【摘要】：大數(shù)據(jù)時(shí)代,數(shù)據(jù)以及數(shù)據(jù)分析技術(shù)是企業(yè)在競(jìng)爭(zhēng)中獲得優(yōu)勢(shì)的重要資源。在企業(yè)的運(yùn)營(yíng)過(guò)程中每時(shí)每刻都會(huì)有海量的信息數(shù)據(jù)的產(chǎn)生,重視對(duì)信息數(shù)據(jù)的處理和分析可以為企業(yè)帶來(lái)巨大的經(jīng)濟(jì)價(jià)值。然而當(dāng)前供應(yīng)鏈上需求管理模式的弊端越來(lái)越突出,已無(wú)法滿(mǎn)足當(dāng)前大數(shù)據(jù)的需要。因此本文運(yùn)用大數(shù)據(jù)理論為完善供應(yīng)鏈上需求管理理論體系提供理論依據(jù),而且為提升供應(yīng)鏈整體競(jìng)爭(zhēng)力提供實(shí)際意義。本文的重點(diǎn)在于探討應(yīng)用大數(shù)據(jù)理論進(jìn)行對(duì)需求管理的改善。其第一章介紹了國(guó)內(nèi)外供應(yīng)鏈管理中需求管理的研究現(xiàn)狀,并第二章敘述了供應(yīng)鏈上需求共享理論、博弈論、協(xié)同學(xué)理論、大數(shù)據(jù)等關(guān)鍵技術(shù),為構(gòu)建基于大數(shù)據(jù)理論的需求信息大數(shù)據(jù)平臺(tái)提供理論基礎(chǔ)和技術(shù)支撐。第三章通過(guò)對(duì)傳統(tǒng)的需求管理中的諸多問(wèn)題進(jìn)行原因和危害分析,發(fā)現(xiàn)其共通的原因——需求信息不共享,進(jìn)而在第四章提出應(yīng)用大數(shù)據(jù)等技術(shù)構(gòu)建以需求信息數(shù)據(jù)共享分析為核心的大數(shù)據(jù)平臺(tái)。本文的核心是構(gòu)建基于大數(shù)據(jù)理論的大數(shù)據(jù)平臺(tái),在結(jié)合平臺(tái)構(gòu)建可行性和原則的基礎(chǔ)上,提出平臺(tái)具有共享需求信息、協(xié)調(diào)鏈上成員企業(yè)等功能。為了實(shí)現(xiàn)上述功能,本文設(shè)計(jì)了平臺(tái)的總體架構(gòu),并具體分為五個(gè)步驟;需求信息大數(shù)據(jù)的獲取、需求信息大數(shù)據(jù)加工存儲(chǔ)、需求信息大數(shù)據(jù)組織管理、需求信息大數(shù)據(jù)分析以及需求信息大數(shù)據(jù)的決策。在需求信息獲取中引入大數(shù)據(jù)理論,旨在匯集供應(yīng)鏈上所有成員企業(yè)經(jīng)營(yíng)中需求信息和鏈外相關(guān)需求信息以及政府政策環(huán)境信息等數(shù)據(jù);為了保障眾多的需求信息數(shù)據(jù)的完整,在大數(shù)據(jù)存儲(chǔ)中建立需求信息數(shù)據(jù)相應(yīng)的數(shù)據(jù)倉(cāng)庫(kù),保障能儲(chǔ)存越來(lái)越多的信息數(shù)據(jù);在大數(shù)據(jù)的組織管理中,是為了實(shí)現(xiàn)需求信息數(shù)據(jù)高效整合和有效利用;在大數(shù)據(jù)分析中提出大數(shù)據(jù)挖掘技術(shù)中的規(guī)則性數(shù)據(jù)分析、預(yù)測(cè)性數(shù)據(jù)分析方法,并從眾多的需求信息數(shù)據(jù)中預(yù)測(cè)市場(chǎng)需求;在最后階段,利用數(shù)據(jù)得出的結(jié)果進(jìn)行決策。在安全機(jī)制中引入了安保措施,以保障需求信息數(shù)據(jù)在供應(yīng)鏈上保存完整和安全。最后,第五章引入傳統(tǒng)需求管理中三個(gè)特殊現(xiàn)象作為分析對(duì)象,分析應(yīng)用大數(shù)據(jù)技術(shù)后,這三個(gè)傳統(tǒng)的需求管理問(wèn)題與應(yīng)用前進(jìn)行對(duì)比,從而驗(yàn)證平臺(tái)的優(yōu)越性。本文的創(chuàng)新點(diǎn)在于:其一,將大數(shù)據(jù)理論引入供應(yīng)鏈上需求管理中,擴(kuò)大需求信息的范圍,并豐富了需求信息共享化理論體系,也順應(yīng)了當(dāng)前大數(shù)據(jù)時(shí)代的發(fā)展趨勢(shì)。其二,從供應(yīng)鏈的實(shí)際需要角度出發(fā),探討并構(gòu)建了大數(shù)據(jù)平臺(tái)的總體架構(gòu)和應(yīng)用職能,并讓信息數(shù)據(jù)具有決策的功能,來(lái)幫助企業(yè)管理者進(jìn)行科學(xué)決策。
[Abstract]:In the era of big data, data and data analysis technology is an important resource for enterprises to gain advantages in competition. In the process of enterprise operation, there is a huge amount of information data at every moment, so it can bring great economic value to enterprises to pay attention to the processing and analysis of information data. However, the drawback of demand management mode in supply chain is more and more prominent, which can not meet the needs of current big data. Therefore, this paper uses big data theory to provide theoretical basis for improving the theoretical system of supply chain demand management, and provides practical significance for enhancing the overall competitiveness of supply chain. This paper focuses on the application of big data theory to improve demand management. The first chapter introduces the research status of demand management in supply chain management at home and abroad, and the second chapter describes the key technologies of supply chain demand sharing theory, game theory, collaboration theory, big data and so on. It provides theoretical foundation and technical support for constructing big data platform of requirement information based on big data