This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2024). AI-powered innovation in digital transformation: Key pillars and industry impact. Sustainability, 16(5), 1790.https://doi.org/10.3390/su16051790AldoseriA.Al-KhalifaK. N.HamoudaA. M. (2024). AI-powered innovation in digital transformation: Key pillars and industry impact. Sustainability, 16(5), 1790. https://doi.org/10.3390/su16051790Search in Google Scholar
Balcerzak, A. P., & Valaskova, K. (2024). Artificial intelligence: Financial management under pressure of transformative technology. Equilibrium Quarterly Journal of Economics and Economic Policy, 19(4), 1127–1137.https://doi.org/10.24136/eq.3394BalcerzakA. P.ValaskovaK. (2024). Artificial intelligence: Financial management under pressure of transformative technology. Equilibrium Quarterly Journal of Economics and Economic Policy, 19(4), 1127–1137. https://doi.org/10.24136/eq.3394Search in Google Scholar
Balcerzak, A. P., Nica, E., Rogalska, E., Poliak, M., Kliestik, T., & Sabie, O. (2022). Blockchain technology and smart contracts in decentralized governance systems. Administrative Sciences, 12 (3), 96.https://doi.org/10.3390/admsci12030096BalcerzakA. P.NicaE.RogalskaE.PoliakM.KliestikT.SabieO. (2022). Blockchain technology and smart contracts in decentralized governance systems. Administrative Sciences, 12 (3), 96. https://doi.org/10.3390/admsci12030096Search in Google Scholar
Barker, M. (2023). Artificial intelligence-based Internet of manufacturing things systems, digital twin data modeling and visualization tools, and multi-sensory extended reality and geospatial mapping technologies in the immersive industrial metaverse. Economics, Management, and Financial Markets, 18(1), 41-56. https://doi.org/10.22381/EMFM18120233BarkerM. (2023). Artificial intelligence-based Internet of manufacturing things systems, digital twin data modeling and visualization tools, and multi-sensory extended reality and geospatial mapping technologies in the immersive industrial metaverse. Economics, Management, and Financial Markets, 18(1), 41-56. https://doi.org/10.22381/EMFM18120233Search in Google Scholar
Brem, A., Giones, F., & Werle, M. (2021). The AI digital revolution in innovation: A conceptual framework of Artificial intelligence technologies for the management of innovation. IEEE Transactions on Engineering Management, 70(2), 770–776.https://doi.org/10.1109/tem.2021.3109983BremA.GionesF.WerleM. (2021). The AI digital revolution in innovation: A conceptual framework of Artificial intelligence technologies for the management of innovation. IEEE Transactions on Engineering Management, 70(2), 770–776. https://doi.org/10.1109/tem.2021.3109983Search in Google Scholar
Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 355(6370), 1530–1534. https://doi.org/10.1126/science.aap8062BrynjolfssonE.MitchellT. (2017). What can machine learning do? Workforce implications. Science, 355(6370), 1530–1534. https://doi.org/10.1126/science.aap8062Search in Google Scholar
Carayannis, E. G., Dumitrescu, R., Falkowski, T., Papamichail, G., & Zota, N. R. (2025). Enhancing SME resilience through artificial intelligence and strategic foresight: A framework for sustainable competitiveness. Technology in Society, 51, 102835.https://doi.org/10.1016/j.techsoc.2025.102835CarayannisE. G.DumitrescuR.FalkowskiT.PapamichailG.ZotaN. R. (2025). Enhancing SME resilience through artificial intelligence and strategic foresight: A framework for sustainable competitiveness. Technology in Society, 51, 102835. https://doi.org/10.1016/j.techsoc.2025.102835Search in Google Scholar
Carter, M., & Carter, C. (2020). The creative business model Canvas. Social Enterprise Journal, 16 (2), 141–158.https://doi.org/10.1108/sej-03-2019-0018CarterM.CarterC. (2020). The creative business model Canvas. Social Enterprise Journal, 16 (2), 141–158. https://doi.org/10.1108/sej-03-2019-0018Search in Google Scholar
CB Insights. (2024). Median valuations for artificial intelligence (AI) and non-AI startups worldwide in 2023, by stage (in million U.S. dollars). https://www.statista.com/statistics/1446293/median-valuations-ai-startups-by-stage/CB Insights (2024). Median valuations for artificial intelligence (AI) and non-AI startups worldwide in 2023, by stage (in million U.S. dollars). https://www.statista.com/statistics/1446293/median-valuations-ai-startups-by-stage/Search in Google Scholar
