Enterprise generative artificial intelligence technologies, Internet of Things and blockchain-based fintech management, and digital twin industrial metaverse in the cognitive algorithmic economy
DOI:
https://doi.org/10.24136/oc.3109Keywords:
enterprise generative artificial intelligence, Internet of Things, blockchain, fintech, digital twin industrial metaverse, cognitive algorithmic economyAbstract
Research background: Enterprise generative AI system-based worker behavior tracking and monitoring, socially responsible organizational practices, employee performance management satisfaction, and human resource management procedures, relationships, and outcomes develop on hiring and objective performance assessment algorithms in terms of human resource management activities, functions, processes, practices, policies, and productivity. Deep reinforcement and machine learning techniques, operational and analytical generative AI and cloud capabilities, and real-time anomalous behavior recognition systems further fintech development for credit and lending services, payment analytics processes, and risk assessment, monitoring, and mitigation. Generative AI tools can bolster predictive analytics by collaborative and interconnected sensor and machine data for tailored, seamless, and fine-tuned product, operational process, and organizational workflow development, efficiency, and innovation, driving agile transformative changes in digital twin industrial metaverse.
Purpose of the article: We show that enterprise generative AI-driven schedule prediction tools, job search and algorithmic hiring systems, and synthetic training data can improve team selection, job performance and firing decisions, hiring decision processes, and workforce productivity in terms of prediction and decision-making by use of algorithmic management, system performance, and production process tracking tools. Blockchain-based fintech operations can shape cloud-based financial and digital banking services, quote-to-cash process automation, cash-settled crypto futures, digital loan decisioning, asset tokenization simulated transactions, transaction switching and routing operations, tailored peer-to-peer lending, and proactive credit line management. Collaborative unstructured enterprise data processing, infrastructure, and governance can develop on AI decision and behavior automation technology, retrieval augmented generation and development management systems, and real-time data descriptive and predictive analytics, driving productivity surges and competitive advantage in digital twin industrial metaverse.
Methods: Reference and review management tools, together with evidence synthesis screening software, harnessed were Abstrackr, AMSTAR, ASReview Lab, CASP, Catchii, Citationchaser, DistillerSR, JBI SUMARI, Litstream, PICO Portal, and Rayyan.
Findings & value added: The current state of the art is improved for theory on organizational issues and for policy making as deep learning-based generative AI tools and workplace monitoring systems can augment performance and productivity, gauge employee effectiveness, build resilient, satisfied, and engaged workforce, assess human capital, skill, and career development, drive employee and productivity expectations in relation to flexibility and stability, and shape turnover, retention, and loyalty. Cloud and account servicing technologies can be deployed in generative AI fintechs for embedded cryptocurrency trading, transaction monitoring and processing, digital asset transfers, payment screening, corporate and retail banking operations, and fraud prevention. Generative AI technologies can reshape jobs and reimagine meaningful work, involving creativity and innovation and adaptable and resilient sustained performance, providing valuable constructive feedback, optimizing workplace flexibility and psychological safety, and measuring and supporting autonomy and flexibility-based efficiency, performance, and productivity, while configuring demanding, engaging, and rewarding experiences by cloud and edge computing devices in digital twin industrial metaverse.
Downloads
References
Abakah, E. J. A.; Tiwari, A. K., Ghosh, S., & Doğan, B. (2023). Dynamic effect of Bitcoin, fintech and artificial intelligence stocks on eco-friendly assets, Islamic stocks and conventional financial markets: Another look using quantile-based approaches. Technological Forecasting and Social Change, 192, 122566.
View in Google Scholar
Agarwal, A., & Alathur, S. (2023). Metaverse revolution and the digital transformation: Intersectional analysis of Industry 5.0. Transforming Government: People, Process and Policy, 17, 688‒707.
View in Google Scholar
Agrawal, A., Gans, J. S., & Goldfarb, A. (2023). Do we want less automation? Science, 381, 155–158.
View in Google Scholar
Agrawal, K. P. (2023). Towards adoption of generative AI in organizational settings. Journal of Computer Information Systems, 64(5), 636–651.
View in Google Scholar
Ahelegbey, D., Giudici, P., & Pediroda, V. (2023). A network based fintech inclusion platform. Socio-Economic Planning Sciences, 87(B), 101555.
