Application of the Hierarchy Analysis Method When Choosing Laboratory Information Management Systems

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Abstract

The article is devoted to the application of a modified hierarchy analysis method for decision- making when choosing laboratory information management systems. A possible set of selection criteria that can be universal for most laboratories is discussed and questions of the relative significance of the criteria are considered. In the developed methodology, a computer statistical modeling was used to quantify the reliability of the decision being made.

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About the authors

I. V. Dyumaeva

IndaSoft LLC

Author for correspondence.
Email: irina.dyumaeva@indusoft.ru

доктор химических наук

 

Russian Federation, Moscow

A. V. Kurochkin

ОУП ВО «Академия труда и социальных отношений»

Email: avkur2@yandex.ru

кандидат физико-математических наук

Russian Federation, Москва

References

  1. Burdeinyi A. A., Dyumaeva I. V. What Should be a Modern Laboratory Information Management System? Analytics. 2022;12(6):432–438.
  2. Khalin V. G. et al. Decision support systems: textbook and workshop for universities / edited by V. G. Khalin, G. V. Chernova. M.: Yurayt Publishing House, 2023. 494 p.
  3. Saati T. L. Making decisions. Hierarchy analysis method. M.: Radio and communication publ., 1993. 320 p.
  4. Gvozdkova I. A., Kurochkin A. V., Martsvaladze G. V. Computer-mathematical modeling of socially oriented personnel solutions. Labour and Social Relations Journal. 2018; 6:28–44.
  5. Gvozdkova I. A., Kurochkin A. V. The reliability evaluation of computer-mathematical models of optimization of personnel solutions by statistical methods. Labour and Social Relations Journal. 2019; 2: 93–109.
  6. Temnikova D. S. Development of a forecast of economic results of an enterprise’s activity using the hierarchy analysis method. Russian Entrepreneurship. 2014; 7: 83–85.
  7. Vyskub V. G. On the issue of automation of scientific and technical expertise method of analytical hierarchy. Innovation and expertise. 2022; 2: 55–63.
  8. Volkov V. I. Methodology of expert evaluation of innovative projects. Bulletin of the Bauman Moscow State Technical University. Ser. Mechanical engineering. 2004;3: 100–113.
  9. Abakarov A. Sh., Sushkov Yu. A. MPRIORITY 1.0 decision support software system. URL: https://cyberleninka.ru/article/n/programmnaya-sistema-podderzhki-prinyatiya-resheniy-mpriority-1–0/viewer (date of access: 1.11.2023)
  10. Decision support system Choice – Text: electronic // CIRITAS: [website]. http://ciritas.ru/product.php?id=10 (date of access: 1.11.2023)
  11. Sobol I. M. Numerical Monte Carlo methods. M.: Nauka. 1973. 312 p.
  12. Janeková J. Monte Carlo simulation – risk analysis tool of investment projects. Transfer inovácií. 2015;32:261–263. URL: https://www.sjf.tuke.sk/transferinovacii/pages/archiv/transfer/32–2015/pdf/261–263.pdf (date of access: 1.11.2023)

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Copyright (c) 2023 Dyumaeva I.V., Kurochkin A.V.

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