Internal control of enterprise green production and legal protection of intellectual property based on organizational behavior theory under artificial intelligence

Abstract

With the continuous development of artificial intelligence (AI) and deep learning technology, technology-based enterprises emerge one after another, but the internal management mode and green production of enterprises cannot keep up with the pace of development. The imperfection of the system has caused different degrees of negative impact on various enterprises. In order to realize the promotion and guidance of organizational behavior theory to the practice of enterprise internal control, and better internal management of enterprise intellectual property rights, firstly, the concept of organizational behavior is introduced in detail, and the influence of organizational behavior theory on the development of enterprise internal control is listed in different stages. Secondly, based on the theory of organizational behavior, meanwhile, the application of AI and deep learning in the internal control of enterprise green production is deeply analyzed. This paper analyzes the internal environment and control management of enterprises in detail, puts forward a conceptual model of internal control management for green innovation in small and medium-sized technological enterprises, and provides effective measures on how to strengthen the legal protection of intellectual property between enterprises. Finally, the management implementation simulation of the proposed model is carried out, and the simulation results are summarized. The results show that: first, the implementation of the concept model of green innovation internal control management can promote the development of enterprises in all aspects. When the second green innovation internal control reaches 10 weeks, the green innovation performance of the enterprise is about 25,000, and it has reached 150,000 by the 20th week, indicating that the accumulation of green innovation performance generated by different government internal control intensity gradually increases with time. Meanwhile, the green innovation performance generated by high-intensity government internal control is faster than that generated by low-intensity government internal control.

Keywords

artificial intelligence deep learning organizational behavior green production intellectual property legal protection management inside enterprises

Get full access to this article

View all access options for this article.

References

Long

. Green development behavior and performance of industrial enterprises based on grounded theory study: evidence from China. Sustainability 2019; 11(15): 4133.

Stewart

Courtright

Manz

. Self-leadership: a paradoxical core of organizational behavior. Annu Rev Organ Psych 2019; 6: 47–67.

Cui

, et al. Organizational behavior in megaprojects: integrative review and directions for future research. J Manag Eng 2019; 35(4): 04019009.

Nyberg

Cragun

Schepker

. Chief executive officer succession and board decision making: review and suggestions for advancing industrial and organizational psychology, human resources management, and organizational behavior research. Annu Rev Organ Psych 2021; 8: 173–198.

Wang

Liu

. Internal control and enterprise green innovation. Energies 2022; 15(6): 2193.

Yang

Qin

Gan

, et al. Internal control quality, enterprise environmental protection investment and finance performance: an empirical study of China’s a-share heavy pollution industry. Int J Environ Res Publ Health 2020; 17(17): 6082.

Gan

Yang

Liu

, et al. The level of regional economic development, green image, and enterprise environmental protection investment: empirical evidence from China. Math Probl Eng 2021; 2021: 1–12.

, et al. Can low-carbon technological innovation truly improve enterprise performance? The case of Chinese manufacturing companies. J Clean Prod 2021; 293: 125949.

Pražák

Kovárník

. Nonlinear phenomena in Cournot duopoly model. Systems 2018; 6(3): 30.

10.

Auriol

Biancini

Paillacar

. Universal intellectual property rights: too much of a good thing? Int J Ind Organ 2019; 65: 51–81.

11.

Wang

Xue

Wang

, et al. Participation mode and production efficiency enhancement mechanism of Geographical Indication products in rural areas: a meta-frontier analysis. Phys Chem Earth, Parts A/B/C 2021; 121: 102982.

12.

Haenlein

Kaplan

. A brief history of artificial intelligence: on the past, present, and future of artificial intelligence. Calif Manag Rev 2019; 61(4): 5–14.

13.

Han

Shiwakoti

Jarvis

, et al. Accounting and auditing with blockchain technology and artificial Intelligence: a literature review. Int J Account Inf Syst 2023; 48: 100598.

14.

Yang

. Research on the application of big data intelligence technology in the optimization of accounts receivable management of E-commerce enterprises under the financial sharing mode. Int J Comput Intell Syst 2023; 16(1): 121.

15.

Urinov

. Review of the trends of management: corporate culture or organizational behavior. Архив научных исследований 2020; 33(1).

16.

