2692-2967ISSN (Online)
2770-0216ISSN (Print)
According to the results of the econometric analysis, a 1% increase in the output of high-tech and science-intensive industries leads to a 0.137655% increase in the GDP, and a 1% increase in the output of high-tech and science-intensive industries is 0.024673% of the GDP. , a 1% increase in high-tech production leads to a 0.030797% increase in GDP. In the future, the growth rate of the gross domestic product in Uzbekistan will have a trend of higher growth. Until 2030, the annual growth rate will be 5.1 percent, which will lead to an increase in the volume of production of the gross domestic product (1.051 10 = 1.64) by about 1.65 times.
Read MoreDoi: https://doi.org/10.54216/AJBOR.090201
Vol. 9 Issue. 2 PP. 08-15, (2023)
This article provides an overview of information about the digital economy and how it affects the development of society as well as many areas of life in the modern world. Digitalization is considered as a factor in the development of the economy and improving the quality of life of the population. It also talks about the advantages of the digital economy, as a manifestation of the growth of the socio-economic effect in the implementation of digital technologies.
Read MoreDoi: https://doi.org/10.54216/AJBOR.090202
Vol. 9 Issue. 2 PP. 16-21, (2023)
The article explores the possibilities of using methods for analyzing the effectiveness of the use of intellectual property objects in the course of an audit. The article formulates proposals on the use of methods for analyzing the effectiveness of the use of intellectual property objects at the stages of the audit. An exemplary form of an intellectual property audit program using analytical operations is also proposed. The proposed approach to the implementation of a comprehensive analysis of the effectiveness of the use of intellectual property objects during the audit makes a certain contribution to the development of the audit methodology.
Read MoreDoi: https://doi.org/10.54216/AJBOR.090203
Vol. 9 Issue. 2 PP. 22-30, (2023)
In construction industry Occupational Health and Safety (OHS) involves the development and implementation of measures to ensure the socio-economic efficiency of enterprises. By creating a safe work culture and environment for workers OHS is considered to raise human dignity in workplaces. As human capital develops to a high level it combines legal, social-economic, organizational-technical, sanitary-hygiene, and treatment-prophylaxis at workplaces. Current research states the human capital development approach from three aspects: health (state of health, occupational health, sanitation, and hygiene); knowledge (education, like-mindedness, mentoring, training), and professional skills (esteem, skills, skills, professional development) from the digitalization prospectives. The econometric methods involved are Latent Class Analysis for accounting the cross-sectional relationship and post estimation concerns in the data. The results denote the hypothesis were proven OHS investment has a positive effect on work personality in the construction industry and Organizational performance has a positive effect at work_experience and flexibility of the workers in the construction industry. Besides, another finding in this study shows that work effectiveness has a positive effect on OHS_investment and flexibility in the construction industry. Therefore, these findings necessitate the human capital in the context of health and safety management in construction industry. More importantly, human capital development should be prioritized for transforming the curse of the natural resources into blessing for these nations. Therefore, we recommend that the researcher and policymakers should promote human capital development regulation in construction sector from the digitaliztion prospective.
Read MoreDoi: https://doi.org/10.54216/AJBOR.090204
Vol. 9 Issue. 2 PP. 31-40, (2023)
Inventory management (InvM) is a critical aspect of supply chain management (SCM) and optimizing inventory levels can lead to significant cost savings and improved customer satisfaction. Hence, business organizations have recently worked to increase the value of their operations by utilizing modern and digital technologies as industry 4.0 (Ind 4.0). In the era of Ind 4.0, the technologies as Internet of Every Things (IoET), AI, BDA…etc. Recognizing the significance of InvM in a supply chain (SC), motivated us to volunteer technologies of Ind 4.0 as machine learning (ML) techniques to boosting Decision Making (DM) process to optimize InvM. Subsequently, this study is constructed for providing an intelligent Decision Support ML framework for automating the process of optimizing inventory management. Our constructed framework ensembles powerful ML prediction algorithms for inventory management, such as Artificial Neural Networks (ANNs), Random Forest (RF), and Support Vector Machine (SVM) for building robust sales regressors. The extensive experimentations on a case study of Walmart suggested that the proposed system has the potential to transform inventory management and improve supply chain performance, but further research is needed to address the challenges of data availability and quality.
Read MoreDoi: https://doi.org/10.54216/AJBOR.090205
Vol. 9 Issue. 2 PP. 41-49, (2023)