Analyzing Financial Performances of the Artificial Intelligence Firms by Using the AHP-TOPSIS Method
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https://doi.org/10.5281/zenodo.8362319Keywords:
Artificial intelligence, Financial Performance , AHP, TOPSISAbstract
This study was carried out to evaluate the financial performance of artificial intelligence companies, which could not be found to be examined in the literature, by using the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). For this purpose, the weights of the liquidity, financial structure, profitability and operating ratios criteria and the weights of the sub-criteria (current ratio, cash ratio, acid test ratio, long-term debt to capital ratio, debt to assets ratio, debt to equity ratio, net profit margin, return on equity (ROE), return on assets (ROA), return on investment (ROI), inventory turnover, asset turnover, receivable turnover) were determined by using the AHP method. As a result of the AHP analysis performed for the criteria, it was concluded that the criterion with the highest weight (n=0.533) was the profitability ratio (C3). In the analysis of all sub-criteria, it was understood that the sub-criterion with the highest global weight (n=0,186) was ROE (C3c). As a result of the TOPSIS analysis of the financial performance of the artificial intelligence companies selected between 2022-2019, it was understood that the artificial intelligence company that achieved the highest score in 2022, 2020 and 2019 was Firm 3. In 2021, it was concluded that Firm 2 achieved the highest score. This study is thought to provide helpful information to researchers and practitioners.
References
Ahmad, N., Shah, F. N., Ijaz, F., & Ghouri, M. N. (2023). Corporate income tax, asset turnover and Tobin’s Q as firm performance in Pakistan: Moderating role of liquidity ratio. Cogent Business & Management, 10(1), 2167287. https://doi.org/10.1080/23311975.2023.2167287
Ahmad, S., Ouenniche, J., Kolosz, B. W., Greening, P., Andresen, J. M., Maroto-Valer, M. M., & Xu, B. (2021). A stakeholders’ participatory approach to multi-criteria assessment of sustainable aviation fuels production pathways. International Journal of Production Economics, 238, 108156. https://doi.org/10.1016/j.ijpe.2021.108156
Al Badi, F. K., Alhosani, K. A., Jabeen, F., Stachowicz-Stanusch, A., Shehzad, N., & Amann, W. (2021). Challenges of AI Adoption in the UAE Healthcare. Vision, 26(2), 193-207. https://doi.org/10.1177/0972262920988398
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, ahead-of-print(ahead-of-print). https://doi.org/10.1108/BIJ-10-2021-0621
Biswas, A., & Wang, H.-C. (2023). Autonomous Vehicles Enabled by the Integration of IoT, Edge Intelligence, 5G, and Blockchain. Sensors, 23(4).
Bloomenthal, A. (2023). Financial Ratio Analysis: Definition, Types, Examples, and How to Use. Retrieved 16.07.2023 from https://www.investopedia.com/terms/r/ratioanalysis.asp
Brian, W., Aline, C.-G., Stefan, G., & Nina, R. S. (2018). Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings? BMJ Global Health, 3(4), e000798. https://doi.org/10.1136/bmjgh-2018-000798
Cahigas, M. M. L., Robielos, R. A. C., & Gumasing, M. J. J. (2021). Application of multiple criteria decision-making methods in the human resource recruitment process, Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management, IEOM Society International, Singapore, March 7-11, 2021.
