Statistical analysis of e-commerce delivery demand modeling framework

Abstract

The e-commerce delivery demand has developed quickly in the past two decades and such trend has intensified tremendously due to the continuing coronavirus pandemic. Given the situation, the requirement for forecasting e-commerce delivery demand and evaluating applicable logistics solutions is expanding. However, the present simulation models for e-commerce delivery demand are still limited and do not address the delivery alternatives and their properties that customers experience on ecommerce order placements. The inability to construct and monitor agent systems that have been deployed throughout a network is one of the primary challenges, along with ensuring that software agents are installed in a manner that is both secure and efficient. The field of multi-agent technology is one of the areas of information and communication technology that is advancing at one of the quickest rates. Virtually every day, new agent-based services, products, and applications are being developed. The coordination, control, and simulation of the architecture of decision support systems that are used in e-commerce are all performed with the use of an agent-based simulation model. The design that was recommended improves the decision support systems that are already in place and achieves a competitive advantage.