Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales ...Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales data of a fresh food e-commerce enterprise as the logistics demand, analyzes the influence of time and meteorological factors on the demand, extracts the characteristic factors with greater influence, and proposes a logistics demand forecast scheme of fresh food e-commerce based on the Bi-LSTM model. The scheme is compared with other schemes based on the BP neural network and LSTM neural network models. The experimental results show that the Bi-LSTM model has good prediction performance on the problem of logistics demand prediction. This facilitates further research on some supply chain issues, such as business decision-making, inventory control, and logistics capacity planning.展开更多
生鲜O2O(0nline to 0ffline)作为传统营销渠道与互联网技术相融合的产物,在充分利用线上与线下资源的同时对冷链运作提出了更高要求。为促进我国冷链物流发展与生鲜电商发展相匹配,文章在阐释生鲜电商配送环节存在的问题与搭建O2O环境...生鲜O2O(0nline to 0ffline)作为传统营销渠道与互联网技术相融合的产物,在充分利用线上与线下资源的同时对冷链运作提出了更高要求。为促进我国冷链物流发展与生鲜电商发展相匹配,文章在阐释生鲜电商配送环节存在的问题与搭建O2O环境下生鲜配送模式必要性的基础上,针对O2O不同的主导方提出了三种不同的配送模式,并从生鲜品价值实现度与企业资源占有度两个方面建立了生鲜品配送模式的判定矩阵,以期不断完善企业现有的生鲜品配送体系,使其与生鲜O2O发展相适应。展开更多
文摘Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales data of a fresh food e-commerce enterprise as the logistics demand, analyzes the influence of time and meteorological factors on the demand, extracts the characteristic factors with greater influence, and proposes a logistics demand forecast scheme of fresh food e-commerce based on the Bi-LSTM model. The scheme is compared with other schemes based on the BP neural network and LSTM neural network models. The experimental results show that the Bi-LSTM model has good prediction performance on the problem of logistics demand prediction. This facilitates further research on some supply chain issues, such as business decision-making, inventory control, and logistics capacity planning.
文摘生鲜O2O(0nline to 0ffline)作为传统营销渠道与互联网技术相融合的产物,在充分利用线上与线下资源的同时对冷链运作提出了更高要求。为促进我国冷链物流发展与生鲜电商发展相匹配,文章在阐释生鲜电商配送环节存在的问题与搭建O2O环境下生鲜配送模式必要性的基础上,针对O2O不同的主导方提出了三种不同的配送模式,并从生鲜品价值实现度与企业资源占有度两个方面建立了生鲜品配送模式的判定矩阵,以期不断完善企业现有的生鲜品配送体系,使其与生鲜O2O发展相适应。