The evolution of data pricing: From economics to computational intelligence

被引：7
|
作者：
Hao, Jun [1 ,2 ]
Deng, Zeyu [1 ,2 ]
Li, Jianping [1 ,2 ]
机构：
[1] Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China
[2] UCAS, MOE Social Sci Lab Digital Econ Forecasts & Policy, Beijing, Peoples R China
来源：
HELIYON | 2023年 / 9卷 / 09期
基金：
中国国家自然科学基金;
关键词：
Data pricing; Pricing approach; Bibliometric analysis; Data market; Future work; BIBLIOMETRIC ANALYSIS; BUNDLING STRATEGY; SERVICE; MODEL; WEB; BLOCKCHAIN; CITESPACE; SELECTION; PRODUCTS;
D O I：
10.1016/j.heliyon.2023.e20274
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Data pricing, which aids in articulating the worth and advantages of data and encourages its opening, sharing, and circulation, is an indispensable component of data trading. Studies pertinent to the topic of data pricing are continuously developing. To undertake a thorough analysis of the literature in data pricing, we use bibliometric and statistical methods for the first time. The 373 data pricing publications from 1990 to 2023 are the study's research object. We mainly analyze the external characteristics, keyword co-occurrence and co-citation networks of data pricing. We find that data pricing has been progressing fairly quickly during the last decade. Two basic approaches have been used by researchers to study how to price various data objects: one is based on economics theory, and the other on computer science algorithms. We provide an indepth study of the overall evolution of data pricing and give the future directions of data pricing.
引用
收藏
页数：18
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