View in Google Scholar
Akmal, S., Talha, M., Faisal, S. M., Ahmad, M., & Khan, A. K. (2023). Perceptions about FinTech: New evidences from the Middle East. Cogent Economics & Finance, 11(1), 2217583.
View in Google Scholar
Alaassar, A., Mention, A. L., & Aas, T. H. (2023). Facilitating innovation in FinTech: A review and research agenda. Review of Managerial Science, 17, 33–66.
View in Google Scholar
Ali, O., Krsteska, K., Said, D., & Momin, M. (2023). Advanced technologies enabled human resources functions: Benefits, challenges, and functionalities: A systematic review. Cogent Business & Management, 10(2), 2216430.
View in Google Scholar
Almansour, M. (2023). Artificial intelligence and resource optimization: A study of Fintech start-ups. Resources Policy, 80, 103250.
View in Google Scholar
Altrock, S., Mention, A.-L., & Aas, T. H. (2023). Being human in the digitally enabled workplace: Insights from the robo-advice literature. IEEE Transactions on Engineering Management, 71, 7876–7891.
View in Google Scholar
Andronie, M., Lăzăroiu, G., Iatagan, M., Hurloiu, I, Ștefănescu, R., Dijmărescu, A., & Dijmărescu, I. (2023b). Big data management algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the Internet of Robotic Things. ISPRS International Journal of Geo-Information, 12(2), 35.
View in Google Scholar
Andronie, M., Lăzăroiu, G., Iatagan, M., Hurloiu, I., & Dijmărescu, I. (2021a). Sustainable cyber-physical production systems in big data-driven smart urban economy: A systematic literature review. Sustainability, 13(2), 751.
View in Google Scholar
Andronie, M., Lăzăroiu, G., Iatagan, M., Uță, C., Ștefănescu, R., & Cocoșatu, M. (2021b). Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and deep learning-assisted smart process management in cyber-physical production systems. Electronics, 10(20), 2497.
View in Google Scholar
Andronie, M., Lăzăroiu, G., Karabolevski, O. L., Ștefănescu, R., Hurloiu, I., Dijmărescu, A., & Dijmărescu, I. (2023a). Remote big data management tools, sensing and computing technologies, and visual perception and environment mapping algorithms in the Internet of Robotic Things. Electronics, 12(1), 22.
View in Google Scholar
Arora, A., Gupta, S., Devi, C., & Walia, N. (2023). Customer experiences in the era of artificial intelligence (AI) in context to FinTech: A fuzzy AHP approach. Benchmarking: An International Journal, 30(10), 4342–4369.
View in Google Scholar
Awais, M., Afzal, A., Firdousi, S., & Hasnaoui, A. (2023). Is fintech the new path to sustainable resource utilisation and economic development? Resources Policy, 81, 103309.
View in Google Scholar
Ayhan, F., & Elal, O. (2023). The impacts of technological change on employment: Evidence from OECD countries with panel data analysis. Technological Forecasting and Social Change, 190, 122439.
View in Google Scholar
Babaei, G., Giudici, P., & Raffinetti, E. (2023). Explainable FinTech lending. Journal of Economics and Business, 125‒126, 106126.
View in Google Scholar
Bankins, S., Ocampo, A. C., Marrone, M., Restubog, S. L. D., & Woo, S. E. (2023). A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior, 45(2), 159–182.
View in Google Scholar
Barbu, C. M., Florea, D. L., Dabija, D. C., & Barbu, M. C. R. (2021). Customer experience in fintech. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1415‒1433.
View in Google Scholar
Bartelheimer, C., Wolf, V., & Beverungen, D. (2023). Workarounds as generative mechanisms for bottom-up process innovation – Insights from a multiple case study. Information Systems Journal, 33(5), 1085–1150.
View in Google Scholar
Bellalouna, F., & Puljiz, D. (2023). Use case for the application of the industrial metaverse approach for engineering design review. Procedia CIRP, 119, 638‒643.
View in Google Scholar
Ben Romdhane, Y., Kammoun, S., & Loukil, S. (2023). The impact of Fintech on inflation and unemployment: The case of Asia. Arab Gulf Journal of Scientific Research, 42(1), 161–181.
