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Self-serving assets (SSAs) are a new interpretation of the intelligent product technology, set to transform product lifecycle management through automation. SSAs are engineering assets that autonomously monitor their health and expiry dates, search for suppliers, and negotiate with them, while they are still in use by the customer. The concept enables more timely and transparent supplier decision making while eliminating central database transactions and tedious manual effort. Autonomous self-interested agents that act on behalf of their stakeholders naturally give rise to an allocation problem, under the assumption of private information held by trade parties and capacity constrained suppliers providing imperfectly substitutable goods (ISGs). In this paper, we develop and compare three automated competition mechanisms, constructed as iterative games, and test them in the context of the aerospace service supply chain. The competition mechanisms include a prioritized selection mechanism, extended Vickrey, and reverse Dutch auctions. Our context drives us to seek mechanisms that will not only perform well in terms of economic theory, but also in terms of computational performance. Key findings are that extended Vickrey auctions can handle multiple criteria and provide higher market efficiency at lower computational cost, especially in small to medium markets. As scalability is an issue in large markets, the use of auctions is recommended only for complex high value assets or under uncertain market scenarios. As business-to-business (B2B) environments are becoming the norm for many global companies, our study aims to be exemplary to those who would like to implement automated auction mechanisms in highly complex environments.