基于TPL的集群式供应链协同及绩效评价研究
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摘要
作为产业集群和供应链耦合而成的集群式供应链,其中存在多条平行的单链式供应链,集群企业不仅在供应链内部紧密合作,而且在供应链间还存在跨链竞争与合作,这种复杂的竞合关系使产业集群具有更好的灵活性。在此背景下,本文从协同的角度将第三方物流(TPL)引入集群式供应链,对其跨链间协同及其绩效评价进行深入探讨,主要研究内容如下：
(1)分析TPL与集群式供应链协同机理,提出协同框架与运作模式。结合产业集群理论与供应链管理理论,构建集群式供应链网络体系结构,从网络的层次性、立体多核性、竞合双重性和信任根植性四个方面剖析集群式供应链的特性。借用生态学中种群间共生关系理论,将TPL与产业集群的协同模式划分为平等共生模式、依托共生模式和单向获利共生模式。在此基础上,建立TPL与集群式供应链协同框架,提出四种不同的协同运作模式。
(2)构建基于TPL的集群式供应链单品库存协同控制系统动力学模型,并模拟分析随机需求下模型的系统表现。运用系统动力学理论,建立集群式供应链单品库存控制模型VMI-APIOBPCSⅠ。考虑集群供应链间零售商跨链双向补货协作,将VMI-APIOBPCSⅠ模型扩展为VMI-APIOBPCSⅡ模型。进一步将TPL引入集群供应链系统,设计跨链双向补货运作流程,构建VMI&TPL-APIOBPCS模型。运用Vensim软件模拟三种模型在随机需求下的系统表现,比较分析引入TPL后集群式供应链系统在库存水平、生产率、牛鞭效应和服务水平等四个方面的变化。结果表明：TPL的加入能显著降低集群式供应链系统总库存水平,有效平滑制造商的生产率,极大地削弱牛鞭效应,明显提高顾客服务水平。
(3)提出基于TPL的集群式供应链多品库存协同控制系统动力学模型并进行模拟研究。将集群式供应链库存协同控制问题由单品扩展到多品环境,分别构建基于TPL参与或不参与集群式供应链两种情景的系统动力学模型,并运用Vensim软件模拟随机需求下两种模型运行情况,比较分析得出引入TPL的作用表现为：使供应商的生产节奏与顾客需求更合拍；降低了供应商库存,使其变化更平稳；极大提高了零售商服务水平；但系统总库存略有上升。
(4)构建BSC-SD集成的集群式供应链协同绩效评价系统动力学模型并进行模拟分析。运用平衡记分卡理论,分别从财务、顾客、内部流程和创新学习等四个方面提出集群式供应链协同绩效评价的关键指标。在此基础上,建立集群式供应链协同绩效评价系统动力学模型。通过仿真模拟不同协同环境和产能政策条件下集群式供应链协同绩效评价情况,结果证实：更高程度的协同能显著提高产能利用率和订单满足率,较明显地提高顾客满意度、产品合格率和产品创新率。
The cluster supply chain is the coupling of industrial cluster and supply chain in which there are many parallel single supply chains. The cluster enterprises not only work together with each other in the same supply chain but also compete or cooperate with the enterprises in other supply chain. The complicated competition and cooperation relationships reinforce the flexibility of industrial cluster. Considering this context, this dissertation brings the Third-party Logistics (TPL) in the cluster supply chain to study deeply the collaboration across chain and the performance evaluation of it. The research work and conclusions are summarized as follows.
Firstly, the collaboration mechanism between TPL and cluster supply chain is analyzed and the collaboration framework and operation models are proposed. On the one side, the network structure of cluster supply chain is formed based on the industrial cluster theory and supply chain theory. The specialty of it is anatomized in four aspects including stratification of network, solid and multi-core, dualism of competition-cooperation and embeddedness based on trust. On the other side, according to the symbiotic relation in species group theory of bionomics, the collaboration models of TPL and industrial cluster are classified as three categories:equality symbiotic model, support symbiotic model and one-way accrual symbiotic model. Combining the two sides, the collaboration framework is constructed and the four operation models are designed.
