Artificial Intelligence, Smart Applications and Sustainable Consumption: A Theoretical Overview

Abstract

Sustainable consumption means consuming natural resources consciously, considering future generations. In today's technological age, artificial intelligence and smart applications are used to achieve sustainability goals. In this context, this article examines the impact of artificial intelligence (AI) and smart applications on promoting sustainable consumption behavior. Providing a comprehensive theoretical framework, this article explores how AI technologies support informed decision-making, maximize resource management, and deliver positive environmental impact across a variety of industries. Through a variety of examples, from energy management plans to environmentally friendly retail platforms, the effects of artificial intelligence and smart applications on sustainable consumption are highlighted. This article includes examples of smart applications used to promote sustainable consumption around the world and in Türkiye. Natural challenges that need to be overcome, such as algorithmic biases, data privacy issues and the digital divide, are also mentioned. The article offers recommendations for Türkiye, highlighting the importance of financing digital infrastructure, data privacy laws, digital literacy initiatives and innovation ecosystems, with the aim of emphasizing the importance of artificial intelligence (AI) and smart applications for sustainable consumption.

Keywords

• Artificial Intelligence
• Smart Applications
• Sustainable Consumption

Yapay Zekâ, Akıllı Uygulamalar ve Sürdürülebilir Tüketim: Teorik Bir Bakış

Öz

Sürdürülebilir tüketim, doğal kaynakların gelecek nesilleri de düşünmek suretiyle bilinçli bir şekilde tüketilmesi anlamına gelmektedir. Günümüz teknoloji çağında, sürdürülebilirlik hedeflerine ulaşmak amacıyla yapay zekâ ve akıllı uygulamalardan yararlanılmaktadır. Bu kapsam çerçevesinde çalışmada, bu makalede, yapay zekanın (AI) ve akıllı uygulamaların sürdürülebilir tüketim davranışını teşvik etmedeki etkisi incelenmektedir. Kapsamlı bir teorik çerçeve sunan bu çalışma, yapay zekâ teknolojilerinin bilinçli karar almayı nasıl desteklediğini, kaynak yönetimini en üst düzeye nasıl çıkardığını ve çeşitli endüstrilerde olumlu çevresel etkiyi nasıl sağladığını araştırmaktadır. Enerji yönetimi planlarından çevreye duyarlı perakende platformlarına kadar çeşitli örnekler aracılığıyla, sürdürülebilir tüketim üzerinde yapay zekanın ve akıllı uygulamaların etkileri vurgulanmaktadır. Bu çalışmada, dünyada ve Türkiye’de sürdürülebilir tüketimi teşvik etmek için kullanılan akıllı uygulama örneklerine yer verilmiştir. Bununla birlikte algoritmik önyargılar, veri gizliliği sorunları ve dijital uçurum gibi aşılması gereken doğal zorluklardan da söz edilmektedir. Çalışma, sürdürülebilir tüketim için yapay zekanın (AI) ve akıllı uygulamaların elzem olduğunu belirtmek amacıyla, dijital altyapının, veri gizliliği yasalarının, dijital okuryazarlık girişimlerinin ve inovasyon ekosistemlerinin finansmanının önemini vurgulayan Türkiye'ye yönelik öneriler sunmaktadır.

Anahtar Kelimeler

• Yapay Zeka
• Akıllı Uygulamalar
• Sürdürülebilir Tüketim

Kaynakça

1. Adamowicz, M., and Zwolińska-Ligaj, M. (2020). The “smart village” as a way to achieve sustainable development in rural areas of Poland. Sustainability, 12(16), 1-28. https://doi.org/10.3390/su12166503
2. Adesipo, A., Fadeyi, O., Kuca, K., Krejcar, O., Maresova, P., Selamat, A., and Adenola, M. (2020). Smart and climate-smart agricultural trends as core aspects of smart village functions. Sensors, 20(21), 1-22. https://doi.org/10.3390/s20215977
3. Adewale, B. A., Ene, V. O., Ogunbayo, B. F., and Aigbavboa, C. O. (2024). Application of artificial intelligence (AI) in sustainable building lifecycle; a systematic literature review. Buildings 2024 (Preprints) https://doi.org/10.20944/preprints202405.2113.v1
4. Adewumi, A., Okoli, C. E., Usman, F. O., Olu-lawal, K. A., and Soyombo, O. T. (2024). Reviewing the impact of AI on renewable energy efficiency and management. International Journal of Science and Research Archive, 11(1), 1518-1527. https://doi.org/10.30574/ijsra.2024.11.1.0245
5. Akintayo, O. T., Eden, C. A., Ayeni, O. O., and Onyebuchi, N. C. (2024). Integrating AI with emotional and social learning in primary education: Developing a holistic adaptive learning ecosystem. Computer Science & IT Research Journal, 5(5), 1076-1089. https://doi.org/10.51594/csitrj.v5i5.1116
6. Akintoye, I. R., Ajayi, M., Joshua, A., and Okunlola, A. F. (2022). Business sustainability through e-commerce: a myth or reality in Nigeria. Business: Theory and Practice, 23(2), 408–416. https://doi.org/10.3846/btp.2022.16657
7. Ally, M., and Perris, K. (2022). Artificial intelligence in the fourth industrial revolution to educate for sustainable development. Canadian Journal of Learning and Technology, 48(4), 1-20. https://doi.org/10.21432/cjlt28287
8. Amani, M. A., and Sarkodie, S. A. (2022). Mitigating spread of contamination in meat supply chain management using deep learning. Scientific Reports, 12(1), 1-10. https://doi.org/10.1038/s41598-022-08993-5