View in Google Scholar
Bhattacharya, P., Saraswat, D., Savaliya, D., Sanghavi, S., Verma, A., Sakariya, V., Tanwar, S., Sharma, R., Raboaca, M. S., & Manea, D. L. (2023). Towards future Internet: The metaverse perspective for diverse industrial applications. Mathematics, 11(4), 941.
View in Google Scholar
Bhutto, S. A., Jamal, Y., & Ullah, S. (2023). FinTech adoption, HR competency potential, service innovation and firm growth in banking sector. Heliyon, 9, e13967.
View in Google Scholar
Bilgram, V., & Laarmann, F. (2023). Accelerating innovation with generative AI: AI-augmented digital prototyping and innovation methods. IEEE Engineering Management Review, 51(2), 18–25.
View in Google Scholar
Birkbeck, A., & Rowe, L. (2023). Navigating towards hyperautomation and the empowerment of human capital in family businesses: A perspective article. Journal of Family Business Management, 14(4), 727–734.
View in Google Scholar
Böhmer, N., & Schinnenburg, H. (2023). Critical exploration of AI-driven HRM to build up organizational capabilities. Employee Relations, 45(5), 1057–1082.
View in Google Scholar
Booyse, D., & Scheepers, C. B. (2023). Barriers to adopting automated organisational decision-making through the use of artificial intelligence. Management Research Review, 47(1), 64–85.
View in Google Scholar
Bouschery, S. G., Blazevic, V., & Piller, F. T. (2023). Augmenting human innovation teams with artificial intelligence: Exploring transformer-based language models. Journal of Product Innovation Management, 40(2), 139–153.
View in Google Scholar
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Cooke, F. L., Decker, S., DeNisi, A., Dey, P. K., Guest, D., Knoblich, A. J., Malik, A., Paauwe, J., Papagiannidis, S., Patel, C., Pereira, V., Ren, & Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(4), 1097–1097.
View in Google Scholar
Campanella, F., Serino, L., Battisti, E., Giakoumelou, A., & Karasamani, I. (2023). FinTech in the financial system: Towards a capital-intensive and high competence human capital reality? Journal of Business Research, 155(A), 113376.
View in Google Scholar
Cao, J., Zhu, X., Sun, S., Wei, Z., Jiang, Y., Wang, J., & Lau, V. K. N. (2023). Toward industrial metaverse: Age of information, latency and reliability of short-packet transmission in 6G. IEEE Wireless Communications, 30(2), 40‒47.
View in Google Scholar
Caragea, D., Cojoianu, T., Dobri, M., Hoepner, A., Peia, O., & Romelli, D. (2023). Competition and innovation in the financial sector: Evidence from the rise of FinTech start-ups. Journal of Financial Services Research, 65(1), 103–140.
View in Google Scholar
Carmel, E., & Sawyer, S. (2023). The multi-dimensional space of the futures of work. Information Technology & People, 36(1), 1–20.
View in Google Scholar
Castañé, G., Dolgui, A., Kousi, N., Meyers, B., Thevenin, S., Vyhmeister, E., & Östberg, P-O. (2023). The ASSISTANT project: AI for high level decisions in manufacturing. International Journal of Production Research, 61(7), 2288–2306.
View in Google Scholar
Cebulla, A., Szpak, Z., & Knight, G. (2023). Preparing to work with artificial intelligence: Assessing WHS when using AI in the workplace. International Journal of Workplace Health Management, 16(4), 294–312.
View in Google Scholar
Chaklader, B., Gupta, B. B., & Panigrahi, P. K. (2023). Analyzing the progress of FINTECH-companies and their integration with new technologies for innovation and entrepreneurship. Journal of Business Research, 161, 113847.
View in Google Scholar
Chang, Y.-L., & Ke, J. (2023). Socially responsible artificial intelligence empowered people analytics: A novel framework towards sustainability. Human Resource Development Review, 23(1), 88–120.
View in Google Scholar
Chen, S., & Guo, Q. (2023). Fintech, strategic incentives and investment to human capital, and MSEs innovation. North American Journal of Economics and Finance, 68, 101963.
View in Google Scholar
Chen, T., Gascó-Hernandez, M., & Esteve, M. (2023a). The adoption and implementation of artificial intelligence chatbots in public organizations: Evidence from U.S. state governments. American Review of Public Administration, 54(3), 255–270.
