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The development of low-carbon production is impeded by the investment costs of green technology research and development (R&D) and carbon emission reduction while facing the uncertain risk of emission reduction investment. With the government's carbon emission constraints, green manufacturers implement the advance selling strategy to increase both profit and reduction level. However, few studies consider the consumer's green preference and emission constraints in advance selling market and spot market independently. The authors' paper investigates the optimal strategies of advance selling pricing and reduction effort for green manufacturers to maximize profits.

The authors' paper designs a stochastic model and investigates the manufacturer's optimal strategies of advance selling price and emission reduction efforts by categorizing different purchasing periods of low-carbon consumers. With the challenges of uncertain demand and government's emission constraints, the authors' develop the non-linear optimization model to investigate the manufacturer's profit-oriented decisions.

The results show the government's carbon constraints cannot influence the manufacturer's profit, but the consumer's low-carbon preference in the advance selling period can. Interestingly, the manufacturer will make fewer reduction efforts even when the consumers have stronger environmental awareness. In addition, the increasing consumer price sensitivity will exacerbate the profit loss from mandatory emissions reduction. Overall, for achieving a win–win situation between emission reduction and profit growth, green manufacturers should not only consider the sales strategies, market demand, and government constraints in a low-carbon market, but also pay attention to the uncertainty of green technology innovation.

With the consideration of the government's carbon emission constraints, uncertain demand, and low-carbon consumer's preferences, the authors' study innovatively incorporates the joint impacts of advance selling strategy and emission reduction effort strategy and then differentiates between two cases that pertain to the diverse carbon emission regulations.

In the hybrid electricity market, renewable energy power generator faces the uncertainty of power market demand and the randomness of the renewable energy generation output. In order to improve the grid-connected quantity of green power, the purpose of this paper is to design the pricing mechanism for renewable energy power generator with revenue-sharing contract in a two-stage “multi-single” electricity supply chain which contains a single dominant power retailer and two kinds of power suppliers providing different power energy species.

Considering the dual uncertainties of renewable energy power output and power market demand, the authors design the full-cooperative contract decision-making model, wholesale price contract decision-making model and revenue-sharing contract decision-making model to compare and optimize grid-connected pricing in order to maximize profit of different parties in power supply chain. Then, this paper performs a numerical simulation, discusses the existence of the equilibrium analytical solutions to satisfy the supply chain coordination conditions and analyzes the optimal contract parameters’ variation characteristics and their interaction relationship.

The authors find that the expected profits of the parties in the hybrid power supply chain are concave about their decision variables in each decision-making mode. The revenue-sharing contract can realize the Pareto improvement for all parties’ interest of the supply chain, and promote the grid-connected quantity of green power effectively. The grid-connected price will reduce with the increase of revenue-sharing ratio, and this impact will be greater on the renewable energy power. The greater the competition intensity in power supply side, the smaller the revenue-sharing ratio from power purchaser. And for the same rangeability of competition intensity, the revenue-sharing ratio reduction of thermal power is less than that of the green power. The more the government subsidizing green power supplier, the smaller the retailer sharing revenue to it.

Facing with the dual uncertainties of green power output and market demand and the competition of thermal power in hybrid electricity market, this study can provide a path to solve the problem of renewable energy power grid-connecting. The results can help green power become competitive in hybrid power market under loose regulations. And this paper suggests that the government subsidy policy should be more tactical in order to implement a revenue-sharing contract of the power supply chain.

This paper studies the renewable energy electricity grid-connected pricing under the uncertainty of power supply and market demand, and compares different contract decision-making strategies in order to achieve the power supply chain coordination. The paper also analyzes the competition between thermal power and renewable energy power in hybrid electricity market.

The purpose of this paper is to investigate and understand China’s rural farmers’ financing intention of inclusive finance, and it examines related drivers like knowledge of inclusive finance, perceived benefits and perceived risks of ordering finance. Besides, the social enterprise embeddedness and digital finance are integrated into the conceptual model to further investigate their moderating impact.

The authors designed an inclusive finance intention model to examine the relations between dependent variable knowledge of inclusive finance, intermediary variables perceived benefits and perceived risks of ordering finance and the independent variable financing intention of inclusive finance. The embeddedness of social enterprise and digital finance were identified as modifying factors. Both exploratory and conclusive research strategies were applied. A structured questionnaire was developed to collect empirical data from the rural areas of China.

It suggests that knowledge of inclusive finance can strengthen both perceived benefits and perceived risk of ordering finance. Interestingly, the embeddness of social enterprise can significantly reduce risk perceptions and improve perceived benefits of ordering finance. Furthermore, perceived benefits of ordering finance can positively enhance rural farmers’ financing intention of inclusive finance, whereas perceived risks can negatively influence the financing intention. Moreover, digital finance as a modifying factor can significantly strengthen the positive correlation between perceived benefits of ordering finance and financing intention of inclusive finance.

The research indicates that a systematic inclusive finance educational project is needed to enhance rural farmers’ understanding of inclusive finance and its components. Moreover, the study reveals that it is crucial to promote social enterprise participation and digital finance to develop inclusive finance in rural China, as the service attributes of social enterprise and efficiency of digital finance can greatly reduce the existing transaction cost of farmers.

