Based on the Mixed Logit model, the willingness-to-pay (WTP) for waste mobile phone recycling among college students in Beijing was investigated using a discrete choice experiment method. The research results three aspects of respondents’ choices and WTP. (1) Their choices are positively affected by information security, recycling price, recycling method and payment method, and negatively affected by payment amount. (2) Respondents have the highest WTP for information security (30.04 yuan), followed by the recycling price (5.94 yuan) and payment method (4.41 yuan), and the lowest WTP for recycling models (2.87 yuan). (3) Personal socio-economic characteristics such as gender, annual household income, and the number of mobile phones held by respondents have significant impacts on their recycling WTP. The deeper the respondents' awareness of the environmental protection effect of waste mobile phone recycling, the more enthusiasm they have for the recycling behavior, the higher their participation in recycling, and the higher their WTP for recycling.

Introducing carbon financial derivatives and improving the carbon trading system are indispensable means for promoting carbon emission reductions. However, the reasonable pricing of carbon financial derivatives is crucial for launching related financial products. Here, the bilateral gamma distribution was used to fit the carbon quota yield series for the first time and compute the volatility of the carbon quota price, based on which the carbon option price was calculated by optimizing the option pricing model. The experimental results show that the carbon quota yield sequence approximately follows the bilateral gamma distribution and the model is reasonable for carbon option pricing. Subsequently, considering the relationship between continuous rise and fall rate in yield and the influence of trading volume on price, the formula of conditional probability of price rise and fall is derived by using bilateral gamma distribution, and numerical verification is carried out. Therefore, bilateral gamma distribution can be used for option pricing and price probability inference in carbon trading.

Transferring the houses of ancient town residents for the development of home-stays is an effective way to leverage the leading role of ancient towns in rural revitalization. Based on the questionnaire survey data of residents in Luomu Ancient Town of Emeishan City, this study used a Logistic regression model to study the residents’ willingness to transfer their houses and its influencing factors. The results showed that the age of the householder, the education level of the householder, the number of migrant workers in the family and the per capita housing area have significant effects on the housing transfer willingness of the residents. The residents of ancient town pay much attention to issues such as the transferring price of the house, whether the transferring rent can be paid to the account on time, the integrity and strength of the home-stay operators, and whether there is any governmental guarantee. According to the results of the data analysis, the following suggestions were put forward: (1) Strengthening the propaganda and guidance of young and well-educated family members, so as to have a positive impact on the householder; (2) Increasing the vocational skills training of the family labor forces in the ancient town, and encouraging more family labor force to be migrant workers; (3) Relocating the resettling the residents of the ancient town in other places; and (4) Increasing investment promotion efforts to attract enterprises with high integrity and strong strength to the overall transferring operation. This would to ensure that they can withstand higher transferring prices, and it is important that multiple measures are taken to reduce the concerns of risks in the residential housing transfer process.