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1. Arnosti, N., & Weinberg, S. M. (2022). Bitcoin: A natural oligopoly. Management Science, 68(7), 4755–4771. https://doi.org/10.1287/mnsc.2021.4095 .

2. Assael, Y., Sommerschield, T., Shillingford, B., et al. (2022). Restoring and attributing ancient texts using deep neural networks. Nature, 603(7900), 280–283. https://doi.org/10.1038/s41586-022-04448-z .

3. Bahoo, S., Cucculelli, M., & Qamar, D. (2023). Artificial intelligence and corporate innovation: A review and research agenda. Technological Forecasting & Social Change, 188, 122264. https://doi.org/10.1016/j.techfore.2022.122264 .

4. Bai, X., & Li, J. (2020). The best configuration of collaborative knowledge innovation management from the perspective of artificial intelligence. Knowledge Management Research & Practice, 1–13. https://doi.org/10.1080/14778238.2020.1834886 .
   Paper not yet in RePEc: Add citation now
   
5. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 .
   Paper not yet in RePEc: Add citation now
   
6. Benetta, A. D., Sobolewski, M., & Nepelski, D. (2021). AI Watch: 2020 EU AI investments (No. JRC126477). Joint Research Centre. https://doi.org/10.2760/017514 .
   Paper not yet in RePEc: Add citation now
   
7. Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196. https://doi.org/10.2307/3250983 .
   Paper not yet in RePEc: Add citation now
   
8. Boiko, K. (2021). R&D activity and firm performance: Mapping the field. Management Review Quarterly, 71(1), 1–37. https://doi.org/10.1007/s11301-021-00220-1 .
   Paper not yet in RePEc: Add citation now
   
9. Bossaerts, P. (2021). How neurobiology elucidates the role of emotions in financial decision-making. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2021.697375 .
   Paper not yet in RePEc: Add citation now
   
10. Braune, C., Besecke, S., & Kruse, R. (2015). Density based clustering: Alternatives to DBSCAN. In Partitional Clustering Algorithms (pp. 193–213). Springer, Cham. https://doi.org/10.1007/978-3-319-09259-1_6 .
    Paper not yet in RePEc: Add citation now
    
11. Bruderer, H. (2016). The birth of artificial intelligence: First conference on artificial intelligence in paris in 1951? In: IFIP International Conference on the History of Computing, 181–185. https://doi.org/10.1007/978-3-319-49463-0_12 .
    Paper not yet in RePEc: Add citation now
    
12. Bui, X. N., Nguyen, H., Choi, Y., Nguyen-Thoi, T., Zhou, J., & Dou, J. (2020). Prediction of slope failure in open-pit mines using a novel hybrid artificial intelligence model based on decision tree and evolution algorithm. Scientific Reports, 10(1), 1–17. https://doi.org/10.1038/s41598-020-66904-y .
    Paper not yet in RePEc: Add citation now
    

13. Cai, Y., Ramis Ferrer, B., & Luis Martinez Lastra, J. (2019). Building university-industry co-innovation networks in transnational innovation ecosystems: Towards a transdisciplinary approach of integrating social sciences and artificial intelligence. Sustainability, 11(17), 4633. https://doi.org/10.3390/su11174633 .

14. Castelvecchi, D. (2015). Artificial intelligence called in to tackle LHC data deluge. Nature, 528(7580), 18–19. https://doi.org/10.1038/528018a .

15. Challa, H., Niu, N., & Johnson, R. (2020). Faulty requirements made valuable: On the role of data quality in deep learning. In 2020 IEEE Seventh International Workshop on Artificial Intelligence for Requirements Engineering (AIRE), 61–69. https://doi.org/10.1109/AIRE51212.2020.00016 .
    Paper not yet in RePEc: Add citation now
    
16. Choi, J., & Contractor, F. J. (2019). Improving the progress of research & development (R&D) projects by selecting an optimal alliance structure and partner type. British Journal of Management, 30(4), 791–809. https://doi.org/10.1111/1467-8551.12267 .
    Paper not yet in RePEc: Add citation now
    
17. Cohen, J. F., & Olsen, K. (2013). The impacts of complementary information technology resources on the service-profit chain and competitive performance of South African hospitality firms. International Journal of Hospitality Management, 34, 245–254. https://doi.org/10.1016/j.ijhm.2013.04.005 .
    Paper not yet in RePEc: Add citation now
    

18. Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2021.102383 .