9. Amofah, D. O., and Chai, J. (2022). Sustaining consumer e-commerce adoption in Sub-Saharan Africa: Do trust and payment method matter? Sustainability, 14(14), 1-20. https://doi.org/10.3390/su14148466
10. Baum, Z. J., Yu, X., Ayala, P. Y., Zhao, Y., Watkins, S. P., and Zhou, Q. (2021). Artificial intelligence in chemistry: Current trends and future directions. Journal of Chemical Information and Modeling, 61(7), 3197–3212. https://doi.org/10.1021/acs.jcim.1c00619
11. Bayashot, Z. (2024). The contribution of AI-powered mobile apps to smart city ecosystems. Journal of Software Engineering and Applications, 17(03), 143-154. https://doi.org/10.4236/jsea.2024.173008
12. Belhadi, A., Mani, V., Kamble, S., Khan, S., and Verma, S. (2021). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: An empirical investigation. Annals of Operations Research, 333(2-3), 627-652. https://doi.org/10.1007/s10479-021-03956-x
13. Blösser, M., and Weihrauch, A. (2024). A consumer perspective of AI certification – the current certification landscape, consumer approval and directions for future research. European Journal of Marketing, 58(2), 441–470. https://doi.org/10.1108/EJM-01-2023-0009
14. Bossert, L., and Hagendorff, T. (2023). The ethics of sustainable AI: why animals (should) matter for a sustainable use of ai. Sustainable Development, 31(5), 3459-3467. https://doi.org/10.1002/sd.2596
15. Bosworth, G., Price, L., Collison, M., and Fox, C. (2020). Unequal futures of rural mobility: Challenges for a “Smart Countryside.” Local Economy: The Journal of the Local Economy Policy Unit, 35(6), 586–608. https://doi.org/10.1177/0269094220968231
16. Bowen, G., Jahankhani, H., and Nawaz, I. Y. (2024). Black swan events: Mitigating disruption to a supply chain using blockchain and artificial intelligence. Preprints. https://doi.org/10.20944/preprints202403.1119.v1
17. Buolamwini, J., and Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. In Conference on Fairness, Accountability and Transparency (pp. 77-91). PMLR.
18. Camaréna, S. (2021). Engaging with artificial intelligence (AI) with a bottom-up approach for the purpose of sustainability: Victorian farmers market association, Melbourne Australia. Sustainability, 13(16), 9314. https://doi.org/10.3390/su13169314
19. Chandratreya, A. (2024). AI-powered innovations in electrical engineering: Enhancing efficiency, reliability, and sustainability. Journal of Electrical Systems, 20(2), 1580-1587. https://doi.org/10.52783/jes.1463
20. Chen, R. (2024). Sustainable supply chain management as a strategic enterprise innovation. Advances in Economics Management and Political Sciences, 85(1), 24-29. https://doi.org/10.54254/2754-1169/85/20240831
21. Cowie, P., Townsend, L., and Salemink, K. (2020). Smart rural futures: Will rural areas be left behind in the 4th industrial revolution? Journal of Rural Studies, 79, 169–176. https://doi.org/10.1016/j.jrurstud.2020.08.042
22. Diachkova, A., Tikhonov, S., Tomyuk, O., and Tikhonova, N. (2022). Criteria for assessing food consumption patterns in the Brics countries in accordance with sustainable development goals. Bio Web of Conferences, 42, 04005. https://doi.org/10.1051/bioconf/20224204005
23. Dijmărescu, E. (2023, 8-10 June). AI trends: Salient aspects for the manufacturing sector and its global supply chain. R. Pamfilie, V. Dinu, C. Vasiliu, D. Pleșea, L. Tăchiciu (Eds). In 9th BASIQ International Conference on New Trends in Sustainable Business and Consumption, (pp. 168-175). Constanța, Romania. https://doi.org/10.24818/basiq/2023/09/053
24. Dikshit, S., Atiq, A., Shahid, M., Dwivedi, V., and Thusu, A. (2023). The use of artificial intelligence to optimize the routing of vehicles and reduce traffic congestion in urban areas. EAI Endorsed Transactions on Energy Web, 10, 1-13. https://doi.org/10.4108/ew.4613