View in Google Scholar
Chen, W., He, W., Shen, J., Tian, X., & Wang, X. (2023b). Systematic analysis of artificial intelligence in the era of Industry 4.0. Journal of Management Analytics, 10(1), 89–108.
View in Google Scholar
Chen, W., Wu, W., & Zhang, T. (2023c). Fintech development, firm digitalization, and bank loan pricing. Journal of Behavioral and Experimental Finance, 39, 100838.
View in Google Scholar
Cheng, A. (2023). Evaluating Fintech industry’s risks: A preliminary analysis based on CRISP-DM framework. Finance Research Letters, 55(B), 103966.
View in Google Scholar
Cheng, M., & Qu, Y. (2023). Does operational risk management benefit from FinTech? Emerging Markets Finance and Trade, 59(14), 4012–4027.
View in Google Scholar
Choudhary, V., Marchetti, A., Shrestha, Y. R., & Puranam, P. (2023). Human-AI ensembles: When can they work? Journal of Management.
View in Google Scholar
Cortez, E. K., & Maslej, N. (2023). Adjudication of artificial intelligence and automated decision-making cases in Europe and the USA. European Journal of Risk Regulation, 14(3), 457–475.
View in Google Scholar
Dong, X., & Yu, M. (2023). Does FinTech development facilitate firms’ innovation? Evidence from China. International Review of Financial Analysis, 89, 102805.
View in Google Scholar
Doumpos, M., Zopounidis, C., Gounopoulos, D., Platanakis, E., & Zhang, W. (2023). Operational research and artificial intelligence methods in banking. European Journal of Operational Research, 306(1), 1–16.
View in Google Scholar
Edo, O. C., Etu, E.-E., Tenebe, I., Oladele, O. S., Edo, S., Diekola, O. A., & Emakhu, J. (2023). Fintech adoption dynamics in a pandemic: An experience from some financial institutions in Nigeria during COVID-19 using machine learning approach. Cogent Business & Management, 10(2), 2242985.
View in Google Scholar
Einola, K., & Khoreva, V. (2023). Best friend or broken tool? Exploring the co-existence of humans and artificial intelligence in the workplace ecosystem. Human Resource Management, 62(1), 117–135.
View in Google Scholar
Ferrari, F., & McKelvey, F. (2023). Hyperproduction: A social theory of deep generative models. Distinktion: Journal of Social Theory, 24(2), 338–360.
View in Google Scholar
Fosso Wamba, S., Queiroz, M. M., Chiappetta Jabbour, C. S., & Shi, C. (V.) (2023). Are both generative AI and ChatGPT game changers for 21st-century operations and supply chain excellence? International Journal of Production Economics, 265, 109015.
View in Google Scholar
França, T. J. F., Mamede, H. S., Barroso, J. M. P., & dos Santos, V. M. P. D. (2023). Artificial intelligence applied to potential assessment and talent identification in an organisational context. Heliyon, 9(4), e14694.
View in Google Scholar
Furendal, M., & Jebari, K. (2023). The future of work: Augmentation or stunting? Philosophy & Technology, 36, 36.
View in Google Scholar
Gama, F., & Magistretti, S. (2023). Artificial intelligence in innovation management: A review of innovation capabilities and a taxonomy of AI applications. Journal of Product Innovation Management.
View in Google Scholar
Gandhi, T. K., Classen, D., Sinsky, C. A., Rhew, D. C., Garde, N. V., Roberts, A., & Federico, F. (2023). How can artificial intelligence decrease cognitive and work burden for front line practitioners? JAMIA Open, 6(3), ooad079.
View in Google Scholar
Garibay, O. O., Winslow, B., Andolina, S., Antona, M., Bodenschatz, A., Coursaris, C., Falco, G., Fiore, S. M., Garibay, I., Grieman, K., Havens, J. C., Jirotka, M., Kacorri, H., Karwowski, W., Kider, J., Konstan, J., Koon, S., Lopez-Gonzalez, M., Maifeld-Carucci, I., McGregor, S., Salvendy, G., Shneiderman, B., Stephanidis, C., Strobel, C., Ten Holter, C., & Xu, W. (2023). Six human-centered artificial intelligence grand challenges. International Journal of Human–Computer Interaction, 39(3), 391–437.