19. D’Este, P., & Perkmann, M. (2010). Why do academics engage with industry? The entrepreneurial university and individual motivations. The Journal of Technology Transfer, 36(3), 316–339. https://doi.org/10.1007/s10961-010-9153-z .
    Paper not yet in RePEc: Add citation now
    
20. Dafoe, A. (2018). AI governance: A research agenda. Oxford, UK, Future of Humanity Institute, University of Oxford.
    Paper not yet in RePEc: Add citation now
    
21. Dahiya, R., Le, S., Ring, J. K., & Watson, K. (2021). Big data analytics and competitive advantage: The strategic role of firm-specific knowledge. Journal of Strategy & Management. https://doi.org/10.1108/jsma-08-2020-0203 .
    Paper not yet in RePEc: Add citation now
    
22. Degravel, D. (2011). Managing organizational capabilities: The keystone step. Journal of Strategy and Management, 4(3), 251–274. https://doi.org/10.1108/17554251111152270 .
    Paper not yet in RePEc: Add citation now
    

23. Ding, J., & Dafoe, A. (2021). The logic of strategic assets: From oil to AI. Security Studies, 30(2), 182–212. https://doi.org/10.1080/09636412.2021.1915583 .

24. Edwards, C. (2021). The best of NLP. Communications of the ACM, 64(4), 9–11. https://doi.org/10.1145/3449049 .
    Paper not yet in RePEc: Add citation now
    

25. Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21(10–11), 1105–1121. https://doi.org/10.1002/1097-0266(200010/11)21:10/11%3c1105::AID-SMJ133%3e3.0.CO;2-E .

26. Etzkowitz, H., & Leydesdorff, L. (1995). The triple helix—university-industry-government relations: A laboratory for knowledge-based economic development. EASST Review, 14(1), 14–19. Available at SSRN: https://ssrn.com/abstract=2480085 .
    Paper not yet in RePEc: Add citation now
    
27. Ferreira, J. J., Fayolle, A., Ratten, V., & Raposo, M. (2018). Introduction: The role of entrepreneurial universities in society. Edward Elgar Publishing. https://doi.org/10.4337/9781786432469.00005 .
    Paper not yet in RePEc: Add citation now
    

28. Fink, L. (2011). How do IT capabilities create strategic value? Toward greater integration of insights from reductionistic and holistic approaches. European Journal of Information Systems, 20(1), 16–33. https://doi.org/10.1057/ejis.2010.53 .

29. Formica, P. (2002). Entrepreneurial universities: The value of education in encouraging entrepreneurship. Industry & Higher Education, 16(3), 167–175. https://doi.org/10.5367/000000002101296261 .
    Paper not yet in RePEc: Add citation now
    
30. Fredström, A., Wincent, J., Sjödin, D., Oghazi, P., & Parida, V. (2021). Tracking innovation diffusion: AI analysis of large-scale patent data towards an agenda for further research. Technological Forecasting & Social Change. https://doi.org/10.1016/j.techfore.2020.120524 .
    Paper not yet in RePEc: Add citation now
    
31. García-Laencina, P. J., Sancho-Gómez, J. L., & Figueiras-Vidal, A. R. (2010). Pattern classification with missing data: A review. Neural Computing & Applications, 19(2), 263–282. https://doi.org/10.1007/s00521-009-0295-6 .
    Paper not yet in RePEc: Add citation now
    

32. Ge, S., & Liu, X. (2022). The role of knowledge creation, absorption and acquisition in determining national competitive advantage. Technovation, 112, 102396. https://doi.org/10.1016/j.technovation.2021.102396 .

