in Gamification Implementation
4.2. Gamification Strategies Tailored Building Types and User Profiles
4.3. Integrating Extrinsic and Intrinsic Motivators in Gamification
4.4. Gamification in Building Components
4.5. Quantitative and Qualitative Assessment Approaches
5. Conclusions and Future Recommendations
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
References
- IEA. World Energy Outlook 2023; IEA: Paris, France, 2023. Available online: https://www.iea.org/reports/world-energy-outlook-2023 (accessed on 24 October 2023).
- Office for National Statistics (ONS). Energy Efficiency of Housing in England and Wales: 2023; Office for National Statistics (ONS): Newport, UK, 2023.
- Parsaee, M.; Demers, C.M.; Hébert, M.; Lalonde, J.F.; Potvin, A. Biophilic, photobiological and energy-efficient design framework of adaptive building façades for Northern Canada. Indoor Built Environ. 2021, 30, 665–691. [Google Scholar] [CrossRef]
- Ascione, F.; Bianco, N.; Iovane, T.; Mastellone, M.; Mauro, G.M. The evolution of building energy retrofit via double-skin and responsive façades: A review. Sol. Energy 2021, 224, 703–717. [Google Scholar] [CrossRef]
- Loonen, R.C.G.M.; Favoino, F.; Hensen, J.L.M.; Overend, M. Review of current status, requirements and opportunities for building performance simulation of adaptive facades†. J. Build. Perform. Simul. 2017, 4, 205–223. [Google Scholar] [CrossRef]
- Khan, M.; Seo, J.; Kim, D. Towards energy efficient home automation: A deep learning approach. Sensors 2020, 20, 7187. [Google Scholar] [CrossRef] [PubMed]
- Tabadkani, A.; Roetzel, A.; Li, H.X.; Tsangrassoulis, A. A review of automatic control strategies based on simulations for adaptive facades. Build. Environ. 2020, 175, 106801. [Google Scholar] [CrossRef]
- Bakker, L.G.; Hoes-van Oeffelen, E.C.M.; Loonen, R.C.G.M.; Hensen, J.L.M. User satisfaction and interaction with automated dynamic facades: A pilot study. Build. Environ. 2014, 78, 44–52. [Google Scholar] [CrossRef]
- Dong, B.; Prakash, V.; Feng, F.; O’Neill, Z. A review of smart building sensing system for better indoor environment control. Energy Build. 2019, 199, 29–46. [Google Scholar] [CrossRef]
- Attia, S. Challenges and Future Directions of Smart Sensing and Control Technology for Adaptive Facades Monitoring. In Proceedings of the COST Action TU1403–Adaptive Facades Network Final Conference, Lucerne University of Applied Sciences and Arts, Lucerne, Switzerland, 26 November 2018. [Google Scholar]
- Heidari Matin, N.; Eydgahi, A. A data-driven optimized daylight pattern for responsive facades design. Intell. Build. Int. 2021, 14, 363–374. [Google Scholar] [CrossRef]
- Abuimara, T.; Hobson, B.W.; Gunay, B.; O’Brien, W. A data-driven workflow to improve energy efficient operation of commercial buildings: A review with real-world examples. Build. Serv. Eng. Res. Technol. 2022, 43, 014362442110696. [Google Scholar] [CrossRef]
- Mokhtar, S.; Leung, C.; Chronis, A. Geometry-material coordination for passive adaptive solar morphing envelopes. Simul. Ser. 2017, 49, 172–179. [Google Scholar] [CrossRef]
- Kuru, A.; Oldfield, P.; Bonser, S.; Fiorito, F. Performance prediction of biomimetic adaptive building skins: Integrating multifunctionality through a novel simulation framework. Sol. Energy 2021, 224, 253–270. [Google Scholar] [CrossRef]
- Obaleye, O.J.; Opaluwa, E.; Ajayi, O.O.; Babamboni, A.S. Understanding the Relationship between Users’ and Experts’ Perception of University Senate Building Façade Elements in Southwest Nigeria. Caleb Int. J. Dev. Stud. 2021, 4, 181–197. [Google Scholar] [CrossRef]
- De La Barra, P.; Luna-Navarro, A.; Prieto, A.; Vásquez, C.; Knaack, U. Influence of Automated Façades on Occupants: A Review. J. Facade Des. Eng. 2022, 10, 19–38. [Google Scholar] [CrossRef]
- Delzendeh, E.; Wu, S.; Lee, A.; Zhou, Y. The impact of occupants’ behaviours on building energy analysis: A research review. Renew. Sustain. Energy Rev. 2017, 80, 1061–1071. [Google Scholar] [CrossRef]
