A negotiation chain is formed when multiple related negotiations are spread over multiple agents. In order to appropriately order and structure the negotiations occurring in the chain so as to optimize the expected utility, we present an extension to a singleagent concurrent negotiation framework. This work is aimed at semi-cooperative multi-agent systems, where each agent has its own goals and works to maximize its local utility; however, the performance of each individual agent is tightly related to other agent's cooperation and the system's overall performance. We introduce a pre-negotiation phase that allows agents to transfer meta-level information. Using this information, the agent can build a more accurate model of the negotiation in terms of modeling the relationship of flexibility and success probability. This more accurate model helps the agent in choosing a better negotiation solution in the global negotiation chain context. The agent can also use this information to allocate appropriate time for each negotiation, hence to find a good ordering of all related negotiations. The experimental data shows that these mechanisms improve the agents' and the system's overall performance significantly.