Climent, R. C., Haftor, D. M., & Staniewski, M. W. (2024). AI-enabled business models for competitive advantage. Journal of Innovation & Knowledge, 9(3), 100532.https://doi.org/10.1016/j.jik.2024.100532ClimentR. C.HaftorD. M.StaniewskiM. W. (2024). AI-enabled business models for competitive advantage. Journal of Innovation & Knowledge, 9(3), 100532. https://doi.org/10.1016/j.jik.2024.100532Search in Google Scholar
Consuegra, L. C., Vasquez, P. a. M., & Perez, A. M. M. (2023). Algoritmos de inteligencia artificial basada en perfiles socio conductuales para la segmentación inteligente de clientes: Estudio de caso. Ingeniería Y Competitividad,25(3). https://doi.org/10.25100/iyc.v25i3.12658ConsuegraL. C.VasquezP. a. M.PerezA. M. M. (2023). Algoritmos de inteligencia artificial basada en perfiles socio conductuales para la segmentación inteligente de clientes: Estudio de caso. Ingeniería Y Competitividad, 25(3). https://doi.org/10.25100/iyc.v25i3.12658Search in Google Scholar
Dabija, D. C., & Vătămănescu, E. (2023). Artificial intelligence: The future is already here. Oeconomia Copernicana, 14(4), 1053–1056. https://doi.org/10.24136/oc.2023.031DabijaD. C.VătămănescuE. (2023). Artificial intelligence: The future is already here. Oeconomia Copernicana, 14(4), 1053–1056. https://doi.org/10.24136/oc.2023.031Search in Google Scholar
De Vasconcelos Gomes, L. A., Farago, F. E., Facin, A. L. F., Flechas, X. A., & Silva, L. E. N. (2023). From open business model to ecosystem business model: A processes view. Technological Forecasting and Social Change, 194, 122668.https:ZZdoi.org/10.1016Zj.techfore.2023.122668De Vasconcelos GomesL. A.FaragoF. E.FacinA. L. F.FlechasX. A.SilvaL. E. N. (2023). From open business model to ecosystem business model: A processes view. Technological Forecasting and Social Change, 194, 122668. https:ZZdoi.org/10.1016Zj.techfore.2023.122668Search in Google Scholar
Deligianni, I., Voudouris, I., Spanos, Y., & Lioukas, S. (2019). Non-linear effects of technological competence on product innovation in new technology-based firms: Resource orchestration and the role of the entrepreneur’s political competence and prior start-up experience. Technovation, 88, 102076.https://doi.org/10.1016/j.technovation2019.05.002DeligianniI.VoudourisI.SpanosY.LioukasS. (2019). Non-linear effects of technological competence on product innovation in new technology-based firms: Resource orchestration and the role of the entrepreneur’s political competence and prior start-up experience. Technovation, 88, 102076. https://doi.org/10.1016/j.technovation2019.05.002Search in Google Scholar
Dokumacı, M. (2024). Legal frameworks for AI regulations. Human Computer Interaction., 8 (1), 133.https://doi.org/10.62802/ytst2927DokumacıM. (2024). Legal frameworks for AI regulations. Human Computer Interaction., 8 (1), 133. https://doi.org/10.62802/ytst2927Search in Google Scholar
Fakieh, B., Al-Ghamdi, A. S. A., & Ragab, M. (2022). The effect of utilizing business model canvas on the satisfaction of operating electronic business. Complexity, 2022(1).https://doi.org/10.1155/2022/1649160FakiehB.Al-GhamdiA. S. A.RagabM. (2022). The effect of utilizing business model canvas on the satisfaction of operating electronic business. Complexity, 2022(1). https://doi.org/10.1155/2022/1649160Search in Google Scholar
Farahani, M. S., & Esfahani, A. (2022). Opportunities and challenges of applying artificial intelligence in the financial sectors and startups during the coronavirus outbreak. International Journal of Innovation in Management Economics and Social Sciences, 2(4), 33–55.https://doi.org/10.52547/ijimes.2.4.33FarahaniM. S.EsfahaniA. (2022). Opportunities and challenges of applying artificial intelligence in the financial sectors and startups during the coronavirus outbreak. International Journal of Innovation in Management Economics and Social Sciences, 2(4), 33–55. https://doi.org/10.52547/ijimes.2.4.33Search in Google Scholar
Fu, D., Jenkinson, T., & Rauch, C. (2022). How do financial contracts evolve for new ventures? Journal of Corporate Finance, 81, 102222. https://doi.org/10.1016/j.jcorpfin.2022.102222FuD.JenkinsonT.RauchC. (2022). How do financial contracts evolve for new ventures?Journal of Corporate Finance, 81, 102222. https://doi.org/10.1016/j.jcorpfin.2022.102222Search in Google Scholar
