Purpose: The online direct selling mode has been widely accepted by enterprises in the O2O era. However, the dual-channel (online/offline, forward/backward) operations of the closed-loop supply chain (CLSC) changed the relationship between manufacturers and retailers, thus resulting in channel conflict. The purpose of this paper is to take a dual-channel operations of CLSC as the research target, where a manufacturer sells a single product through a direct e-channel as well as a conventional retail channel; the retailer are responsible for collecting used products in the reverse supply chain and the manufacturer are responsible for remanufacturing.Design/methodology/approach: The authors build a benchmark model of dual-channel price and service competition and take the return rate, which is considered to be related to the service level of the retailer, as the function of the service level to extend the model in the reverse SC. The authors then analyze the optimal pricing and service decision under centralization and decentralization, respectively. Finally, with the revenue-sharing factor, wholesale price and recycling price transfer payment coefficient as contract parameters, the paper also designs a revenue-sharing contract led by the manufacturer and explores in what situation the contract could realize the Pareto optimization of all players.Findings: In the baseline model, the results show that optimal price and service level correlate positively in centralization; however, the relation relies on consumers’ price sensitivity in decentralization. In the extension model, the relationship between price and service level also relies on the relative value of increased service cost and remanufacturing saved cost. When the return rate correlates with the service level, a recycling transfer payment can elevate the service level and thus raise the return rate. Through analyzing the parameters in revenue-sharing contract, a point can be reached where lowering the wholesale price and raising the transfer payment coefficient will promote retailers to share revenue.Practical implications: Many enterprises establish the dual-channel distribution system both online and offline, which need to understand how to resolve their channel conflict. The conflict is especially strong in CLSC with remanufacturing. The result helps the node enterprises realize the coordination of the dual-channel CLSC.Originality/value: It takes into account the fact that there are two complementary relationships, such as online selling and offline delivery; used product recycling and remanufacturing. The authors optimize the strategy of product pricing and service level in order to solve channel conflict and double marginalization in the closed-loop dual-channel distribution network.

Purpose: When the power generator faces uncertain and independent electricity spot price and renewable energy source supply, two different conditions need to be considered: the distributions of renewable energy source electricity and electricity spot price are independent or dependent. The purpose of this paper is to explore the capacity investment strategy under volatile electricity spot price when renewable energy penetration rate is low, taking into account these two conditions. Design/methodology/approach: The authors design a capacity investment model under dual uncertainties and consider how to optimize the investment capacity in order to maximize profit under two different conditions. Findings: The authors find that when renewable energy supply fluctuation is unrelated to spot electricity price fluctuation, the renewable energy power profitability is determined by the average cost of spot electricity price and equivalent cost. When renewable energy supply fluctuation is related to spot electricity price fluctuation, the renewable energy power profitability is determined by the market value and the construction and maintenance cost. Practical implications: Faced with the conflict of the renewable energy supply, the authors need to understand how to plan the generation capacity with intermittent renewable sources. The result helps renewable energy become competitive in the electricity market under loose regulations. Originality/value: The authors compare two capacity investment strategies that the renewable energy supply fluctuation is related and unrelated to spot electricity price.

Purpose: In the hybrid electricity market consisting of renewable and conventional energy, the generation output of renewable power is uncertain because of its intermittency, and the power market demand is also fluctuant. Meanwhile, there is fierce competition among power producers in the power supply market and retailers in the demand market after deregulation, which increases the difficulty of renewable energy power grid-connection. To promote grid-connection of renewable energy power in the hybrid electricity market, the authors construct different contract decision-making models in the “many-to-many” hybrid power supply chain to explore the pricing strategy of renewable energy power grid-connecting.Design/methodology/approach: Considering the dual-uncertainty of renewable energy power output and electricity market demand, the authors construct different decision-making models of wholesale price contract and revenue-sharing contract to compare and optimize grid-connecting pricing, respectively, to maximize the profits of different participants in the hybrid power supply chain. Besides, the authors set different parameters in the models to explore the influence of competition intensity, government subsidies, etc. on power pricing. Then, a numerical simulation is carried out, they verify the existence of the equilibrium solutions satisfying the supply chain coordination, compare the differences of pricing contracts and further analyze the variation characteristics of optimal contract parameters and their interaction relations.Findings: Revenue-sharing contract can increase the quantity of green power grid-connection and realize benefits Pareto improvement of all parties in hybrid power supply chain. The competition intensity both of power supply and demand market will have an impact on the sharing ratio, and the increase of competition intensity results in a reduction of power supply chain coordination pressure. The power contract price, spot price and selling price have all been reduced with the increase of the sharing ratio, and the price of renewable power is more sensitive to the ratio change. The sharing ratio shows a downward trend with the increase of government green power subsidies.Originality/value: On the basis of expanding the definition of hybrid power market and the theory of newsvendor model, considering the dual-uncertainty of green power generation output and electricity market demand, this paper builds and compares different contract decision-making models to study the grid-connection pricing strategy of renewable energy power. And as an extension of supply chain structure types and management, the authors build a “many-to-many” power supply chain structure model and analyze the impact of competition intensity among power enterprises and the government subsidy on the power grid-connecting pricing.

