Using survey, we discuss how climate and environmental issues awareness affects residents’ low carbon use behaviour. The results are following. Firstly, climate and environmental issues awareness positively affects residents’ low carbon use. Secondly, perceived effectiveness has mediate effect on the relationship between climate and environmental issues awareness and low carbon use behaviour partly. Thirdly, perceived value has negative moderate effect on the relationship between climate and environmental issues awareness and low carbon use conduct. The results of this study show that when residents feel higher perceived value about their low carbon consumption, they will engage in low carbon use even with lower climate and environmental issues awareness. It tells us that we should treat the residents differently with classification when advocate low carbon use. Specifically, there are some product and service in which consumers can gain high perceived value if the residents frugally use them with high efficiency. And we need to make effort to the following things: we improve the perceived value with hard working, and on the other hand, we make enough effort to enable the residents to deeply experience the perceived value via multiple means.
We examined how orientation of self-determination affects the use of online self-presentation strategies among social networking site users. Participants were 374 young adult WeChat users (age range = 18–22 years; 166 men, 208 women) who completed the self-report measures of the General Causality Orientations Scale and the Online Interpersonal Communication Strategies Scale. The results indicated that an autonomy orientation of self-determination was positively related to the use of automatic ingratiation strategies; a controlled orientation of self-determination was the most active motivational orientation and was related to the use of the online self-presentation strategies of ingratiation, self-promotion, exemplification, and supplication; and an impersonal orientation of self-determination was primarily associated with use of the supplication strategy of self-presentation. These novel insights regarding self-determination could help to explain individual differences in online self-presentation.
As the number of users' social connections on social networking sites increases, different types of role stress may occur for these users. We conducted an empirical analysis of 312 WeChat Moments users, to obtain insight into how perceived role stress (role conflict, role overload, and role ambiguity) and different stress responses (impression management vs. social fatigue) influence online selfdisclosure behaviors. The results suggest that role overload and role ambiguity both had a suppressive effect on self-disclosure: Role ambiguity reduced social networking site users' need to maintain a personal network impression, whereas role overload increased their psychological fatigue in relation to interpersonal interactions. Further, although role conflict increased social fatigue, it also promoted the use of more impression management measures to promote self-disclosure. Theoretical and practical implications of the study are discussed.
As renewable energy sources such as wind are connected to the grid on a large scale, the safe and stable operation of the power system is facing challenges and the demand for flexibility is becoming increasingly prominent. In recent years, with the advancement of Vehicle-to-Grid (V2G) technology, electric vehicles (EVs) have become a non-negligible flexibility resource for the power system and an emerging path to solve the renewable energy consumption problem. To address the problem of wind farms' difficulty in making profits in the power market, this paper considers the cooperation between wind farms and EV aggregators and uses the levelable characteristics of EVs charging load to ease the anti-peak characteristics of wind power. Given this, this paper proposes a cooperation mode between the wind farm and the Electric Vehicle (EV) aggregator, constructs a cooperation income and income distribution model, and solves the model using the Asynchronous Advantage Actor-Critic (A3C) reinforcement learning algorithm. Finally, based on the simulation analysis of historical data, the following conclusions are drawn: (1) the cooperation between the wind farm and the EV aggregator can effectively mitigate the negative impact of the anti-peak characteristics of wind power on profitability and achieve an increase in overall economic benefits; (2) the income distribution based on the Shapley value method ensures that the respective income of the wind farm and the EV aggregator increase after cooperation, which is conducive to the promotion of the willingness of both parties to cooperate; (3) the A3C reinforcement learning algorithm is applied to solve the model with good convergence to achieve fast and continuous intelligent pricing decisions for EV aggregators, thus optimizing the charging schedule of EVs promptly.
In a two-echelon supply chain consisting of a manufacturer and a retailer, the carbon emission reduction model is established for the scenario where manufacturer invests R&D for carbon emission reduction, retailer shares R&D cost, government implements carbon cap-and-trade policy, and consumers have a low-carbon-preference. This research compares the optimal profits, the total carbon emission reduction level (TCRL) in supply chain and product sales volume, and discusses the impact of stakeholder behavior on carbon emission reduction in supply chain.
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