A Comprehensive Optimization Approach on Financial Resource Allocation in Scale-Ups

Abstract

Many startups try to pass the transition phase and begin the scale-up phase successfully. However, few are able to survive during this phase. One of the most important factors that can assist these startups in the scale-up phase is managing their financial resource. By doing so, the startups can reduce the consumption of these resources and, at the same time, increase their productivity. Cash flow is considered the pillar of the financial resources in the transition phase, and by managing the cash flow consumption, the probability of surviving in the transition phase will increase. This study aims to propose a model for the startup’s transition to allocate the optimal cash flow at the beginning of the scale-up phase. The components of the proposed optimization model are constructed based on the Mean-Variance framework, which was established by Harry Markowitz in 1952, to find the best composition of the cash flow allocation at each stage (financial period ). According to the cash flow statement, cash flows are separated into three categories: investing, operations, and financing activities. Finally, the model’s mechanism is boosted by adopting the principles of the behavioral theory of the firm to form a reinforcement learning model for resource allocation at the edge of the transition/scale-up phase. Therefore, by utilizing the proposed model during the transition phase, entrepreneurs may plan for a successful scale-up before wasting financial resources to reach sustainable growth. This paper introduces a model that offers critical insights and a novel framework, paving the way for future research in this emerging area; the model serves as a significant foundation, highlighting key opportunities and setting a new direction for impactful advancements in the field.