Cao, G., Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2021). Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation, 106, 102312. https://doi.org/10.1016/j.technovation.2021.102312
Cayamcela, M. E. M., & Lim, W. (2018, 17-19 Oct. 2018). Artificial Intelligence in 5G Technology: A Survey. 2018 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea (South), 2018, 860-865. https://doi.org/10.1109/ICTC.2018.8539642
Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16-24. https://doi.org/10.1016/j.procs.2018.08.233
Chowdhury, T., Hasan, S., Chowdhury, H., Hasnat, A., Rashedi, A., Asyraf, M. R. M., Hassan, M. Z., & Sait, S. M. (2022). Sizing of an Island Standalone Hybrid System Considering Economic and Environmental Parameters: A Case Study. Energies, 15(16), 5940. https://doi.org/10.3390/en15165940
Companies Market Cap. (2023). Largest airlines by market cap. Retrieved 10.07.2023 from https://companiesmarketcap.com/artificial-intelligence/largest-ai-companies-by-marketcap/
de Oliveira, A. C. L., dos Santos Renato, N., Martins, M. A., de Mendonça, I. M., Moraes, C. A., & Lago, L. F. R. (2023). Renewable energy solutions based on artificial intelligence for farms in the state of Minas Gerais, Brazil: Analysis and proposition. Renewable Energy, 204, 24-38. https://doi.org/10.1016/j.renene.2022.12.101
Dirican, C. (2015). The Impacts of Robotics, Artificial Intelligence On Business and Economics. Procedia - Social and Behavioral Sciences, 195, 564-573. https://doi.org/10.1016/j.sbspro.2015.06.134
Dohale, V., Akarte, M., Gunasekaran, A., & Verma, P. (2022). Exploring the role of artificial intelligence in building production resilience: learnings from the COVID-19 pandemic. International Journal of Production Research, 1-17. https://doi.org/10.1080/00207543.2022.2127961
Du, Y., & Gao, H. (2022). Determinants affecting teachers’ adoption of AI-based applications in EFL context: An analysis of analytic hierarchy process. Education and Information Technologies, 27(7), 9357-9384. https://doi.org/10.1007/s10639-022-11001-y
Durkadevi, K., Revathi, T., & Shenbagalakshmi, G. (2022). Generic Method for SDN Controller Selection Using AHP and TOPSIS Methods. International Journal of Information Technology & Decision Making, 21(03), 1031-1059. https://doi.org/10.1142/s0219622022500067
Flores-Vivar, J. M. (2019). Inteligencia artificial y periodismo: diluyendo el impacto de la desinformación y las noticias falsas a través de los bots. Doxa Comunicación. Revista Interdisciplinar de Estudios de Comunicación y Ciencias Sociales(29), 197-212. https://doi.org/10.31921/doxacom.n29a10
Galloway, C., & Swiatek, L. (2018). Public relations and artificial intelligence: It’s not (just) about robots. Public Relations Review, 44(5), 734-740. https://doi.org/10.1016/j.pubrev.2018.10.008
Göçmen, E. (2021). Smart Airport: Evaluation of Performance Standards and Technologies for a Smart Logistics Zone. Transportation Research Record, 2675(7), 480-490. https://doi.org/10.1177/03611981211019740
Guan, X., & Zhao, J. (2022). A Two-Step Fuzzy MCDM Method for Implementation of Sustainable Precision Manufacturing: Evidence from China. Sustainability, 14(13), 8085.
Guo, C., Sun, Y., Su, S., & Peng, C. (2023). Risk assessment method for controlled flight into terrain of airlines based on QAR data. Aircraft Engineering and Aerospace Technology, ahead-of-print(ahead-of-print). https://doi.org/10.1108/AEAT-10-2022-0269
Guo, L., Yao, Z., Lin, M., & Xu, Z. (2023). Fuzzy TOPSIS-based privacy measurement in multiple online social networks. Complex & Intelligent Systems. https://doi.org/10.1007/s40747-023-00991-y
Gupta, K. P., & Bhaskar, P. (2020). Inhibiting and motivating factors influencing teachers’ adoption of AI-based teaching and learning solutions: Prioritization using analytic hierarchy process. Journal of Information Technology Education: Research, 19, 693-723. https://doi.org/10.28945/4640
Guzman, A. L., & Lewis, S. C. (2019). Artificial intelligence and communication: A Human–Machine Communication research agenda. New Media & Society, 22(1), 70-86. https://doi.org/10.1177/1461444819858691