33. Grassano, N., Hernandez, H., Fako, P., Tuebke, A., Amoroso, S., Georgakaki, A., .. & Panzica, R. (2022). The 2021 EU Industrial R&D Investment Scoreboard, No. JRC127360. Joint Research Centre. https://doi.org/10.2760/559391 .
    Paper not yet in RePEc: Add citation now
    
34. Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. Metabolism, 69(Supplement), S36–S40. https://doi.org/10.1016/j.metabol.2017.01.011 .
    Paper not yet in RePEc: Add citation now
    
35. Hassanzadeh, P., Atyabi, F., & Dinarvand, R. (2019). The significance of artificial intelligence in drug delivery system design. Advanced Drug Delivery Reviews, 151, 169–190. https://doi.org/10.1016/j.addr.2019.05.001 .
    Paper not yet in RePEc: Add citation now
    
36. Henard, D. H., & McFadyen, M. A. (2006). R&D knowledge is power. Research-Technology Management, 49(3), 41–47. https://doi.org/10.1080/08956308.2006.11657377 .
    Paper not yet in RePEc: Add citation now
    
37. Hou, J., Gao, H., & Li, X. (2016). Dsets-DBSCAN: A parameter-free clustering algorithm. IEEE Transactions on Image Processing, 25(7), 3182–3193. https://doi.org/10.1109/TIP.2016.2559803 .
    Paper not yet in RePEc: Add citation now
    
38. Hu, Y., Kuang, W., Qin, Z., Li, K., Zhang, J., Gao, Y., & Li, K. (2021). Artificial intelligence security: Threats and countermeasures. ACM Computing Surveys (CSUR), 55(1), 1–36. https://doi.org/10.1145/3487890 .
    Paper not yet in RePEc: Add citation now
    

39. Huggins, R., Johnston, A., & Stride, C. (2012). Knowledge networks and universities: Locational and organisational aspects of knowledge transfer interactions. Entrepreneurship & Regional Development, 24(7–8), 475–502. https://doi.org/10.1080/08985626.2011.618192 .

40. Jácome de Moura, P., Jr., & Porto-Bellini, C. G. (2019). Shared flow in teams: Team vibration as emergent property, metaphor, and surrogate measure. Team Performance Management, 25(7/8), 440–456. https://doi.org/10.1108/TPM-12-2018-0072 .
    Paper not yet in RePEc: Add citation now
    

41. Jeon, S., Chang, Y. S., & Jo, S. J. (2024). Speed of catch-up and convergence of the artificial intelligence divide: AI investment, robotic, start-ups, and patents. Journal of Global Information Technology Management, 27(1). https://doi.org/10.1080/1097198X.2023.2297636 .

42. Johnston, A. (2019). The roles of universities in knowledge-based urban development: A critical review. International Journal of Knowledge-Based Development, 10(3), 213–231. https://doi.org/10.1504/IJKBD.2019.103205 .

43. Karami, A., & Johansson, R. (2014). Choosing DBSCAN parameters automatically using differentiation evolution. International Journal of Computer Applications, 91(7), 1–11.
    Paper not yet in RePEc: Add citation now
    
44. Kaur, D., Uslu, S., & Durresi, A. (2020). Requirements for trustworthy artificial intelligence—a review. In International Conference on Network-Based Information Systems (pp. 105–115). https://doi.org/10.1007/978-3-030-57811-4_11 .
    Paper not yet in RePEc: Add citation now
    
45. Kerr, A., Barry, M., & Kelleher, J. D. (2020). Expectations of artificial intelligence and the performativity of ethics: Implications for communication governance. Big Data & Society, 7(1). https://doi.org/10.1177/2053951720915 .
    Paper not yet in RePEc: Add citation now
    
