IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v81y2025ics0160791x25000375.html
   My bibliography  Save this article

Energy Gen-AI technology framework: A perspective of energy efficiency and business ethics in operation management

Author

Listed:
  • Fontoura, Leonardo
  • Luiz de Mattos Nascimento, Daniel
  • Neto, Julio Vieira
  • Gusmão Caiado, Rodrigo Goyannes

Abstract

Considering the mounting request for viable energy solutions emphasising sustainability, this study addresses the context by positioning Generative Artificial Intelligence (Gen-AI) as a pivotal remedy for improved process efficiency. Concerns about its uncontrolled use and ethical implications prompted a thorough examination of problems and gaps in this domain. This study innovates by positioning Gen-AI as a critical solution for improving energy efficiency amidst rising demand for sustainable energy at the operation and supply chain management levels. Based on technological determinism, it introduces an Energy Gen-AI Technology Framework (EnGen-AI) that integrates Gen-AI, energy efficiency, Business Ethics (BE), and Corporate Social Responsibility (CSR) principles for implementing Gen-AI to enhance sustainable energy management. The methodology includes a scoping review, a multi-criteria analysis, and a technology framework. The study harmonises BE-CSR with Gen-AI practices, offering essential guidance for management implementing Gen-AI in sustainable energy solutions whilst observing its impacts on ethical and social aspects.

