本文選題：大數(shù)據(jù)交易 + 現(xiàn)狀　； 參考：《價格月刊》2017年12期

【摘要】：大數(shù)據(jù)具有數(shù)量巨大、信息多樣以及實時更新等特征,這會使其價值具有很大的不確定性、稀缺性和多樣性。如何進行大數(shù)據(jù)分類、科學定價以及如何進行實質性交易都是大數(shù)據(jù)發(fā)展中面臨的現(xiàn)實問題。效用價格理論可以明確大數(shù)據(jù)交易的最高定價,而成本價格理論則指出了大數(shù)據(jù)的最低定價線。我國大數(shù)據(jù)交易實踐表明,多數(shù)大數(shù)據(jù)交易平臺及其交易實踐都還處于初級階段,整個大數(shù)據(jù)交易規(guī)模也還比較小,主要原因就在于當前的大數(shù)據(jù)交易缺乏行業(yè)性的科學定價。應根據(jù)大數(shù)據(jù)的特征,采取預處理定價、大數(shù)據(jù)拍賣定價、大數(shù)據(jù)協(xié)商定價和反饋性定價等定價策略,不斷擴大大數(shù)據(jù)交易規(guī)模,加快大數(shù)據(jù)行業(yè)發(fā)展步伐。
[Abstract]:Big data has the characteristics of large quantity, diverse information and real time updating, which will make its value have great uncertainty, scarcity and diversity. How to classify big data, how to price scientifically and how to carry out substantial transaction are all the realistic problems in big data's development. The utility price theory can define the maximum price of big data's transaction, while the cost price theory points out the minimum pricing line of big data. The trading practice of big data in China shows that the majority of big data trading platform and its trading practice are still in the primary stage, and the scale of the entire big data transaction is still relatively small, which is mainly due to the lack of scientific pricing in the current big data transaction. According to the characteristics of big data, we should adopt pricing strategies such as pretreatment pricing, auctioneering pricing with big data, and pricing by way of consultation and feedback pricing, so as to expand the scale of big data trade and accelerate the pace of the development of big data industry.
【作者單位】： 吉林工程技術師范學院;
【基金】：吉林省教育科學“十二五”規(guī)劃課題“基于工作過程導向的應用型本科院校課程改革研究”(編號:GH14417)
【分類號】：F49
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本文編號：1844585