View in Google Scholar
Gonçalves, A. R., Breda Meira, A., Shuqair, S., & Costa Pinto, D. (2023). Artificial intelligence (AI) in FinTech decisions: The role of congruity and rejection sensitivity. International Journal of Bank Marketing, 41(6), 1282‒1307.
View in Google Scholar
Guang-Wen, Z., & Siddik, A. B. (2023). The effect of Fintech adoption on green finance and environmental performance of banking institutions during the COVID-19 pandemic: The role of green innovation. Environmental Science and Pollution Research, 30, 25959–25971.
View in Google Scholar
Guliyev, H. (2023). Artificial intelligence and unemployment in high-tech developed countries: New insights from dynamic panel data model. Research in Globalization, 7, 100140.
View in Google Scholar
Guo, J., Fang, H., Liu, X., Wang, C., & Wang, Y. (2023). FinTech and financing constraints of enterprises: Evidence from China. Journal of International Financial Markets, Institutions and Money, 82, 101713.
View in Google Scholar
Guo, P., & Zhang, C. (2023). The impact of bank FinTech on liquidity creation: Evidence from China. Research in International Business and Finance, 64, 101858.
View in Google Scholar
Ha, L. T. (2023). Dynamic connectedness between FinTech innovation and energy volatility during the war in time of pandemic. Environmental Science and Pollution Research, 30, 83530–83544.
View in Google Scholar
He, C., Geng, X., Tan, C., & Guo, R. (2023a). Fintech and corporate debt default risk: Influencing mechanisms and heterogeneity. Journal of Business Research, 164, 113923.
View in Google Scholar
He, M., Song, G., & Chen, Q. (2023b). Fintech adoption, internal control quality and bank risk taking: Evidence from Chinese listed banks. Finance Research Letters, 57, 104235.
View in Google Scholar
Jagatheesaperumal, S. K., & Rahouti, M. (2022). Building digital twins of cyber physical systems with metaverse for Industry 5.0 and beyond. IT Professional, 24(6), 34‒40.
View in Google Scholar
Jagatheesaperumal, S. K., Yang, Z., Yang, Q., Huang, C., Xu, W., Shikh-Bahaei, M., & Zhang, Z. (2023). Semantic-aware digital twin for metaverse: A comprehensive review. IEEE Wireless Communications, 30(4), 38‒46.
View in Google Scholar
Jaimini, U., Zhang, T., Brikis, G. O., & Sheth, A. (2022). iMetaverseKG: Industrial metaverse knowledge graph to promote interoperability in design and engineering applications. IEEE Internet Computing, 26(6), 59‒67.
View in Google Scholar
Jarrahi, M. H., Lutz, C., Boyd, K., Oesterlund, C., & Willis, M. (2023). Artificial intelligence in the work context. Journal of the Association for Information Science and Technology, 74(3), 303–310.
View in Google Scholar
Jiang, B. (2023). Does fintech promote the sustainable development of renewable energy enterprises? Environmental Science and Pollution Research, 30, 65141–65148.
View in Google Scholar
Kaarlela, T., Pitkäaho, T., Pieskä, S., Padrão, P., Bobadilla, L., Tikanmäki, M., Haavisto, T., Bataller, V. B., Laivuori, N., & Luimula, M. (2023). Towards metaverse: Utilizing extended reality and digital twins to control robotic systems. Actuators, 12(6), 219.
View in Google Scholar
Kambur, E., & Yildirim, T. (2023). From traditional to smart human resources management. International Journal of Manpower, 44(3), 422–452.
View in Google Scholar
Kanbach, D. K., Heiduk, L., Blueher, G., Schreiter, M., & Lahmann, A. (2023). The GenAI is out of the bottle: Generative artificial intelligence from a business model innovation perspective. Review of Managerial Science, 18, 1189–1220.
View in Google Scholar
Kanitz, R., Gonzalez, K., Briker, R., & Straatmann, T. (2023). Augmenting organizational change and strategy activities: Leveraging generative artificial intelligence. Journal of Applied Behavioral Science, 59(3), 345–363.
View in Google Scholar
Kar, A. K., Varsha, P. S., & Rajan, S. (2023). Unravelling the impact of generative artificial intelligence (GAI) in industrial applications: A review of scientific and grey literature. Global Journal of Flexible Systems Management, 24, 659–689.