Purpose: A public emission reduction project offers saleable carbon credits to encourage individual residents to participate in activities with low carbon emissions: if the residents participate, they will earn carbon credits that can be sold to polluting firms for carbon offsetting. This study explores the economic and environmental implications of these projects.Design/methodology/approach: The authors develop a multiperiod model to incorporate the decisions of individual residents and a polluting firm. The model captures residents' difference in estimating the price of carbon credits: A proportion of residents are naive residents who shortsightedly take the previous market price of carbon credits as the basis of their decision-making.Findings: A public emission reduction project can improve the cost-efficiency of carbon reduction, increase both the profit of the polluting firm and consumer surplus, but may hurt the welfare of the participating residents. Reducing transaction costs of carbon credits may cause a greater loss to participating residents. As the ratio of naive residents decreases, the overall welfare of participating residents increases and the number of participating residents decreases.Practical implications: To encourage more residents to reduce carbon emissions, the project should be promoted to new areas (e.g. rural areas) where there are more naive residents. Although reducing transaction costs is an effective way to increase the economic viability of the project, the government should pay attention to protecting the welfare of residents, and educating residents is an effective way to improve their overall welfare.Originality/value: This paper is the first to reveal the economic and environmental implications of public emission reduction projects.

Purpose: Although the wind power industry has been booming in China during the last decade, the development of wind turbine aftermarket service is still lagging behind, which seriously affects the operational efficiency of wind farms. If wind turbine manufacturers get involved in the aftermarket, the service pricing policy will impact the profits of both the manufacturer and the wind farm. Therefore, it is necessary to discuss an optimal service pricing strategy in the wind turbine aftermarket and design a method to improve electricity generation efficiency through service contract design. The paper aims to discuss these issues. Design/methodology/approach: In order to decide the maintenance quantity and channel effort level, the authors design a normal Stackelberg game and an efficiency value-added revenue-sharing contract and discuss two kinds of revenue increment sharing models under situations, in which the supply chain’s leaders are the wind farm and the wind turbine manufacturer, respectively. Findings: The results show that in either case, there exist optimal power generation revenue-sharing ratios that can maximize profit. At the same time, the authors outline an optimal service pricing policy, maintenance demand policy and channel service effort-level policy. The results summarize the influences of wind aftermarket services on wind farms’ and wind turbine manufacturers’ profit, which provides managerial insights into the process of manufacturing servitization. Practical implications: The manufacturer’s channel effort level will influence the power generation increments very much, so the authors have developed a mechanism to stimulate the manufacturer improving the efficiency of aftermarket services. Originality/value: Taking the power generation increment revenue as the profit increment function, the authors discuss the influence of service price on the profit increment of the wind farm and the wind turbine manufacturer and also consider the influence of service price on the wind farms maintenance quantity and wind turbine manufacturers channel effort level.

Purpose: Rapidly increasing the proportion of installed wind power capacity with zero carbon emission characteristics will help adjust the energy structure and support the realization of carbon neutrality targets. The intermittency of wind resources and fluctuations in electricity demand has exacerbated the contradiction between power supply and demand. The time-of-use pricing and supply-side allocation of energy storage power stations will help “peak shaving and valley filling” and reduce the gap between power supply and demand. To this end, this paper constructs a decision-making model for the capacity investment of energy storage power stations under time-of-use pricing, which is intended to provide a reference for scientific decision-making on electricity prices and energy storage power station capacity.Design/methodology/approach: Based on the research framework of time-of-use pricing, this paper constructs a profit-maximizing electricity price and capacity investment decision model of energy storage power station for flat pricing and time-of-use pricing respectively. In the process, this study considers the dual uncertain scenarios of intermittency of wind resources and random fluctuations in power demand.Findings: (1) Investment in energy storage power stations is the optimal decision. Time-of-use pricing will reduce the optimal capacity of the energy storage power station. (2) The optimal capacity of the energy storage power station and optimal electricity price are related to factors such as the intermittency of wind resources, the unit investment cost, the price sensitivities of the demand, the proportion of time-of-use pricing and the thermal power price. (3) The carbon emission level is affected by the intermittency of wind resources, price sensitivities of the demand and the proportion of time-of-use pricing. Incentive policies can always reduce carbon emission levels.Originality/value: This paper creatively introduced the research framework of time-of-use pricing into the capacity decision-making of energy storage power stations, and considering the influence of wind power intermittentness and power demand fluctuations, constructed the capacity investment decision model of energy storage power stations under different pricing methods, and compared the impact of pricing methods on optimal energy storage power station capacity and carbon emissions.Highlights: Electricity pricing and capacity of energy storage power stations in an uncertain electricity market. Investment strategy of energy storage power stations on the supply side of wind power generators. Impact of pricing method on the investment decisions of energy storage power stations. Impact of pricing method, energy storage investment and incentive policies on carbon emissions. A two-stage wind power supply chain including energy storage power stations.