- Paone, A.; Bacher, J.P. The impact of building occupant behavior on energy efficiency and methods to influence it: A review of the state of the art. Energies 2018, 11, 953. [Google Scholar] [CrossRef]
- Deterding, S.; Dixon, D.; Khaled, R.; Nacke, L. From game design elements to gamefulness: Defining “gamification”. In Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek, Tampere, Finland, 28–30 September 2011; pp. 9–15. [Google Scholar] [CrossRef]
- Wünderlich, N.V.; Gustafsson, A.; Hamari, J.; Parvinen, P.; Haff, A. The great game of business: Advancing knowledge on gamification in business contexts. J. Bus. Res. 2020, 106, 273–276. [Google Scholar] [CrossRef]
- Saleem, A.N.; Noori, N.M.; Ozdamli, F. Gamification Applications in E-learning: A Literature Review. Technol. Knowl. Learn. 2022, 27, 139–159. [Google Scholar] [CrossRef]
- Antonaci, A.; Klemke, R.; Specht, M. The effects of gamification in online learning environments: A systematic literature review. Informatics 2019, 6, 32. [Google Scholar] [CrossRef]
- Sardi, L.; Idri, A.; Fernández-Alemán, J.L. A systematic review of gamification in e-Health. J. Biomed. Inform. 2017, 1, 31–48. [Google Scholar] [CrossRef]
- Comello, M.L.G.; Qian, X.; Deal, A.M.; Ribisl, K.M.; Linnan, L.A.; Tate, D.F. Impact of game-inspired infographics on user engagement and information processing in an ehealth program. J. Med. Internet Res. 2016, 18, e237. [Google Scholar] [CrossRef]
- Marczewski, A. Gamification: A Simple Introduction. N.p.: Andrzej Marczewski 2013. Available online: https://www.google.co.uk/books/edition/Gamification_A_Simple_Introduction/IOu9kPjlndYC?hl=en (accessed on 14 May 2024).
- Iria, J.; Fonseca, N.; Cassola, F.; Barbosa, A.; Soares, F.; Coelho, A.; Ozdemir, A. A gamification platform to foster energy efficiency in office buildings. Energy Build. 2020, 222, 110101. [Google Scholar] [CrossRef]
- Soares, F.; Madureira, A.; Pagès, A.; Barbosa, A.; Coelho, A.; Cassola, F.; Ribeiro, F.; Viana, J.; Andrade, J.; Dorokhova, M.; et al. Feedback: An ict-based platform to increase energy efficiency through buildings’ consumer engagement. Energies 2021, 14, 1524. [Google Scholar] [CrossRef]
- Vandenbogaerde, L.; Verbeke, S.; Audenaert, A. Optimizing building energy consumption in office buildings: A review of building automation and control systems and factors influencing energy savings. J. Build. Eng. 2023, 76, 107233. [Google Scholar] [CrossRef]
- Johnson, D.; Horton, E.; Mulcahy, R.; Foth, M. Gamification and serious games within the domain of domestic energy consumption: A systematic review. Renew. Sustain. Energy Rev. 2017, 73, 249–264. [Google Scholar] [CrossRef]
- Darejeh, A.; Salim, S.S. Gamification Solutions to Enhance Software User Engagement—A Systematic Review. Int. J. Hum.-Comput. Interact. 2016, 32, 613–642. [Google Scholar] [CrossRef]
- Khakpour, A.; Colomo-Palacios, R. Convergence of Gamification and Machine Learning: A Systematic Literature Review. Technol. Knowl. Learn. 2021, 26, 597–636. [Google Scholar] [CrossRef]
- Konstantakopoulos, I.C.; Barkan, A.R.; He, S.; Veeravalli, T.; Liu, H.; Spanos, C. A deep learning and gamification approach to improving human-building interaction and energy efficiency in smart infrastructure. Appl. Energy 2019, 237, 810–821. [Google Scholar] [CrossRef]
- Franco, A. Balancing user comfort and energy efficiency in public buildings through social interaction by ICT systems. Systems 2020, 8, 29. [Google Scholar] [CrossRef]
- Wu, X.; Liu, S.; Shukla, A. Serious games as an engaging medium on building energy consumption: A review of trends, categories and approaches. Sustainability 2020, 12, 8508. [Google Scholar] [CrossRef]
- Konstantakopoulos, I. Statistical Learning Towards Gamification in Human-Centric Cyber-Physical Systems. University of California, Berkeley; 2018. Available online: http://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-139.html (accessed on 14 May 2024).
