Yapay Zekâ ve Sürdürülebilir İş Modelleri Üzerine Sistematik Bir Derleme

Abstract

Sürdürülebilirlik, günümüzde ülkelerin kalkınma hedeflerinin merkezinde yer almaktadır. Dolayısıyla sürdürülebilirlik kapsamında çevresel ve insani sorumlulukları gözeten iktisadi modellerin benimsenmesi ve uygulanması teşvik edilmektedir. Ülkelerin sürdürülebilir rekabet güçlerini artırmasında, yapay zekânın iş modelleri ile entegrasyonunun çeşitli avantajlar sunacağı öngörülmektedir. Bu çalışma, yapay zekânın sürdürülebilir iş modellerine entegre edilmesini konu edinen makalelerin sistematik derlemesine dayanmaktadır. Çalışmalar, yapay zekânın iş teknolojilerine uygulanmasının, sosyal, ekonomik ve çevresel boyutlarıyla sürdürülebilir kalkınma açısından önemli avantajlar sağladığını göstermektedir. İncelenen makalelere göre, yapay zekânın çevresel açıdan olumlu etkileri kapsamında enerji, kaynak ve malzeme tasarrufu, atık yönetimi ve geri dönüştürülebilir ürünlerin üretimi, karbon salınımının azaltılması ve yeşil finansın etkili yönetimi hususları ön plana çıkmaktadır. Ekonomik avantajlar açısından değerlendirildiğinde; verimlilik ve performans artışı, sürdürülebilir tedarik zinciri ve platform tabanlı iş birlikleri önemli görülmektedir. Çalışma sonuçlarına göre yapay zekânın sosyal açıdan sunduğu fırsatlar ise çalışma koşullarının iyileşmesi, çalışanların yönetim ve karar alma süreçlerine dahil edilmesi ve çalışan yeteneklerinin ve potansiyellerinin geliştirilmesi olarak görünürlük kazanmaktadır.

Keywords

• Sürdürülebilirlik
• Yapay Zekâ
• Sürdürülebilir İş Modelleri
• Endüstri 4.0
• Toplumsal Değişme

A Systematic Review on Artificial Intelligence and Sustainable Business Models

Abstract

Sustainability is central to countries' development goals today. Therefore, the adoption and implementation of economic models that consider environmental and human responsibilities within the scope of sustainability are encouraged. Integrating AI into business models can offer various advantages for countries to increase their sustainable competitiveness. This study is based on a systematic review of studies on the integration of AI into sustainable business models. The study demonstrates that the application of AI to business technologies provides significant advantages for sustainable development in terms of social, economic, and environmental dimensions. According to the results of the reviewed articles, the positive environmental impacts of AI include energy, resource, and material savings, waste management and the production of recyclable products, carbon emission reduction, and effective green finance management. In terms of economic advantages, productivity and performance increases, sustainable supply chains, and platform-based collaborations are considered significant. According to the study results, the social opportunities offered by AI include improved working conditions, including employees in management and decision-making processes, and developing employee skills and potential.

Keywords

• Sustainability
• Artificial Intelligence
• Sustainable Business Models
• Industry 4.0
• Social Change

