Identifying risk factors and their causal dependencies in startups: A Delphi-DEMATEL study in the context of Iranian venture capital

Introduction: Venture capital is one of the newest concepts that has attracted significant attention from investment professionals in recent years. A major challenge in venture capital is the risk analysis of knowledge-based companies and startups. A review of the literature indicates that valuation of knowledge-based companies and startups in the venture capital process is a difficult task due to their lack of historical records. One of the key factors that can enhance the accuracy of evaluations and, consequently, help venture capitalists select suitable investment opportunities is the identification and analysis of qualitative risks. The primary objectives of this study are, first, to identify key risk indicators based on previous studies and examine risk assessment models in venture capital firms, and second, to model the relationships between key risk indicators, which can aid in analyzing, understanding, and assessing the value of businesses within venture capitalists' portfolios.

Method: In this study, at the first step, the Delphi method was implemented by surveying 30 experts active in the venture capital field. Based on the results obtained from the first Delphi round, opinions falling outside the ±2σ range were identified, and some experts revised their responses. In the second Delphi round, internal correlation coefficients and Cronbach’s alpha were calculated to examine the consistency of the results, and the most critical key risk indicators were determined through the Delphi method. Subsequently, the DEMATEL method was used to quantitatively analyze the relationships between key risk indicators in investee companies.

Results and Discussion: According to the findings, after conducting two Delphi rounds, eight key indicators were finalized and approved by the experts. Based on Cronbach’s alpha and internal correlation coefficients, the consensus among experts was confirmed. The approved key risk indicators included financial risk, operational risk, market risk, legal and regulatory risk, strategic risk, credit risk, technological risk, and business future risk. In the second phase, which aimed to examine the relationships between key risk indicators, the DEMATEL results showed that financial risk, strategic risk, and operational risk had the highest influence coefficients on other key risk indicators, while business future risk, credit risk, and legal and regulatory risks had the highest dependence coefficients, meaning other key risk indicators most influenced them. This indicates that key risk indicators are highly interrelated.

Conclusion This study was conducted with the aim of identifying and examining the causal dependencies among key risk factors in startup companies within the Iranian venture capital space. Accordingly, the key risk factors were identified and confirmed using the Delphi method. Subsequently, the dependencies and causal relationships among the key risk factors were identified using the DEMATEL method. Based on the obtained results, it was determined that the key risk factors have influential and impactable interrelationships through the coefficients extracted from the DEMATEL output model, which were presented in the form of a causal diagram. Venture capital institutions can use this model to evaluate potential investee companies. The innovation of this research compared to previous studies lies in two dimensions: first, examining the relationships among key risk factors, and second, investigating the reverse relationships between key risk factors.