需求类政策对中药产业集群形成的影响研究
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摘要
应用多Agent方法,构建需求类政策实施背景下中药企业是否进入中药产业集群的仿真模型,通过模型仿真,揭示了需求类政策对中药产业集群形成的作用机理。研究发现,在需求类政策强度分别提升20%、50%、100%的情况下,有85%的中药企业依次在第8年、第7年、第6年进入了中药产业集群;三种情况分别比初始情况快了1年、2年、3年;当需求类政策强度提升100%时,与强度提升50%相比,产业集群形成速度并未明显加快;随着需求类政策强度提升,中药产品批发销售企业进入产业集群速度逐渐快于其他两类企业。因此政府实施需求类政策的强度不是越高越好,应根据中药企业的不同类型和中药产业集群形成的不同阶段,实施不同强度的需求类政策。
This paper applies the multi-agent method to construct a simulation model of whether Chinese medicine enterprises entering the Chinese medicine industry cluster under the background of demand policy implementation. Through model simulation, it reveals the mechanism of demand policy on the formation of Chinese medicine industry clusters. The study found that 85% of Chinese medicine companies entered the Chinese medicine industry cluster in the 8 th, 7 th and 6 th years respectively when the demand policy intensity increased by 20%, 50%, and 100% respectively; Compared with the initial situation, they are 1 year, 2 years, and 3 years faster than it respectively. When the demand policy intensity is increased by 100%, the rate of industrial cluster formation is not significantly accelerated compared with the 50% increase in intensity; The wholesale and sales of Chinese medicine products gradually faster than the other two types of enterprises when entered the industrial cluster. Therefore, the intensity of the government's implementation of demand-based policies is not as high as possible. Different types of demand-based policies should be implemented according to the different types of Chinese medicine enterprises and the different stages of the formation of Chinese medicine industry clusters.
This paper applies the multi-agent method to construct a simulation model of whether Chinese medicine enterprises entering the Chinese medicine industry cluster under the background of demand policy implementation. Through model simulation, it reveals the mechanism of demand policy on the formation of Chinese medicine industry clusters. The study found that 85% of Chinese medicine companies entered the Chinese medicine industry cluster in the 8 th, 7 th and 6 th years respectively when the demand policy intensity increased by 20%, 50%, and 100% respectively; Compared with the initial situation, they are 1 year, 2 years, and 3 years faster than it respectively. When the demand policy intensity is increased by 100%, the rate of industrial cluster formation is not significantly accelerated compared with the 50% increase in intensity; The wholesale and sales of Chinese medicine products gradually faster than the other two types of enterprises when entered the industrial cluster. Therefore, the intensity of the government's implementation of demand-based policies is not as high as possible. Different types of demand-based policies should be implemented according to the different types of Chinese medicine enterprises and the different stages of the formation of Chinese medicine industry clusters.
引文
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[7] 曹阳,朱洁.基于灰色多指标评价模型的江苏省生物医药产业集群竞争力研究[J].中国药房,2015,26(19):2593.
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[2] 中华人民共和国工业与信息化部.中药材保护和发展规划(2015-2020年)[EO/BL].(2015-4-17)[2016-4-29] http://www.gov.cn/xinwen/2015-04/27/content_2853739.htm.
[3] 卜庆军,章莉莉.产业集聚与产业升级关系研究[J].工业技术经济,2014,33(12):33.
[4] 李开,江天鹏,崔小龙.政府行为与产业集群企业间合作营销-基于传统集群和高新技术集群的对比[J].工业技术经济,2014,33(3):152.
[5] Porter.Clusters and the new economics of competition[J].Harvard Business Review,1998,76(6):76.
[6] 刘盈,李祺,汪晓凡.中药产业链结构复杂性分析[J].中国中药杂志,2014,39(16):3187.
[7] 曹阳,朱洁.基于灰色多指标评价模型的江苏省生物医药产业集群竞争力研究[J].中国药房,2015,26(19):2593.
[8] ADAM SMITH.An Inquiry into the Nature and Causes of the Wealth of Nations[M].北京:中央编译出版社,2012.
[9] 绳立成,刘峰,张浩.基于多Agent的信息产业集群形成模型研究[J].情报科学,2012,30(2):178.
[10] 谢洪明,金占明,陈盛松.产业集群、企业行为与企业竞争力的实证研究[J].科学学与科学技术管理,2005,26(5):90.