We apply Multi-Agent Deep Reinforcement Learning (MADRL) to inventory management problems with multiple echelons and evaluate MADRL's performance to minimize the overall costs of a supply chain. We also examine whether the upfront-only information-sharing mechanism used in MADRL helps alleviate...

Trade credit is often extended by suppliers to buyers who often have easier access to external financing. Moreover, many buyers also delay paying their suppliers beyond the agreed due day. Prior literature attributes this phenomenon to quality assurance or buyer's abuse of market power. In this...

We consider a monopolistic firm selling two substitutable products to a stream of sequential arrivals whose purchase decisions can be influenced by earlier purchases. Before demand realizes, the firm faces a newsvendor problem for the two products with economies of scale in production for each....

We analyze a general model in which, at each echelon of the supply process, an arbitrary number of firms compete, offering one or multiple products to some or all of the firms at the next echelon, with firms at the most downstream echelon selling to the end consumer. At each echelon, the offered...

We consider a socially responsible firm that is concerned with its profit as well as consumer surplus, following the preference of pro-social executives or a government shareholder. Specifically, we study the decisions faced by a newsvendor whose objective is modeled as a weighted average of the...

Problem definition: This paper provides a theoretical investigation into the value and design of traceability-driven blockchains under different supply chain structures. Methodology/results: We use game theory to study the quality contracting equilibrium between one buyer and two suppliers and...