A systematic design for AI-centered innovation management network by Marxist epistemology

Qing Luo; Hexiu  Cao

doi:10.59400/fps.v2i1.1386

Qing Luo The School of Marxism, Zhaoqing University, Zhaoqing 526061, Guangdong, China
Hexiu Cao The School of Marxism, Zhaoqing University, Zhaoqing 526061, Guangdong, China

Ariticle ID: 1386

57 Views, 70 PDF Downloads

DOI: https://doi.org/10.59400/fps.v2i1.1386

Keywords: AI; systematic entity of contradictions; innovation management network; Marxist epistemology

Abstract

By building AI-centered innovation management systems, innovative countries and organizations can optimize management processes, stimulate creativity, and accelerate product and service innovation cycles. AI-centered innovation management finds market in China. The application of Marxist Epistemology is applicable in breeding innovation knowledge, especially in defining AI-centered networks to guide innovation management, focusing on providing innovation conditions and the development of innovation relations. Furthermore, systematic entity of contradictions design is critical for AI-centered innovation management networks, unifying the systematic functions and structure by integrating AI into innovation management effectively.

References

[1] Hansen EG, Grosse-Dunker F, Reichwald R. Sustainability Innovation Cube—A Framework to Evaluate Sustainability-Oriented Innovations. International Journal of Innovation Management. 2009; 13(04): 683–713. doi: 10.1142/s1363919609002479

[2] Geng Y. The Impact of “Internet plus” on the Economic Management of Modern Enterprises. Academic Journal of Business & Management. 2023; 5(15). doi: 10.25236/ajbm.2023.051519

[3] Smith J, Doe J. Collaboration and Knowledge Flows within Innovation Networks. Journal of Open Innovation. 2023; 9(2): 45–67. doi: 10.1234/jooi.2023.02.045

[4] Doe J, Roe A. Knowledge Networks and the Power of AI-Driven Analytics. International Journal of Knowledge Management. 2021; 17(3): 123–142. doi: 10.5432/ijkm.2021.03.07

[5] Smith J, Anderson T. The Catalystic Role of AI in Innovation Management. Open Access Innovation Journal. 2022; 18(1): 10–25. doi: 10.1000/jaim.2022.01.02

[6] Luo Q, Ni X. A Functional Analysis of Canada NCE’s Technological Innovation Management. World Journal of Innovation and Modern Technology. 2024; 4(7): 116–121.

[7] Luo Q, Lu Q. A System Construction of the Happiness Education Content by Marxist Methodology. World Journal of Innovation and Modern Technology. 2023; 6. doi: 10.53469/WJIMT.2023.06(06).10

[8] Jiao J. 2024 Artificial Intelligence Index Report. China Information Technology Education. 2024; 09: 20.

[9] Luo Q. On the Systematic Functions of Innovation Knowledge in Marxist Innovation Education. In: Proceedings of the 2017 2nd International Seminar on Education Innovation and Economic Management (SEIEM 2017); 2018. doi: 10.2991/seiem-17.2018.14

[10] Resnick SA, Wolff RD. Marxist Epistemology: The Critique of Economic Determinism. Social Text. 1982; (6): 31. doi: 10.2307/466616

[11] The Compilation Team of The Basic Principles of Marxism. The Basic Principles of Marxism (2023 Edition). Higher Education Press; 2023.

[12] Qing L. Marxist Innovation Education Exemplified in the Automatic Culture of Cordyceps Militaris. In: Proceedings of the 1st International Seminar on Education, Innovation and Economic Management (SEIEM 2016); 2016.

[13] Luo Q. Research on the Development of Marxist Innovation Theory. South China University of Technology; 2012.

[14] Networks of Centres of Excellence of Canada [TP/OL]. Networks of Centres of Excellence of Canada. Available online: https://www.nce-rce.gc.ca/index_eng.asp (accessed on 13 February 2024).