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This paper evaluates the optimal pricing for two Internet service providers and two network providers; all are competing on price, which is based on quality. To find the optimal prices of service and network providers and to determine optimal scenarios, a two-stage competition is modeled. In the first stage, network providers compete on market prices by setting the quality in four scenarios. At this stage, we found the equilibrium prices in the market. In the second stage, by obtaining market prices, service providers compete on network prices. Finally, the equilibrium solutions are compared with each other by considering the intensity of market competition in price and quality. It is shown that equilibrium never occurs in the case when the smaller service provider has a higher Internet quality than the other (scenario 2) and the more significant service provider offers a higher Internet quality (scenario 4). Besides, when both Internet service providers offer low-quality Internet (scenario 1) and high-quality Internet (scenario 3), the companies make the most profit. By increasing and decreasing the competition in quality, equilibrium would still exist for the first scenario, and the third scenario, respectively. The intensity of market competition in price behaves oppositely as quality. [ABSTRACT FROM AUTHOR]

This paper studies Bertrand price-setting behavior when firms face capacity constraints (Bertrand-Edgeworth game). This game is known to lack equilibria in pure strategies, while the mixed-strategy equilibria are hard to characterize. We explore families of heuristic rules for individual price-setting behavior and the resulting market patterns, through simulations of agent-based models and laboratory experiments. Overall, the individual pricing strategies observed experimentally can be represented approximately by a sales-based simple rule. In the experiments, average market prices tend to converge from above and approach a state resembling a steady state, with slow aggregate price variations and low price dispersion around an average near the competitive level. However, that configuration can be disturbed occasionally by excursions triggered by discrete price raises of some agents. Salient features of experimental results can be described by simulations where agents use sales-based heuristics with parameters calibrated from the experiments. The results obtained here suggest the existence of useful complementarities between analytical, experimental and agent-based simulation approaches. [ABSTRACT FROM AUTHOR]

• Propose an OD competitive network equilibrium model for ride-sourcing market. • Adopt finite-dimensional variational inequality based on non-cooperative game theory. • Incorporate heavy-asset and light-asset transportation network companies (TNCs). • Derive analytical monotonicity of equilibrium optima and sensitivity analysis. • Gain managerial insights for both the government and TNCs. The ride-sourcing market (RSM) consists of three parts: ride-sourcing platforms or transportation network companies (TNCs) that set the price for passengers and wage of drivers, passengers requesting on-demand ride services, and drivers offering the services. This paper proposes an origin–destination (OD) competitive network equilibrium model for RSM with heterogeneous TNCs. A finite-dimensional variational inequality is adopted to formulate the RSM competitive network equilibrium model based on the non-cooperative game theory. It assumes that each TNC and individual drivers aim to maximize profits or earnings, while passengers of demand regions seek utility maximization. The monotonicity of equilibrium optima is analytically derived, and the sensitivity analysis of parameters is theoretically conducted and numerically illustrated. The managerial insights are gained both for the government and TNCs. The analytical findings include: (a) market equilibrium price increases and market equilibrium travel quantity decreases in either the transaction cost, driver cost, or TNC cost; (b) market equilibrium price decreases in the number of light-asset TNCs, while the market equilibrium travel quantity increases in it; and (c) raising RSM entry requirements improves the market equilibrium price and reduces travel demand on RSM. The numerical results illustrate the plausibility and flexibility of the analytical model. The proposed model is general and capable of analyzing the network equilibrium with multi-type drivers, demand regions, and heterogeneous ride-sourcing platforms. [ABSTRACT FROM AUTHOR]