25. Donati, F., Dente, S. M. R., Li, C., Vilaysouk, X., Froemelt, A., Nishant, R., Liu, G., Tukker, A., and Hashimoto, S. (2022). The future of artificial intelligence in the context of industrial ecology. Journal of Industrial Ecology, 26(4), 1175–1181. https://doi.org/10.1111/jiec.13313
26. Eyo-Udo, N. (2024). Leveraging artificial intelligence for enhanced supply chain optimization. Open Access Research Journal of Multidisciplinary Studies, 7(2), 001-015. https://doi.org/10.53022/oarjms.2024.7.2.0044
27. Hao, X. and Demir, E. (2023). Artificial intelligence in supply chain decision-making: An environmental, social, and governance triggering and technological inhibiting protocol. Journal of Modelling in Management, 19(2), 605-629. https://doi.org/10.1108/jm2-01-2023-0009
28. Hasan, R. and Ojala, A. (2024). Managing artificial intelligence in international business: Toward a research agenda on sustainable production and consumption. Thunderbird International Business Review, 66(2), 151-170. https://doi.org/10.1002/tie.22369
29. He, Q. (2024). Popularization of AI for psychological as well as educational applications. Lecture Notes in Education Psychology and Public Media, 42(1), 112-117. https://doi.org/10.54254/2753-7048/42/20240815
30. Hermann, E. (2023). Artificial intelligence in marketing: friend or foe of sustainable consumption? AI & Society, 38, 1975-1976. https://doi.org/10.1007/s00146-021-01227-8
31. Honarmand Ebrahimi, S., Ossewaarde, M. and Need, A. (2021). Smart fishery: A systematic review and research agenda for sustainable fisheries in the age of AI. Sustainability, 13(11), 6037, 1-20. https://doi.org/10.3390/su13116037
32. Joel, O. S., Oyewole, A. T., Odunaiya, O. G., and Soyombo, O. T. (2024). Leveraging artificial intelligence for enhanced supply chain optimization: A comprehensive review of current practices and future potentials. International Journal of Management & Entrepreneurship Research, 6(3), 707-721. https://doi.org/10.51594/ijmer.v6i3.882
33. Kamkar, M., Leonard, K. C., Ferrer, I., Loo, S. C. J., Biddinger, E. J., Brady, D., Carrier, D. J., Gathergood, N., Han, H., Hermans, I., Hii, K. K. M., Hwang, B. J., Loh, W., Meier, M. A. R., Marr, A. C., Newton, G. N., Srubar, W. V., Yan, N., Tam, M. K., Chen, J., Moores, A. H., Subramaniam, B., Licence, P. and Serrano, J. F. (2024). Artificial intelligence (AI) for sustainable resource management and chemical processes. ACS Sustainable Chemistry and Engineering, 12(8), 2924–2926. https://doi.org/10.1021/acssuschemeng.4c01004
34. Kar, A. K., Ilavarasan, V., Gupta, M. P., Janssen, M. and Kothari, R. (2019). Moving beyond smart cities: Digital nations for social innovation and sustainability. Information Systems Frontiers, 21(3), 495–501. https://doi.org/10.1007/s10796-019-09930-0
35. Kindylidi, I. and Cabral, T. S. (2021). Sustainability of AI: The case of provision of information to consumers. Sustainability, 13(21), 1-14. https://doi.org/10.3390/su132112064
36. Le, T. (2020). Strength from the past: How nostalgia and self-construal affect consumers’ willingness to continue participating in sustainable behavior. American Journal of Industrial and Business Management, 10(02), 432–450. https://doi.org/10.4236/ajibm.2020.102029
37. Lee, K. (2021). A systematic review on social sustainability of artificial intelligence in product design. Sustainability, 13(5), 1-29. https://doi.org/10.3390/su13052668
38. Liao, H. T., Pan, C.-L. and Zhang, Y. (2023). Smart digital platforms for carbon neutral management and services: Business models based on ITU standards for green digital transformation. Frontiers in Ecology and Evolution, 11, 1-10. https://doi.org/10.3389/fevo.2023.1134381
39. Liu, L., Liu, R., Lee, M. and Chen, J. (2019). When will consumers be ready? A psychological perspective on consumer engagement in social media brand communities. Internet Research, 29(4), 704–724. https://doi.org/10.1108/IntR-05-2017-0177
