The market size of live streaming on the Internet, in which the streamer earns profit by prompting users to give virtual gifts through emotional labor, is getting bigger and bigger. However, most users will only buy cheap virtual gifts in live streaming, therefore exploring how to promote users to buy expensive virtual gifts is a valuable topic in live commerce research. Based on social presence theory and information overload theory, this study used the PLS-SEM method to investigate the factors influencing live streaming users to shift from buying cheap virtual gifts to buying expensive virtual gifts, and analyzed the moderating role of information overload in these relationships. The results show that immediate interaction anxiety, verbal intimacy, and virtual physical intimacy positively influence users’ shift to purchasing expensive virtual gifts, and that perceived network size and perceived financial risk are negative factors in users’ shift to purchasing expensive virtual gifts. Information overload has a moderating role in the relationship between immediate interaction anxiety and switch intention, and it also plays a moderating role in the relationship between perceived network size and perceived financial risk on users’ switch intention.

Crowdsourcing logistics-based O2O (online to offline) has been increasingly implemented to help individuals or merchants tackle down the problem of intra city instant delivery in China. However, since insufficient control is imposed on free couriers, consumers are subjected to certain risks generated by the uneven service quality provided by free couriers, such that the continuous-use intention to adopt crowdsourcing logistics may be affected in an unexpected manner. A sampling survey was carried out in China's first- and second-tier cities, with 292 valid questionnaires collected. On that basis, the corresponding hypotheses were tested using the partial least squares (PLS) method. The findings of this study revealed that trust, perceived value, and satisfaction positively contributed to continuous-use intention, where trust contributed the most. Perceived risk exerted a significant negative effect on continuous use intention. Trust is capable of notably reducing perceived risk. Crowdsourcing logistics service quality is the critical driving variable of perceived value and satisfaction. Perceived risk has a negative moderating effect on satisfaction-continuous-use intention relationship, showing that the higher the perceived risk, the weaker the effect of satisfaction on continuous-use intention. Given perceived risk, a conceptual model was built by integrating e-CSI model (e-Customer Satisfaction Index Model) and PAM-ISC model (Post-acceptance Model of IS Continuance Model). From the integration, the findings of this study are expected to provide decision-making basis for crowdsourcing logistics platforms to help solve the “last mile” delivery problem.

During the COVID-19 pandemic, many countries have used digital contact tracing apps (DCTAs) to implement contact tracing. Although the use of DCTAs has contributed to the prevention and control of COVID-19, there are doubts in academia about their actual effectiveness. In this study, the role of DCTAs in the prevention of COVID-19 was analyzed in terms of both the responsibility and inconvenience to life in a large-scale DCTA overuse environment, based on the normative activation model. The findings suggest that the overuse of a DCTA activates people’s personal norms by triggering awareness of the consequences and ascription of responsibility, leading people to consistently cooperate with the government to prevent COVID-19. However, the inconvenience of living with DCTA overuse weakens the effect of the awareness of consequences and ascription of responsibility and the role of the ascription of responsibility in influencing personal norms. These effects may bear on people’s willingness to consistently cooperate with the government to prevent COVID-19. The results of this study confirm the effectiveness of DCTA in counteracting pandemics from a social responsibility perspective in a large-scale environment where DCTA is used, enriching the literature on DCTA research in the COVID-19 pandemic. The results of this study can also help governments develop and improve policies to prevent COVID-19, as well as improve the DCTAs’ operating patterns.

The government has introduced a series of green financial support policies to support the low-carbon technological innovation of enterprises, and it has become an inevitable trend to take the road of high-quality development with clean, low-carbon efficiency and safety. In this paper, in order to further realize the quantitative analysis of green financial reform on the sustainable development of low-carbon enterprises, based on the principles of the evaluation index system construction on the sustainable development of low-carbon enterprises evaluation index system design, to determine the evaluation index level thesis domain, its data dimensionless processing, so that its evaluation indexes are composed of fuzzy relationship matrix. With the help of a recursive neural network, we analyze the low-carbon sustainable development of enterprises in the context of green financial reform. It is found that the squared error of the mean value of the enterprise low carbon sustainable development ability index based on a recursive neural network is 0.044. During the implementation of the green financial reform policy, the low carbon sustainable development ability of the sample enterprises has been improved, among which the growth trend of enterprise D (0.50415-0.44039=0.06376) is more rapid, which strongly confirms that the green financial reform and innovation promote the sustainable development of the low carbon enterprises. The promotion of green financial reform and innovation has been confirmed to have a strong effect on the sustainable development of low-carbon enterprises.