Abstract
Supported by a third-party capacity sharing platform, manufacturers can share capacities with others to match the rapidly changing demand. Both the capacity requestor and the capacity provider can choose to seek or wait for matches, forming different trading strategies (capacity- and demand-driven strategies). Based on the game and chaos theories, this paper analyzes the preference of the capacity provider, the capacity requestor, and the capacity platform operator on different trading strategies from the aspects of profitability and stability. It finds that the platform operator values stability much more than profitability, although the latter may reach higher optimal expected profits. The preference of each supply chain member is influenced by the production cost, potential market size, and the limited capacity of the capacity requestor. A stable system can result in higher long-run profits than a profitable system. We further propose the all-win situation for the capacity provider, capacity requestor, and platform operator.
Highlights
Manufacturing capacity sharing can efficiently solve the problem of mismatch between demand and supply
We focus on the decision-making process in a capacity sharing supply chain, investigating which trading strategy is preferable for the platform operator, the capacity requestor, and the capacity provider, respectively
When taking the bounded rationality of the platform operator into account, if the platform operator is bounded rational and highlights the stability of the system, it is wise to recommend the firms with a relatively high cost to accept demand-driven strategy (DD) trading strategy. e analysis has shown that the stability performance will be put as the first consideration since the trading strategy with better stability can result in higher long-run profits. erefore, we propose the decision-making principle for the platform operator to provide insights for its recommendation and analyze the best choice in different situations
Summary
Manufacturing capacity sharing can efficiently solve the problem of mismatch between demand and supply. We focus on the decision-making process in a capacity sharing supply chain, investigating which trading strategy is preferable for the platform operator, the capacity requestor, and the capacity provider, respectively. This paper investigates the profitability performance and the stability performance of the capacity- and demand-driven trading strategies in the manufacturing capacity sharing platform. We study how the platform operator sets a trading strategy for the manufacturers making different products with different production costs considering the profitability and stability of the strategies and how the decisions affect the choices of the manufacturers. Chaos theory shows the potential to be a tool that can be instrumental in helping explain why unpredictability occurs within nonlinear systems This may assist managers in making better supply chain management decisions, benefiting organizations and customers by simultaneously enhancing cost-effectiveness and improving customer service levels [21]. Stability means that the optimal equilibrium solutions and the corresponding profits can be obtained after the decision adjustment based on a specific rule
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