View in Google Scholar
Kazachenok, O. P., Stankevich, G. V., Chubaeva, N. N., & Tyurina, Y. G. (2023). Economic and legal approaches to the humanization of FinTech in the economy of artificial intelligence through the integration of blockchain into ESG Finance. Humanities and Social Sciences Communications, 10, 167.
View in Google Scholar
Kemp, A. (2023). Competitive advantage through artificial intelligence: Toward a theory of situated AI. Academy of Management Review, 49(3), 618–635.
View in Google Scholar
Khan, S., Khan, H. U., & Nazir, S. (2023). Utilizing the collective wisdom of fintech in the gcc region: A systematic mapping approach. Measurement and Control, 56(3/4), 713–732.
View in Google Scholar
Kliestik, T., Nagy, M., & Valaskova, K. (2023). Global value chains and Industry 4.0 in the context of lean workplaces for enhancing company performance and its comprehension via the digital readiness and expertise of workforce in the V4 nations. Mathematics, 11(3), 601.
View in Google Scholar
Koivisto, M., & Grassini, S. (2023). Best humans still outperform artificial intelligence in a creative divergent thinking task. Scientific Reports, 13, 13601.
View in Google Scholar
Kolbjørnsrud, V. (2023). Designing the intelligent organization: Six principles for human-AI collaboration. California Management Review, 66(2), 44‒64.
View in Google Scholar
Kraus, S., Ferraris, A., & Bertello, A. (2023). The future of work: How innovation and digitalization re-shape the workplace. Journal of Innovation & Knowledge, 8(4), 100438.
View in Google Scholar
Kshetri, N. (2023). The economics of the industrial metaverse. IT Professional, 25(1), 84‒88.
View in Google Scholar
Lai, X., Yue, S., Guo, C., & Zhang, X. (2023). Does FinTech reduce corporate excess leverage? Evidence from China. Economic Analysis and Policy, 77, 281–299.
View in Google Scholar
Lăzăroiu, G., Andronie, M., Iatagan, M., Geamănu, M., Ștefănescu, R., & Dijmărescu, I. (2022). Deep learning-assisted smart process planning, robotic wireless sensor networks, and geospatial big data management algorithms in the Internet of Manufacturing Things. ISPRS International Journal of GeoInformation, 11(5), 277.
View in Google Scholar
Lee, J., & Kundu, P. (2022). Integrated cyber-physical systems and industrial metaverse for remote manufacturing. Manufacturing Letters, 34, 12‒15.
View in Google Scholar
Lisha, L., Mousa, S., Arnone, G., Muda, I., Huerta-Soto, R., & Shiming, Z. (2023). Natural resources, green innovation, fintech, and sustainability: A fresh insight from BRICS. Resources Policy, 80, 103119.
View in Google Scholar
Liu, S., Xie, J., & Wang, X. (2023). QoE enhancement of the industrial metaverse based on mixed reality application optimization. Displays, 79, 102463.
View in Google Scholar
Lyu, Z., & Fridenfalk, M. (2024). Digital twins for building industrial metaverse. Journal of Advanced Research, 66, 31‒38.
View in Google Scholar
Magalhães, L. C., Magalhães, L. C., Ramos, J. B., Moura, L. R., de Moraes, R. E. N., Gonçalves, J. B., Hisatugu, W. H., Souza, M. T., de Lacalle, L. N. L., & Ferreira, J. C. E. (2022). Conceiving a digital twin for a flexible manufacturing system. Applied Sciences, 12(19), 9864.
View in Google Scholar
Mahmud, K., Joarder, M. M. A., & Sakib, K. (2023). Customer Fintech readiness (CFR): Assessing customer readiness for fintech in Bangladesh. Journal of Open Innovation: Technology, Market, and Complexity, 9(2), 100032.
View in Google Scholar
Malhan, R., & Gupta, S. K. (2023). The role of deep learning in manufacturing applications: Challenges and opportunities. Journal of Computing and Information Science in Engineering, 23(6), 060816.
View in Google Scholar
Mazarakis, A., Bernhard-Skala, C., Braun, M., & Peters, I. (2023). What is critical for human-centered AI at work? – Toward an interdisciplinary theory. Frontiers in Artificial Intelligence, 6, 1257057.