Secondly, the system dynamics model of single-item inventory collaboration control in cluster supply chain with TPL is established and the system performances under the stochastic demand environment is simulated. The single product inventory control model of cluster supply chain is constructed based on System Dynamics (SD). Then considering the across-chain replenishment of retailers between different supply chains, the VMI-APIOBPCS I model is extended to VMI-APIOBPCS II. Further, the third party logistics provider is introduced into the cluster supply chain network, the VMI&TPL-APIOBPCS model is proposed. The soft of Vensim is used to simulate the three models under stochastic demand. The simulation results are comparatively analyzed in inventory level, production rate, Bullwhip Effect and service level. The study shows that the model with TPL can remarkably decrease the cluster supply chain system inventory, effectively smooth the production rate, greatly reduce the Bullwhip Effect and clearly improve the customer service level.
Thirdly, the system dynamics model of multi-item inventory collaboration control in cluster supply chain with TPL is constructed and simulated. The inventory item context is extended from single to multiple. Two system dynamics models of multi-item inventory collaboration control in cluster supply chain are formed based on two different scenes that TPL is included or not. Vensim is applied to simulate the operation of two models. The simulation results are compared and reveal that the participation of TPL can help to gain better match between the supply and demand, effectively reduce the inventory of manufacturers and smooth the variation of it, obviously improve customer service level of retailers but increase the system inventory a little.
Last but not the least, the collaboration performance evaluation model of cluster supply chain based on BSC-SD is brought forward and simulated. According to the Balanced Scorecard (BSC), the key collaboration performance evaluation indexes are designed in four views including finance view, customer view, internal process and innovation study view. Then the system dynamics model of collaboration performance evaluation of cluster supply chain (CPV-CSC) is structured. The scenes in different collaboration environments and capacity policies are simulated and the collaboration performances of cluster supply chain are analyzed. The results show that higher degree of collaboration can greatly enhance capacity utility and fill rate, clearly increase customer satisfaction, product quality and innovation rate.
(1)分析TPL与集群式供应链协同机理,提出协同框架与运作模式。结合产业集群理论与供应链管理理论,构建集群式供应链网络体系结构,从网络的层次性、立体多核性、竞合双重性和信任根植性四个方面剖析集群式供应链的特性。借用生态学中种群间共生关系理论,将TPL与产业集群的协同模式划分为平等共生模式、依托共生模式和单向获利共生模式。在此基础上,建立TPL与集群式供应链协同框架,提出四种不同的协同运作模式。
(2)构建基于TPL的集群式供应链单品库存协同控制系统动力学模型,并模拟分析随机需求下模型的系统表现。运用系统动力学理论,建立集群式供应链单品库存控制模型VMI-APIOBPCSⅠ。考虑集群供应链间零售商跨链双向补货协作,将VMI-APIOBPCSⅠ模型扩展为VMI-APIOBPCSⅡ模型。进一步将TPL引入集群供应链系统,设计跨链双向补货运作流程,构建VMI&TPL-APIOBPCS模型。运用Vensim软件模拟三种模型在随机需求下的系统表现,比较分析引入TPL后集群式供应链系统在库存水平、生产率、牛鞭效应和服务水平等四个方面的变化。结果表明：TPL的加入能显著降低集群式供应链系统总库存水平,有效平滑制造商的生产率,极大地削弱牛鞭效应,明显提高顾客服务水平。
(3)提出基于TPL的集群式供应链多品库存协同控制系统动力学模型并进行模拟研究。将集群式供应链库存协同控制问题由单品扩展到多品环境,分别构建基于TPL参与或不参与集群式供应链两种情景的系统动力学模型,并运用Vensim软件模拟随机需求下两种模型运行情况,比较分析得出引入TPL的作用表现为：使供应商的生产节奏与顾客需求更合拍；降低了供应商库存,使其变化更平稳；极大提高了零售商服务水平；但系统总库存略有上升。
(4)构建BSC-SD集成的集群式供应链协同绩效评价系统动力学模型并进行模拟分析。运用平衡记分卡理论,分别从财务、顾客、内部流程和创新学习等四个方面提出集群式供应链协同绩效评价的关键指标。在此基础上,建立集群式供应链协同绩效评价系统动力学模型。通过仿真模拟不同协同环境和产能政策条件下集群式供应链协同绩效评价情况,结果证实：更高程度的协同能显著提高产能利用率和订单满足率,较明显地提高顾客满意度、产品合格率和产品创新率。
