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With the rapid development of information technology, live-streaming e-commerce has risen rapidly as a new business model. However, product quality problems that exist in the development of live-streaming e-commerce continue to emerge. The influence of strategic interactions between social media influencers, live-streaming e-commerce platforms, and consumers on product quality deserves to be studied. Therefore, this paper constructs a tripartite game model of "social media influencers–the live-streaming e-commerce platform–consumers" and analyzes the dynamic evolution process of the strategy selection among subjects and influencing factors by using evolutionary game theory. This study shows that products with high functional value are more likely to stimulate consumer rights protection behavior, prompting social media influencers to shift from lax to strict quality control. But when the emotional value is high, consumers are more inclined to give up on defending their rights, which leads to the maintenance of lax quality control, and the platform supervision will be weakened accordingly. Moreover, less quality differences motivate social media influencers to choose lax quality control. An increase in quality differences will promote a shift from an equilibrium strategy to strict quality control. However, if the penalty of the platforms is not strong enough, this strategic shift will not happen. In addition, a high percentage of platform commissions can encourage influencers to implement strict quality control, while platforms can maintain weak supervision. This study's findings provide valuable guidance for understanding and managing product quality issues in live-streaming e-commerce. In the future, the government will be considered a new player in the game in studying the impact of its policies on product quality in live-streaming e-commerce. [ABSTRACT FROM AUTHOR]

In small-scale pumped-storage reservoirs, physical disturbances have been suggested to be one of the main factors influencing phytoplankton structure and water quality. This study presented data on dynamic changes of the phytoplankton structure and the quality of raw water sampled monthly from January 2011 to June 2012, in three locations (with two different water levels each) of a small pumped-storage reservoir of Macau main storage reservoir. The trophic state index, phytoplankton structure indices, and multivariate statistical techniques were applied for assessing trophic state, phytoplankton community, and spatio-temporal variations of the reservoir, respectively. The results showed that the reservoir was categorized as a eutrophic–hypereutrophic reservoir, with the dominance ofCyanophytain 2011,and ofChlorophytaandBacillariophytain 2012. Lowest diversity/evenness and highest dominance happened in June 2011, while highest diversity/evenness and lowest dominance occurred in May 2012. Principle component analysis identified four factors that can explain 80.8% of the total variance of the water quality data, and cluster analysis generated two clusters of spatial similarity among the six sampling points and two clusters of temporal similarity among the 18 months. Discriminant analysis results revealed only three parameters (TP, NO3-N, and Chl-a) that could afford 100% correct assignation in temporal analysis, while no spatial variation was found in spatial analysis. This study highlighted the usefulness of combination of these methods for the evaluation and interpretation of complex water quality data-sets and assessment of pollution level of small-scale eutrophic reservoirs. The results from the study can be used in developing monitoring program of freshwater bodies. [ABSTRACT FROM PUBLISHER]