We study a vertical agricultural supply chain with a farmer cooperative who decides his agricultural product selling price and a social enterprise who makes her order quantity decision and resells products to the end market. The effect of market information and agricultural advice provided by the government on the system's outcomes is investigated. A two-stage game model is proposed to characterise this vertical relationship. The equilibrium decisions of the two players under different government supporting cases are derived. We contrast the system outcomes under different cases and conduct comparative analysis. It is found that (1) the farmer cooperative's profit increases if the government provides market information to him and the social enterprise at the same time; (2) the agricultural advice provided by the government can increase the benefits to each participant in the supply chain; (3) to maximise the total supply chain profit as well as its sustainability, the government may choose to provide market information to the social enterprise only; (4) when the wholesale price is intervened by the government or exogenously provided, the social enterprise's social responsibility concern can increase both the farmer cooperative's profit and the social enterprise's social payoff.

This paper studies the competition and cooperation problem in a regional port system with two container terminals. Two game models are proposed to analyze the decisions of container terminal operators and the local government, respectively. We consider the emission tax, container terminal’s service level and service price and derive the optimal decisions of the players. From the numerical analysis results, we find that in the regional port system, (1) a relatively developed container terminal is a good choice for consumers who prefer high-quality and efficient service, while those whose main concern is price can choose a developing container terminal; (2) for the benefit of all players, cleaner fuels should be used to decrease the proportion of unit pollution emission; (3) if social welfare is more emphasized than environmental protection, competition between the two container terminals is preferred, otherwise, cooperation is more beneficial.

Purpose: This paper aims to study the pricing problems on the two-sided market for cases of monopoly and duopoly competition, specifically investigating the impact of platform service quality on the market. Theoretical analysis and computational studies are conducted to investigate the impact of different parameters on the system outcomes. Design/methodology/approach: Mathematical formulations are proposed for cases of monopoly and duopoly competition. For monopolistic market, the optimal pricing and service quality strategies are obtained using mathematical programming method. For duopolistic market, the equilibrium outcomes are derived by game theory. Sensitivity analysis and numerical studies are also adopted to investigate the impact of different parameters. Findings: For monopolistic market, the platform will provide a low service quality when the service cost parameter is large. However, when the cost parameter is small, the platform provides a higher service quality and higher registration prices. Furthermore, the sum of the optimal prices is proportional to the service quality and inversely proportional to the user price sensitivity. For duopolistic market, the competitive equilibrium prices exist under a certain condition. The determinants of equilibrium prices are the gap between the service qualities of two platforms and the cross-group externalities. Originality/value: For monopolistic market, this paper specifies the role of platform service quality in determining the platform’s pricing strategy. For duopolistic market, this paper presents a market sharing mechanism between two platforms and explores the equilibrium pricing strategies for platforms with different service quality level.

This paper studies a supply chain network design model with price competition. The supply chain provides multiple products for a market area in multiple periods. The model considers the location of manufacturers and retailers and assumes a probabilistic customer behavior based on an attraction function depending on both the location and the quality of the retailers. We aim to design the supply chain under the capacity constraint and maximize the supply chain profit in the competitive environment. The problem is formulated as a mixed integer nonlinear programming model. To solve the problem, we propose two heuristic algorithms—Simulated Annealing Search (SA) and Particle Swarm Optimization (PSO)—and numerically demonstrate the effectiveness of the proposed algorithms. Through the sensitivity analysis, we give some management insights.