本文選題：大數(shù)據(jù) + 農(nóng)超對接供應鏈��； 參考：《江西財經(jīng)大學》2017年碩士論文

【摘要】：伴隨著人們對大數(shù)據(jù)認識的不斷深入,大數(shù)據(jù)的應用在各行各業(yè)不斷滲透,大數(shù)據(jù)思維正通過驅(qū)動經(jīng)營決策的管理變革、商業(yè)模式的創(chuàng)新、運營管理的提升、科技創(chuàng)造的進步等多種方式為社會主體創(chuàng)造新的價值源泉。農(nóng)超對接是近幾年我國提倡和發(fā)展的重要農(nóng)產(chǎn)品流通方式,而農(nóng)超對接風生水起的背后,卻難掩農(nóng)超對接供應鏈叫苦不迭的現(xiàn)實。農(nóng)超對接供應鏈遇到不少痛點,如供需分散、產(chǎn)品非標準化、鏈條中斷、物流成本高,嚴重限制了農(nóng)超對接的正常發(fā)展。大數(shù)據(jù)的應用,能在很大程度上實現(xiàn)整條供應鏈的數(shù)據(jù)共享,將有效解決這些問題。大數(shù)據(jù)在給農(nóng)超對接供應鏈帶來便利的同時,也不可避免的帶來了新風險。本文旨在分析大數(shù)據(jù)環(huán)境下農(nóng)超對接供應鏈的基礎(chǔ)上,研究新環(huán)境下農(nóng)超對接供應鏈的風險識別、風險評價和風險控制三個方面。首先,本文在研究背景中對農(nóng)超對接的背景進行了介紹,并對國內(nèi)外大數(shù)據(jù)應用、農(nóng)超對接、農(nóng)產(chǎn)品供應鏈、供應鏈風險管理都進行了綜述。接著對傳統(tǒng)農(nóng)產(chǎn)品供應鏈、傳統(tǒng)農(nóng)超對接供應鏈都進行了相關(guān)介紹,過渡到對大數(shù)據(jù)環(huán)境下農(nóng)超對接供應鏈的介紹,其中分為五個環(huán)節(jié),即生產(chǎn)環(huán)節(jié)、加工環(huán)節(jié)、配送環(huán)節(jié)、零售環(huán)節(jié)、銷售環(huán)節(jié)。另外,分析了農(nóng)超對接供應鏈存在的問題,大數(shù)據(jù)應用后的好處,并從生產(chǎn)環(huán)節(jié)、加工環(huán)節(jié)、配送環(huán)節(jié)、零售環(huán)節(jié)、銷售環(huán)節(jié)五個方面對風險進行識別,其中包括傳統(tǒng)環(huán)境下已存在的風險及大數(shù)據(jù)引進之后帶來的新風險。其次,本文采用定性分析和定量計算相結(jié)合的方式來進行風險評價。與已有文獻不同的是,本文通過實證分析的方法,通過對農(nóng)民專業(yè)合作社、超市和消費者相關(guān)的人員方法問卷,得出所有風險因素的排序,很好的客服了主觀排除影響小和概率較小的缺陷;然后對排在前十的風險因素用FLINMAP法進行評價,給出了相關(guān)的模糊評價等級和風險評價的標準,通過專家評價,也得出了新的風險排序,與實證分析結(jié)果相差不大,也對實證結(jié)果的進行了驗證。再次,對農(nóng)超對接供應鏈進行風險控制。主要以演化博弈的方法為主,把農(nóng)戶和超市利益看做衡量農(nóng)超對接供應鏈穩(wěn)定性的標準,分析了傳統(tǒng)風險和大數(shù)據(jù)引進的風險帶來后對農(nóng)超對接供應鏈穩(wěn)定性的影響,從實現(xiàn)農(nóng)超對接雙方利益的最大化目的的角度,得出了理性的風險控制措施。
[Abstract]:With the deepening of people's understanding of big data, the application of big data has been permeated in all walks of life. Big data thinking is driving the management reform of management decision, the innovation of business model, the promotion of operation management. The progress of science and technology creates a new source of value for social subjects. Agricultural super docking is an important agricultural product circulation mode advocated and developed in our country in recent years, but it is difficult to hide the reality of agricultural super docking supply chain. There are many pain points in the supply chain, such as the dispersion of supply and demand, the non-standardization of products, the interruption of chain and the high cost of logistics, which seriously limit the normal development of agricultural docking. The application of big data can realize the data sharing of the whole supply chain to a great extent, which will solve these problems effectively. Big data not only brings convenience to supply chain, but also inevitably brings new risks. The purpose of this paper is to study the risk identification, risk evaluation and risk control of the agricultural super docking supply chain under the new environment based on the analysis of the supply chain in the big data environment. First of all, this paper introduces the background of agricultural super docking in the research background, and summarizes the application of big data, agricultural supply chain, supply chain risk management at home and abroad. Then the traditional agricultural product supply chain, the traditional agricultural supply chain, the transition to the big data environment of agricultural supply chain introduction, which is divided into five links, that is, production, processing, distribution, Retail link, sales link. In addition, the paper analyzes the problems existing in the supply chain, the benefits of the application of big data, and identifies the risks from five aspects: production, processing, distribution, retail and sales. These include the existing risks in the traditional environment and the new risks brought about by the introduction of big data. Secondly, this paper uses qualitative analysis and quantitative calculation to carry out risk assessment. Different from the existing literature, this paper through the empirical analysis method, through the farmers' professional cooperatives, supermarkets and consumers related to the personnel method questionnaire, the ranking of all risk factors, Very good customer service, subjective elimination of small impact and small probability of defects; then the top 10 risk factors were evaluated by FLINMAP method, given the relevant fuzzy evaluation level and risk evaluation criteria, through expert evaluation, The new risk ranking is also obtained, which is not different from the empirical analysis results, and the empirical results are verified. Thirdly, we control the risk of agricultural supply chain. Based on the evolutionary game, the interests of farmers and supermarkets are regarded as the standard to measure the stability of the supply chain, and the influence of the traditional risk and the risk introduced by big data on the stability of the supply chain is analyzed. The rational risk control measures are obtained from the view of maximizing the interests of both parties.
【學位授予單位】：江西財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F326.6;F721.7

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