Gambardella, A., & McGahan, A. M. (2009). Business-model innovation: General purpose technologies and their implications for industry structure. Long Range Planning, 43(2–3), 262–271.https://doi.Org/10.1016/j.lrp.2009.07.009GambardellaA.McGahanA. M. (2009). Business-model innovation: General purpose technologies and their implications for industry structure. Long Range Planning, 43(2–3), 262–271. https://doi.Org/10.1016/j.lrp.2009.07.009Search in Google Scholar
Gentsch, P. (2019). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Springer.https://doi.org/10.1007/978-3-319-89957-2GentschP. (2019). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Springer. https://doi.org/10.1007/978-3-319-89957-2Search in Google Scholar
Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660.https://doi.org/10.5465/annals.2018.0057GliksonE.WoolleyA. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057Search in Google Scholar
Gültekin, D. G., Pinarbasi, F., Yazici, M., & Adiguzel, Z. (2024). Commercialisation of artificial intelligence: A research on entrepreneurial companies with challenges and opportunities. Business Process Management Journal, 31(2), 605–630. https://doi.org/10.1108/bpmj-10-2023-0836GültekinD. G.PinarbasiF.YaziciM.AdiguzelZ. (2024). Commercialisation of artificial intelligence: A research on entrepreneurial companies with challenges and opportunities. Business Process Management Journal, 31(2), 605–630. https://doi.org/10.1108/bpmj-10-2023-0836Search in Google Scholar
Hartmann, P. M., Zaki, M., Feldmann, N., & Neely, A. (2016). Capturing value from big data – a taxonomy of data-driven business models used by start-up firms. International Journal of Operations & Production Management, 36(10), 1382–1406.https://doi.org/10.1108/ijopm-02-2014-0098HartmannP. M.ZakiM.FeldmannN.NeelyA. (2016). Capturing value from big data a taxonomy of data-driven business models used by start-up firms. International Journal of Operations & Production Management, 36(10), 1382–1406. https://doi.org/10.1108/ijopm-02-2014-0098Search in Google Scholar
Hossain, M. A., Akter, S., Yanamandram, V., & Wamba, S. F. (2023). Data-driven market effectiveness: The role of a sustained customer analytics capability in business operations. Technological Forecasting and Social Change, 194, 122745.https://doi.org/10.1016/j.techfore.2023.122745HossainM. A.AkterS.YanamandramV.WambaS. F. (2023). Data-driven market effectiveness: The role of a sustained customer analytics capability in business operations. Technological Forecasting and Social Change, 194, 122745. https://doi.org/10.1016/j.techfore.2023.122745Search in Google Scholar
Jan, Z., Ahamed, F., Mayer, W., Patel, N., Grossmann, G., Stumptner, M., & Kuusk, A. (2022). Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities. Expert Systems with Applications, 216, 119456.https://doi.org/10.1016Zj.eswa.2022.119456JanZ.AhamedF.MayerW.PatelN.GrossmannG.StumptnerM.KuuskA. (2022). Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities. Expert Systems with Applications, 216, 119456. https://doi.org/10.1016Zj.eswa.2022.119456Search in Google Scholar
Jiang, Y., Li, X., Luo, H., Yin, S., & Kaynak, O. (2022). Quo vadis artificial intelligence? Discover Artificial Intelligence, 2(1).https://doi.org/10.1007/s44163-022-00022-8JiangY.LiX.LuoH.YinS.KaynakO. (2022). Quo vadis artificial intelligence?Discover Artificial Intelligence, 2(1). https://doi.org/10.1007/s44163-022-00022-8Search in Google Scholar
Jin, Y., Ji, S., Liu, L., & Wang, W. (2021). Business model innovation canvas: A visual business model innovation model. European Journal of Innovation Management, 25(5), 1469–1493.https://doi.org/10.1108/ejim-02-2021-0079JinY.JiS.LiuL.WangW. (2021). Business model innovation canvas: A visual business model innovation model. European Journal of Innovation Management, 25(5), 1469–1493. https://doi.org/10.1108/ejim-02-2021-0079Search in Google Scholar
Kaggwa, S., Eleogu, T. F., Okonkwo, F., Farayola, O. A., Uwaoma, P. U., & Akinoso, A. (2024). AI in decision making: Transforming business strategies. International Journal of Research and Scientific Innovation, 10(12), 423–444. https://doi.org/10.51244/ijrsi.2023.1012032KaggwaS.EleoguT. F.OkonkwoF.FarayolaO. A.UwaomaP. U.AkinosoA. (2024). AI in decision making: Transforming business strategies. International Journal of Research and Scientific Innovation, 10(12), 423–444. https://doi.org/10.51244/ijrsi.2023.1012032Search in Google Scholar
