Research output: Contribution to journal › Article › peer-review
Метод поддержки принятия решений по управлению научными исследованиями и разработками на основе комплекса моделей. / Стоянова, Ольга Владимировна; Москалева, Валерия Дмитриевна.
In: ПРИКЛАДНАЯ ИНФОРМАТИКА, Vol. 17, No. 3, 31.05.2022, p. 52-69.Research output: Contribution to journal › Article › peer-review
}
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