View in Google Scholar
Mikhaylov, A., Dinçer, H., & Yüksel, S. (2023). Analysis of financial development and open innovation oriented fintech potential for emerging economies using an integrated decision-making approach of MF-X-DMA and golden cut bipolar q-ROFSs. Financial Innovation, 9(1), 4.
View in Google Scholar
Mirza, N., Elhoseny, M., Umar, M., & Metawa, N. (2023a). Safeguarding FinTech innovations with machine learning: Comparative assessment of various approaches. Research in International Business and Finance, 66, 102009.
View in Google Scholar
Mirza, N., Umar, M., Afzal, A., & Firdousi, S. F. (2023b). The role of fintech in promoting green finance, and profitability: Evidence from the banking sector in the euro zone. Economic Analysis and Policy, 78, 33–40.
View in Google Scholar
Mourad, N., Alsattar, H. A., Qahtan, S., Zaidan, A. A., Deveci, M., Sangaiah, A. K., & Pedrycz, W. (2023). Optimising control engineering tools using digital twin capabilities and other cyber-physical metaverse manufacturing system components. IEEE Transactions on Consumer Electronics, 70(1), 3212–3221.
View in Google Scholar
Nagy, M., & Lăzăroiu, G. (2022). Computer vision algorithms, remote sensing data fusion techniques, and mapping and navigation tools in the Industry 4.0-based Slovak automotive sector. Mathematics, 10, 3543.
View 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.
View in Google Scholar
Naz, F., Kumar, A., Agrawal, R., Garza-Reyes, J. A., Majumdar, A., & Chokshi, H. (2024). Artificial intelligence as an enabler of quick and effective production repurposing: An exploratory review and future research propositions. Production Planning & Control, 35(6), 2154–2177.
View in Google Scholar
Negri, E., & Abdel-Aty, T. A. (2023). Clarifying concepts of metaverse, digital twin, digital thread and AAS for CPS-based production systems. IFAC-PapersOnLine, 56(2), 6351‒6357.
View in Google Scholar
Osei-Assibey Bonsu, M., Wang, Y., & Guo, Y. (2023). Does fintech lead to better accounting practices? Empirical evidence. Accounting Research Journal, 36(2/3), 129–147.
View in Google Scholar
Pan, Y., & Froese, F. J. (2023). An interdisciplinary review of AI and HRM: Challenges and future directions. Human Resource Management Review, 33(1), 100924.
View in Google Scholar
Pelau, C., Dabija, D.-C., & Ene, I. (2021). What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry. Computers in Human Behavior, 122, 106855.
View in Google Scholar
Peters, M. A., Jackson, L., Papastephanou, M., Jandrić, P., Lăzăroiu, G., Evers, C. W., Cope, B., Kalantzis, M., Araya, D., Tesar, M., Mika, C., Chen, L., Wang, C. B., Sturm, S., Rider, S., & Fuller, S. (2024). AI and the future of humanity: ChatGPT-4, philosophy and education – Critical responses. Educational Philosophy and Theory, 56(9), 828‒862.
View in Google Scholar
Qiu, Z., Wang, J., Wu, K., & Yang, S. (2023). The value of FinTech innovations for the finance industry: Evidence from China. Economic and Political Studies, 12(1), 1–19.
View in Google Scholar
Rafiuddin, A., Gaytan, J. C. T., Mohnot, R., Sisodia, G. S., & Ahmed, G. (2023). Growth evaluation of fintech connectedness with innovative thematic indices – An evidence through wavelet analysis. Journal of Open Innovation: Technology, Market, and Complexity, 9(2), 100023.
View in Google Scholar
Rjoub, H., Adebayo, T. S., & Kirikkaleli, D. (2023). Blockchain technology-based FinTech banking sector involvement using adaptive neuro-fuzzy-based K-nearest neighbors algorithm. Financial Innovation, 9, 65.
View in Google Scholar
Sampat, B., Mogaji, E., & Nguyen, N. P. (2024). The dark side of FinTech in financial services: A qualitative enquiry into FinTech developers’ perspective. International Journal of Bank Marketing, 42(1), 38‒65.
View in Google Scholar
Sharma, S. K., Ilavarasan, P. V., & Karanasios, S. (2023b). Small businesses and FinTech: A systematic review and future directions. Electronic Commerce Research, 24(1), 535–575.
