With both cost and safety taken into account in the context of the life-threatening COVID-19 pandemic globally, rural tourism is expected to be the top choice for Chinese residents for relaxation and enhancing parent-child relationships. In this paper, a structural equation (SEM) model was proposed to compare risk knowledge, risk perception, risk aversion attitudes and behavioral intentions towards rural tourism. According to the empirical results, there was a large proportion of tourists showing preference for rural tourism recently. Potential participants in rural tourism paid most attention to the performance realization and time cost of scenic spots, while the psycho-social risk posed by COVID-19 had little impact. The inherent risk nature of risk aversion attitudes made knowledge of the pneumonia risk less effective in reducing tourists’ intentions, while knowledge of the pneumonia risk was more effective in alleviating the risk perception that potential tourists have towards rural tourism. With regard to travel intention and recommendation intention of rural tourism, the negative impacts of risk aversion attitude were more considerable compared to risk perception. Meanwhile, the parallel mediating effect of risk perception and risk aversion attitude in rural tourism needed to be taken into consideration together.

Tourism and transportation have extremely complex interactions. Tourism developments have expanded demand and stimulated transportation development, which has consequently affected the environment of cities striving towards low-carbon sustainable development. Therefore, there has been an increased research focus on the coordinated binary development of the tourism and transportation industries to ensure sustainable low-carbon cities. To this end also this paper first developed a comprehensive evaluation index system with three subsystems, seven aspects, and 31 indicators. Then, entropy weight and gray correlation were combined to determine the index weights and a physics coupling concept employed to build a tourism, transportation and low-carbon city (TTLC) coupling coordination degree model, which was then applied to quantitatively analyze the coupling and evolutionary trends in Chongqing’s TTLC efforts from 2008 to 2017. It was found that the overall coupling coordination was volatile and rising, and that industry scale, industry performance, and energy consumption had the most significant impact on the coupled systems, indicating that these key factors must be considered in macro decision-making. In general, it was shown that the combination of the coupling coordination degree model and entropy weight gray correlation was able to effectively evaluate dynamic coupling relationships.

Hazardous waste can cause severe environmental pollution if not disposed of properly, which in turn can seriously affect the sustainable development of the entire ecology and will inevitably bring disaster to companies. However, because of limited available disposal capacity, it is often difficult to safely dispose of hazardous waste, meaning that it must be kept as passive inventory. For the passive inventory of hazardous waste, risk evaluation of safe operation of the inventory is crucial and urgently needs to be resolved. Based on this, this paper focuses on the risk management of hazardous waste inventory of waste-producing companies and proposes a risk evaluation system for safely dealing with hazardous waste inventory, which expands the scope of inventory safety management and provides guidance to companies on developing appropriate measures to ensure hazardous waste inventory safety. First, the risk evaluation index system for hazardous waste inventory is constructed from equipment, management level, nature of hazardous waste and operational aspects. Then, the best worst method (BWM) is employed to calculate the criteria weights and the technique for order performance by similarity to ideal solution (TOPSIS) is employed to rank the alternatives. Finally, risk evaluation on four waste-producing companies was conducted using the developed method. The results show that Case Company 4 has the greatest risk of hazardous waste inventory, which should be reduced by improving storage method and the amount of hazardous waste. It was found that the proposed evaluation system was effective for hazardous waste inventory safety risk assessments and that the designed index system could assist companies improve their hazardous waste inventory management.

Measuring the success of sustainable urban development has been difficult in the past. However, as this has become more important in the past few years, this paper develops an innovative sustainable urban development capacity measurement model based on principal component analysis (PCA) and Grey TOPSIS methodology, which has a significantly more comprehensive measurement, and reduces processing time and calculation difficulty. First, PCA is used to extract the main components that affect a city’s sustainable development capacity. Then, the actual sustainable development capacity level is measured using Grey TOPSIS, from which the sustainable development capacity measurement value is then calculated. To prove the model’s effectiveness and operability, it is then applied to measure the sustainable development capacity in 13 cities in Jiangsu province, China.