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今天小編為大家帶來文章：81研讀分享論文5-3：精讀博士論文-《不确定性分析視角下大資料資訊服務定價研究》文獻綜述。
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Today's small series for you to bring the article:81 Study and share thesis 5-3: Intensive doctoral dissertation - Literature review of "Research on Big Data Information Service Pricing from the Perspective of Uncertainty Analysis" .
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今日内容摘要Abstract：
閱讀并分析博士論文《不确定性分析視角下大資料資訊服務定價研究》中文獻綜述的寫作。
Read and analyze the writing of the literature review in the doctoral dissertation "Research on the Pricing of Big Data Information Services from the Perspective of Uncertainty Analysis".
正文 body part：
首先，作者對不确定性的來源進行文獻分析（圖1、2）。按照該課題的研究進度，依次介紹了國外對不确定性來源的研究成果，總共得到七種來源。分别是：最終客戶需求、需求放大、制造過程的不确定性、供應不确定性、控制的不确定性、并行互動、決策的複雜性。國内學者對不确定性的來源，給出的回答有：需求不确定性和服務過程的不确定性、風險和非風險、外生不确定性和内生不确定性、市場和政策。還有一些學者針對特定的服務目标，提出了不确定性模型。作者根據國内外的研究成果，将不确定性的來源進行了分類和總結，得到内部組織不确定性、内部供應鍊不确定性和外部不确定性。
First, the authors conducted a literature analysis of sources of uncertainty (Figures 1, 2). According to the research progress of this topic, the foreign research results on the sources of uncertainty are introduced in turn, and seven sources are obtained in total. They are: final customer demand, demand amplification, manufacturing process uncertainty, supply uncertainty, control uncertainty, parallel interactions, and decision-making complexity. The answers given by domestic scholars to the sources of uncertainty include: demand uncertainty and service process uncertainty, risk and non-risk, exogenous and endogenous uncertainty, market and policy. Some scholars have proposed uncertainty models for specific service goals. According to the research results at home and abroad, the author classifies and summarizes the sources of uncertainty, and obtains the internal organizational uncertainty, internal supply chain uncertainty and external uncertainty.
圖1 Figure 1
圖2 Figure 2
對于不确定性的管理政策，作者從兩方面進行總結。分别是減少不确定性（圖3）和降低不确定性帶來的影響（圖4）。在減少不确定性方面，可以做的有精藝操作、産品設計、過程性能測量、ＤＳＳ、協同、短期計劃、決策方案和程式、資訊通信技術系統、定價政策、重構供應鍊配置和基礎設施。降低不确定帶來的影響，可行的措施有提高供應鍊的靈活性、提高制造商的靈活性。本文的研究屬于從定價方面來減少不确定性。
For the management strategy of uncertainty, the author summarizes from two aspects. These are uncertainty reduction (Figure 3) and the impact of uncertainty reduction (Figure 4). In terms of reducing uncertainty, there are refined operations, product design, process performance measurement, DSS, collaboration, short-term planning, decision-making programs and procedures, ICT systems, pricing strategies, reconfiguring supply chain configurations and infrastructure . To reduce the impact of uncertainty, feasible measures include improving the flexibility of the supply chain and improving the flexibility of manufacturers. The research in this paper belongs to reducing uncertainty from the pricing aspect.
圖3 Figure 3
圖4 Figure 4
在論述大資料資訊服務定價之前，需要先研究資訊服務定價，進一步地，需要論述定價需要考慮的因素——特定服務或産品的目标；成本函數的性質和成本回收的目的；需求和市場的性質／水準（圖5）。對于資訊服務的定價，作者首先找到了2000年關于商務資訊服務的研究文獻，文獻對該服務分類為——打包資訊服務和線上資訊服務。後續的文獻中（圖6），依次研究資訊技術服務的價值定價、網絡服務定價、銷售資訊服務的網絡平台定價、物流資訊服務定價、雲服務定價、物流平台資訊服務定價。
Before discussing the pricing of big data information services, it is necessary to study the pricing of information services. Further, it is necessary to discuss the factors that need to be considered in pricing - the goal of a particular service or product; the nature of the cost function and the purpose of cost recovery; the nature of demand and market / level (Figure 5). Regarding the pricing of information services, the author first found the research literature on business information services in 2000, and the literature classified the services as packaged information services and online information services. In the subsequent literature (Figure 6), the value pricing of information technology services, network service pricing, network platform pricing for selling information services, logistics information service pricing, cloud service pricing, and logistics platform information service pricing are studied in turn.
圖5 Figure 5
圖6 Figure 6
有了前面的文獻做理論基礎，作者進一步對大資料資訊服務定價8篇研究文獻進行分析（圖7、8）。總結來看，這8篇文章隻有一篇與大資料資訊服務定價直接相關，其他文獻則是從網絡轉換效率、雲計算平台的服務定價、大資料本身品質及價值評估等問題進行了探讨，但對大資料資訊服務的定價機制和不同主體之間的大資料資訊服務定價問題并未做深入細緻的研究。
With the previous literature as the theoretical basis, the author further analyzes 8 research literatures on big data information service pricing (Figures 7 and 8). To sum up, only one of the eight articles is directly related to the pricing of big data information services, and the other papers discuss issues such as network conversion efficiency, service pricing of cloud computing platforms, and the quality and value evaluation of big data itself. There is no in-depth and detailed research on the pricing mechanism of big data information services and the pricing of big data information services among different entities.
圖7 Figure 7
圖8 Figure 8
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參考文獻：
郭春芳. 不确定性分析視角下大資料資訊服務定價研究[D]. 北京交通大學, 2019.
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