Search Results (2)

Small and medium-sized enterprises (SMEs) play a critical role in promoting the development of China’s real economy and improving national productivity, but their financing still faces challenges. In recent years, supply chain finance (SCF) has become one of the most important solutions to SMEs’ financing difficulties. Promoting the digital and innovative development of SCF can better meet the financing needs of SMEs. This study is based on a case study of Zhejiang MYbank Co., Ltd. (MYbank) in Hangzhou, China, which is a representative institution of digital supply chain finance development in China and committed to realizing the digital innovation development of SCF. Based on MYbank’s financial index data from 2018 to 2022, the implementation effect of MYbank’s digital supply chain finance is quantitatively analyzed from the perspectives of SMEs and MYbank. The main findings are as follows.(1) In the practice of digital supply chain finance, MYbank implements the new concepts of SCF decentralization and full coverage of supply chain links while enhancing the sustainability of SCF. (2) For SMEs, MYbank’s digital supply chain finance development has led to an increase in the financing scale and financing availability of SMEs. (3) The analysis of MYbank’s comprehensive benefits shows that the digital innovation development of SCF effectively increased the overall economic value of the enterprise during the period of 2018–2022. Based on these findings, this study provides implications for commercial banks and other financial institutions to develop digital supply chain finance. Full article

Accurate and reliable farmland crop mapping is an important foundation for relevant departments to carry out agricultural management, crop planting structure adjustment and ecological assessment. The current crop identification work mainly focuses on conventional crops, and there are few studies on parcel-level mapping of horticultural crops in complex mountainous areas. Using Miaohou Town, China, as the research area, we developed a parcel-level method for the precise mapping of horticultural crops in complex mountainous areas using very-high-resolution (VHR) optical images and Sentinel-2 optical time-series images. First, based on the VHR images with a spatial resolution of 0.55 m, the complex mountainous areas were divided into subregions with their own independent characteristics according to a zoning and hierarchical strategy. The parcels in the different study areas were then divided into plain, greenhouse, slope and terrace parcels according to their corresponding parcel characteristics. The edge-based model RCF and texture-based model DABNet were subsequently used to extract the parcels according to the characteristics of different regions. Then, Sentinel-2 images were used to construct the time-series characteristics of different crops, and an LSTM algorithm was used to classify crop types. We then designed a parcel filling strategy to determine the categories of parcels based on the classification results of the time-series data, and accurate parcel-level mapping of a horticultural crop orchard in a complex mountainous area was finally achieved. Based on visual inspection, this method appears to effectively extract farmland parcels from VHR images of complex mountainous areas. The classification accuracy reached 93.01%, and the Kappa coefficient was 0.9015. This method thus serves as a methodological reference for parcel-level horticultural crop mapping and can be applied to the development of local precision agriculture. Full article