Fehr

Welsh

Yam

, et al. The role of moral decoupling in the causes and consequences of unethical pro-organizational behavior. Organ Behav Hum Decis Process 2019; 153: 27–40.

17.

Urinov

. Theoretical aspects of organizational behavior and corporate culture. Econ Innov Tech 2020; 2020(2): 7.

18.

Zhang

Han

. Paradoxical leader behavior in long-term corporate development: antecedents and consequences. Organ Behav Hum Decis Process 2019; 155: 42–54.

19.

Wang

Long

. Research on the impact mechanism of heterogeneous environmental regulation on enterprise green technology innovation. J Environ Manag 2022; 322: 116127.

20.

Raza

Farrukh

Iqbal

, et al. Corporate social responsibility and employees’ voluntary pro-environmental behavior: the role of organizational pride and employee engagement. Corp Soc Responsib Environ Manag 2021; 28(3): 1104–1116.

21.

May

AYC

Hao

Carter

. Intertwining corporate social responsibility, employee green behavior, and environmental sustainability: the mediation effect of organizational trust and organizational identity. Econ Manag Financ Mark 2021; 16(2): 32–61.

22.

Simpson

Robertson

White

. How co-creation increases employee corporate social responsibility and organizational engagement: the moderating role of self-construal. J Bus Ethics 2020; 166(2): 331–350.

23.

Arefieva

Polous

Arefiev

, et al. Managing sustainable development by human capital reproduction in the system of company’s organizational behavior. IOP Conf Ser Earth Environ Sci 2021; 628(1): 012039.

24.

Gamidullaeva

Vasin

Wise

. Increasing small-and medium-enterprise contribution to local and regional economic growth by assessing the institutional environment. J Small Bus Enterprise Dev 2020; 20(15): 142–158.

25.

Selamat

Ran

. The mediating effect of organizational citizenship behavior on the organizational justice and organizational performance in small and medium-sized enterprise of China. Int J Bus Manag 2019; 14(173): 10–5539.

26.

Lemańska-Majdzik

. Actions for knowledge integration capability in building an innovative enterprise: organizational perspective. Euro Conf Know Manage 2022; 23(2): 750–756.

27.

Zusman

. Participants’ ethical attitudes and organizational structure and performance: application to the cooperative enterprise. Agricultural cooperatives in transition. Milton Park: Routledge, 2021, pp. 23–54.

28.

Shao

. Interaction effect of strategic leadership behaviors and organizational culture on IS-Business strategic alignment and enterprise systems assimilation. Int J Inf Manag 2019; 44: 96–108.

29.

Wang

Zeng

. Behavior decision of top management team and enterprise green technology innovation. J Clean Prod 2022; 367: 133120.

30.

Wang

Xiang

Meng

, et al. External corporate social responsibility promotes employees’ unethical pro-organizational behavior: an attribution perspective. Curr Psychol 2022; 42: 1–15.

31.

Jnr

. Examining the role of green IT/IS innovation in collaborative enterprise-implications in an emerging economy. Technol Soc 2020; 62: 101301.

32.

Chan

Chen

Liu

. The linear and non-linear effects of internal control and its five components on corporate innovation: evidence from Chinese firms using the COSO framework. Eur Account Rev 2021; 30(4): 733–765.

33.

Kharytonov

Kharytonova

Tkalych

, et al. Intellectual property law in the field of sports: specifics of manifestations and features of legal regulation. Cuestiones Políticas 2021; 39(69): 530.

34.

Chu

Gao

. Intellectual property protection and creative enterprises’ investment efficiency: alleviating financing constraints or inhibiting agency problem? Asia-Pac J Account E 2019; 26(6): 747–766.

35.

Yang

. The correlation between enterprise internal control quality and research and development investment intensity. Comput Intell Neurosci 2022; 2022: 1788142.

36.

Song

Chen

. Research on enterprise internal control risk based on Kangmei pharmaceutical event. In: Proceedings of the 2020 4th international conference on management engineering, software engineering and service sciences, Wuhan China, 17–19 January 2020, pp. 184–189.

37.

Zufarova

. Development of institutional models of intellectual property rights protection in foreign countries. Am J Polit Sci Law Cri 2022; 4(03): 31–40.