Hammond, P., Opoku, M. O., & Kwakwa, P. A. (2022). Identification of factors for developing going concern prediction models. Cogent Business & Management, 9(1), 2152160. https://doi.org/10.1080/23311975.2022.2152160
Hong Yun, Z., Alshehri, Y., Alnazzawi, N., Ullah, I., Noor, S., & Gohar, N. (2022). A decision-support system for assessing the function of machine learning and artificial intelligence in music education for network games. Soft Computing, 26(20), 11063-11075. https://doi.org/10.1007/s00500-022-07401-4
Huang, X. (2021). Aims for cultivating students’ key competencies based on artificial intelligence education in China. Education and Information Technologies, 26(5), 5127-5147. https://doi.org/10.1007/s10639-021-10530-2
Huang, X., Liu, X., Chen, L., Lei, Z., Shi, G., Luo, M., & Wang, Y. (2023). Research on supplier selection based on AHP-TOPICS model. In W. Dai & S. Jin (Eds.), Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 125972J, Nanjing, China. https://doi.org/10.1117/12.2672578
Huang, Z., He, J., & Ren, X. (2021). Application of artificial intelligence in enterprise knowledge management performance evaluation. Knowledge Management Research & Practice, 1-9. https://doi.org/10.1080/14778238.2020.1850187
Hussain, S. A. I., Chandra, H., & Mandal, U. K. (2022). Comparison of Cross-Entropy Based MCDM Approach for Selection of Material in Sugar Industry. In M. Fausto Pedro García (Ed.), Advances in Decision Making (pp. Ch. 5). IntechOpen. https://doi.org/10.5772/intechopen.98242
Ishiaku, O. K., Haruna, U., Danwanka, H. A., & Suleiman, H. R. (2017). Resource use efficiency of fadama III small-scale rice farmers in Nasarawa State, Nigeria. International Journal of Agricultural Economics and Extension, 5(4), 284-294.
Jenis, J., Ondriga, J., Hrcek, S., Brumercik, F., Cuchor, M., & Sadovsky, E. (2023). Engineering Applications of Artificial Intelligence in Mechanical Design and Optimization. Machines, 11(6), 577.
Kalvakolanu, S., Sama, H. R., Mathew, M., & Somasekhar, D. (2022). Measuring job satisfaction levels of airport employees using entropy, critic and TOPSIS methods. International Journal of Business Excellence, 27(1), 1-22. https://doi.org/10.1504/IJBEX.2022.123031
Kamoonpuri, S. Z., & Sengar, A. (2023). Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail. Journal of Retailing and Consumer Services, 72, 103258. https://doi.org/10.1016/j.jretconser.2023.103258
Karim, R., & Karmaker, C. L. (2016). Machine Selection by AHP and TOPSIS Method. American Journal of Industrial Engineering, 4(1), 7-13.
Kavitha, V., & Lohani, R. (2019). A critical study on the use of artificial intelligence, e-Learning technology and tools to enhance the learners experience. Cluster Computing, 22(3), 6985-6989. https://doi.org/10.1007/s10586-018-2017-2
Khan, H. U., & Nazir, S. (2023). Assessing the Role of AI-Based Smart Sensors in Smart Cities Using AHP and MOORA. Sensors, 23(1), 494. https://doi.org/10.3390/s23010494
Kim, S., & Kim, B. (2020). A Decision-Making Model for Adopting Al-Generated News Articles: Preliminary Results. Sustainability, 12(18), 7418. https://doi.org/10.3390/su12187418
Kong, F. (2020). Application of Artificial Intelligence in Modern Art Teaching. International Journal of Emerging Technologies in Learning (iJET), 15(13), 238-251. https://doi.org/10.3991/ijet.v15i13.15351
Krenicky, T., Hrebenyk, L., & Chernobrovchenko, V. (2022). Application of Concepts of the Analytic Hierarchy Process in Decision-Making. Management Systems in Production Engineering, 30(4), 304-310. https://doi.org/doi:10.2478/mspe-2022-0039
Kunze, L., Hawes, N., Duckett, T., Hanheide, M., & Krajník, T. (2018). Artificial Intelligence for Long-Term Robot Autonomy: A Survey. IEEE Robotics and Automation Letters, 3(4), 4023-4030. https://doi.org/10.1109/LRA.2018.2860628
Li, K., Duan, T., Li, Z., Xiahou, X., Zeng, N., & Li, Q. (2022). Development Path of Construction Industry Internet Platform: An AHP-TOPSIS Integrated Approach. Buildings, 12(4), 441. https://doi.org/doi:10.3390/buildings12040441
