References
- Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S. A.(2019). Applications of artificial intelligence in transport: An overview. Sustainability, 11(1), 189.
- Abernathy, W. J., & Clark, K. B.(1985). Innovation: Mapping the winds of creative destruction. Research policy, 14(1), 3-22. https://doi.org/10.1016/0048-7333(85)90021-6
- Albayrak, E., & Erensal, Y. C.(2004). Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem. Journal of intelligent manufacturing, 15, 491-503. https://doi.org/10.1023/B:JIMS.0000034112.00652.4c
- Alnamrouti, A., Rjoub, H., & Ozgit, H.(2022). Do strategic human resources artificial intelligence help to make organisations more sustainable? evidence from non-governmental organisations. Sustainability, 14(12), 7327.
- Barrios, M. A. O., De Felice, F., Negrete, K. P., Romero, B. A., Arenas, A. Y., & Petrillo, A.(2016). An AHP-topsis integrated model for selecting the most appropriate tomography equipment. International Journal of Information Technology & Decision Making, 15(04), 861-885. https://doi.org/10.1142/S021962201640006X
- Brynjolfsson, E., & McAfee, A.(2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
- Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R.(2018). Notes from the AI frontier: Modeling the impact of AI on the world economy. McKinsey Global Institute, 4.
- Chai, J., Liu, J. N., & Ngai, E. W.(2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert systems with applications, 40(10), 3872-3885. https://doi.org/10.1016/j.eswa.2012.12.040
- Chidamber, S. R., & Kon, H. B.(1994). A research retrospective of innovation inception and success: the technology-push, demand-pull question. International Journal of Technology Management, 9(1), 94-112.
- Choudhury, P., Allen, R. T., & Endres, M. G.(2021). Machine learning for pattern discovery in management research. Strategic Management Journal, 42(1), 30-57. https://doi.org/10.1002/smj.3215
- Dagdeviren, M., Yavuz, S., & Kilinc, N.(2009). Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert systems with applications, 36(4), 8143-8151. https://doi.org/10.1016/j.eswa.2008.10.016
- Davenport, T. H., & Kirby, J.(2015). Beyond automation. Harvard Business Review, 93(6), 58-65.
- Deloitte(2023). Summer 2023 Fortune/Deloitte CEO Survey. Retrieved (2023.10.18) from [https://www2.deloitte.com/us/en/pages/chief-executive-officer/articles/ceo-survey.html].
- Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., & Houlsby, N.(2020). An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929.
- Fountaine, T., McCarthy, B., & Saleh, T.(2019). Building the AI-powered organization. Harvard Business Review, 97(4), 50-59.
- Geum, Y., Jeon, H., & Lee, H.(2016). Developing new smart services using integrated morphological analysis: integration of the market-pull and technology-push approach. Service Business, 10, 531-555. https://doi.org/10.1007/s11628-015-0281-2
- Gunasekaran, A., & Ngai, E. W.(2004). Information systems in supply chain integration and management. European journal of operational research, 159(2), 269-295. https://doi.org/10.1016/j.ejor.2003.08.016
- Hajduk, S.(2021). Multi-criteria analysis in the decision-making approach for the linear ordering of urban transport based on TOPSIS technique. Energies, 15(1), 274.
- Hajduk, S., & Jelonek, D.(2021). A decision-making approach based on TOPSIS method for ranking smart cities in the context of urban energy. Energies, 14(9), 2691.
- Hinton, G., Deng, L., Yu, D., Dahl, G. E., Mohamed, A. R., Jaitly, N., ... & Kingsbury, B.(2012). Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal processing magazine, 29(6), 82-97.
- Hwang, C. L., Lai, Y. J., & Liu, T. Y.(1993). A new approach for multiple objective decision making. Computers & operations research, 20(8), 889-899. https://doi.org/10.1016/0305-0548(93)90109-V
- Hwang, C. L., Yoon, K., Hwang, C. L., & Yoon, K.(1981). Methods for multiple attribute decision making. Multiple attribute decision making: methods and applications a state-of-the-art survey, 58-191.
- Jain, V., Sangaiah, A. K., Sakhuja, S., Thoduka, N., & Aggarwal, R.(2018). Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry. Neural computing and applications, 29, 555-564. https://doi.org/10.1007/s00521-016-2533-z
- Juell-Skielse, G., Balasuriya, P., Guner, E. O., & Han, S.(2022). Cognitive robotic process automation: Concept and impact on dynamic IT capabilities in public organizations. Cham: Springer International Publishing, (pp. 65-88).