Kaplan, A., & Haenlein, M. (2018). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25.https://doi.org/10.1016/j.bushor.2018.08.004KaplanA.HaenleinM. (2018). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004Search in Google Scholar
Kellogg, K. C., Valentine, M. A., & Christin, A. (2019). Algorithms at work: the new contested terrain of control. Academy of Management Annals, 14(1), 366–410.https://doi.org/10.5465/annals.2018.0174KelloggK. C.ValentineM. A.ChristinA. (2019). Algorithms at work: the new contested terrain of control. Academy of Management Annals, 14(1), 366–410. https://doi.org/10.5465/annals.2018.0174Search in Google Scholar
Kerzel, U. (2020). Enterprise AI canvas integrating artificial intelligence into business. Applied Artificial Intelligence, 35 (1), 1–12.https://doi.org/10.1080/08839514.2020.1826146KerzelU. (2020). Enterprise AI canvas integrating artificial intelligence into business. Applied Artificial Intelligence, 35 (1), 1–12. https://doi.org/10.1080/08839514.2020.1826146Search in Google Scholar
Khan, I. U., Taherdoost, H., Madanchian, M., Ouaissa, M., Hajjami, S. E., & Rahman, H. (2024). Future tech startups and innovation in the age of AI (1st ed.). CRC Press. https://doi.org/10.1201/9781032715957KhanI. U.TaherdoostH.MadanchianM.OuaissaM.HajjamiS. E.RahmanH. (2024). Future tech startups and innovation in the age of AI (1st ed.). CRC Press. https://doi.org/10.1201/9781032715957Search in Google Scholar
Kliestik, T., Kral, P., Bugaj, M., & Durana, P. (2024). Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse. Equilibrium Quarterly Journal of Economics and Economic Policy, 19(2), 429–461.https://doi.org/10.24136/eq.3108KliestikT.KralP.BugajM.DuranaP. (2024). Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse. Equilibrium Quarterly Journal of Economics and Economic Policy, 19(2), 429–461. https://doi.org/10.24136/eq.3108Search in Google Scholar
Kuteesa, N. K. N., Akpuokwe, N. C. U., & Udeh, N. C. A. (2024). Navigating the digital transformation journey: Strategies for startup growth and innovation in the digital era. International Journal of Scholarly Research in Multidisciplinary Studies, 4(2), 038–053.https://doi.org/10.56781/ijsrms.2024.4.2.0031KuteesaN. K. N.AkpuokweN. C. U.UdehN. C. A. (2024). Navigating the digital transformation journey: Strategies for startup growth and innovation in the digital era. International Journal of Scholarly Research in Multidisciplinary Studies, 4(2), 038–053. https://doi.org/10.56781/ijsrms.2024.4.2.0031Search in Google Scholar
Lee, B., Kim, B., & Ivan, U. V. (2023). Enhancing the competitiveness of AI technology-based startups in the digital era. Administrative Sciences, 14(1), 6. https://doi.org/10.3390/admsci14010006LeeB.KimB.IvanU. V. (2023). Enhancing the competitiveness of AI technology-based startups in the digital era. Administrative Sciences, 14(1), 6. https://doi.org/10.3390/admsci14010006Search in Google Scholar
Libai, B., Bart, Y., Gensler, S., Hofacker, C. F., Kaplan, A., Kötterheinrich, K., & Kroll, E. B. (2020). Brave new world? On AI and the management of customer relationships. Journal of Interactive Marketing, 51 (1), 44–56.https://doi.org/10.1016/j.intmar.2020.04.002LibaiB.BartY.GenslerS.HofackerC. F.KaplanA.KötterheinrichK.KrollE. B. (2020). Brave new world? On AI and the management of customer relationships. Journal of Interactive Marketing, 51 (1), 44–56. https://doi.org/10.1016/j.intmar.2020.04.002Search in Google Scholar
Macha-Huamán, R., Zavala-Zavala, O. M., Soto, F. C. N., Suárez, J. S. Z., Castañeda, D. R. Y., Lucar, R. G. C., Jibaja, L. C., Mejía, P. J. C., Montoya, C. M. S., Casco, R. J. E., & Romero-Carazas, R. (2023). Business model canvas in the entrepreneurs’ business model: A system approach. ICST Transactions on Scalable Information Systems, 10(5), 1–9. https://doi.org/10.4108/eetsis.3594Macha-HuamánR.Zavala-ZavalaO. M.SotoF. C. N.SuárezJ. S. Z.CastañedaD. R. Y.LucarR. G. C.JibajaL. C.MejíaP. J. C.MontoyaC. M. S.CascoR. J. E.Romero-CarazasR. (2023). Business model canvas in the entrepreneurs’ business model: A system approach. ICST Transactions on Scalable Information Systems, 10(5), 1–9. https://doi.org/10.4108/eetsis.3594Search in Google Scholar
