Improving management tools to increase the efficiency of using labor potential at the oil industry enterprises

Gafurova, V.M.; Zakharova, Ya.M.

doi:10.22394/2304-3369-2022-4-47-60

2022

DOI: 10.22394/2304-3369-2022-4-47-60

|View full text |Cite

Improving management tools to increase the efficiency of using labor potential at the oil industry enterprises

V.M. Gafurova¹,

Ya.M. Zakharova²

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Managing the staffing process of the Samara region oil industry

Tuponosova,

Livshits,

Golovanov

2023

Vestnik of Samara State Technical University. Technical Science

View full text Add to dashboard Cite

The problem of constructing dynamic models in the form of differential equations or transfer functions linking the performance indicators of the oil industry of the Samara region with the performance indicators of a regional university with a large institute of oil and gas technologies, considered as the controlling factors of staffing the oil industry, is solved. The input factors of the model are the normative performance indicators of the Samara State Technical University (SamSTU). The effectiveness of the regional oil cluster of the Samara region is assessed by indicators established by the Federal State Statistics Service (Rosstat), in particular, the amount of oil received for processing. For the algorithm of personnel management of the oil industry of the region, the problem of structural and parametric identification of the personnel training process at the university based on statistical characteristics as experimental data is solved. Using the library of typical linear models of management objects by N.S. Raibman, mathematical models of the process of staffing the industry in the form of transfer functions are constructed. Verification of mathematical models is carried out by comparison with official statistical data. On the basis of the obtained transfer functions, the synthesis of algorithms for automatic management of the personnel management process of the regulatory industry in the management decision support system is carried out.

show abstract

Managing the staffing process of the Samara region oil industry

Tuponosova,

Livshits,

Golovanov

2023

Vestnik of Samara State Technical University. Technical Science

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Improving management tools to increase the efficiency of using labor potential at the oil industry enterprises

Cited by 1 publication

References 6 publications

Managing the staffing process of the Samara region oil industry

Managing the staffing process of the Samara region oil industry

Contact Info

Product

Resources

About