46. Kovacevich, A. (2022). Take it from a software engineer: Big tech’s monopoly is stifling innovation. Accessed June 28, 2022. https://www.newsweek.com/take-it-software-engineer-big-techs-monopoly-stifling-innovation-opinion-1718646 .
    Paper not yet in RePEc: Add citation now
    
47. Lai, W., Zhou, M., Hu, F., Bian, K., & Song, Q. (2019). A new DBSCAN parameters determination method based on improved MVO. IEEE Access, 7, 104085–104095. https://doi.org/10.1109/ACCESS.2019.2931334 .
    Paper not yet in RePEc: Add citation now
    
48. Li, K., Zhang, J., & Li, D. (2021). Research status and hotspot analysis of literature metrology in artificial intelligence field. Journal of Physics: Conference Series, 2024(1), 012055. https://doi.org/10.1088/1742-6596/2024/1/012055 .
    Paper not yet in RePEc: Add citation now
    
49. Li, Z., Li, Y., Lu, W., & Huang, J. (2020). Crowdsourcing logistics pricing optimization model based on DBSCAN clustering algorithm. IEEE Access, 8, 92615–92626. https://doi.org/10.1109/ACCESS.2020.2995063 .
    Paper not yet in RePEc: Add citation now
    
50. Lindbloom, C. E. (1959). The science of “muddling through.” Public Administration Review, 19(2), 79–88.
    Paper not yet in RePEc: Add citation now
    

51. Liu, N., Shapira, P., & Yue, X. (2021). Tracking developments in artificial intelligence research: Constructing and applying a new search strategy. Scientometrics, 126(4), 3153–3192. https://doi.org/10.1007/s11192-021-03868-4 .

52. Mahdi, O. R., Nassar, I. A., & Almsafir, M. K. (2019). Knowledge management processes and sustainable competitive advantage: An empirical examination in private universities. Journal of Business Research, 94, 320–334. https://doi.org/10.1016/j.jbusres.2018.02.013 .

53. Marakova, V., Wolak-Tuzimek, A., & Tuckova, Z. (2021). Corporate social responsibility as a source of competitive advantage in large enterprises. Journal of Competitiveness, 13(1), 113–128. https://doi.org/10.7441/joc.2021.01.07 .
    Paper not yet in RePEc: Add citation now
    

54. Marimon, R., & Quadrini, V. (2011). Competition, human capital and income inequality with limited commitment. Journal of Economic Theory, 146(3), 976–1008. https://doi.org/10.1016/j.jet.2011.01.001 .

55. Martin, D., Fowlkes, C., Tal, D., & Malik, J. (2001). A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proceedings 8th IEEE International Conference on Computer Vision. ICCV 2001, 416–423. https://doi.org/10.1109/ICCV.2001.937655 .
    Paper not yet in RePEc: Add citation now
    

56. Mayer, K. J., Somaya, D., & Williamson, I. O. (2012). Firm-specific, industry-specific, and occupational human capital and the sourcing of knowledge work. Organization Science, 23(5), 1311–1329. https://doi.org/10.1287/orsc.1110.0722 .

57. Menke, M. M. (1997). Managing R&D for competitive advantage. Research-Technology Management, 40(6), 40–42. https://doi.org/10.1080/08956308.1997.11671169 .
    Paper not yet in RePEc: Add citation now
    
58. Mikhaylov, S. J., Esteve, M., & Campion, A. (2018). Artificial intelligence for the public sector: Opportunities and challenges of cross-sector collaboration. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2128). https://doi.org/10.1098/rsta.2017.0357 .
    Paper not yet in RePEc: Add citation now
    
59. Miotti, L., & Sachwald, F. (2003). Co-operative R&D: Why and with whom? An integrated framework of analysis. Research Policy, 32(8), 1481–1499. https://doi.org/10.1016/S0048-7333(02)00159-2 .
    Paper not yet in RePEc: Add citation now
    

60. Miotto, G., Del-Castillo-Feito, C., & Blanco-González, A. (2020). Reputation and legitimacy: Key factors for higher education institutions’ sustained competitive advantage. Journal of Business Research, 112, 342–353. https://doi.org/10.1016/j.jbusres.2019.11.076 .