The conceptual model would potentially contribute to researchers interested in investigating the financing intention of inclusive financial services relating to rural population. The integration of social enterprise embeddedness and digital finance is the uniqueness of this research conceptual model.

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.

The authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.

The study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.

With the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.

Authors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.

The purpose of this paper is to discuss how wind farms attract wind turbine manufacturers to get involved in wind turbines’ maintenance service with revenue sharing contract of bundled service under which the background of operation and maintenance (O&M) aftermarket of wind turbine exists. The authors also try to extend the results to the application of product plus service business mode on large-scale equipment O&M service. At present, Chinese wind power industry is suffering from production capacity redundancy. The profit levels for both wind farm and wind turbine manufacturers are relatively low. It is significant for Chinese wind power industry development to coordinate the supply chain of wind power in order to reduce O&M costs and increase revenues.

The present paper discusses product plus aftermarket service contract design on the background of closed-loop product service chain and uncertain equipment demand using revenue sharing contract model.

If centralized decision making is assumed, the authors find that the wind turbine order increases as the aftermarket service effort level and aftermarket service profit increase; aftermarket service effort level is positively correlative to the service efficiency. On the other hand, if decentralized decision making is assumed, the wind turbine order increases as share of the aftermarket service chain by manufacturer to wind farm increases and share of product supply chain by wind farm to manufacturer decreases. The optimal effort level of wind farm increases as the share of aftermarket service chain increases while the optimal effort level of the manufacturer is a concave function of share of aftermarket service chain if service quality linear correlates with effort level. Meanwhile, the authors find that the revenues of the product supply chain and aftermarket service chain have a concave relationship. This relationship is not affected by the format of relationship between service quality and effort level (linear or exponential).

The results could potentially be used to provide the wind turbine manufacturer with a greater profit space and satisfy wind farm’s equipment maintenance demand at the same time. It can also guide the practice of revenue sharing in the aftermarket service and manufacturing servitization.

In this model, the authors assumed that both the forward revenue sharing of power generation by wind farm to manufacturer and the backward revenue sharing of maintenance service by the manufacturer to wind farm exist in closed-loop product service chain. Then the authors discussed channel coordination of such cross-revenue sharing contract.

To promote the development of renewable energy, the Chinese Government adopts the policy of Feed-in Tariff and subsidy. However, the high purchase price and the intermittence limit the development of renewable energy source electricity (RES-E). The purpose of this paper is to discuss the pricing strategy for system operators to stimulate the development of the RES-E industry under the scenario of uncertain supply and demand.

The authors establish a two-echelon supply chain investment model led by a power grid operator considering the uncertainties in both demand and supply, and study the impact of the power purchase price designed by a system operator using Stackelberg’s model.

There is an optimal capacity for RES-E generators, that is, independent of the market demand. Besides, the optimal order of grid operators is independent of the uncertain RES-E supply and the purchase price of fossil fuel. By properly setting the purchase prices, the system operator can stimulate the capacity investment in renewable energy. Finally, increasing the punishment in power shortage can stimulate the capacity investment in RES-E under certain conditions.

The result of this paper can mitigate the phenomenon of power abandonment in the RES-E industry and promote the grid integration of RES-E.

Both uncertain demand and supply are considered in this paper. A heuristic algorithm is provided to compute the optimal purchase price combination.

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.

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.

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.

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.

The authors compare two capacity investment strategies that the renewable energy supply fluctuation is related and unrelated to spot electricity price.

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.

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.

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.

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.

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.

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.

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.

(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.

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.

1. Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

2. Investment strategy of energy storage power stations on the supply side of wind power generators.

3. Impact of pricing method on the investment decisions of energy storage power stations.

4. Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

5. A two-stage wind power supply chain including energy storage power stations.

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.

Based on the background of enterprise digital transformation, this paper aims to examine the impact of digitization on the cooperative behavior and environmental performance of green technology innovation.

By constructing a model of quantity competition between the two enterprises, this paper examines the impact of digitization on the cooperative behavior and environmental performance of green technology innovation from the micro level. It uses Shanghai and Shenzhen A-share-listed companies as research samples. An unbalanced panel data set from 2011 to 2018 was constructed to empirically test the effect of digital transformation on the environmental performance of enterprises.

The findings reveal the following. First, digital transformation can significantly improve the environmental performance of enterprises. Second, green technological innovation sharing plays an intermediary role between digital transformation and enterprise environmental performance. Third, when the level of digitization is high, the sharing effect of green technology innovation brought about by digital technology is stronger and enterprises tend to carry out cooperative green technology innovation. Lastly, the level of development of regional science and technology finance plays a positive regulatory role in digital transformation and enterprise environmental performance.

This paper first proposes that green technology innovation-sharing is an important mechanism that can significantly improve enterprises' environmental performance. The authors empirically examine the mechanism and analyze the heterogeneity of the impact of digitalization level on enterprises' environmental performance. The authors also discuss the moderating effect of regional technology and finance development levels on the relationship between digitalization and enterprises' environmental performance.