The cluster supply chain is the coupling of industrial cluster and supply chain in which there are many parallel single supply chains. The cluster enterprises not only work together with each other in the same supply chain but also compete or cooperate with the enterprises in other supply chain. The complicated competition and cooperation relationships reinforce the flexibility of industrial cluster. Considering this context, this dissertation brings the Third-party Logistics (TPL) in the cluster supply chain to study deeply the collaboration across chain and the performance evaluation of it. The research work and conclusions are summarized as follows.
Firstly, the collaboration mechanism between TPL and cluster supply chain is analyzed and the collaboration framework and operation models are proposed. On the one side, the network structure of cluster supply chain is formed based on the industrial cluster theory and supply chain theory. The specialty of it is anatomized in four aspects including stratification of network, solid and multi-core, dualism of competition-cooperation and embeddedness based on trust. On the other side, according to the symbiotic relation in species group theory of bionomics, the collaboration models of TPL and industrial cluster are classified as three categories:equality symbiotic model, support symbiotic model and one-way accrual symbiotic model. Combining the two sides, the collaboration framework is constructed and the four operation models are designed.
Secondly, the system dynamics model of single-item inventory collaboration control in cluster supply chain with TPL is established and the system performances under the stochastic demand environment is simulated. The single product inventory control model of cluster supply chain is constructed based on System Dynamics (SD). Then considering the across-chain replenishment of retailers between different supply chains, the VMI-APIOBPCS I model is extended to VMI-APIOBPCS II. Further, the third party logistics provider is introduced into the cluster supply chain network, the VMI&TPL-APIOBPCS model is proposed. The soft of Vensim is used to simulate the three models under stochastic demand. The simulation results are comparatively analyzed in inventory level, production rate, Bullwhip Effect and service level. The study shows that the model with TPL can remarkably decrease the cluster supply chain system inventory, effectively smooth the production rate, greatly reduce the Bullwhip Effect and clearly improve the customer service level.
Thirdly, the system dynamics model of multi-item inventory collaboration control in cluster supply chain with TPL is constructed and simulated. The inventory item context is extended from single to multiple. Two system dynamics models of multi-item inventory collaboration control in cluster supply chain are formed based on two different scenes that TPL is included or not. Vensim is applied to simulate the operation of two models. The simulation results are compared and reveal that the participation of TPL can help to gain better match between the supply and demand, effectively reduce the inventory of manufacturers and smooth the variation of it, obviously improve customer service level of retailers but increase the system inventory a little.
Last but not the least, the collaboration performance evaluation model of cluster supply chain based on BSC-SD is brought forward and simulated. According to the Balanced Scorecard (BSC), the key collaboration performance evaluation indexes are designed in four views including finance view, customer view, internal process and innovation study view. Then the system dynamics model of collaboration performance evaluation of cluster supply chain (CPV-CSC) is structured. The scenes in different collaboration environments and capacity policies are simulated and the collaboration performances of cluster supply chain are analyzed. The results show that higher degree of collaboration can greatly enhance capacity utility and fill rate, clearly increase customer satisfaction, product quality and innovation rate.
引文
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