40. Mhlanga, D. (2021). Artificial intelligence in the industry 4.0, and its impact on poverty, innovation, infrastructure development, and the sustainable development goals: Lessons from emerging economies?. Sustainability, 13(11), 5788. https://doi.org/10.3390/su13115788
41. Mhlanga, D. (2022). The role of artificial intelligence and machine learning amid the COVID-19 Pandemic: What lessons are we learning on 4IR and the sustainable development goals. International Journal of Environmental Research and Public Health, 19(3), 1-22. https://doi.org/10.3390/ijerph19031879
42. Michels, L., Ochmann, J., Günther, S. A., Laumer, S. and Tiefenbeck, V. (2022). Empowering consumers to make environmentally sustainable online shopping decisions: A digital nudging approach, Proceedings of the 55th Hawaii International Conference on System Sciences, 4707-4716. https://doi.org/10.24251/HICSS.2022.574
43. Moktadir, M. A., Rahman, T., Rahman, M. H., Ali, S. M. and Paul, S. K. (2018). Drivers to sustainable manufacturing practices and circular economy: A perspective of leather industries in Bangladesh. Journal of Cleaner Production, 174, 1366–1380. https://doi.org/10.1016/j.jclepro.2017.11.063
44. Muniandi, B., Maurya, P. K., Bhavani, C. H., Kulkarni, S., Yellu, R. R., and Chauhan, N. (2024). AI-driven energy management systems for smart buildings. Power System Technology, 48(1), 322-337. https://doi.org/10.52783/pst.280
45. Naeeni, S. K., and Nouhi, N. (2023). The environmental impacts of AI and digital technologies. AI and Tech in Behavioral and Social Sciences, 1(4), 11-18. https://doi.org/10.61838/kman.aitech.1.4.3
46. Olan, F., Arakpogun, E., Jayawickrama, U., Suklan, J., and Liu, S. (2024). Sustainable supply chain finance and supply networks: the role of artificial intelligence. IEEE Transactions on Engineering Management, 71, 13296-13311. https://doi.org/10.1109/tem.2021.3133104
47. Olan, F., Liu, S., Suklan, J., Jayawickrama, U., and Arakpogun, E. (2021). The role of artificial intelligence networks in sustainable supply chain finance for food and drink industry. International Journal of Production Research, 60(14), 4418-4433. https://doi.org/10.1080/00207543.2021.1915510
48. Olatunde, T. M., Okwandu, A. C., Akande, D. O., and Sikhakhane, Z. Q. (2024). Reviewing the role of artificial intelligence in energy efficiency optimization. Engineering Science & Technology Journal, 5(4), 1243-1256. https://doi.org/10.51594/estj.v5i4.1015
49. Padmanaban, H. (2024). Privacy-preserving architectures for AI/ML applications: Methods, balances, and illustrations. JAIGS, 3(1), 66-85. https://doi.org/10.60087/jaigs.vol03.issue01.p85
50. Paiva, S., Ahad, M., Tripathi, G., Feroz, N. and Casalino, G. (2021). Enabling technologies for urban smart mobility: Recent trends, opportunities and challenges. Sensors, 21(6), 1-41. https://doi.org/10.3390/s21062143
51. Radanliev, P., Santos, O., Brandon-Jones, A., and Joinson, A. (2024). Ethics and responsible AI deployment. Frontiers in Artificial Intelligence, 7, 1-17. https://doi.org/10.3389/frai.2024.1377011
52. Reynolds, S. (2024). Exploring the influence of corporate social responsibility on supply chain sustainability in renewable energy. Preprints. https://doi.org/10.20944/preprints202405.1888.v1
53. Singh, R., Modgil, S., and Shore, A. (2023). Building artificial intelligence enabled resilient supply chain: a multi-method approach. Journal of Enterprise Information Management, 37(2), 414-436. https://doi.org/10.1108/jeim-09-2022-0326
54. Sova, O., Bieliaieva, N., Antypenko, N., and Drozd, N. (2023). Impact of artificial intelligence and digital HRM on the resource consumption within sustainable development perspective. E3s Web of Conferences, 408, 01006. https://doi.org/10.1051/e3sconf/202340801006
55. Strother, J. B., and Fazal, Z. (2011). Can green fatigue hamper sustainability communication efforts?. In 2011 IEEE International Professional Communication Conference (pp. 1-6). IEEE. https://doi.org/10.1109/IPCC.2011.6087206
