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@article{bf64ab75b93742a7812e9b57391d9737,
title = "Метод поддержки принятия решений по управлению научными исследованиями и разработками на основе комплекса моделей",
abstract = "Research and development (R&D) ensure stable functioning and forms the innovative potential of most companies in the production sector. Ineffective R&D management leads to the fact that many initiated projects go beyond planned deadlines and budgets, and much of the intermediate R&D results are not completed. The complexity of R&D management is associated with high information uncertainty regarding the performance of R&D and the productivity of employees. The paper considers a multi-model method of decision support for R&D management in companies. To reduce information uncertainty in solving various management problems it is proposed to use an ontological model of intellectual capital of the company, simulation models of R&D processes and individual stages, fuzzy logic models to obtain integral assessments of management decisions. The method provides a basis for making decisions on the possibility and expediency of using previously obtained R&D results (scientific and technological reserve); on the feasibility of the proposed project based on the assessment of its feasibility; on the project organization (volume-calendar planning); on the allocation of resources to tasks; on the incentives for performers; on the planning of activities for additional training and organization of information support. The paper provides a general description of the method, as well as an example of its use to support decision-making on the feasibility of an R&D project based on its assessment. Two structures for organizing the R&D process in a manufacturing company are considered as alternatives. After selecting the best structure, the impact of staffing quality on the integral feasibility assessment is evaluated.",
author = "Стоянова, {Ольга Владимировна} and Москалева, {Валерия Дмитриевна}",
year = "2022",
month = may,
day = "31",
doi = "10.37791/2687-0649-2022-17-3-16-33",
language = "русский",
volume = "17",
pages = "52--69",
journal = "ПРИКЛАДНАЯ ИНФОРМАТИКА",
issn = "1993-8314",
publisher = "СИНЕРГИЯ",
number = "3",

}

RIS

TY - JOUR

T1 - Метод поддержки принятия решений по управлению научными исследованиями и разработками на основе комплекса моделей

AU - Стоянова, Ольга Владимировна

AU - Москалева, Валерия Дмитриевна

PY - 2022/5/31

Y1 - 2022/5/31

N2 - Research and development (R&D) ensure stable functioning and forms the innovative potential of most companies in the production sector. Ineffective R&D management leads to the fact that many initiated projects go beyond planned deadlines and budgets, and much of the intermediate R&D results are not completed. The complexity of R&D management is associated with high information uncertainty regarding the performance of R&D and the productivity of employees. The paper considers a multi-model method of decision support for R&D management in companies. To reduce information uncertainty in solving various management problems it is proposed to use an ontological model of intellectual capital of the company, simulation models of R&D processes and individual stages, fuzzy logic models to obtain integral assessments of management decisions. The method provides a basis for making decisions on the possibility and expediency of using previously obtained R&D results (scientific and technological reserve); on the feasibility of the proposed project based on the assessment of its feasibility; on the project organization (volume-calendar planning); on the allocation of resources to tasks; on the incentives for performers; on the planning of activities for additional training and organization of information support. The paper provides a general description of the method, as well as an example of its use to support decision-making on the feasibility of an R&D project based on its assessment. Two structures for organizing the R&D process in a manufacturing company are considered as alternatives. After selecting the best structure, the impact of staffing quality on the integral feasibility assessment is evaluated.

AB - Research and development (R&D) ensure stable functioning and forms the innovative potential of most companies in the production sector. Ineffective R&D management leads to the fact that many initiated projects go beyond planned deadlines and budgets, and much of the intermediate R&D results are not completed. The complexity of R&D management is associated with high information uncertainty regarding the performance of R&D and the productivity of employees. The paper considers a multi-model method of decision support for R&D management in companies. To reduce information uncertainty in solving various management problems it is proposed to use an ontological model of intellectual capital of the company, simulation models of R&D processes and individual stages, fuzzy logic models to obtain integral assessments of management decisions. The method provides a basis for making decisions on the possibility and expediency of using previously obtained R&D results (scientific and technological reserve); on the feasibility of the proposed project based on the assessment of its feasibility; on the project organization (volume-calendar planning); on the allocation of resources to tasks; on the incentives for performers; on the planning of activities for additional training and organization of information support. The paper provides a general description of the method, as well as an example of its use to support decision-making on the feasibility of an R&D project based on its assessment. Two structures for organizing the R&D process in a manufacturing company are considered as alternatives. After selecting the best structure, the impact of staffing quality on the integral feasibility assessment is evaluated.

UR - https://www.mendeley.com/catalogue/4b88cd9f-979d-33a3-ba1f-209e19d12a86/

U2 - 10.37791/2687-0649-2022-17-3-16-33

DO - 10.37791/2687-0649-2022-17-3-16-33

M3 - статья

VL - 17

SP - 52

EP - 69

JO - ПРИКЛАДНАЯ ИНФОРМАТИКА

JF - ПРИКЛАДНАЯ ИНФОРМАТИКА

SN - 1993-8314

IS - 3

ER -

ID: 98874918