Li, R., Zhao, Z., Zhou, X., Ding, G., Chen, Y., Wang, Z., & Zhang, H. (2017). Intelligent 5G: When Cellular Networks Meet Artificial Intelligence. IEEE Wireless Communications, 24(5), 175-183. https://doi.org/10.1109/MWC.2017.1600304WC
Li, X., Wang, J., Chen, X., & Sun, C. (2023). Safety Evaluation of Steel Temporary Beam Service Status Based on the Combination Weighting-Fuzzy Model of Game Theory. Mathematical Problems in Engineering, 2023, 6271946. https://doi.org/10.1155/2023/6271946
Ling, Z. (2022). Financial Valuation and Investment Analysis of Carrefour. Accounting and Corporate Management, 4(Num. 5), 19-35. https://doi.org/10.23977/acccm.2022.040503
Liu, J.-W., Chen, S.-H., Chen, C.-H., & Huang, T.-H. (2023). Constructing an artificial intelligence strategy algorithm for the identification of talented rowing athletes. Soft Computing, 27(3), 1743-1750. https://doi.org/10.1007/s00500-021-06050-3
Liu, Y., Al-Atawi, A. A., Khan, I. A., Gohar, N., & Zaman, Q. (2023). Using the fuzzy analytical hierarchy process to prioritize the impact of visual communication based on artificial intelligence for long-term learning. Soft Computing, 27(1), 157-168. https://doi.org/10.1007/s00500-022-07556-0
Londa, M. A., & Tute, K. J. (2020). Performance Assessment System for Structural Officers to Support Employee Acceptance Decision at Flores University Using AHP Method. International Journal of Multidisciplinary Research and Publications, 3(4), 52-58.
Macrotrends. (2023). Macrotrends - The Premier Research Platform for Long Term Investors. Retrieved 10.07.2023 from https://www.macrotrends.net/
Madushanka, K. H. I., & Jathurika, M. (2018). The Impact of Liquidity Ratios on Profitability (With special reference to Listed Manufacturing Companies in Sri Lanka). International Research Journal of Advanced Engineering and Science, 3(4), 157-161.
Maheshwari, R. (2023). Advantages Of Artificial Intelligence (AI) In 2023. Retrieved 06.07.2023 from https://www.forbes.com/advisor/in/business/software/advantages-of-ai/
Mateos-Ronco, A., & Mas, Á. L. (2011). Developing a business failure prediction model for cooperatives: Results of an empirical study in Spain. African Journal of Business Management, 5(26), 10565-10576. https://doi.org/10.5897/AJBM11.1415
Mudzakar, M. K., & Wardanny, I. P. (2021). The Effect Of Return On Asset, Return On Equity, Earning Per Share, And Price Earning Ratio Toward Stock Return (Empirical Study Of Transportation) Turkish Journal of Computer and Mathematics Education, 12(8), 387-392.
Natale, S. (2021). Communicating Through or Communicating with: Approaching Artificial Intelligence from a Communication and Media Studies Perspective. Communication Theory, 31(4), 905-910. https://doi.org/10.1093/ct/qtaa022
Nguyen, T. M. H., Nguyen, V. P., & Nguyen, D. T. (2022). A new hybrid Pythagorean fuzzy AHP and COCOSO MCDM based approach by adopting artificial intelligence technologies. Journal of Experimental & Theoretical Artificial Intelligence, 1-27. https://doi.org/10.1080/0952813X.2022.2143908
Nikhil, S., Danumah, J. H., Saha, S., Prasad, M. K., Rajaneesh, A., Mammen, P. C., Ajin, R. S., & Kuriakose, S. L. (2021). Application of GIS and AHP Method in Forest Fire Risk Zone Mapping: a Study of the Parambikulam Tiger Reserve, Kerala, India. Journal of Geovisualization and Spatial Analysis, 5(1), 14. https://doi.org/10.1007/s41651-021-00082-x
Nizar, Z. M., Laith, W. H., & Al-Najjar, A. K. (2023). Optimal Decision Making to Select the Best Suppliers Using Integrating AHP-TOPSIS. In A. Khanna, Z. Polkowski, & O. Castillo (Eds.), Proceedings of Data Analytics and Management . Lecture Notes in Networks and Systems, vol 572 (pp. 407-418). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-7615-5_35
Nong, T. N. M., & Ha, D. S. Application of MCDM methods to Qualified Personnel Selection in Distribution Science: Case of Logistics Companies. Journal of Distribution Science, 19(8), 25-35. https://doi.org/10.15722/jds.19.8.202108.25
Oubahman, L., & Duleba, S. (2022). A Comparative Analysis of Homogenous Groups’ Preferences by Using AIP and AIJ Group AHP-PROMETHEE Model. Sustainability, 14(10), 5980.
