A Discrete Scenario-Based Robust Network Data Envelopment Analysis for Evaluating Startups Value Chain Efficiency Based on the Weakest Link Theory

Startups have always played a vital role in driving innovation, fostering economic growth, and creating new employment opportunities, making them an essential catalyst for societal progress and development. An approach is proposed for evaluating startups’ efficiency considering the different stages of the value chain and the inherent uncertainty in a business environment. To reach this goal, a robust network data envelopment analysis (DEA) is developed for a three-stage structure, making it possible to tackle uncertainty and enable the handling of multistage processes. The proposed model formulates the overall efficiency of the startup’s value chain considering Weibull weakest link theory and employs the Maximin function to maximize the minimum (weakest) efficiency of value chain stages. The robust counterpart of the model is then formulated using a scenario-based approach. To demonstrate the applicability of the proposed method, the model is applied to a case study involving information and communication technology (ICT) startups in Iran. Three economic recession, stability, and growth scenarios are considered, and the results are presented. Sensitivity analysis is also performed considering different probabilities in each scenario. This study makes a significant contribution to the field of efficiency evaluation by (1) introducing a novel robust three-stage network data envelopment analysis model for evaluating the efficiency of startups’ value chains and (2) addressing the challenges posed by uncertain conditions in efficiency analysis