- Méndez, J.I.; Ponce, P.; Meier, A.; Peffer, T.; Mata, O.; Molina, A. Empower saving energy into smart communities using social products with a gamification structure for tailored Human–Machine Interfaces within smart homes. Int. J. Interact. Des. Manuf. 2023, 17, 1363–1387. [Google Scholar] [CrossRef]
- Lu, C.H. IoT-enabled adaptive context-aware and playful cyber-physical system for everyday energy savings. IEEE Trans. Hum.-Mach. Syst. 2018, 48, 380–391. [Google Scholar] [CrossRef]
- Méndez, J.I.; Ponce, P.; Pecina, M.; Schroeder, G.; Castellanos, S.; Peffer, T.; Meier, A.; Molina, A. A Rapid HMI Prototyping Based on Personality Traits and AI for Social Connected Thermostats. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Springer Science and Business Media Deutschland GmbH: Berlin/Heidelberg, Germany, 2021; Volume13068 LNAI, pp. 216–227. [Google Scholar] [CrossRef]
- Ferreira, J.C.; Afonso, J.A.; Monteiro, V.; Afonso, J.L. An energy management platform for public buildings. Electronics 2018, 7, 294. [Google Scholar] [CrossRef]
- Avila, M.; Méndez, J.I.; Ponce, P.; Peffer, T.; Meier, A.; Molina, A. Energy management system based on a gamified application for households. Energies 2021, 14, 3445. [Google Scholar] [CrossRef]
- Morton, A.; Reeves, A.; Bull, R.; Preston, S. Empowering and Engaging European building users for energy efficiency. Energy Res. Soc. Sci. 2020, 70, 101772. [Google Scholar] [CrossRef]
- Kim, H.; Ham, S.; Promann, M.; Devarapalli, H.; Bihani, G.; Ringenberg, T.; Kwarteng, V.; Bilionis, I.; Braun, J.E.; Rayz, J.T.; et al. MySmartE—An eco-feedback and gaming platform to promote energy conserving thermostat-adjustment behaviors in multi-unit residential buildings. Build. Environ. 2022, 221, 109252. [Google Scholar] [CrossRef]
- Albertarelli, S.; Fraternali, P.; Novak, J.; Rizzoli, A.-E.; Rottondi, C. DROP and FUNERGY: Two Gamified Learning Projects for Water and Energy Conservation. In Proceedings of the 11th European Conference on Games Based Learning, ECGBL 2017, Graz, Austria, 5–6 October 2017; Academic Conferences and Publishing International Limited: Manchester, UK, 2017; pp. 935–938. [Google Scholar]
- Patlakas, P.; Raslan, R. A computer game to help people understand the energy performance of buildings. Proc. Inst. Civ. Eng. Eng. Sustain. 2017, 170, 308–321. [Google Scholar] [CrossRef]
- Méndez, J.I.; Ponce, P.; Meier, A.; Peffer, T.; Mata, O.; Molina, A. S4 Product Design Framework: A Gamification Strategy Based on Type 1 and 2 Fuzzy Logic. In Lecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Springer: Berlin/Heidelberg, Germany, 2020; Volume 12015 LNCS, pp. 509–524. [Google Scholar] [CrossRef]
- Gangolells, M.; Casals, M.; Macarulla, M.; Forcada, N. Exploring the potential of a gamified approach to reduce energy use and carbon emissions in the household sector. Sustainability 2021, 13, 3380. [Google Scholar] [CrossRef]
- Fraternali, P.; Cellina, F.; Herrera, S.; Krinidis, S.; Pasini, C.; Rizzoli, A.E.; Rottondi, C.; Tzovaras, D. A Socio-Technical System Based on Gamification Towards Energy Savings. In Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Athens, Greece, 19–23 March 2018; pp. 59–64. [Google Scholar] [CrossRef]
- Paris, J.; Cambeiro, J.; Amaral, V.; Rodrigues, A. Using gamification to motivate occupants to energy efficiency in a social setting of a building automation system. In Proceedings of the International Computer Software and Applications Conference, Milwaukee, WI, USA, 15–19 July 2019; Volume 1, pp. 638–643. [Google Scholar] [CrossRef]