Öngel, V. (2022). Üretimde Etkinlik, Rekabet ve Finansal Performansın Belirlenmesi: Türk Çimento Sektörü Örneği [Unpublished doctoral thesis, Istanbul University Social Sciences Institute]. Istanbul.
Parikh, R. B., Teeple, S., & Navathe, A. S. (2019). Addressing Bias in Artificial Intelligence in Health Care. JAMA, 322(24), 2377-2378. https://doi.org/10.1001/jama.2019.18058
Pradhan, S., Patel, G., & Priya, P. (2021). Measuring Customer Lifetime Value: Application of Analytic Hierarchy Process in Determining Relative Weights of ‘LRFM’. International Journal of the Analytic Hierarchy Process, 13(3), 526-547. https://doi.org/10.13033/ijahp.v13i3.892
Precedence Research. (2023). Artificial Intelligence (AI) Market. Retrieved 06.07.2023 from https://www.precedenceresearch.com/artificial-intelligence-market
Prentice, C. (2023). Demystify Artificial Intelligence. In C. Prentice (Ed.), Leveraging Emotional and Artificial Intelligence for Organisational
Performance (pp. 25-40). Singapore: Springer Nature. https://doi.org/10.1007/978-981-99-1865-2_3
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.2018.0072
Ren, Z., Xu, Z., & Wang, H. (2019). The Strategy Selection Problem on Artificial Intelligence With an Integrated VIKOR and AHP Method Under Probabilistic Dual Hesitant Fuzzy Information. IEEE Access, 7, 103979-103999. https://doi.org/10.1109/ACCESS.2019.2931405
Rudžionienė, K., Černiauskaitė, M., & Klimaitienė, R. (2022). The impact of IFRS adoption on companies' financial ratios: evidence from Lithuania. Entrepreneurship and Sustainability Issues, 9(3), 212-226. https://doi.org/10.9770/jesi.2022.9.3(13)
Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98.
Sano, H., & Yamada, K. (2021). Prediction accuracy of sales surprise for inventory turnover. International Journal of Production Research, 59(17), 5337-5351. https://doi.org/10.1080/00207543.2020.1778205
Shaban-Nejad, A., Michalowski, M., & Buckeridge, D. L. (2018). Health intelligence: how artificial intelligence transforms population and personalized health. npj Digital Medicine, 1, 53. https://doi.org/10.1038/s41746-018-0058-9
Shafiee, M. (2022). Wind Energy Development Site Selection Using an Integrated Fuzzy ANP-TOPSIS Decision Model. Energies, 15(12), 4289.
Shalini, K., G. Rohini, G., P. Vishal, P., & Polasi, S. (2022). Analytical Hierarchy Process (AHP):A Steady Method for Quality Decision Making: A Case Study in Snack Food Industry. Journal of Pharmaceutical Negative Results, 13(6), 1787-1798. https://doi.org/10.47750/pnr.2022.13.S06.235
Sharma, J. (2018). Economics of Decision Making: Exploring Analytical Hierarchical Process (AHP). Theoretical Economics Letters, 8, 3141-3156. https://doi.org/10.4236/tel.2018.814195
Sharma, K., Jain, M., & Dhir, S. (2022). Analysing the impact of artificial intelligence on the competitiveness of tourism firms: a modified total interpretive structural modeling (m-TISM) approach. International Journal of Emerging Markets, 17(4), 1067-1084.