61. Mitchell, T. M. (1997). Machine learning. McGraw-Hill Science/Engineering.
    Paper not yet in RePEc: Add citation now
    
62. Mongeau, S., Hajdasinski, A. (2021). Managerial recommendations. In: Cybersecurity Data Science. Springer, Cham. https://doi.org/10.1007/978-3-030-74896-8_6 .
    Paper not yet in RePEc: Add citation now
    

63. Nayak, B., Bhattacharyya, S. S., & Krishnamoorthy, B. (2022). Exploring the black box of competitive advantage—an integrated bibliometric and chronological literature review approach. Journal of Business Research, 139, 964–982. https://doi.org/10.1016/j.jbusres.2021.10.047 .

64. Newbert, S. L. (2008). Value, rareness, competitive advantage, and performance: A conceptual-level empirical investigation of the resource-based view of the firm. Strategic Management Journal, 29(7), 745–768. https://doi.org/10.1002/smj.686 .

65. Newman, D. (2017). Inside look: The world’s largest tech companies are making massive AI investments. Accessed May 4, 2022. https://www.forbes.com/sites/danielnewman/2017/01/17/inside-look-the-worlds-largest-tech-companies-are-making-massive-ai-investments/?sh=4d7f17cc4af2 .
    Paper not yet in RePEc: Add citation now
    
66. OECD. (2020). A first look at the OECD’s framework for the classification of AI systems, designed to give policymakers clarity. Accessed May 2, 2022. https://oecd.ai/en/wonk/a-first-look-at-the-oecds-framework-for-the-classification-of-ai-systems-for-policymakers .
    Paper not yet in RePEc: Add citation now
    
67. Orlando, B., Ballestra, L. V., Magni, D., & Ciampi, F. (2021). Open innovation and patenting activity in health care. Journal of Intellectual Capital, 22(2), 384–402. https://doi.org/10.1108/JIC-03-2020-0076 .
    Paper not yet in RePEc: Add citation now
    

68. Pang, B., Nijkamp, E., & Wu, Y. N. (2020). Deep learning with TensorFlow: A review. Journal of Educational & Behavioral Statistics, 45(2), 227–248. https://doi.org/10.3102/10769986198727 .

69. Parmigiani, F., Haller, I., Gkantsidis, C., & Ballani, H. (2021, May). Optics for the cloud: Challenges and opportunities. In: CLEO: Science and Innovations (pp. STu1J-2). Optical Society of America.
    Paper not yet in RePEc: Add citation now
    
70. Pełka, M. (2018). Analysis of innovations in the European Union via ensemble symbolic density clustering. Ekonometria, 22(3). https://doi.org/10.15611/eada.2018.3.06 .
    Paper not yet in RePEc: Add citation now
    

71. Pereira, V., & Bamel, U. (2021). Extending the resource and knowledge-based view: A critical analysis into its theoretical evolution and future research directions. Journal of Business Research, 132, 557–570. https://doi.org/10.1016/j.jbusres.2021.04.021 .

72. Premaratne, G., & Bera, A. (2005). A test for symmetry with leptokurtic financial data. Journal of Financial Econometrics, 3(2), 169–187. https://doi.org/10.1093/jjfinec/nbi009 .

73. Ramanathan, V., Wang, R., & Mahajan, D. (2021). Predet: Large-scale weakly supervised pre-training for detection. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2865–2875. https://doi.org/10.1109/ICCV48922.2021.00286 .
    Paper not yet in RePEc: Add citation now
    
74. Řezanková, H. A. N. A. (2018). Different approaches to the silhouette coefficient calculation in cluster evaluation. In: 21st International Scientific Conference AMSE Applications of Mathematics and Statistics in Economics, 1–10.
    Paper not yet in RePEc: Add citation now
    

75. Riani, M., Atkinson, A. C., & Cerioli, A. (2009). Finding an unknown number of multivariate outliers. Journal of the Royal Statistical Society: Series B, 71(2), 447–466. https://doi.org/10.1111/j.1467-9868.2008.00692.x .

