资源与产业 ›› 2022, Vol. 24 ›› Issue (1): 46-54.DOI: 10.13776/j.cnki.resourcesindustries.20211221.003

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基于改进SIR模型的黄河流域产业优化仿真研究

尹庆民,诸 清   

  1. (河海大学 商学院,江苏 南京 211100
  • 收稿日期:2021-02-23 修回日期:2021-10-23 出版日期:2022-02-20 发布日期:2022-03-12
  • 通讯作者: 诸清,硕士生,主要从事应用经济学研究。1477603729@qq.com
  • 作者简介:尹庆民,博士、副教授,主要从事应用经济学、金融工程与投融资管理研究。E-mail: yinqingmin@hhu.edu.cn

SIMULATED INDUSTRIAL OPTIMIZATION OF YELLOW RIVER BASIN BASED ON IMPROVED SIR MODEL

YIN Qingmin, ZHU Qing   

  1. (Business School, Hohai University, Nanjing 211100, China
  • Received:2021-02-23 Revised:2021-10-23 Online:2022-02-20 Published:2022-03-12
  • Contact: ZHU Qing
  • About author:E-mail: yinqingmin@hhu.edu.cn

摘要: 评估黄河流域产业结构合理化及高级化水平,分析影响黄河流域产业结构发展的因素,为黄河流域实现产业结构优化提供建议与参考。根据2009—2018年黄河流域三次产业产值数据及就业情况,利用Hamming贴近度、Moore结构指数测算流域产业的合理化及高级化水平;在无标度网络的情形下,根据得出的结果,结合改进SIR模型对产业优化效果最为显著的因素进行研究分析。结果表明:1)从横向来看,黄河流域下游的产业产值结构与就业结构的贴近度最高,中游次之,上游的贴近度最低,其中上游的平均得分为0.783 4,中游为0.795 6,下游为0.817 6;从纵向来看,合理化程度逐渐上升,产业状况整体呈向好发展态势,但上中下游之间仍存在较大差异;2)从区域维度来看,下游地区的产业结构高级化水平最高,平均值达到了8.792 0,上游地区与中游地区的发展水平大致相当,均值分别为6.296 0和6.305 5;从产业结构变动速率来看,下游地区从2009年的1.597 7上升到2018年的15.895 1,增加了14.297 4,中游地区上升了9.183 4,上游地区上升了9.536 9,三大区域总体呈现“上游崛起、中游起伏、下游领先”的发展格局;3)在产业的初始比例以及产业优化成功率和失败率不变的情况下,调整产业影响力对优化结果几乎不起作用;而调整优化成功概率及优化失败产业再优化可能性时,产业优化状况发生了显著变化。结合黄河流域产业结构现状及仿真模型的研究结论,黄河流域各省(区)政府应加大产业优化支持力度,注重对失败产业的再升级指导;中上游地区应把握“一带一路”政策机遇,加大改革创新力度;而下游地区则应注重信息化技术的发展,加强区域间的产业合作。

关键词: 产业优化, 产业结构合理化, 产业结构高级化, 改进的SIR模型, 黄河流域

Abstract: The objectives of this paper are to evaluate industrial structural rationalization and escalation of the Yellow River Basin, study the factors of industrial structural development, and provide suggestions for optimizing industrial structure. According to 2009-2018 three industries production data and employment in the Yellow River Basin, this paper uses Hamming osculation and Moore structural index to estimate industrial rationalization and escalation, and applies improved SIR model to study the optimization factors under unmarked grid. Geographically, Hamming osculation between industrial production structure and employment structure is highest in the down-reach, followed by the middle- and then the upper-reach, average at 0.783 4 in the upper-reach, 0.795 6 in the middle- and 0.817 6 in the down-reach. Temporally, rationalization is gradually rising with an escalating industrial developing trend in general with variance among the three reaches. Industrial structural escalation is highest up to 8.792 0 in the down-reach, 6.296 0 in the middle- and 6.305 5 in the down-reach. Industrial structural changing rate has increased by 14.297 4(from 1.597 7 in 2009 to 15.895 1 in 2018) in the down-reach, by 9.183 4 in the middle- and by 9.536 9 in the upper-reach, displaying a pattern of rising upper-reach, fluctuating middle-reach and leading down-reach. Adjusting industrial influence has little impact on industrial structural optimization, if industrial initial proportion, industrial optimization success ratio and failure ratio keep constant. However, industrial optimization may be largely improved if it is possible to increase industrial optimization success rate and the re-optimization possibility of failed industries. This paper presents suggestions on boosting industrial optimization, upgrading failed industries, using "the Belt and Road" policy to intensity innovation in the middle- and upper-reach, and focusing on information technology and industrial cooperation in the down-reach.

Key words: industrial optimization, industrial structural rationalization, industrial structural escalation, improved SIR model, the Yellow River Basin

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