Risk prioritization model driven by success factor in the light of multicriteria decision making

Abstract: Some factors in the product development process can increase success. Evaluating the risks and success factors is necessary for a more successful product development process. Some inadequacies arise in classical risk assessment methods due to the subjective nature of likelihood and severity ratings. Different probability and impact values can give the same risk size. Due to these inadequacies, doubts about the accuracy of risk prioritization may arise. In this study, a new risk prioritization model is proposed to eliminate these doubts and to consider their contribution to the success of the process they affect while prioritizing the risks, with a detailed literature review and the support of the experts of the applied company, the risks affecting the product development process. The importance levels of risks and success factors were calculated using the analytical hierarchy process. With the proposed model, unlike the classical method, when calculating the risk size, the risk weight and the total score from the success factors are added to the likelihood and severity values of the risk. Thus, companies will obtain more detailed and objective results, considering success factors and risk importance levels, and use the resources they allocate for risk reduction activities more efficiently.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Risk prioritization model driven by success factor in the light of multicriteria decision making ; volume:20 ; number:1 ; year:2022 ; pages:759-776 ; extent:18
Open chemistry ; 20, Heft 1 (2022), 759-776 (gesamt 18)

Urheber
Tomak, Necmiye
Polat, Tulay Korkusuz

DOI
10.1515/chem-2022-0188
URN
urn:nbn:de:101:1-2022081714262251824843
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:23 MESZ

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Beteiligte

  • Tomak, Necmiye
  • Polat, Tulay Korkusuz

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