76. Roberts, H., Cowls, J., Morley, J., Taddeo, M., Wang, V., & Floridi, L. (2021). The Chinese approach to artificial intelligence: An analysis of policy, ethics, and regulation. AI & society, 36(1), 59–77. https://doi.org/10.1007/s00146-020-00992-2 .
    Paper not yet in RePEc: Add citation now
    
77. Rosenblatt, F. (1960). Perceptron simulation experiments. Proceedings of the IRE, 48(3), 301–309. https://doi.org/10.1109/JRPROC.1960.287598 .
    Paper not yet in RePEc: Add citation now
    
78. Samuel, A. (1959). Some studies in machine learning using the game of checkers. IBM Journal of Research & Development., 44(1), 206–226. https://doi.org/10.1147/rd.33.0210 .
    Paper not yet in RePEc: Add citation now
    
79. Schubert, E., Sander, J., Ester, M., Kriegel, H. P., & Xu, X. (2017). DBSCAN revisited, revisited: Why and how you should (still) use DBSCAN. ACM Transactions on Database Systems (TODS), 42(3), 1–21. https://doi.org/10.1145/3068335 .
    Paper not yet in RePEc: Add citation now
    
80. Shao, Z., Yuan, S., & Wang, Y. (2020). Institutional collaboration and competition in artificial intelligence. IEEE Access, 8, 69734–69741. https://doi.org/10.1109/ACCESS.2020.2986383 .
    Paper not yet in RePEc: Add citation now
    
81. Soni, N., & Ganatra, A. (2016). Aged (automatic generation of eps for DBSCAN). International Journal of Computer Science & Information Security, 14(5), 536.
    Paper not yet in RePEc: Add citation now
    
82. Statista. (2022). Estimated number of companies worldwide from 2000 to 2020. Statista. Accessed March 28, 2022. https://www.statista.com/statistics/1260686/global-companies/#statisticContainer .
    Paper not yet in RePEc: Add citation now
    

83. Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7%3c509::AID-SMJ882%3e3.0.CO;2-Z .

84. Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433–460. https://doi.org/10.1093/mind/LIX.236.433 .
    Paper not yet in RePEc: Add citation now
    
85. Uhr, L., & Vossler, C. (1961). A pattern recognition program that generates, evaluates, and adjusts its own operators. In: Papers presented at the May 9-11, 1961, Western Joint IRE-AIEE-ACM Computer Conference, 555–569. https://doi.org/10.1145/1460690.1460751 .
    Paper not yet in RePEc: Add citation now
    

86. Ullah, Z., & Arslan, A. (2022). R&D contribution to sustainable product attributes development: The complementarity of human capital. Sustainable Development, 30(5), 902–915. https://doi.org/10.1002/sd.2289 .

87. Wang, C., Chen, M. N., & Chang, C. H. (2020). The double-edged effect of knowledge search on innovation generations. European Journal of Innovation Management, 23(1), 156–176. https://doi.org/10.1108/EJIM-04-2018-0072 .
    Paper not yet in RePEc: Add citation now
    
88. Wang, H., Choi, J., Wan, G., & Dong, J. Q. (2016). Slack resources and the rent-generating potential of firm-specific knowledge. Journal of Management, 42(2), 500–523. https://doi.org/10.1177/0149206313484519 .
    Paper not yet in RePEc: Add citation now
    
89. Webb, A. (2019). The big nine: How the tech titans and their thinking machines could warp humanity. NY, PublicAffairs.
    Paper not yet in RePEc: Add citation now
    
90. Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36–45. https://doi.org/10.1145/365153.365168 .
    Paper not yet in RePEc: Add citation now
    
