With the progress of epidemic containment, the Chinese government has relaxed its regulatory policies on street vending, hoping to help people who have lost their livelihoods and to assist in the restoration of social and economic order. In response, Chinese people poured into the stall economy, especially individual peddlers, with great expectations for street vending. Street vending has become a hot topic on Chinese social network sites (SNSs). Based on the push-pull-mooring framework, SNS information overload theory was introduced and combined with the actual situations of street vending in China, and a structural equation model was established to study factors affecting individual Chinese peddlers' intention to engage in street vending and the effects of SNS information overload on these factors. Results revealed that perceived policy benefits, subjective norms, and switching cost perceptions of individual peddlers were positive factors affecting their intention to engage in street vending. SNS information overload positively affected individual peddlers' dissatisfaction with their original business model, anxieties over their livings, perception of policy benefits, and subjective norms but negatively affected individual peddlers’ perception of switching costs.

In this paper, we examine the influences of vertical and horizontal cooperation models on the optimal decisions and performance of a low-carbon closed-loop supply chain (CLSC) with a manufacturer and two retailers, and study optimal operation in the competitive pricing, competitive the low-carbon promotion, the carbon emission reduction, the used-products collection and the profits. We consider the completely decentralized model, M-R vertical cooperation model, R-R horizontal cooperation model, M-R-R vertical and horizontal cooperation model and completely centralized model, and also identify the optimal decision results and profits. It can be observed from a systematic comparison and numerical analysis that the completely centralized model is best in all optimal decision results among all models. In semi-cooperation, the M-R vertical cooperation model is positive, the R-R horizontal cooperation model is passive, and the positivity of the M-R-R vertical and horizontal cooperation model decreases with competitive intensity increasing in the used-products returning, carbon emissions reduction level, low-carbon promotion effort and the profits of the manufacturer and the entire supply chain.

This study examines manufacturers' carbon emission reduction level and retailers' low‐carbon promotion effort in a low‐carbon closed‐loop supply chain (CLSC), in which a manufacturer directly collects the used‐products from consumers. Considering both the carbon emission reduction level and low‐carbon promotion effort depending on the market demands, this study investigates the optimal decisions and performances of CLSC under four different game structures, that is, one non‐cooperative structure and three cooperative structures. In the non‐cooperative structure, the manufacturer controls the carbon emission level, the collection level as well as the wholesale price, while the retailer controls the low‐carbon promotion effort and retail price. The cooperative structures consist of one‐way and two‐way cooperation. In one‐way cooperative structure, the manufacturer shares only a part of retailer's low‐carbon promotion cost. In two‐way cooperative structure, the retailer shares partial manufacturer's carbon emission reduction cost or collection cost based on the one‐way cooperative structure. It shows that the two‐way cooperative structure of the co‐op promotion and carbon emission reduction is the optimal in pricing decisions and carbon emission reduction level, as well as two‐way cooperative structure of the co‐op promotion and collection is the optimal in the collection effort. Under lower the consumer's low‐carbon preferences, the retailer agrees to share the manufacturer's collection cost. When the consumer's low‐carbon preferences are higher, the retailer agrees to share the manufacturer's carbon emission reduction cost. © 2018 American Institute of Chemical Engineers Environ Prog, 38: 143–153, 2019

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.

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