Makarius, E. E., Mukherjee, D., Fox, J. D., & Fox, A. K. (2020). Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization. Journal of Business Research, 120, 262–273. https://doi.org/10.1016/j.jbusres.2020.07.045MakariusE. E.MukherjeeD.FoxJ. D.FoxA. K. (2020). Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization. Journal of Business Research, 120, 262–273. https://doi.org/10.1016/j.jbusres.2020.07.045Search in Google Scholar
Mao, H., Zhang, T., & Tang, Q. (2021). Research framework for determining how artificial intelligence enables information technology service management for business model resilience. Sustainability, 13(20), 11496. https://doi.org/10.3390/su132011496MaoH.ZhangT.TangQ. (2021). Research framework for determining how artificial intelligence enables information technology service management for business model resilience. Sustainability, 13(20), 11496. https://doi.org/10.3390/su132011496Search in Google Scholar
Martinović, M., Barać, R., & Maljak, H. (2024). Exploring Croatian consumer adoption of subscription-based e-commerce for business innovation. Administrative Sciences, 14 (7), 149.https://doi.org/10.3390/admsci14070149MartinovićM.BaraćR.MaljakH. (2024). Exploring Croatian consumer adoption of subscription-based e-commerce for business innovation. Administrative Sciences, 14 (7), 149. https://doi.org/10.3390/admsci14070149Search in Google Scholar
Metzker, Z. (2024). Selected demographic determinants of CSR, financial & environmental management and business ethics in SMEs. Deleted Journal, 2(1), 79–88.https://doi.org/10.62222/fend1256MetzkerZ. (2024). Selected demographic determinants of CSR, financial & environmental management and business ethics in SMEs. Deleted Journal, 2(1), 79–88. https://doi.org/10.62222/fend1256Search in Google Scholar
Mohammadi, N., & Shafiee, M. (2022). Predicting the success of seed-stage startups to enter the acceleration program and receive seed money. International Journal of Entrepreneurial Venturing, 14(2), 168.https://doi.org/10.1504/ijev.2022.122654MohammadiN.ShafieeM. (2022). Predicting the success of seed-stage startups to enter the acceleration program and receive seed money. International Journal of Entrepreneurial Venturing, 14(2), 168. https://doi.org/10.1504/ijev.2022.122654Search in Google Scholar
Murray, A., & Scuotto, V. (2016). The business model canvas. Symphonya Emerging Issues in Management, 3, 94–109.https://doi.org/10.4468/2015.3.13murray.scuottoMurrayA.ScuottoV. (2016). The business model canvas. Symphonya Emerging Issues in Management, 3, 94–109. https://doi.org/10.4468/2015.3.13murray.scuottoSearch in Google Scholar
Musch, S., Borrelli, M. C., & Kerrigan, C. (2024). Bridging compliance and innovation: A comparative analysis of the EU AI Act and GDPR for enhanced organisational strategy. Journal of Data Protection & Privacy, 7(1), 14. https://doi.org/10.69554/fwhu3837MuschS.BorrelliM. C.KerriganC. (2024). Bridging compliance and innovation: A comparative analysis of the EU AI Act and GDPR for enhanced organisational strategy. Journal of Data Protection & Privacy, 7(1), 14. https://doi.org/10.69554/fwhu3837Search in Google Scholar
Nagy, M., Figura, M., Valaskova, K., & Lăzăroiu, G. (2025). Predictive maintenance algorithms, artificial intelligence digital twin technologies, and internet of robotic things in big data-driven industry 4.0 manufacturing systems. Mathematics, 13(6), 981.https://doi.org/10.3390/math13060981NagyM.FiguraM.ValaskovaK.LăzăroiuG. (2025). Predictive maintenance algorithms, artificial intelligence digital twin technologies, and internet of robotic things in big data-driven industry 4.0 manufacturing systems. Mathematics, 13(6), 981. https://doi.org/10.3390/math13060981Search in Google Scholar
Nagy, M., Lăzăroiu, G., & Valaskova, K. (2023). Machine intelligence and autonomous robotic technologies in the corporate context of SMES: Deep learning and virtual simulation algorithms, cyber-physical production networks, and industry 4.0-based manufacturing systems. Applied Sciences, 13(3), 1681. https://doi.org/10.3390/app13031681NagyM.LăzăroiuG.ValaskovaK. (2023). Machine intelligence and autonomous robotic technologies in the corporate context of SMES: Deep learning and virtual simulation algorithms, cyber-physical production networks, and industry 4.0-based manufacturing systems. Applied Sciences, 13(3), 1681. https://doi.org/10.3390/app13031681Search in Google Scholar