91. Yiu, L. D., Yeung, A. C., & Jong, A. P. (2020). Business intelligence systems and operational capability: An empirical analysis of high-tech sectors. Industrial Management & Data Systems, 120(6), 1195–1215. https://doi.org/10.1108/IMDS-12-2019-0659 .
    Paper not yet in RePEc: Add citation now
    
92. Zahra, S. A., Neubaum, D. O., & Hayton, J. (2020). What do we know about knowledge integration: Fusing micro-and macro-organizational perspectives. Academy of Management Annals, 14(1), 160–194. https://doi.org/10.5465/annals.2017.0093 .
    Paper not yet in RePEc: Add citation now
    
93. Zhao, B. (2017). Web scraping. Encyclopedia of big data, 1–3.
    Paper not yet in RePEc: Add citation now
    

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   In: Sustainability.
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12. Artificial intelligence, corporate information governance and ESG performance: Quasi-experimental evidence from China. (2025). Wang, Qunwei ; Li, Gaochao ; Zhou, Xiaoyong.
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    Full description at Econpapers || Download paper

14. Can artificial intelligence technology improve companies capacity for green innovation? Evidence from listed companies in China. (2025). Hu, Guoheng ; Guo, JU ; Shen, Fangbing ; Liu, Yingji ; Song, Yuegang.
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15. Can artificial intelligence empower energy enterprises to cope with climate policy uncertainty?. (2025). Zhang, Qun ; Zhong, Qian ; Yang, Jingjing.
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16. The effects of Artificial intelligence orientation on inefficient investment: Firm-level evidence from Chinas energy enterprises. (2025). Zhai, Minhan ; Tsai, Sang-Bing ; Wu, Wenqing.
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17. Does public data openness accelerate new quality productive forces? Evidence from China. (2025). Guo, Lixiang ; Zhong, Yuan ; Lai, Huisu ; Zhang, Liang.
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18. The impact of AI adoption on R&D productivity: Evidence from Chinese pharmaceutical manufacturing industry. (2025). Yuan, Yiming ; Wu, Yifan ; Song, Xueyin.
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19. The Over-Concentration of Innovation and Firm-Specific Knowledge in the Artificial Intelligence Industry. (2024). Lima, Jos Jorge ; Porto-Bellini, Carlo Gabriel ; Santos, Carlos Denner ; de Moura, Pedro Jcome.
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20. Forecasting volatility with machine learning and rough volatility: example from the crypto-winter. (2024). Zhou, Chao ; Rosenbaum, Mathieu ; Tang, Siu Hin.
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21. THE ROLE OF ARTIFICIAL INTELLIGENCE: INCREASING ECOMMERCE PURCHASE INTENTIONS IN INDONESIA. (2024). Qut, Rafika Indi ; Najwa, Nabila Az-Zahra ; Febrian, Angga.
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22. AI technologies affording the orchestration of ecosystem-based business models: the moderating role of AI knowledge spillover. (2024). Chin, Tachia ; Deveci, Muhammet ; Ayub, Muhammad Waleed ; Jin, Jiyang.
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27. Bringing employee learning to AI stress research: A moderated mediation model. (2024). Zhou, Qiwei ; Chen, Keyu ; Cheng, Shuang.
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29. What drives digital innovation cycles? Evidence from manufacturing enterprises in China. (2024). Li, Zhongshun ; Zou, Yukun ; Xie, Weihong ; Guo, Haizhen.
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30. The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification. (2024). Lin, Boqiang ; Xu, Chongchong.
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31. Impact of AI-focussed technologies on social and technical competencies for HR managers – A systematic review and research agenda. (2024). Sekar, Srinivasan ; Attri, Rekha ; Deepa, R ; Kumar, Jitender ; Malik, Ashish.
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32. Impacts of bitcoin on monetary system: Is Chinas bitcoin ban necessary?. (2024). Li, Xiao ; Wu, Ruoxi ; Wang, Chen.
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33. Revisiting the determinants of cryptocurrency excess return: Does scarcity matter?. (2024). Pham, Huy ; Thanh, Binh Nguyen ; Tiwari, Aviral Kumar ; Bui, Mai.
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34. The impact of human AI skills on organizational innovation: The moderating role of digital organizational culture. (2024). Luo, Xin ; An, Meng ; Lin, Jiabao.
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    Full description at Econpapers || Download paper