- Fraternali, P.; Herrera, S.; Novak, J.; Melenhorst, M.; Tzovaras, D.; Krinidis, S.; Rizzoli, A.E.; Rottondi, C.; Cellina, F. enCOMPASS—An integrative approach to behavioural change for energy saving. In Proceedings of the 2017 Global Internet of Things Summit (GIoTS), Geneva, Switzerland, 6–9 June 2017; pp. 1–6. [Google Scholar] [CrossRef]
- Papaioannou, T.G.; Dimitriou, N.; Vasilakis, K.; Schoofs, A.; Nikiforakis, M.; Pursche, F.; Deliyski, N.; Taha, A.; Kotsopoulos, D.; Bardaki, C.; et al. An IoT-based gamified approach for reducing occupants’ energy wastage in public buildings. Sensors 2018, 18, 537. [Google Scholar] [CrossRef] [PubMed]
- Mendez, J.I.; Ponce, P.; Medina, A.; Peffer, T.; Meier, A.; Molina, A. A smooth and accepted transition to the future of cities based on the standard ISO 37120, artificial intelligence, and gamification constructors. In Proceedings of the 2021 IEEE European Technology and Engineering Management Summit, E-TEMS 2021—Conference Proceedings, Dortmund, Germany, 18–20 March 2021; pp. 65–71. [Google Scholar] [CrossRef]
- Gandhi, P.; Brager, G.S. Commercial office plug load energy consumption trends and the role of occupant behavior. Energy Build. 2016, 125, 1–8. [Google Scholar] [CrossRef]
- Sintov, N.D.; Orosz, M.D.; Wesley Schultz, P. Personalized energy reduction cyber-physical system (PERCS): A gamified end-user platform for energy efficiency and demand response. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Springer: Berlin/Heidelberg, Germany, 2015; Volume 9189, pp. 602–613. [Google Scholar] [CrossRef]
- Friedrich, K.; Eldridge, M.; York, D.; Witte, P.; Kushler, M. Saving Energy Cost-Effectively: A National Review of the Cost of Energy Saved through Utility-Sector Energy Efficiency Programs; 2009; Volume 600. Available online: https://www.aceee.org/sites/default/files/publications/researchreports/U092.pdf (accessed on 14 May 2024).
- Waide, P.; Buchner, B. Utility energy efficiency schemes: Savings obligations and trading. Energy Effic. 2008, 1, 297–311. [Google Scholar] [CrossRef]
- Das, H.P.; Konstantakopoulos, I.C.; Manasawala, A.B.; Veeravalli, T.; Liu, H.; Spanos, C.J. A Novel Graphical Lasso based approach towards Segmentation Analysis in Energy Game-Theoretic Frameworks. In Proceedings of the 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), Boca Raton, FL, USA, 16–19 December 2019. [Google Scholar] [CrossRef]
- Gao, B.; Chen, C.; Qin, Y.; Liu, X.; Zhu, Z. Evolutionary Game-theoretic Analysis for Residential Users Considering Integrated Demand Response. J. Mod. Power Syst. Clean Energy 2021, 9, 1500–1509. [Google Scholar] [CrossRef]
- Gibbens, M.; Gniady, C.; Zhang, B. Towards eco-friendly home networking. Sustainable Computing: Informatics and Systems. Sustain. Comput. Inform. Syst. 2016, 11, 16–25. [Google Scholar] [CrossRef]
- Yu, L.; Xu, Z.; Zhang, T.; Guan, X.; Yue, D. Energy-efficient personalized thermal comfort control in office buildings based on multi-agent deep reinforcement learning. Build. Environ. 2022, 223, 109458. [Google Scholar] [CrossRef]
- Marisa, F.; Sakinah Syed Ahmad, S.; Izzah Mohd Yusoh, Z.; Maukar, A.L.; David Marcus, R.; Aris Widodo, A. Evaluation of Student Core Drives on E-Learning during the COVID-19 with Octalysis Gamification Framework. Int. J. Adv. Comput. Sci. Appl. 2020, 11, 104–116. [Google Scholar] [CrossRef]