theory. The third chapter analyzes the causes and harm of many problems in the traditional demand management, and finds out that the common reason is that the demand information is not shared. In the fourth chapter, we put forward the application of big data and other technologies to construct a big data platform which is based on the analysis of information and data sharing. The core of this paper is to build a big data platform based on big data theory. On the basis of the feasibility and principle of constructing the platform, it is proposed that the platform has the functions of sharing demand information, coordinating the member enterprises in the chain, and so on. In order to realize the above functions, this paper designs the overall architecture of the platform, and it is divided into five steps: the acquisition of the requirement information big data, the processing and storage of the requirement information big data, the organization and management of the requirement information big data. Requirement information big data analysis and requirement information big data decision making. In order to ensure the integrity of numerous demand information, big data theory is introduced into the demand information acquisition, which aims to collect the data of all member enterprises in the supply chain, such as the demand information, the off-chain demand information and the government policy environment information, and so on, in order to ensure the integrity of the numerous demand information data. In order to realize the efficient integration and utilization of the demand information data in the organization and management of big data, the corresponding data warehouse of the requirement information data is established in the storage of big data to ensure that more and more information data can be stored. In the analysis of big data, the methods of regular data analysis and predictive data analysis in big data mining technology are put forward, and the market demand is forecasted from a lot of demand information data, and in the final stage, the results obtained from the data are used to make decision. Security measures are introduced into the security mechanism to ensure the integrity and security of demand information data in the supply chain. Finally, the fifth chapter introduces three special phenomena in traditional demand management as the analysis object. After analyzing the application of big data technology, the three traditional requirement management problems are compared with those before application, so as to verify the superiority of the platform. The innovation of this paper lies in the following: firstly, the big data theory is introduced into the demand management of supply chain, which expands the scope of demand information, enriches the theoretical system of sharing demand information, and conforms to the development trend of current big data era. Secondly, from the point of view of the actual demand of supply chain, this paper discusses and constructs the overall structure and application function of big data platform, and makes the information data have the function of decision making, to help enterprise managers to make scientific decision.
【學(xué)位授予單位】：北京建筑大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：F274

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