Resource allocation plays a critical role in the strategic, tactical, and operational planning of the supply chain. The study focuses on aspects of resource allocation in the case of pure players, manufacturers, and Clicks & Mortars that have launched online sales. These e-retailers offer a wide selection of customized services and so need an efficient management on every level and process. The goal of the research was to explore a concrete approach to improve customer satisfaction, reduce costs and risks and to maintain the benefits of e-retailers and of its collaborators. Our contribution is a decision support system and a tool to improve operational resources allocation in B2C supply chains. Hence, we started by modeling operations and the different scenarios. Then we introduced an optimization model founded on the analysis of resource allocation in B2C supply chains and applicable on any B2C e-retailer. It helps in choosing the most optimal resources for each order. The model is based on a multi-objective optimization approach that takes into consideration the collaboration of resources throughout the supply chain operations process including dynamic costs and collaborator capabilities as well as associated risks and the quality of delivered services.

This paper proposes a novel form of supplier selection involving the supply chain dyad as the buyer and the suppliers as sellers. The main proposed contribution is a multi-attribute decision hybrid protocol for supplier selection based on collaboration and negotiation, adapted to dyadic collaboration in a supply chain context. Suppliers and the purchasing dyad can reach an agreement on the details of the products simultaneously and exploit the preferences of the customer dyadic partner to enlarge the criteria choices of the products. For this, the proposed protocol combines a one-to-one bilateral dyadic collaboration protocol inside the purchasing dyad along with a one-to-many multi-bilateral bargaining protocol between the purchasing dyad and suppliers. Illustrative multi-agent simulation experiments were carried out to prove the effectiveness of the proposed protocol. The protocol implementation shows better negotiation results than the classic supplier selection process, along with expected higher customer partner satisfaction and a more embedded dyadic relationship. .