35. A comparative analysis of the price explosiveness in Bitcoin and forked coins. (2024). Baltas, Konstantinos ; Ren, Yi-Shuai ; Kong, Xiaolin ; Narayan, Seema ; Ma, Chaoqun.
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36. How does artificial intelligence promote renewable energy development? The role of climate finance. (2024). Nepal, Rabindra ; Dong, Kangyin ; Wang, Kun ; Zhao, Congyu.
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37. AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies. (2024). Ren, Xiaohang ; Wang, Zongrun ; Shi, Yukun ; Zhang, Taiyu.
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38. The automated sustainability auditor: Does artificial intelligence curtail greenwashing behavior in Chinese firms?. (2024). Huo, Chunhui ; Khan, Muhammad Kaleem ; Ammar, R M ; Maqsood, Umer Sahil.
    In: Business Strategy and the Environment.
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39. Forecasting Volatility with Machine Learning and Rough Volatility: Example from the Crypto-Winter. (2024). Tang, Siu Hin ; Rosenbaum, Mathieu ; Zhou, Chao.
    In: Papers.
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40. Disentangling the cultural evolution of ancient China: a digital humanities perspective. (2023). Duan, Siyu ; Su, QI ; Wang, Jun ; Yang, Hao.
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41. Use of Artificial Intelligence in Terms of Open Innovation Process and Management. (2023). Broek, Paulina ; Sira, Mariya ; Kuzior, Aleksandra.
    In: Sustainability.
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    Full description at Econpapers || Download paper

42. Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework. (2023). Al-Khatib, Ayman Wael.
    In: Technology in Society.
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    Full description at Econpapers || Download paper

43. Bitcoin transaction fees and the decentralization of Bitcoin mining pools. (2023). Li, Zhicheng ; Zhou, KE.
    In: Finance Research Letters.
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    Full description at Econpapers || Download paper

44. Intelligent transformation and sustainable innovation capability: Evidence from China. (2023). Wang, Wenzhi ; Ding, Tao ; Yang, Siying.
    In: Finance Research Letters.
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    Full description at Econpapers || Download paper

45. Determination of equilibrium transaction fees in the Bitcoin network: A rank-order contest. (2023). Webb, Robert I ; Ryu, Doojin ; Kim, Daehan.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:86:y:2023:i:c:s1057521923000030.

    Full description at Econpapers || Download paper

46. Trading under the proof‐of‐stake protocol – A continuous‐time control approach. (2023). Yao, David D ; Tang, Wenpin.
    In: Mathematical Finance.
    RePEc:bla:mathfi:v:33:y:2023:i:4:p:979-1004.

    Full description at Econpapers || Download paper

47. Crowdsearch. (2023). Pitsuwan, Fikri ; Gersbach, Hans ; Mamageishvili, Akaki.
    In: Papers.
    RePEc:arx:papers:2311.08532.

    Full description at Econpapers || Download paper

48. Trading under the Proof-of-Stake Protocol -- a Continuous-Time Control Approach. (2023). Tang, Wenpin ; Yao, David D.
    In: Papers.
    RePEc:arx:papers:2207.12581.

    Full description at Econpapers || Download paper

49. SoK: Blockchain Decentralization. (2023). Liu, Yulin ; Ma, Xinshi ; Zhang, Luyao.
    In: Papers.
    RePEc:arx:papers:2205.04256.

    Full description at Econpapers || Download paper

50. Stability of shares in the Proof of Stake Protocol -- Concentration and Phase Transitions. (2022). Tang, Wenpin.
    In: Papers.
    RePEc:arx:papers:2206.02227.

    Full description at Econpapers || Download paper

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