A Systems-Based Framework for Startup Risk Management: Integrating Axiomatic Design, Qualitative Research Synthesis, and Real Options Analysis

(1) Background: Startups operate in highly uncertain environments where ineffective risk management increases the likelihood of failure. While several risk management frameworks have been developed specifically for startups and SMEs, they typically lack systematic validation and quantitative decision support under uncertainty. General standards such as ISO 31000, COSO ERM, and PMBOK, in turn, are not designed specifically for the startup context. This study develops and structurally assesses an integrated, systems-oriented risk management framework that adapts established risk management processes to the specific characteristics of startups. (2) Methods: The framework was developed through a systematic literature review and examined using Axiomatic Design and Qualitative Research Synthesis. Structural consistency was assessed through the Independence Axiom, while agreement with the proposed classification was evaluated using expert judgments and inter-rater reliability measures (Cohen’s κ, ARI, and NMI). Real Options Analysis was incorporated into the quantitative risk analysis stage to evaluate alternative risk response strategies. (3) Results: The proposed framework comprises seven interconnected risk management processes. The Axiomatic Design matrix confirmed its structural consistency, and expert evaluation demonstrated substantial to almost perfect agreement (κ = 0.634–0.847, ARI = 0.609–0.846, NMI = 0.689–0.889). A single case study of a software startup provided initial evidence of the framework’s practical applicability and illustrated the identification of a preferred risk response strategy. (4) Conclusions: The proposed framework structurally assessed and conceptually examined a systematic approach to startup risk management by integrating structured risk management processes with quantitative decision support under uncertainty.