- Ratliff, L.J.; Jin, M.; Konstantakopoulos, I.C.; Spanos, C.J.; Sastry, S. Social Game for Building Energy Efficiency: Incentive Design; UC Berkeley: Center for Research in Energy Systems Transformation (CREST): Berkeley, CA, USA, 2014. [Google Scholar]
- Jain, R.K.; Gulbinas, R.; Taylor, J.E.; Culligan, P.J. Can social influence drive energy savings? Detecting the impact of social influence on the energy consumption behavior of networked users exposed to normative eco-feedback. Energy Build. 2013, 66, 119–127. [Google Scholar] [CrossRef]
- Peeters, M.; Megens, C.; van den Hoven, E.; Hummels, C.; Brombacher, A. Social Stairs: Taking the Piano Staircase towards Long-Term Behavioral Change. In Proceedings of the Persuasive Technology: 8th International Conference, PERSUASIVE 2013, Sydney, NSW, Australia, 3–5 April 2013; Volume 7822, pp. 174–179. [Google Scholar] [CrossRef]
- Spangher, L.; Gokul, A.; Khattar, M.; Palakapilly, J.; Tawade, A.; Bouyamourn, A.; Devonport, A.; Spanos, C. Prospective Experiment for Reinforcement Learning on Demand Response in a Social Game Framework. In Proceedings of the e-Energy 2020—Proceedings of the 11th ACM International Conference on Future Energy Systems, Virtual, 22–26 June 2020; pp. 438–444. [Google Scholar] [CrossRef]
- Papaioannou, T.G.; Hatzi, V.; Koutsopoulos, I. Optimal design of serious games for consumer engagement in the smart grid. IEEE Trans. Smart Grid 2018, 9, 1241–1249. [Google Scholar] [CrossRef]
- Chou, Y. Actionable Gamification: Beyond Points, Badges, and Leaderboards; Packt Publishing Ltd.: Birmingham, UK, 2019. [Google Scholar]
- Costa, C.J.; Aparicio, M.; Aparicio, S.; Aparicio, J.T. Gamification usage ecology. In Proceedings of the SIGDOC 2017—35th ACM International Conference on the Design of Communication, Halifax, NS, Canada, 11–13 August 2017. [Google Scholar] [CrossRef]
- Gallego-Durán, F.J.; Villagrá-Arnedo, C.J.; Satorre-Cuerda, R.; Compañ-Rosique, P.; Molina-Carmona, R.; Llorens-Largo, F. A guide for game-design-based gamification. Informatics 2019, 6, 49. [Google Scholar] [CrossRef]
- Verbrugge, R.J. Do the consumer Price index’s utilities adjustments for Owners’ Equivalent Rent distort inflation measurement? J. Bus. Econ. Stat. 2012, 30, 143–148. [Google Scholar] [CrossRef]
App [32,37,48] | HMI [38,45,53] | IoT [39,48,50] | Web-Based [43,52] | ICT [27,46,53] | Software [44] | GUI [32,41] | |
---|---|---|---|---|---|---|---|
User-friendliness | 3 | 3 | 1 | 2 | 1 | 2 | 2 |
Customization | 3 | 3 | 2 | 3 | 2 | 3 | 3 |
Data collection | 3 | 2 | 3 | 2 | 3 | 2 | 2 |
Data analysis | 2 | 2 | 3 | 3 | 2 | 2 | 1 |
Real-time control | 2 | 3 | 3 | 2 | 3 | 3 | 2 |
User accessibility | 3 | 2 | 2 | 1 | 3 | 1 | 2 |
System integration | 3 | 3 | 2 | 3 | 2 | 2 | 3 |
Total score | 19 | 18 | 16 | 16 | 16 | 15 | 15 |
Techniques | Target Interface | Gamification Elements | Resource Utilization | Energy Consumption Savings |
---|---|---|---|---|
HMI | Thermostat, PV, HVAC | Points, feedback, competition, dashboard, statistics | Control, monitoring | 15% [38,40] |
App | Thermostat, PV, smart meters, smart plugs, sensors, HVAC | Feedback, points, challenges, dashboard, statistics, leaderboard | Get user engage in resource interaction | 20% [26] |
IoT | Smart meters, plugs, sensors | Competition, points | Enable real-time automation and data-driven decisions | 40% [50] |
Web-based | Computer | Points, competition, feedback, leaderboard, cooperation | Media and social network to support user engagement | 10% [43] |
Software | Computer | Points | Customization with optimize resource utilization | 8% [44] |