56. Tomar, P., and Grover, V. (2023). Transforming the energy sector: Addressing key challenges through generative AI, digital twins, AI, data science and analysis. EAI Endorsed Transactions on Energy Web, 10. https://doi.org/10.4108/ew.4825
57. Tran, L. T. T. (2021). Managing the effectiveness of e-commerce platforms in a pandemic. Journal of Retailing and Consumer Services, 58, 1-9. https://doi.org/10.1016/j.jretconser.2020.102287
58. Tsolakis, N., Schumacher, R., Dora, M., and Kumar, M. (2023). Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation? Annals of Operations Research, 327(1), 157–210. https://doi.org/10.1007/s10479-022-04785-2
59. Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., and Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11(1), 1-10. https://doi.org/10.1038/s41467-019-14108-y
60. Visvizi, A., and Lytras, M. (2018). It’s not a fad: smart cities and smart villages research in European and global contexts. Sustainability, 10(8), 1-10. https://doi.org/10.3390/su10082727
61. Visvizi, A., and Lytras, M. D. (2019). Sustainable smart cities and smart villages research: Rethinking security, safety, well-being, and happiness. Sustainability, 12(1), 1-4. https://doi.org/10.3390/su12010215
62. Wang, C., Zhang, J., Lassi, N., and Zhang, X. (2022). Privacy protection in using artificial intelligence for healthcare: Chinese regulation in comparative perspective. Healthcare, 10(10), 1878. https://doi.org/10.3390/healthcare10101878
63. Wehlmann, C. Z. (2024). Resilient and Sustainable AI. Positioning paper on the relation of AI, resilience and sustainability. In: Zinke-Wehlmann, C., Friedrich, J. (Eds), First Working Conference on Artificial Intelligence Development for a Resilient and Sustainable Tomorrow (pp. 5-19). Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-43705-3_2
64. White, K., Habib, R., and Hardisty, D. J. (2019). How to shift consumer behaviors to be more sustainable: A literature review and guiding framework. Journal of Marketing, 83(3), 22–49. https://doi.org/10.1177/0022242919825649
65. Wilfred, P., Milner-Gulland, E. J., and Travers, H. (2019). Attitudes to illegal behaviour and conservation in western Tanzania. Oryx, 53(3), 513-522. https://doi.org/10.1017/S0030605317000862
66. Williamson, S. M., and Prybutok, V. (2024). Balancing privacy and progress: A review of privacy challenges, systemic oversight, and patient perceptions in AI-driven healthcare. Applied Sciences, 14(2), 675. https://doi.org/10.3390/app14020675
67. Xiao, D. (2023). Neuroscience-inspired continuous learning: A sustainable approach to AI energy challenge. Preprints. https://doi.org/10.31219/osf.io/twn9q
68. Yan, K., Wang, X., Du, Y., Jin, N., Huang, H., and Zhou, H. (2018). Multi-step short-term power consumption forecasting with a hybrid deep learning strategy. Energies, 11(11), 1-15. https://doi.org/10.3390/en11113089
69. Yigitcanlar, T. (2021). Greening the artificial intelligence for a sustainable planet: An editorial commentary. Sustainability, 13(24), 1-9. https://doi.org/10.3390/su132413508
70. Yigitcanlar, T. and Cugurullo, F. (2020). The sustainability of artificial intelligence: An urbanistic viewpoint from the lens of smart and sustainable cities. Sustainability, 12(20), 1-24. https://doi.org/10.3390/su12208548
71. Yigitcanlar, T., Desouza, K., Butler, L., and Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: İnsights from a systematic review of the literature. Energies, 13(6), 1-38. https://doi.org/10.3390/en13061473
72. Yu, S., Carroll, F., and Bentley, B. L. (2024). Insights into privacy protection research in AI. IEEE Access, 12, 41704-41726. https://doi.org/10.1109/access.2024.3378126
73. Zavratnik, V., Kos, A., and Stojmenova Duh, E. (2018). Smart villages: Comprehensive review of initiatives and practices. Sustainability, 10(7), 1-14. https://doi.org/10.3390/su10072559