Ozay, D., Jahanbakht, M., Shoomal, A., & Wang, S. (2024). Artificial intelligence (AI)-based customer relationship management (CRM): A comprehensive bibliometric and systematic literature review with outlook on future research. Enterprise Information Systems, 18(7).https://doi.org/10.1080/17517575.2024.2351869OzayD.JahanbakhtM.ShoomalA.WangS. (2024). Artificial intelligence (AI)-based customer relationship management (CRM): A comprehensive bibliometric and systematic literature review with outlook on future research. Enterprise Information Systems, 18(7). https://doi.org/10.1080/17517575.2024.2351869Search in Google Scholar
Piotrowski, D., & Orzeszko, W. (2023). Artificial intelligence and customers’ intention to use robo-advisory in banking services. Equilibrium Quarterly Journal of Economics and Economic Policy, 18(4), 967–1007.https://doi.org/10.24136/eq.2023.031PiotrowskiD.OrzeszkoW. (2023). Artificial intelligence and customers’ intention to use robo-advisory in banking services. Equilibrium Quarterly Journal of Economics and Economic Policy, 18(4), 967–1007. https://doi.org/10.24136/eq.2023.031Search in Google Scholar
Purwanto, A. N. I., Fauzan, M., Widya, T., & Azzaky, N. S. (2024). Ethical Implications and challenges of AI implementation in business operations. Techcomp Innovations, 1(2), 68–82.https://doi.org/10.70063/techcompinnovations.v1i2.52PurwantoA. N. I.FauzanM.WidyaT.AzzakyN. S. (2024). Ethical Implications and challenges of AI implementation in business operations. Techcomp Innovations, 1(2), 68–82. https://doi.org/10.70063/techcompinnovations.v1i2.52Search in Google Scholar
Rahim, M. J., Afroz, A., & Akinola, O. (2025). Predictive analytics in healthcare: big data, better decisions. International Journal of Scientific Research and Modern Technology, 4 (1), 1-21.https://doi.org/10.5281/zenodo.14630840RahimM. J.AfrozA.AkinolaO. (2025). Predictive analytics in healthcare: big data, better decisions. International Journal of Scientific Research and Modern Technology, 4 (1), 1-21. https://doi.org/10.5281/zenodo.14630840Search in Google Scholar
Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210.https://doi.org/10.5465/amr.2018.0072RaischS.KrakowskiS. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072Search in Google Scholar
Riedl, R. (2022). Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions. Electronic Markets, 32(4), 2021–2051.https://doi.org/10.1007/s12525-022-00594-4RiedlR. (2022). Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions. Electronic Markets, 32(4), 2021–2051. https://doi.org/10.1007/s12525-022-00594-4Search in Google Scholar
Rios-Campos, C., Zambrano, E. O. G., Vargas, D. J. C., Merino, L. a. A., Vallejos, P. a. A., Alcantara, I. M. B., Rubio, D. E. D., Rodriguez, D. S., Tomanguilla, J. H., & Calderón, E. V. (2024). Startups and artificial intelligence. South Florida Journal of Development, 5(2), 950–969.https://doi.org/10.46932/sfjdv5n2-042Rios-CamposC.ZambranoE. O. G.VargasD. J. C.MerinoL. a. A.VallejosP. a. A.AlcantaraI. M. B.RubioD. E. D.RodriguezD. S.TomanguillaJ. H.CalderónE. V. (2024). Startups and artificial intelligence. South Florida Journal of Development, 5(2), 950–969. https://doi.org/10.46932/sfjdv5n2-042Search in Google Scholar
Salwin, M., Jacyna-Gołda, I., Kraslawski, A., & Waszkiewicz, A. E. (2022). The use of business model canvas in the design and classification of product-service systems design methods. Sustainability, 14(7), 4283.https://doi.org/10.3390/su14074283SalwinM.Jacyna-GołdaI.KraslawskiA.WaszkiewiczA. E. (2022). The use of business model canvas in the design and classification of product-service systems design methods. Sustainability, 14(7), 42–83. https://doi.org/10.3390/su14074283Search in Google Scholar
Sarma, M., Senaratne, C., & Matheus, T. (2023). Challenges and opportunities of ethical AI and digital technology use in emerging economies. In M. Findlay, L. M. Ong & W. Zhang (Eds.), Elgar Companion to Regulating AI and Big Data in Emerging Economies (pp. 42–58). Edward Elgar Publishing.https://doi.org/10.4337/9781785362408.00009SarmaM.SenaratneC.MatheusT. (2023). Challenges and opportunities of ethical AI and digital technology use in emerging economies. In M.FindlayL. M.OngW.Zhang (Eds.), Elgar Companion to Regulating AI and Big Data in Emerging Economies (pp. 42–58). Edward Elgar Publishing. https://doi.org/10.4337/9781785362408.00009Search in Google Scholar
