| 摘要: |
| 借助Scopus和CNKI检索了物流需求预测的相关文献，通过文献可视化软件CiteSpace对国内外研究文献进行关键词共现、突现、时区图等图谱分析。结果表明：研究热点方面，国内研究多集中于中微观层面，从经典统计学模型、优化算法到神经网络预测模型及其改进等方面对具体行业的物流量进行预测，而国外则更关注智能网络模型等方法在宏观区域物流上的应用。研究前沿方面，国内近三年在智能优化算法与多元回归模型的组合研究较多，国外则更关注大数据发展下人工智能方法及其组合的应用，且对物流供应链中企业库存、备件的资源优化配置较为重视。最后对新的研究方向提出了展望。 |
| 关键词: 物流 需求预测 知识图谱 文献计量 |
| DOI： |
| 分类号: |
| 基金项目: |
|
| Visual Analysis of Research Trends in Logistics Demand Forecasting at Home and Abroad |
|
CHEN Rong-hu, REN Li
|
|
School of Management Science and Engineering, Anhui University of Technology, Ma’anshan 243032, Anhui, China
|
| Abstract: |
| By reviewing literature related to logistics demand forecasting retrieved from two academic databases of Scopus and CNKI and using the literature visualization software CiteSpace, this paper analyzes the co occurrence, emergence, and time zone maps of key words in these articles. The results show that in terms of research hotspots, Chinese researchers mostly focus on the meso-micro level, from classical statistical models and optimization algorithms to neural network prediction models and their improvements for predicting the logistics in specific industries, while global researchers pay more attention to the application of intelligent network models and other methods in macro-regional logistics. In terms of research frontiers, in the past three years, there has been a lot of research on the combination of intelligent optimization algorithms and multiple regression models in China, while global researchers pay more attention to the application of artificial intelligence methods and their combinations under the development of big data, and pay more attention to the optimization of the resource allocation of enterprise inventory and spare parts in the logistics supply chain. Finally, this paper puts forward some possible research lines. |
| Key words: logistics demand forecast knowledge graph bibliometrics |