References

1. ABDELFATTAH, F., SALAH, M., DAHLEEZ, K., DARWAZEH, R. & HALBUSI, H. Al. (2024). The future of competitive advantage in Oman: Integrating green product innovation, AI, and intellectual capital in business strategies, International Journal of Innovation Studies, Cilt 8 (2), 154-171, doi: 10.1016/j.ijis.2024.02.001.
2. ADAŞ, E., & ERBAY, B. (2022). Yapay zekâ sosyolojisi üzerine bir değerlendirme. Gaziantep University Journal of Social Sciences, Cilt 21(1), 326-337. doi:10.21547/jss.991383
3. AGARWAL, A., & OJHA, R. (2024). Prioritizing implications of Industry-4.0 on the sustainable development goals: A perspective from the analytic hierarchy process in manufacturing operations. Journal of Cleaner Production, Cilt 444, 141189. Doi: 10.1016/j.jclepro.2024.141189
4. ATA, B. & URMAN, B. (2008). Sistematik derlemelerin kritik analizi. Journal of Turkish Society of Obstetric and Gynecology, Cilt 5(4), 233-240.
5. BADGHISH, S. & SOOMRO, Y. A. (2024). Artificial intelligence adoption by SMEs to achieve sustainable business performance: Application of technology–organization–environment framework. Sustainability, Cilt 16(5), 1864. doi: 10.3390/su16051864
6. BAG, S., & RAHMAN, M. S. (2023). Navigating circular economy: Unleashing the potential of political and supply chain analytics skills among top supply chain executives for environmental orientation, regenerative supply chain practices, and supply chain viability. Business Strategy and the Environment, Cilt 33(2), 504-528. doi: 10.1002/bse.3507
7. BAR-ILAN, J. (2010). Citations to the ‘‘Introduction to informetrics’’ indexed by WOS, Scopus and Google Scholar. Scientometrics Cilt 82, 495–506 doi: 10.1007/s11192-010-0185-9
8. BICLESANU I., SAVASTANO M., CHINIE C. & ANAGNOSTE S. (2023). The role of business students’ entrepreneurial ıntention and technology preparedness in the digital age. Administrative Sciences, Cilt 13(8), 177. doi: 10.3390/admsci13080177