Selvakumar, P., Shanthi, M., Pitchiah, R., Sharma, M., Dahake, P. S., & T. C., M. (2025). The Role of Artificial Intelligence in Business Model Innovation: Overview of AI Technologies. In M. Khokhar (Ed.), AI-Driven Business Model Innovation (pp. 219-246). IGI Global Scientific Publishing.https://doi.org/10.4018/979-8-3693-9571-4.ch009SelvakumarP.ShanthiM.PitchiahR.SharmaM.DahakeP. S.T. C., M. (2025). The Role of Artificial Intelligence in Business Model Innovation: Overview of AI Technologies. In M.Khokhar (Ed.), AI-Driven Business Model Innovation (pp. 219-246). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9571-4.ch009Search in Google Scholar
Sestino, A., & De Mauro, A. (2021). Leveraging artificial intelligence in business: implications, applications and methods. Technology Analysis and Strategic Management, 34(1), 16–29.https://doi.org/10.1080/09537325.2021.1883583SestinoA.De MauroA. (2021). Leveraging artificial intelligence in business: implications, applications and methods. Technology Analysis and Strategic Management, 34(1), 16–29. https://doi.org/10.1080/09537325.2021.1883583Search in Google Scholar
Sjödin, D., Parida, V., Palmié, M., & Wincent, J. (2021). How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 134, 574–587.https://doi.org/10.1016/j.jbusres.2021.05.009SjödinD.ParidaV.PalmiéM.WincentJ. (2021). How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 134, 574–587. https://doi.org/10.1016/j.jbusres.2021.05.009Search in Google Scholar
Smuha, N. A. (2021). From a ‘race to AI’ to a ‘race to AI regulation’: regulatory competition for artificial intelligence. Law Innovation and Technology, 13(1), 57–84.https://doi.org/10.1080/17579961.2021.1898300SmuhaN. A. (2021). From a ‘race to AI’ to a ‘race to AI regulation’: regulatory competition for artificial intelligence. Law Innovation and Technology, 13(1), 57–84. https://doi.org/10.1080/17579961.2021.1898300Search in Google Scholar
Song, X., & Bonanni, C. (2024). AI-driven business model: How AI-powered try-on technology is refining the luxury shopping experience and customer satisfaction. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 3067–3087.https://doi.org/10.3390/jtaer19040148SongX.BonanniC. (2024). AI-driven business model: How AI-powered try-on technology is refining the luxury shopping experience and customer satisfaction. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 3067–3087. https://doi.org/10.3390/jtaer19040148Search in Google Scholar
Soussi, A., Zero, E., Sacile, R., Trinchero, D., & Fossa, M. (2024). Smart sensors and smart data for precision agriculture: A review. Sensors, 24(8), 2647.https://doi.org/10.3390/s24082647SoussiA.ZeroE.SacileR.TrincheroD.FossaM. (2024). Smart sensors and smart data for precision agriculture: A review. Sensors, 24(8), 2647. https://doi.org/10.3390/s24082647Search in Google Scholar
Stork, S., Morgenstern, R., Pölling, B., & Feil, J. (2023). Holistic business model conceptualisation—capturing sustainability contributions illustrated by nature-based solutions. Sustainability, 15(19), 14091.https://doi.org/10.3390/su151914091StorkS.MorgensternR.PöllingB.FeilJ. (2023). Holistic business model conceptualisation—capturing sustainability contributions illustrated by nature-based solutions. Sustainability, 15(19), 14091. https://doi.org/10.3390/su151914091Search in Google Scholar
Svobodova, Z., Vecerova, V., Redlichova, R., & Somerlikova, K. (2024). Evaluation of the performance of SMEs in the context of regional development. Deleted Journal, 2(1), 47–60.https://doi.org/10.62222/riox8892SvobodovaZ.VecerovaV.RedlichovaR.SomerlikovaK. (2024). Evaluation of the performance of SMEs in the context of regional development. Deleted Journal, 2(1), 47–60. https://doi.org/10.62222/riox8892Search in Google Scholar
Tang, X., Du, S., & Deng, W. (2025). Business innovation in digital startups: A case study of an AI startup. International Review of Economics & Finance, 98, 103898.https://doi.org/10.1016/j.iref.2025.103898TangX.DuS.DengW. (2025). Business innovation in digital startups: A case study of an AI startup. International Review of Economics & Finance, 98, 103898. https://doi.org/10.1016/j.iref.2025.103898Search in Google Scholar
