科技服务供应链风险识别与预测研究

发布时间：2018-04-03 23:44

本文选题：科技服务供应链　切入点：风险识别与评测方法　出处：《重庆理工大学》2017年硕士论文

【摘要】：科技服务供应链风险识别与评估研究,是保障科技服务供应链持续性运作的根本途径,也是提高科技服务供应链各构成主体决策水平的前提条件。虽然政府及企业为了整合科技服务资源,梳理并延伸科技服务供应链,为其提供了良好的发展环境,但仍然面临重重风险。在此背景下,本文针对科技服务供应链风险识别,风险等级评估及检验性风险预测等方面,展开深入的研究,希望能从根源上减轻各方面风险因素对科技服务供应链整个流程系统的不良影响。本文首先在构建TSSC科技服务供应链结构模型的基础之上,构建科技服务供应链风险指标体系,并应用PAJEK社会网络分析法计算出对各风险要素的相关变量值,以准确识别出影响科技服务供应链的关键风险要素;其次,通过深度融合BP神经网络与主成分分析法,构建科技服务供应链评估模型,并通过应用MATLAB7.0对该评估模型进行训练和检验;然后,为了进一步检验模型的有效性,本文选取了作用于科技服务供应链风险的重要变量,根据变量分析结果,建立了多元二次非线性回归预测模型,在模型检验的基础之上,又建立了基于残差序列的随机性ARMA预测模型,通过两种模型的组合运算结果,对未来三年的科技服务供应链风险进行预测分析;最后,根据科技服务供应链各构成主体面临的风险差异,提出相应的保障措施。本文的主要结论包括:(1)围绕整个科技服务供应链运作流程,从关键流程主体出发,发现关键资源损失风险是影响科技服务供应商的关键风险要素;科技服务集成商却相对面临更多的关键风险因素,主要有组织的不协调风险、供应链流程中的联盟企业间关系稳定性差的风险、供应链内外部信息不对称风险、科技服务集成商对科技服务供应链运作的相关政策信息解读难的风险;而对于科技用户而言,其在最后环节面临的关键风险要素是科技成果转化率低的风险。(2)基于PCA-BP集成网络的科技服务供应链风险等级评估模型具有较高的适用性和可靠性,能够实现对科技服务供应链风险的准确评估、检测与分析,并能验证过去几年我国科技服务供应链面临的风险等级。(3)进一步验证了科技服务供应链风险等级评估模型的有效性,并能实现对当前及未来科技服务供应链面临的风险水平进行预测研究,发现未来三年科技服务供应链仍然处于相对较高的风险状态,需要引起各相关主体的高度关注。
[Abstract]:The research on risk identification and evaluation of S & T service supply chain is the fundamental way to guarantee the sustainable operation of S & T service supply chain, and is also the precondition to improve the decision-making level of the main components of S & T service supply chain.In order to integrate scientific and technological service resources, the government and enterprises have provided a good development environment for them by combing and extending the scientific and technological service supply chain, but they are still faced with many risks.In this context, this paper carries out in-depth research on the risk identification, risk grade assessment and test risk prediction of the S & T service supply chain.It is hoped that the adverse effects of various risk factors on the whole process system of the S & T service supply chain can be alleviated at the root.Based on the structure model of TSSC S & T service supply chain, this paper first constructs the risk index system of S & T service supply chain, and calculates the relevant variables of each risk factor by using PAJEK social network analysis method.In order to accurately identify the key risk factors that affect the S & T service supply chain, secondly, through the deep fusion of BP neural network and principal component analysis, the evaluation model of S & T service supply chain is constructed.Then, in order to further test the effectiveness of the model, this paper selects the important variables acting on the supply chain risk of science and technology services, according to the results of variable analysis.The multivariate quadratic nonlinear regression prediction model is established. On the basis of model checking, the stochastic ARMA prediction model based on residual sequence is established. The combined operation results of the two models are given.Finally, according to the risk differences of the main components of the S & T service supply chain, the corresponding protection measures are put forward.The main conclusions of this paper are as follows: (1) the key resource loss risk is the key risk factor that affects the S & T service provider from the key process body around the whole S & T service supply chain operation process;However, the service integrators are facing more and more key risk factors, mainly organized disharmony risk, the risk of poor stability of the relationship between the alliance enterprises in the supply chain process, the risk of asymmetric information inside and outside the supply chain.The risk of the ISI to interpret the relevant policy information about the operation of the S & T service supply chain is difficult, and for the users of science and technology,The key risk factor in the final link is the risk of low conversion rate of scientific and technological achievements.) the model based on PCA-BP integrated network for evaluating the risk level of S & T service supply chain has high applicability and reliability.It can realize the accurate assessment, detection and analysis of the risk in the S & T service supply chain, and can verify the effectiveness of the risk rating evaluation model of the S & T service supply chain in the past few years.It can also predict the risk level of the current and future S & T service supply chain, and find that the S & T service supply chain is still in a relatively high risk state in the next three years.
【学位授予单位】：重庆理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F274

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