https://doi.org/10.1108/IJOEM-05-2021-0810
Shi, Y., Gao, Y., & Cao, R. (2019). Research on the Construction of Analytic Hierarchy Process of Cultural Tourism Competitiveness. Proceedings of the 4th International Conference on Economy, Judicature, Administration and Humanitarian Projects (JAHP 2019), Atlantis Press: Paris, France, 853-856. https://doi.org/10.2991/jahp-19.2019.173
Shijin, L., & Xiaoqing, G. (2023). A Risk Framework for Human-centered Artificial Intelligence in Education: Based on Literature Review and Delphi-AHP Method. Educational Technology & Society, 26(1), 187-202. https://doi.org/10.30191/ETS.202301_26(1).0014
Sompolgrunk, A., Banihashemi, S., Hosseini, M. R., Golzad, H., & Hajirasouli, A. (2023). An integrated model of BIM return on investment for Australian small- and medium-sized enterprises (SMEs). Engineering, Construction and Architectural Management, 30(5), 2048-2074.
https://doi.org/10.1108/ECAM-09-2021-0839
Stofkova, J., Krejnus, M., Stofkova, K. R., Malega, P., & Binasova, V. (2022). Use of the Analytic Hierarchy Process and Selected Methods in the Managerial Decision-Making Process in the Context of Sustainable Development. Sustainability, 14(18), 11546. https://doi.org/doi:10.3390/su141811546
Strohmeier, S., & Piazza, F. (2015). Artificial Intelligence Techniques in Human Resource Management—A Conceptual Exploration. In C. Kahraman & S. Çevik Onar (Eds.), Intelligent Techniques in Engineering Management: Theory and Applications (pp. 149-172). Springer International Publishing. https://doi.org/10.1007/978-3-319-17906-3_7
Sutomo, H., & Budiharjo, R. (2019). The Effect of Dividend Policy and Return on Equity on Firm Value. International Journal of Academic Research in Accounting, Finance and Management Sciences, 9(3), 211-220. https://doi.org/10.6007/IJARAFMS/v9-i3/6364
Taherdoost, H. (2017). Decision Making Using the Analytic Hierarchy Process (AHP); A Step by Step Approach. International Journal of Economics and Management Systems, 2, 244-246.
Tang, J., & Hai, L. (2021). Construction and Exploration of an Intelligent Evaluation System for Educational APP through Artificial Intelligence Technology. International Journal of Emerging Technologies in Learning (iJET), 16(05), 17-31. https://doi.org/10.3991/ijet.v16i05.20293
Tao, Z., Si Jun, B., & Xi Bai, R. (2021). Research on marketing management system based on independent ERP and business BI using fuzzy TOPSIS. Journal of Intelligent & Fuzzy Systems, 40, 8247-8255. https://doi.org/10.3233/JIFS-189647
Tavana, M., Soltanifar, M., & Santos-Arteaga, F. J. (2021). Analytical hierarchy process: revolution and evolution. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04432-2
Vásquez, J. A., Escobar, J. W., & Manotas, D. F. (2022). AHP–TOPSIS Methodology for Stock Portfolio Investments. Risks, 10(1), 4. https://doi.org/10.3390/risks10010004
Wang, Q., & Gong, C. (2021). Study on College Students’ Psychological Health Service System Design Based on Artificial Intelligence Techonology. 2021 2nd International Conference on Intelligent Design (ICID),
Wubalem, A. (2023). Modeling of land suitability for surface irrigation using analytical hierarchy process method in Belessa Districts, northwestern Ethiopia. Heliyon, 9(3), e13937. https://doi.org/10.1016/j.heliyon.2023.e13937
Xu, Y., & Nazir, S. (2022). Ranking the art design and applications of artificial intelligence and machine learning. Journal of Software: Evolution and Process, e2486. https://doi.org/10.1002/smr.2486
Yang, X. (2019). Satisfaction Evaluation and Optimization of Tourism E-Commerce Users Based on Artificial Intelligence Technology. In 2019 International Conference on Robots & Intelligent System (ICRIS) (pp. 373-375). https://doi.org/10.1109/ICRIS.2019.00100
Yao, M., Sohul, M., Marojevic, V., & Reed, J. H. (2019). Artificial Intelligence Defined 5G Radio Access Networks. IEEE Communications Magazine, 57(3), 14-20. https://doi.org/10.1109/MCOM.2019.1800629
Zhang, R. (2021). Exploration of Social Benefits for Tourism Performing Arts Industrialization in Culture–Tourism Integration Based on Deep Learning and Artificial Intelligence Technology [Original Research]. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.592925
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