Search results

Many studies have investigated dynamic positions and their importance, but there is less attention paid to how to enter more central positions. Interorganizational relationships are an important factor in network structural change. In Chinese society, firms allocate significant human, financial and material resources towards cultivating guanxi. The purpose of this study is to explore whether and how the three aspects of guanxi, namely renqing, ganqing and xinyong, can make firms more central, and to examine the mediating role of interaction.

The study used a mixed method to collect data from 256 Chinese Cops (complex product systems) firms. And, hypotheses were tested using SPSS 25.0 and AMOS 26.0.

The results indicate that renqing, ganqing and xinyong have significant positive effects on the increase in centrality, but with varying magnitudes. Additionally, the interaction was found to mediate the relationship between the three aspects of guanxi (renqing, ganqing and xinyong) and the increase in centrality.

The study provides new insights to help firms become more central by combining guanxi (renqing, ganqing and xinyong) with change in centrality, enriching the literature on network dynamics and guanxi-related research. Moreover, the study provides managers with a clear understanding of how to use guanxi to make the firm more central in situations with limited resources.

Technical knowledge is a key factor in firm innovation. This study aims to construct a theoretical framework of technological boundary-spanning search, exploratory innovation and exploitative innovation to help firms adjust their search strategies and improve the effect of external resources on internal innovation.

The study uses questionnaires to collect data and conducts empirical analysis using SPSS25 and AMOS24.

Technological boundary-spanning search is positively correlated with ambidextrous innovation. Additionally, knowledge base positively moderates the effect of technological boundary-spanning search on ambidextrous innovation and knowledge distance negatively moderates the effect of technological boundary-spanning search on ambidextrous innovation. When a firm’s knowledge base is robust, its ambidextrous innovation can benefit more from technological boundary-spanning search. Additionally, when the knowledge distance is less, a firm’s ambidextrous innovation can benefit more from technological boundary-spanning search.

Considering organizational ambidexterity, this study divides firm innovation into exploratory innovation and exploitative innovation and presents a theoretical framework for the effect of technological boundary-spanning search on ambidextrous innovation. Additionally, it provides a comprehensive understanding of the crucial roles of knowledge base and knowledge distance in the relationship between technological boundary-spanning search and exploratory and exploitative innovation.

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.

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.

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.

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.

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.