Suggested Citation

  • Fontoura, Leonardo & Luiz de Mattos Nascimento, Daniel & Neto, Julio Vieira & Gusmão Caiado, Rodrigo Goyannes, 2025. "Energy Gen-AI technology framework: A perspective of energy efficiency and business ethics in operation management," Technology in Society, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:teinso:v:81:y:2025:i:c:s0160791x25000375
    DOI: 10.1016/j.techsoc.2025.102847
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X25000375
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techsoc.2025.102847?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Cabello-López, Tomás & Carranza-García, Manuel & Riquelme, José C. & García-Gutiérrez, Jorge, 2023. "Forecasting solar energy production in Spain: A comparison of univariate and multivariate models at the national level," Applied Energy, Elsevier, vol. 350(C).
    2. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Stahre, Johan, 2017. "Maintenance in digitalised manufacturing: Delphi-based scenarios for 2030," International Journal of Production Economics, Elsevier, vol. 191(C), pages 154-169.
    3. Ahmad, Tanveer & Madonski, Rafal & Zhang, Dongdong & Huang, Chao & Mujeeb, Asad, 2022. "Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    4. Kumar, Devinder & Singh, Rajesh Kr & Mishra, Ruchi & Daim, Tugrul U., 2023. "Roadmap for integrating blockchain with Internet of Things (IoT) for sustainable and secured operations in logistics and supply chains: Decision making framework with case illustration," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Guo Li & Na Li & Suresh P. Sethi, 2021. "Does CSR Reduce Idiosyncratic Risk? Roles of Operational Efficiency and AI Innovation," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2027-2045, July.
    6. Gazi Islam & Michelle Greenwood, 2024. "Generative Artificial Intelligence as Hypercommons: Ethics of Authorship and Ownership," Journal of Business Ethics, Springer, vol. 192(4), pages 659-663, July.
    7. Contreras-Cruz, Angel & Kirbac, Aynur & Dennett, Christopher & Daim, Tugrul U., 2023. "Human-centered design as a tool to improve employee experience: The case of a US plant-based food manufacturer," Technology in Society, Elsevier, vol. 73(C).
    8. Charlene H. Chu & Simon Donato-Woodger & Shehroz S. Khan & Rune Nyrup & Kathleen Leslie & Alexandra Lyn & Tianyu Shi & Andria Bianchi & Samira Abbasgholizadeh Rahimi & Amanda Grenier, 2023. "Age-related bias and artificial intelligence: a scoping review," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    9. Safarzadeh, Soroush & Rasti-Barzoki, Morteza, 2019. "A game theoretic approach for assessing residential energy-efficiency program considering rebound, consumer behavior, and government policies," Applied Energy, Elsevier, vol. 233, pages 44-61.
    10. Xiaofeng Shi & Jianying Li & Fei Wang & Hasan Dinçer & Serhat Yüksel, 2019. "A Hybrid Decision-Making Approach for the Service and Financial-Based Measurement of Universal Health Coverage for the E7 Economies," IJERPH, MDPI, vol. 16(18), pages 1-20, September.
    11. Adeel Luqman & Qingyu Zhang & Shalini Talwar & Meena Bhatia & Amandeep Dhir, 2024. "Artificial intelligence and corporate carbon neutrality: A qualitative exploration," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 3986-4003, July.
    12. Dhruv Patel & Chandan Kumar Sahu & Rahul Rai, 2024. "Security in modern manufacturing systems: integrating blockchain in artificial intelligence-assisted manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 62(3), pages 1041-1071, February.
    13. Huang, Yaohui & Zhao, Yuan & Wang, Zhijin & Liu, Xiufeng & Liu, Hanjing & Fu, Yonggang, 2023. "Explainable district heat load forecasting with active deep learning," Applied Energy, Elsevier, vol. 350(C).
    14. Ilya Jackson & Dmitry Ivanov & Alexandre Dolgui & Jafar Namdar, 2024. "Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation," International Journal of Production Research, Taylor & Francis Journals, vol. 62(17), pages 6120-6145, September.
    15. Chen, G.Q. & Wu, X.D. & Guo, Jinlan & Meng, Jing & Li, Chaohui, 2019. "Global overview for energy use of the world economy: Household-consumption-based accounting based on the world input-output database (WIOD)," Energy Economics, Elsevier, vol. 81(C), pages 835-847.
    16. Vlačić, Božidar & Corbo, Leonardo & Costa e Silva, Susana & Dabić, Marina, 2021. "The evolving role of artificial intelligence in marketing: A review and research agenda," Journal of Business Research, Elsevier, vol. 128(C), pages 187-203.
    17. Miguel Núñez-Merino & Juan Manuel Maqueira-Marín & José Moyano-Fuentes & Pedro José Martínez-Jurado, 2020. "Information and digital technologies of Industry 4.0 and Lean supply chain management: a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 58(16), pages 5034-5061, July.
    18. Thomas, Asha & Duggal, Harshleen Kaur & Khatri, Puja & Corvello, Vincenzo, 2024. "ChatGPT appropriation: A catalyst for creative performance, innovation orientation, and agile leadership," Technology in Society, Elsevier, vol. 78(C).
    19. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    20. Gülşen Aydın Keskin, 2015. "Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection," International Journal of Production Research, Taylor & Francis Journals, vol. 53(12), pages 3586-3602, June.
    21. Du, Shuili & Xie, Chunyan, 2021. "Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities," Journal of Business Research, Elsevier, vol. 129(C), pages 961-974.
    22. Herrera-Vega, Eliana, 2015. "Relevance of N. Luhmann's theory of social systems to understand the essence of technology today. The Case of the Gulf of Mexico Oil Spill," Technology in Society, Elsevier, vol. 40(C), pages 25-42.
    23. Fosso Wamba, Samuel & Bawack, Ransome Epie & Guthrie, Cameron & Queiroz, Maciel M. & Carillo, Kevin Daniel André, 2021. "Are we preparing for a good AI society? A bibliometric review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    24. G. Castañé & A. Dolgui & N. Kousi & B. Meyers & S. Thevenin & E. Vyhmeister & P-O. Östberg, 2023. "The ASSISTANT project: AI for high level decisions in manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 61(7), pages 2288-2306, April.
    25. Valentina Di Pasquale & Salvatore Miranda & W. Patrick Neumann, 2020. "Ageing and human-system errors in manufacturing: a scoping review," International Journal of Production Research, Taylor & Francis Journals, vol. 58(15), pages 4716-4740, July.