9. BİRLEŞMİŞ MİLLETLER (UNITED NATIONS). (t.y.) Sürdürülebilir kalkınma amaçları. Erişim tarihi: 17.04.2025. https://turkiye.un.org/tr/sdgs
10. BLOOMFİELD B. P. (2018). The Culture of Artificial Intelligence. The Question of Artificial Intelligence: Philosophical And Sociological Perspectives (ed. B. P. Bloomfıeld). Oxon: Routledge.
11. BROCCARDO, L., ZICARI, A. JABEEN, F. & BHATTI, Z. A. (2023). How digitalization supports a sustainable business model: A literature review. Technological Forecasting and Social Change, Cilt 187, 122146. doi: 10.1016/j.techfore.2022.122146.
12. BUCHANAN, B. G. (2005). A (very) brief history of artificial ıntelligence. AI Magazine, Cilt 26(4), 53. doi:10.1609/aimag.v26i4.1848
13. CAI, Z., YANG, Y., ZHANG, X., & ZHOU, Y. (2022). Design a robust logistics network with an artificial physarum swarm algorithm. Sustainability, Cilt 14(22), 14930. doi: 10.3390/su142214930
14. CASTELLS, M. (2008). Enformasyon çağı: Ekomomi, toplum ve kültür. Birinci cilt: Ağ toplumunun yükselişi. İstanbul: İstanbul Üniversitesi Bilgi Yayınları.
15. CHIN, T., GHOURI, M. W. A., JIN, J., & DEVECI, M. (2024). AI technologies affording the orchestration of ecosystem-based business models: the moderating role of AI knowledge spillover. Humanities and Social Sciences Communications, Cilt 11. 496. doi: 10.1057/s41599-024-03003-7
16. CHINNATHAI, M. K., & ALKAN, B. (2023). A digital life-cycle management framework for sustainable smart manufacturing in energy intensive industries. Journal of Cleaner Production, Cilt 419. 138259. doi: 10.1016/j.jclepro.2023.138259
17. COECKELBERGH, M. (2021). AI for climate: freedom, justice, and other ethical and political challenges. AI Ethics, Cilt 1, 67–72. doi: 10.1007/s43681-020-00007-2
18. COSTA, E., FONTES, M., & BENTO, N. (2023). Transformative business models for decarbonization: Insights from prize-winning start-ups at the web summit. Sustainability, Cilt 15(18). doi: 10.3390/su151814007
19. COWLS, J., TSAMADOS, A., TADDEO, M. & FLORIDI, L. (2023). The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations. AI & SOCIETY Cilt 38, 283–307. 14007. doi: 10.1007/s00146-021-01294-x
20. DEY, P. K., CHOWDHURY, S., ABADIE, A., VANN YAROSON, E., & SARKAR, S. (2023). Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises. International Journal of Production Research, Cilt 62(15), 5417–5456. doi: 10.1080/00207543.2023.2179859
21. DRUCKER, P. F. (1993). Kapitalist ötesi toplum. İstanbul: İnkılap Kitabevi.
22. DWIVEDI, Y. K., SHARMA, A., RANA, N. P., GIANNAKIS, M., GOEL, P., & DUTOT, V. (2023). Evolution of artificial ıntelligence research in technological forecasting and social change: Research topics, trends, and future directions. Technological Forecasting and Social Change, Cilt 192, doi: 10.1016/j.techfore.2023.122579
23. ENİŞ-ERDOĞAN, T. & EKŞİOĞLU, S. (2024). Yapay Zekâ Okuryazarlığı Ölçeği’nin Türkçeye uyarlanması. TEBD, Cilt 22(2), 1196-1211. doi: 10.37217/tebd.1496716
24. FARUQE, F., WATKINS, R., & MEDSKER, L. (2022). Competency model approach to AI literacy: research-based path from initial framework to model. Advances in Artificial Intelligence and Machine Learning, Cilt 2(4), 580-587. https://doi.org/10.48550/arXiv.2108.05809
25. FERREIRA, J. J., LOPES, J. M., GOMES, S., & RAMMAL, H. G. (2023). Industry 4.0 implementation: Environmental and social sustainability in manufacturing multinational enterprises. Journal of Cleaner Production, Cilt 404, 136841. doi: 10.1016/j.jclepro.2023.136841
26. FLECK, J. (2018). Development and establishment in artificial intelligence. The Question of Artificial Intelligence: Philosophical And Sociological Perspectives (ed. B. P. Bloomfıeld). Oxon: Routledge.
27. FLORIDI, L., COWLS, J., BELTRAMETTİ, M., CHATILA, R., CHAZERAND, P., DİGNUM, V., LUETGE, C., MADELİN, R., PAGALLO, U., ROSSI, F., SCHAFER, B., VALCKE, P., & VAYENA, E. (2018). AI4People-an ethical framework for a good aı society: Opportunities, risks, principles, and recommendations. Minds and machines, Cilt 28(4), 689–707. doi:10.1007/s11023-018-9482-5
28. GRAÇA, P. & CAMARINHA-MATOS, L.M. (2021). assessment of sustainable collaboration in collaborative business ecosystems. Computers, Cilt 10, 167. doi: 10.3390/computers10120167
