本文選題：科技服務(wù)供應(yīng)鏈　切入點(diǎn)：風(fēng)險(xiǎn)識(shí)別與評(píng)測(cè)方法　出處：《重慶理工大學(xué)》2017年碩士論文

【摘要】：科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)識(shí)別與評(píng)估研究,是保障科技服務(wù)供應(yīng)鏈持續(xù)性運(yùn)作的根本途徑,也是提高科技服務(wù)供應(yīng)鏈各構(gòu)成主體決策水平的前提條件。雖然政府及企業(yè)為了整合科技服務(wù)資源,梳理并延伸科技服務(wù)供應(yīng)鏈,為其提供了良好的發(fā)展環(huán)境,但仍然面臨重重風(fēng)險(xiǎn)。在此背景下,本文針對(duì)科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)識(shí)別,風(fēng)險(xiǎn)等級(jí)評(píng)估及檢驗(yàn)性風(fēng)險(xiǎn)預(yù)測(cè)等方面,展開(kāi)深入的研究,希望能從根源上減輕各方面風(fēng)險(xiǎn)因素對(duì)科技服務(wù)供應(yīng)鏈整個(gè)流程系統(tǒng)的不良影響。本文首先在構(gòu)建TSSC科技服務(wù)供應(yīng)鏈結(jié)構(gòu)模型的基礎(chǔ)之上,構(gòu)建科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)指標(biāo)體系,并應(yīng)用PAJEK社會(huì)網(wǎng)絡(luò)分析法計(jì)算出對(duì)各風(fēng)險(xiǎn)要素的相關(guān)變量值,以準(zhǔn)確識(shí)別出影響科技服務(wù)供應(yīng)鏈的關(guān)鍵風(fēng)險(xiǎn)要素;其次,通過(guò)深度融合BP神經(jīng)網(wǎng)絡(luò)與主成分分析法,構(gòu)建科技服務(wù)供應(yīng)鏈評(píng)估模型,并通過(guò)應(yīng)用MATLAB7.0對(duì)該評(píng)估模型進(jìn)行訓(xùn)練和檢驗(yàn);然后,為了進(jìn)一步檢驗(yàn)?zāi)Ｐ偷挠行?本文選取了作用于科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)的重要變量,根據(jù)變量分析結(jié)果,建立了多元二次非線性回歸預(yù)測(cè)模型,在模型檢驗(yàn)的基礎(chǔ)之上,又建立了基于殘差序列的隨機(jī)性ARMA預(yù)測(cè)模型,通過(guò)兩種模型的組合運(yùn)算結(jié)果,對(duì)未來(lái)三年的科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)進(jìn)行預(yù)測(cè)分析;最后,根據(jù)科技服務(wù)供應(yīng)鏈各構(gòu)成主體面臨的風(fēng)險(xiǎn)差異,提出相應(yīng)的保障措施。本文的主要結(jié)論包括:(1)圍繞整個(gè)科技服務(wù)供應(yīng)鏈運(yùn)作流程,從關(guān)鍵流程主體出發(fā),發(fā)現(xiàn)關(guān)鍵資源損失風(fēng)險(xiǎn)是影響科技服務(wù)供應(yīng)商的關(guān)鍵風(fēng)險(xiǎn)要素;科技服務(wù)集成商卻相對(duì)面臨更多的關(guān)鍵風(fēng)險(xiǎn)因素,主要有組織的不協(xié)調(diào)風(fēng)險(xiǎn)、供應(yīng)鏈流程中的聯(lián)盟企業(yè)間關(guān)系穩(wěn)定性差的風(fēng)險(xiǎn)、供應(yīng)鏈內(nèi)外部信息不對(duì)稱風(fēng)險(xiǎn)、科技服務(wù)集成商對(duì)科技服務(wù)供應(yīng)鏈運(yùn)作的相關(guān)政策信息解讀難的風(fēng)險(xiǎn);而對(duì)于科技用戶而言,其在最后環(huán)節(jié)面臨的關(guān)鍵風(fēng)險(xiǎn)要素是科技成果轉(zhuǎn)化率低的風(fēng)險(xiǎn)。(2)基于PCA-BP集成網(wǎng)絡(luò)的科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)等級(jí)評(píng)估模型具有較高的適用性和可靠性,能夠?qū)崿F(xiàn)對(duì)科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)的準(zhǔn)確評(píng)估、檢測(cè)與分析,并能驗(yàn)證過(guò)去幾年我國(guó)科技服務(wù)供應(yīng)鏈面臨的風(fēng)險(xiǎn)等級(jí)。(3)進(jìn)一步驗(yàn)證了科技服務(wù)供應(yīng)鏈風(fēng)險(xiǎn)等級(jí)評(píng)估模型的有效性,并能實(shí)現(xiàn)對(duì)當(dāng)前及未來(lái)科技服務(wù)供應(yīng)鏈面臨的風(fēng)險(xiǎn)水平進(jìn)行預(yù)測(cè)研究,發(fā)現(xiàn)未來(lái)三年科技服務(wù)供應(yīng)鏈仍然處于相對(duì)較高的風(fēng)險(xiǎn)狀態(tài),需要引起各相關(guān)主體的高度關(guān)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.
【學(xué)位授予單位】：重慶理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F274

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本文編號(hào)：1707427