Sharing accommodation has emerged recently as a new business model in the accommodation sector. Due to the potential gentrification Airbnb might bring to an area, it is critical to understand the spatial patterns of sharing economy and its possible determinants. The neighbourhood environment has proven to be an important factor in the traditional hotel business, and whether it is the same for sharing accommodation is worth investigating. In this study, location data of 29,780 houses/apartments on Airbnb.com in London was collected. Using Ordinal Least Square and Geography Weighed Regression analysis, the spatial distribution features of Airbnb and its relationship with neighbourhood environment in London were explored. The results show that sharing accommodation is mainly located in the city centre and around tourist attractions. Neighbourhood elements such as Water, Vegetation Coverage, Art & Human Landscape, Travel & Transport, University, Nightlife Spot emerged as important factors influencingAirbnb. In addition, the distribution of Airbnb in London is spatially nonstationary, in some areas high Airbnb is associated with higher transportation accessibility, in other areas, high Airbnb is associated with more attractions or nightlife spots, suggesting that the role of different factors varies in different regions, proving Tobler's first law of geography.

No abstract

Discrepancies in trade statistics can be normal or benign and attributed to a wide variety of unintentional factors, or in some instances within the timber products sector, such discrepancies can be associated with “systemic” factors that distort trade statistics, including (i) measurement and shipment issues, (ii) misreporting of product volumes, (iii) misclassification of timber product types, and (iv) government regulations concerned about trade. This study measured trade discrepancies in logs and lumber trade statistics for China and its trading partner countries from 2002 to 2018 using a time-lagged function, based on the customs data available from Global Trade Information Services (GTIS), with the aim of exploring a more nuanced understanding of trade discrepancies and their “systemic” factors. The results showed that the range of overall discrepancies in logs and lumber trade statistics shrunk over time, from [−0.069, 1.207] in 2002–2007 to [−0.120, 0.408] in 2013–2018. The larger trade flows of logs and lumber from Russia, New Zealand, and the U.S. (each above 10% of total China’s import) showed small trade statistics discrepancy ratios, which were less than ± 0.06. However, trade discrepancies still remained large at the disaggregated level, and significant differences of trade discrepancies between tropical and non-tropical countries. The range of trade discrepancies in hardwood logs increased from 2002 to 2018 and appeared to be attributed to misclassification and misreporting in tropical countries such as Indonesia, the Philippines, Thailand, and Ghana. However, these countries’ trade flows are becoming relatively minor over time. Government policies are suggested to play an important role in influencing both the occurrence and resolution of trade discrepancies.

No abstract

The efficiency and productivity improvement are the core requirements of high-quality development, while improving the efficiency of forest carbon sinks is an important means and fundamental way to achieve their high-quality development. Based on the forests and socioeconomic development data of 31 provinces (cities and districts) in China from 2004 to 2018, the biomass method and DEA-Tobit panel regression model were used to analyze the level of forest carbon stock, carbon sink and carbon sink efficiency, and factors influencing forest carbon sink efficiency in China’s provinces. The results indicated that: ① nationwide forest carbon stocks and carbon sinks increased successively while carbon density decreased. The regions with higher carbon stock, carbon sink, and carbon density were concentrated in the northeast and southwest forest areas with abundant forest resources. ② During the 7th to 9th forest inventory, the efficiency of forest carbon sinks was on a low and decreasing trend. The mean values of comprehensive efficiency in general for the 7th to 9th forest inventory periods were 0.421 and 0.336, respectively. The scale efficiency in the decomposition efficiency was above 0.650 for both inventory periods, and gradually increased, showing that the gap between the actual scale and the optimal production scale of forestry carbon sink was decreasing. The pure technical efficiency level represented the production efficiency of input factors at the optimal scale of forestry carbon sinks. The mean values of the two periods are 0.639 and 0.514, respectively, while the differences within the production frontier surface are 0.361 and 0.486, which indicates that there is input redundancy or output deficiency in the two periods as a whole. ③ The total annual precipitation and the level of socioeconomic development have significant driving effects on the improvement of forest carbon sink efficiency, while the incidence of pests and diseases, abnormal changes in temperature, afforestation area and the development of population urbanization have significant inhibiting effects on the improvement of forest carbon sink efficiency in China.