29. HEMANAND, D., MISHRA, N., PREMALATHA, G., MAVALURU, D., VAJPAYEE, A., KUSHWAHA, S., & SAHILE, K. (2022). Applications of Intelligent Model to Analyze the Green Finance for Environmental Development in the Context of Artificial Intelligence. Computational Intelligence and Neuroscience, vol: 2022, 2977824. https://doi.org/10.1155/2022/2977824
30. HU, B., ASIM, S., SIBT, E. A. M., JAVAID, M. Q., & RAMZAN, M. (2023). Exploring the relationships between attitudes toward emission trading schemes, artificial intelligence, climate entrepreneurship, and sustainable performance. Environmental Science and Pollution Research, Cilt 30(42), 95720-95737. doi: 10.1007/s11356-023-29051-1
31. JIANG, Y., LI, X., LUO, H., YIN, S. & KAYNAK, O. (2022). Quo vadis artificial intelligence? Discover Artificial Intelligence, Cilt 2(4). doi: 10.1007/s44163-022-00022-8
32. JORZIK, P. & ANTONIO, J. L. & KANBACH, D. K. & KALLMUENZER, A. & KRAUS, S. (2024). Sowing the seeds for sustainability: A business model innovation perspective on artificial intelligence in green technology startups. Technological Forecasting and Social Change, Cilt 208(12365). doi:10.1016/j.techfore.2024.123653
33. KAGERMANN, H., WAHLSTER, W. & HELBIG, J. (2013) Securing the future of German manufacturing industry: recommendations for ımplementing the strategic initiative industrie 4.0. final report of the industrie 4.0 working group, Acatech— National Academy of Science and Engineering.
34. KAZANCOGLU, I., OZBİLTEKİN-PALA, M., MANGLA, S. K., KUMAR, A., & KAZANCOGLU, Y. (2023). Using emerging technologies to improve the sustainability and resilience of supply chains in a fuzzy environment in the context of COVID-19. Annals of Operations Research, Cilt 322(1), 217-240. doi: 10.1007/s10479-022-04775-4
35. KEINER, M. (2005). History, definition(s) and models of sustainable development. ETH Zürich. doi: 10.3929/ethz-a-004995678
36. LIN, W.-K., LIN, S.-J., & YANG, T.-N. (2017). Integrated business prestige and artificial ıntelligence for corporate decision making in dynamic environments. Cybernetics and Systems, Cilt 48(4), 303–324. doi: 10.1080/01969722.2017.1284533
37. LUTOSLAWSKI, K., HERNES, M., RADOMSKA, J., HAJDAS, M., WALASZCZYK, E., & KOZINA, A. (2021). Food demand prediction using the nonlinear autoregressive exogenous neural network. IEEE Access, Cilt 9, 146123-146136. doi: 10.1109/access.2021.3123255
38. MAHER, H. MEINECKE, H., GROMIER, D., GARCIA-NOVELLI, M. & FORTMANN, R. (2022). How AI Can Be a Powerful Tool in the Fight Against Climate Change. BCG GAMMA, AI for the Planet.
39. MCLUHAN, M., FİORE, Q. (2019). Yaradanımız medya: Medyanın etkileri üzerine bir keşif yolculuğu. İstanbul: Nora.
40. MOHER, D., LIBERATI, A., TETZLAFF, J., ALTMAN, DG, & THE PRISMA GROUP (2009) preferred reporting ıtems for systematic reviews and meta analyses: The PRISMA Statement. PLoS Med, Cilt 6(7): e1000097. doi:10.1371/journal.pmed.1000097
41. MONROY-OSORIO, J. C. (2024). Charting the digital route to net-zero: A framework for sustainable industry practices. Cleaner Logistics and Supply Chain, Cilt 13. doi: 10.1016/j.clscn.2024.100191
42. MUNIR, S., ABDUL RASID, S. Z., AAMIR, M., JAMIL, F., & AHMED, I. (2023). Big data analytics capabilities and innovation effect of dynamic capabilities, organizational culture and role of management accountants. Foresight, Cilt 25(1), 41-66. doi: 10.1108/fs-08-2021-0161
43. NORDGREN, A. (2023), Artificial intelligence and climate change: ethical issues. Journal of Information, Communication and Ethics in Society,Cilt 21(1), 1-15. doi: 10.1108/JICES-11-2021-0106
44. OECD (2019). Artificial intelligence in society. Paris: OECD Publishing. doi: 10.1787/eedfee77-en.
45. OGBURN, W. F. (1922). Social change with respect to culture and original nature. New York: B.W. Huebsch, Inc.
46. POPKOVA, E. G., BOGOVIZ, A. V., EKIMOVA, K. V., & SERGI, B. S. (2023). Will Russia become a blueprint for emerging nations’ high-tech reforms? Evidence from a 26-countries dataset. International Journal of Innovation Studies, Cilt 7(4), 294-306. doi: 10.1016/j.ijis.2023.05.001