Tani, M., Muto, V., Basile, G., & Nevi, G. (2025). A bibliometric analysis to study the evolution of artificial intelligence in business ethics. Business Ethics the Environment & Responsibility.https://doi.org/10.1111/beer.12797TaniM.MutoV.BasileG.NeviG. (2025). A bibliometric analysis to study the evolution of artificial intelligence in business ethics. Business Ethics the Environment & Responsibility. https://doi.org/10.1111/beer.12797Search in Google Scholar
Ting, D. S., Peng, L., Varadarajan, A. V., Keane, P. A., Burlina, P. M., Chiang, M. F., Schmetterer, L., Pasquale, L. R., Bressler, N. M., Webster, D. R., Abramoff, M., & Wong, T. Y. (2019). Deep learning in ophthalmology: The technical and clinical considerations. Progress in Retinal and Eye Research, 72, 100759.https://doi.org/10.1016/j.preteyeres.2019.04.003TingD. S.PengL.VaradarajanA. V.KeaneP. A.BurlinaP. M.ChiangM. F.SchmettererL.PasqualeL. R.BresslerN. M.WebsterD. R.AbramoffM.WongT. Y. (2019). Deep learning in ophthalmology: The technical and clinical considerations. Progress in Retinal and Eye Research, 72, 100759. https://doi.org/10.1016/j.preteyeres.2019.04.003Search in Google Scholar
Vasenska, I. P. (2024). Economic implications of deep machine learning for tourism time series forecasting. Ekonomicko-manažerske Spektrum, 18(1), 90-101. https://doi.org/10.26552/ems.2024.1.90–101VasenskaI. P. (2024). Economic implications of deep machine learning for tourism time series forecasting. Ekonomicko-manažerske Spektrum, 18(1), 90–101. https://doi.org/10.26552/ems.2024.1.90-101Search in Google Scholar
Wang, Q., Zhang, F., & Li, R. (2024). Artificial intelligence and sustainable development during urbanization: Perspectives on AI R&D innovation, AI infrastructure, and AI market advantage. Sustainable Development, 33(1), 1136–1156.https://doi.org/10.1002/sd.3150WangQ.ZhangF.LiR. (2024). Artificial intelligence and sustainable development during urbanization: Perspectives on AI R&D innovation, AI infrastructure, and AI market advantage. Sustainable Development, 33(1), 1136–1156. https://doi.org/10.1002/sd.3150Search in Google Scholar
Winecoff, A. A., & Watkins, E. A. (2022). Artificial concepts of artificial intelligence: Institutional compliance and resistance in AI startups. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (AIES ‘22) (pp. 788–799). ACM.https://doi.org/10.1145/3514094.3534138WinecoffA. A.WatkinsE. A. (2022). Artificial concepts of artificial intelligence: Institutional compliance and resistance in AI startups. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (AIES ‘22) (pp. 788–799). ACM. https://doi.org/10.1145/3514094.3534138Search in Google Scholar
Wu, W., & Liu, S. (2023). Dilemma of the artificial intelligence regulatory landscape. Communications of the ACM, 66(9), 28–31. https://doi.org/10.1145/3584665WuW.LiuS. (2023). Dilemma of the artificial intelligence regulatory landscape. Communications of the ACM, 66(9), 28–31. https://doi.org/10.1145/3584665Search in Google Scholar
Xie, X., Han, Y., Anderson, A., & Ribeiro-Navarrete, S. (2022). Digital platforms and SMEs’ business model innovation: Exploring the mediating mechanisms of capability reconfiguration. International Journal of Information Management, 65, 102513.https://doi.org/10.1016/j.ijinfomgt.2022.102513XieX.HanY.AndersonA.Ribeiro-NavarreteS. (2022). Digital platforms and SMEs’ business model innovation: Exploring the mediating mechanisms of capability reconfiguration. International Journal of Information Management, 65, 102513. https://doi.org/10.1016/j.ijinfomgt.2022.102513Search in Google Scholar
Zafar, A. (2024). Balancing the scale: Navigating ethical and practical challenges of artificial intelligence (AI) integration in legal practices. Discover Artificial Intelligence, 4 (1), 27.https://doi.org/10.1007/s44163-024-00121-8ZafarA. (2024). Balancing the scale: Navigating ethical and practical challenges of artificial intelligence (AI) integration in legal practices. Discover Artificial Intelligence, 4 (1), 27. https://doi.org/10.1007/s44163-024-00121-8Search in Google Scholar
Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224.https://doi.org/10.1016/j.jii.2021.100224ZhangC.LuY. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224Search in Google Scholar