    26. wael AL-khatib, Ayman, 2023. "Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework," Technology in Society, Elsevier, vol. 75(C).
    27. Md. Abdul Moktadir & Towfique Rahman & Syed Mithun Ali & Nazmun Nahar & Sanjoy Kumar Paul, 2020. "Examining barriers to reverse logistics practices in the leather footwear industry," Annals of Operations Research, Springer, vol. 293(2), pages 715-746, October.
    28. Germán Arana-Landín & Naiara Uriarte-Gallastegi & Beñat Landeta-Manzano & Iker Laskurain-Iturbe, 2023. "The Contribution of Lean Management—Industry 4.0 Technologies to Improving Energy Efficiency," Energies, MDPI, vol. 16(5), pages 1-19, February.
    29. Subodha Kumar & Rakesh R. Mallipeddi, 2022. "Impact of cybersecurity on operations and supply chain management: Emerging trends and future research directions," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4488-4500, December.
    30. Ilia Shumailov & Zakhar Shumaylov & Yiren Zhao & Nicolas Papernot & Ross Anderson & Yarin Gal, 2024. "AI models collapse when trained on recursively generated data," Nature, Nature, vol. 631(8022), pages 755-759, July.
    31. Ilya Jackson & Maria Jesus Saenz & Dmitry Ivanov, 2024. "From natural language to simulations: applying AI to automate simulation modelling of logistics systems," International Journal of Production Research, Taylor & Francis Journals, vol. 62(4), pages 1434-1457, February.
    32. Wu, X.D. & Guo, J.L. & Ji, Xi & Chen, G.Q., 2019. "Energy use in world economy from household-consumption-based perspective," Energy Policy, Elsevier, vol. 127(C), pages 287-298.
    33. Jizhong Xue & Zaohui Kang & Chun Sing Lai & Yu Wang & Fangyuan Xu & Haoliang Yuan, 2023. "Distributed Generation Forecasting Based on Rolling Graph Neural Network (ROLL-GNN)," Energies, MDPI, vol. 16(11), pages 1-18, May.
    34. Ma, Xiaoyue & Huo, Yudi, 2023. "Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework," Technology in Society, Elsevier, vol. 75(C).
    35. Baek, Hyun & Lee, Heesang, 2021. "Framework of Socio-Technology Analysis and Prescriptions for a sustainable society: Focusing on the mobile technology case," Technology in Society, Elsevier, vol. 65(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rehman, Anisur & Behera, Rajat Kumar & Islam, Md Saiful & Elahi, Yasir Arafat & Abbasi, Faraz Ahmad & Imtiaz, Asma, 2024. "Drivers of metaverse adoption for enhancing marketing capabilities of retail SMEs," Technology in Society, Elsevier, vol. 79(C).
    2. Ji, Xi & Liu, Yifang & Wu, Guowei & Su, Pinyi & Ye, Zhen & Feng, Kuishuang, 2022. "Global value chain participation and trade-induced energy inequality," Energy Economics, Elsevier, vol. 112(C).
    3. Usubiaga-Liaño, Arkaitz & Arto, Iñaki & Acosta-Fernández, José, 2021. "Double accounting in energy footprint and related assessments: How common is it and what are the consequences?," Energy, Elsevier, vol. 222(C).
    4. Zhang, Yaqiong & Wang, Shifu, 2023. "The influence of anthropomorphic appearance of artificial intelligence products on consumer behavior and brand evaluation under different product types," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    5. Li, Lixu & Liu, Yaoqi & Jin, Yong & Cheng, T.C. Edwin & Zhang, Qianjun, 2024. "Generative AI-enabled supply chain management: The critical role of coordination and dynamism," International Journal of Production Economics, Elsevier, vol. 277(C).
    6. Singh, Nidhi & Jain, Monika & Kamal, Muhammad Mustafa & Bodhi, Rahul & Gupta, Bhumika, 2024. "Technological paradoxes and artificial intelligence implementation in healthcare. An application of paradox theory," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    7. Piotr Tomasz Makowski & Yuya Kajikawa, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Papers 2103.02395, arXiv.org.
    8. Nazareno, Luísa & Schiff, Daniel S., 2021. "The impact of automation and artificial intelligence on worker well-being," Technology in Society, Elsevier, vol. 67(C).
    9. Gábor Szabó-Szentgróti & Bence Végvári & József Varga, 2021. "Impact of Industry 4.0 and Digitization on Labor Market for 2030-Verification of Keynes’ Prediction," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    10. Makowski, Piotr Tomasz & Kajikawa, Yuya, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    11. José A. Camacho & Lucas Silva Almeida & Mercedes Rodríguez & Jesús Molina, 2022. "Domestic versus foreign energy use: an analysis for four European countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 4602-4622, April.
    12. Zhou, Zhikai & Liu, Dewen & Chen, Zhongjie & Pancho, Martin, 2025. "Government adoption of generative artificial intelligence and ambidextrous innovation," International Review of Economics & Finance, Elsevier, vol. 98(C).
    13. Cifone, Fabiana Dafne & Hoberg, Kai & Holweg, Matthias & Staudacher, Alberto Portioli, 2021. "‘Lean 4.0’: How can digital technologies support lean practices?," International Journal of Production Economics, Elsevier, vol. 241(C).
    14. O. C. Ferrell & Dana E. Harrison & Linda K. Ferrell & Haya Ajjan & Bryan W. Hochstein, 2024. "A theoretical framework to guide AI ethical decision making," AMS Review, Springer;Academy of Marketing Science, vol. 14(1), pages 53-67, June.
    15. Nitya Singh & Paul Hong, 2023. "CSR, Risk Management Practices, and Performance Outcomes: An Empirical Investigation of Firms in Different Industries," JRFM, MDPI, vol. 16(2), pages 1-20, January.
    16. Hermann, Erik & Puntoni, Stefano, 2024. "Artificial intelligence and consumer behavior: From predictive to generative AI," Journal of Business Research, Elsevier, vol. 180(C).
    17. Wang, Yuyan & Gao, Junhong & Cheng, T.C.E. & Jin, Mingzhou & Yue, Xiaohang & Wang, Huajie, 2025. "Is it necessary for the supply chain to implement artificial intelligence-driven sales services at both the front-end and back-end stages?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    18. Loebbing, Jonas, 2018. "An Elementary Theory of Endogenous Technical Change and Wage Inequality," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181603, Verein für Socialpolitik / German Economic Association.
    19. Zeng, Ying & Liu, Xinyi & Zhang, Xinyuan & Li, Zhiyong, 2024. "Retrospective of interdisciplinary research on robot services (1954–2023): From parasitism to symbiosis," Technology in Society, Elsevier, vol. 78(C).
    20. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:81:y:2025:i:c:s0160791x25000375. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.