ICT | Lighting, HVAC, meters, plugs | Points, dashboard, feedback, competition, social | Data exchange, communication and collaboration | 15–30% [46] |
GUI | Sensors, meters | Points, dashboard | Visualization, easy to understand | 40% [32] |
Reference | Gamification Principles | Experimental | Duration | N. of Participants | Behavior Change Driver | Assessment Method |
---|---|---|---|---|---|---|
Soares et al., 2021a [27] | Goals, rewards | No | - | - | Accomplishment | - |
Franco 2020 [33] | Goals, social interaction | No | - | - | Social influence | - |
Méndez et al., 2021 [38] | Personalization | No | - | - | Unpredictability | - |
Morton et al., 2020b [41] | Challenges and competition | No | - | - | Empowerment | Surveys |
Albertarelli et al., 2017 [43] | Goals, data analytics | No | - | - | Social influence | User acceptance |
Méndez et al., 2020 [45] | Personalization | No | - | - | Unpredictability | User analytics |
Paris et al., 2019 [48] | Goals, personalization | No | - | - | Unpredictability | - |
Mendez et al., 2021 [51] | Feedback, rewards | No | - | - | Empowerment | - |
Sintov et al., 2015 [53] | Choice and autonomy | No | - | - | Empowerment | - |
Iria et al., 2020 [26] | Challenges and competition | Yes | 2 years | 24 | Social influence and accomplishment | Energy usage |
Konstantakopoulos et al., 2019 [32] | Goals | Yes | 7 months | 72 | Scarcity | Goal achievement |
Lu 2018 [37] | Data and analytics | Yes | 1 year | 22 | Social influence | Energy saving |
Ferreira et al., 2018 [39] | Goals | Yes | 2 months | 80 | Social influence | Surveys |
Avila et al., 2021 [40] | Goals | Yes | 6 months | 30 | Accomplishment | Energy saving |
Kim et al., 2022 [42] | Challenges and competition | Yes | 2 years | 13 | Empowerment and accomplishment | Energy saving |
Patlakas and Raslan 2017 [44] | Rewards | Yes | 2 years | 89 | Ownership | Surveys |
Gangolells et al., 2021 [46] | Goals, feedback | Yes | 1 year | 137 | Epic meaning | Energy saving |
Fraternali et al., 2018 [47] | Rewards, achievement | Yes | 2 years | 2000 | Accomplishment | Surveys |
Fraternali et al., 2017 [49] | Goals, social interaction | Yes | 3 years | 120 | Accomplishment | Surveys |
Papaioannou et al., 2018 [50] | Data and analytics | Yes | 1 year | 200 | Unpredictability | Energy saving |
Gandhi and Brager 2016 [52] | Choice and autonomy | Yes | 2 years | 30 | Empowerment | Energy saving |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, W.-T.; Iuorio, O.; Fang, H.; Mak, M.W.T. Gamification Approaches and Assessment Methodologies for Occupants’ Energy Behavior Change in Buildings: A Systematic Review. Buildings 2024, 14, 1497. https://doi.org/10.3390/buildings14061497
Li W-T, Iuorio O, Fang H, Mak MWT. Gamification Approaches and Assessment Methodologies for Occupants’ Energy Behavior Change in Buildings: A Systematic Review. Buildings. 2024; 14(6):1497. https://doi.org/10.3390/buildings14061497
Chicago/Turabian StyleLi, Wen-Ting, Ornella Iuorio, Han Fang, and Michele Win Tai Mak. 2024. "Gamification Approaches and Assessment Methodologies for Occupants’ Energy Behavior Change in Buildings: A Systematic Review" Buildings 14, no. 6: 1497. https://doi.org/10.3390/buildings14061497
APA StyleLi, W. -T., Iuorio, O., Fang, H., & Mak, M. W. T. (2024). Gamification Approaches and Assessment Methodologies for Occupants’ Energy Behavior Change in Buildings: A Systematic Review. Buildings, 14(6), 1497. https://doi.org/10.3390/buildings14061497