- Jung, D. H(2021). Proposing an AI-based new product development methodology: An ambidexterity approach. Technology Innovation Research, 29(4), 161-196. https://doi.org/10.14386/SIME.2021.29.4.161
- Kudyba, S., & Diwan, R.(2002). Increasing returns to information technology. Information Systems Research, 13(1), 104-111. https://doi.org/10.1287/isre.13.1.104.98
- Kwon, H., Park, Y., & Geum, Y.(2018). Toward data-driven idea generation: Application of Wikipedia to morphological analysis. Technological Forecasting and Social Change, 132, 56-80. https://doi.org/10.1016/j.techfore.2018.01.009
- Lee, S. A., & Jeang, T. H.(2023). Analyzing and predicting venture investment in generative AI startups: Focusing on the United States and South Korea. Venture Capital Research, 18(4), 21-35.
- Likert, R.(1932). A technique for the measurement of attitudes. Archives of psychology, 22 140, 55.
- Liu, H., Ke, W., Wei, K. K., & Hua, Z.(2013). The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility. Decision support systems, 54(3), 1452-1462. https://doi.org/10.1016/j.dss.2012.12.016
- Mandal, P., & Gunasekaran, A.(2003). Issues in implementing ERP: A case study. European Journal of Operational Research, 146(2), 274-283. https://doi.org/10.1016/S0377-2217(02)00549-0
- Mardani, A., Jusoh, A., Nor, K., Khalifah, Z., Zakwan, N., & Valipour, A.(2015). Multiple criteria decision-making techniques and their applications-a review of the literature from 2000 to 2014. Economic research-Ekonomska istrazivanja, 28(1), 516-571. https://doi.org/10.1080/1331677X.2015.1075139
- Mitchell, M.(2021). Why AI is harder than we think. arXiv preprint arXiv:2104.12871.
- Munakata, T.(1994). Commercial and industrial AI. Communications of the ACM, 37(3), 23-26. https://doi.org/10.1145/175247.175248
- Olson, D. L.(2004). Comparison of weights in TOPSIS models, Mathematical and Computer Modelling. 40(7-8), 721-727. https://doi.org/10.1016/j.mcm.2004.10.003
- Parkan, C., & Wu, M. L.(1997). On the equivalence of operational performance measurement and multiple attribute decision making. International Journal of Production Research, 35(11), 2963-2988. https://doi.org/10.1080/002075497194246
- Purcell, A. T., & Gero, J. S.(1996). Design and other types of fixation. Design studies, 17(4), 363-383. https://doi.org/10.1016/S0142-694X(96)00023-3
- Raju, S. S., Murali, G. B., & Patnaik, P. K.(2020). Ranking of Al-CSA composite by MCDM approach using AHP-TOPSIS and MOORA methods. Journal of Reinforced Plastics and Composites, 39(19-20), 721-732. https://doi.org/10.1177/0731684420924833
- Rammer, C., Fernandez, G. P., & Czarnitzki, D.(2022). Artificial intelligence and industrial innovation: Evidence from German firm-level data. Research Policy, 51(7), 104555.
- Roy, R., & Sarkar, M. B.(2016). Knowledge, firm boundaries, and innovation: Mitigating the incumbent's curse during radical technological change. Strategic Management Journal, 37(5), 835-854.
- Saaty, T. L.(1980). The Analytic Hierarchy Process Mcgraw Hill, New York. Agricultural Economics Review, 70. 34.
- Saaty, T. L.(1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26. https://doi.org/10.1016/0377-2217(90)90057-I
- Syamsudin, S., & Rahim, R.(2017). Study Approach Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS). Int. J. Recent Trends Eng. Res, 3(3), 268-285.
- Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., & Polosukhin, I.(2017). Attention is all you need. Advances in neural information processing systems, 30.
- Verganti, R., Vendraminelli, L., & Iansiti, M.(2020). Innovation and design in the age of artificial intelligence. Journal of Product Innovation Management, 37(3), 212-227. https://doi.org/10.1111/jpim.12523
- Wamba-Taguimdje, S. L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E.(2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893-1924. https://doi.org/10.1108/BPMJ-10-2019-0411
- Wei, C. C., Chien, C. F., & Wang, M. J. J.(2005). An AHP-based approach to ERP system selection. International journal of production economics, 96(1), 47-62. https://doi.org/10.1016/j.ijpe.2004.03.004
- Wissema, J. G.(1976). Morphological analysis: its application to a company TF investigation, Futures, 8(2), 146-153. https://doi.org/10.1016/0016-3287(76)90064-1
- Yoon, B., & Park, Y.(2005). A systematic approach for identifying technology opportunities: Keyword-based morphology analysis. Technological Forecasting and Social Change, 72(2), 145-160. https://doi.org/10.1016/j.techfore.2004.08.011
- Younus, A. M.(2022). The Effect of Artificial Intelligence on Job Performance in China's Small and Medium-Sized Enterprises (SMEs).
- Zahedi, F.(1986). The analytic hierarchy process-a survey of the method and its applications. interfaces, 16(4), 96-108. https://doi.org/10.1287/inte.16.4.96