47. RONAGHI, M. H. (2023). The influence of artificial intelligence adoption on circular economy practices in manufacturing industries. Environment, Development and Sustainability, Cilt 25(12), 14355-14380. Doi:10.1007/s10668-022-02670-3
48. SAMADHAYIA, A., KUMAR, A., YADAV, S., LUTHRA, S., JABBOUR, C. J. C. & AGRAWAL, R. (2023). Artificial intelligence - partner relationships management for climate management in B2B firms to achieve sustainable competitiveness. Industrial Marketing Management, Cilt 115, 510-525. doi:10.1016/j.indmarman.2023.11.002
49. SHAHZAD, F., ZAIED, Y. B., SHAHZAD, M. A., & MAHMOOD, F. (2024). Insights into the performance of green supply chain in the Chinese semiconductor industry. International Journal of Production Economics, Cilt 273. 109286. doi: 10.1016/j.ijpe.2024.109286
50. SHAIK, A. S., ALSHIBANI, S. M., JAIN, G., GUPTA, B., & MEHROTRA, A. (2023). Artificial intelligence (AI)‐driven strategic business model innovations in small‐ and medium‐sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses. Business Strategy and the Environment, Cilt 33(4), 2731-2751. doi: 10.1002/bse.3617
51. SMIT, J., KREUTZER, S., MOELLER, C. & CARLBERG, M. (2016) Industry 4.0: Study for the ITR Committee. Directorate General For Internal Policies, Policy Department A: Economic and scientific policy. European Parliament. EU.
52. SOCOL, A., MARIN-PANTELESCU, A., TAMAS-SZORA, A. & CIOCA, C. I. (2024). The impact of artificial intelligence applied in businesses on economic growth, welfare and social disparities. Amfiteatru Economic, Cilt 26(66), 475-493.
53. SONG, M., PAN, H., SHEN, Z., & TAMAYO-VERLEENE, K. (2024). Assessing the influence of artificial intelligence on the energy efficiency for sustainable ecological products value. Energy Economics, Cilt 131. 107392. doi:10.1016/j.eneco.2024.107392
54. SUMARLIAH, E. & AL-HAKEEM, B. (2023). The effects of digital innovations and sustainable supply chain management on business competitive performance post-COVID-19. Kybernetes, Cilt 52(7), 2568-2596. doi:10.1108/K-09-2022-1326
55. TOFFLER, A. (2008). Üçüncü dalga: Bir fütürist ekonomi analizi klasiği. İstanbul: Koridor Yayıncılık.
56. TRABUCCO, M., & DE GIOVANNI, P. (2021). Achieving resilience and business sustainability during COVID-19: The role of lean supply chain practices and digitalization. Sustainability, Cilt 13(22), 12369. doi:10.3390/su132212369
57. TUĞAÇ, Ç. (2023). İklim değişikliği ve yapay zekâ: fırsatlar ve sorunlar. Hitit Sosyal Bilimler Dergisi, Cilt 16(1), 74-94. doi:10.17218/hititsbd.1240744
58. TUPA, J., SIMOTA J., & STEINER F. (2017). Aspects of risk management implementation for Industry 4.0. Procedia Manufacturing, Cilt 11, 1223 – 1230.
59. VRCHOTA, J., VOLEK, T., & NOVOTNÁ, M. (2019). Factors introducing industry 4.0 to SMES. Social Sciences, cilt 8(5), 130. doi:10.3390/socsci8050130
60. WANG B., RAU, P.-L. P. & YUAN, T. (2023). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, Cilt 42(9), 1324-1337, doi: 10.1080/0144929X.2022.2072768
61. WANG, F., WONG, W.-K., ORTIZ, G. G. R., AL SHRAAH, A., MABROUK, F., LI, J., & LI, Z. (2023). Economic analysis of sustainable exports value addition through natural resource management and artificial intelligence. Resources Policy, Cilt 82(103541). doi:10.1016/j.resourpol.2023.103541
62. WANG, J., WANG, X., SUN, F., & LI, X. (2024). The functional mechanisms through which artificial ıntelligence influences the innovation of green processes of enterprises. Systems, Cilt 12(378). doi:10.3390/systems12090378
63. WEBER-LEWERENZ, B. (2021). Corporate digital responsibility (CDR) in construction engineering—ethical guidelines for the application of digital transformation and artificial intelligence (AI) in user practice. SN Applied Sciences, Cilt 3(801). doi:10.1007/s42452-021-04776-1
64. XU, Y., LIU, X., CAO, X., HUANG, C., LIU, E., QIAN, S., ... & ZHANG, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, Cilt 2(4), 1-20. doi: 10.1016/j.xinn.2021.100179
65. YILMAZ, K. (2021). Sosyal bilimlerde ve eğitim bilimlerinde sistematik derleme, meta değerlendirme ve bibliyometrik analizler. Manas Sosyal Araştırmalar Dergisi, Cilt 10(2), 1457-1490.
66. YI, Y. (2021). Establishing the concept of ai literacy: Focusing on competence and purpose. JAHR, Cilt 12/2(24), 353-368. https://doi.org/10.21860/j.12.2.8