The growing tendency for suppliers to encroach on the retailers’ market has forced the retailers, being independent entities, to distort shared information to maintain their information superiority. Previous studies on asymmetric information assumed that retailers share information truthfully or that demand satisfies a two-point distribution, which does not always conform to the reality of the dual-channel supply chain. Considering the potential information leakage problem, this paper studied the optimal strategies of the participants and focused on the strategic information management of the dual-channel supply chain. By introducing the retailers’ adverse selection behavior, a sequential game model under general uncertain demand was established, which replaced the classic high-low demand model. The perfect Bayesian Nash equilibrium was characterized, which depended on stochastic demand disturbance, product heterogeneity, supply chain structure, and market investigation cost. The results showed that asymmetric information made the supply chain management inefficient. When the demand disturbance was within the threshold, the retailer distorted order quantity to maintain the information advantage under potential information leakage, and information acquisition was not always good for the retailer—in some cases due to adverse selection problems. A numerical example and a sensitivity analysis were done to validate the model. Our work provides participants in the dual-channel supply chain with decision-making support and direction for improving information management.

The deepening of electricity reform results in increasingly frequent auctions and the surge of generators, making it difficult to analyze generators’ behaviors. With the difficulties to find analytical market equilibriums, approximate equilibriums were obtained instead in previous studies by market simulations, where in some cases the results are strictly bound to the initial estimations and the results are chaotic. In this paper, a multi-unit power bidding model is proposed to reveal the bidding mechanism under clearing pricing rules by employing an auction approach, for which initial estimations are non-essential. Normalized bidding price is introduced to construct generators’ price-related bidding strategy. Nash equilibriums are derived depending on the marginal cost and the winning probability which are computed from bidding quantity, transmission cost and demand distribution. Furthermore, we propose a comparative analysis to explore the impact of uncertain elastic demand on the performance of the electricity market. The result indicates that, there exists market power among generators, which lead to social welfare decreases even under competitive conditions but elastic demand is an effective way to restrain generators’ market power. The feasibility of the models is verified by a case study. Our work provides decision support for generators and a direction for improving market efficiency.

The deepening of electricity reform results in increasingly frequent auctions and the surge of generators, it becomes difficult to analyze generators’ behaviors. Since it’s hard to find analytical market equilibriums, approximate equilibriums were obtained instead in previous studies by market simulations, which are strict to initial estimations and simulation results are chaotic in some cases. In this paper, a multi-unit power bidding model is proposed to reveal the bidding mechanism under clearing pricing rule by employing auction approach, for which initial estimations are non-essential. Normalized bidding price is introduced to construct generator's price-related bidding strategy. Nash equilibriums are derived depend on the marginal cost and the winning probability which are computed from bidding quantity, transmission cost and demand distribution. Furthermore, we propose a comparative analysis to explore the impact of uncertain elastic demand on the performance of the electricity market. The result indicates that, there exists market power among generators leading to social welfare decreases even under competitive conditions but elastic demand is an effective way to restrain generators’ market power. The feasibility of the models is verified by a case study. Our work provides decision support for generators and a direction for improving market efficiency.