View in Google Scholar
Sharma, S., Aggarwal, V., Dixit, N., & Yadav, M. P. (2023a). Time and frequency connectedness among emerging markets and QGREEN, FinTech and artificial intelligence-based index: Lessons from the outbreak of COVID-19. Vision.
View in Google Scholar
Starly, B., Koprov, P., Bharadwaj, A., Batchelder, T., & Breitenbach, B. (2023). Unreal’ factories: Next generation of digital twins of machines and factories in the industrial metaverse. Manufacturing Letters, 37, 50‒52.
View in Google Scholar
Stary, C. (2023). Digital process twins as intelligent design technology for engineering metaverse/XR applications. Sustainability, 15(22), 16062.
View in Google Scholar
Su, F., & Xu, C. (2023). Curbing credit corruption in China: The role of FinTech. Journal of Innovation & Knowledge, 8(1), 100292.
View in Google Scholar
Sun, R., & Zhang, B. (2023). Can fintech make corporate investments more efficient? A study on financing constraints and agency conflicts. Economic Research-Ekonomska Istraživanja, 36(3), 2185795.
View in Google Scholar
Sun, Y., Li, S., & Wang, R. (2023). Fintech: from budding to explosion – An overview of the current state of research. Review of Managerial Science, 17, 715–755.
View in Google Scholar
Tan, Z., Wang, H., & Hong, Y. (2023). Does bank FinTech improve corporate innovation? Finance Research Letters, 55(A), 103830.
View in Google Scholar
Thomas, N. M., Mendiratta, P., & Kashiramka, S. (2023). FinTech credit: uncovering knowledge base, intellectual structure and research front. International Journal of Bank Marketing, 41(7), 1769–1802.
View in Google Scholar
Upreti, K., Syed, M. H., Khan, M. A., Fatima, H., Alam, M. S., & Sharma, A. K. (2023). Enhanced algorithmic modelling and architecture in deep reinforcement learning based on wireless communication Fintech technology. Optik, 272, 170309.
View in Google Scholar
Wu, D., Yang, Z., Zhang, P., Wang, R., Yang, B., & Ma, X. (2023a). Virtual-reality interpromotion technology for metaverse: A survey. IEEE Internet of Things Journal, 10(18), 15788‒15809.
View in Google Scholar
Wu, G., Luo, J., & Tao, K. (2023b). Research on the influence of FinTech development on credit supply of commercial banks: The case of China. Applied Economics, 56(6), 639–65.
View in Google Scholar
Xinyi, T., Juuso, A., Riku, A.-L., Chao, Y., Pauli, S., & Kari, T. (2023). TwinXR: method for using digital twin descriptions in industrial eXtended reality applications. Frontiers in Virtual Reality, 4, frvir.2023.1019080.
View in Google Scholar
Yan, X. (2023). Research on financial field integrating artificial intelligence: Application basis, case analysis, and SVR model-based overnight. Applied Artificial Intelligence, 37(1), 2222258.
View in Google Scholar
Yang, J., Wang, X., & Zhao, Y. (2022). Parallel manufacturing for industrial metaverses: A new paradigm in smart manufacturing. IEEE/CAA Journal of Automatica Sinica, 9(12), 2063‒2070.
View in Google Scholar
Yang, X., Yang, J., Hou, Y., Li, S., & Sun, S. (2023). Gamification of mobile wallet as an unconventional innovation for promoting Fintech: An fsQCA approach. Journal of Business Research, 155(A), 113406.
View in Google Scholar
Zaidan, A. A., Alsattar, H. A., Qahtan, S., Deveci, M., Pamucar, D., & Hajiaghaei-Keshteli, M. (2023). Uncertainty decision modeling approach for control engineering tools to support industrial cyber-physical metaverse smart manufacturing systems. IEEE Systems Journal, 17(4), 5303‒5314.
View in Google Scholar
Zhao, Y., Goodell, J. W., Wang, Y., & Abedin, M. Z. (2023). Fintech, macroprudential policies and bank risk: Evidence from China. International Review of Financial Analysis, 87, 102648.
View in Google Scholar
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Oeconomia Copernicana

This work is licensed under a Creative Commons Attribution 4.0 International License.