This research aims at providing a meta-analysis of empirical findings of the literature on the characteristics of social media influencers on customer engagement and purchase intention. For this purpose, researchers derived eight social media influencers’ characteristics, i.e., homophily, expertise, trustworthiness, credibility, congruence with the product, entertainment value, informative value, and attractiveness. The current study synthesizes 176 effect sizes derived from 62 individual studies, and 22,554 individuals act as an aggregate sample. Results revealed that these characteristics have a moderate to high correlation with customer engagement and purchase intention. The entertainment value of social media influencers has the strongest association with customer engagement among all the attributes studied in this analysis. It also concluded that the credibility of influencers impacts purchase intention more than any other attribute. This work provides a novel approach to reducing the heterogeneity in influencer marketing research by empirically specifying the directions of relationships and the extent of the effect of these relationships.
This paper discusses the power generation characteristics between new energy and traditional energy. This paper uses different energy alliance operation modes for a power system led by new energy power generation. The peak-valley power imbalance issue for real-time load is mitigated through coordinated and optimized energy supply by wind, photovoltaic, hydro (hydropower station with pumped storage function as an example.), and thermal power, aiming to peak load shifting for the system. Moreover, from the perspective of optimal allocation of resources within the alliance and multi-scale cost equilibrium optimization of each subject’s power generation combination, the marginal contribution of different agents is considered. A multi-energy alliance operation optimization decision-making method is designed based on the Shapley value method. This paper studies the multi-scale combination cost allocation of each subject and the distribution law of dynamic optimization of its output ratio. The relationship between the power generation ratio and the cost allocation for each subject. Moreover, the discrete coefficient equation of cost equilibrium values is constructed to verify the equilibrium distribution effect of the Shapley cost allocation model. The case analysis shows that the 46th combination scheme for the multi-energy alliance can realize the main output of wind power and photovoltaic new energy under the premise of the relatively stable alliance corresponding output ratio of 0.2 and 0.4, respectively. The research proves that the operation mechanism of the multi-energy alliance plays a supporting role in the optimal operation of the new energy power system. Meanwhile, this method can be used as a basis for the power generation planning, cost control, and power generation combination optimization decisions on each entity within the alliance.
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