Bulletin of Chinese Academy of Sciences (Chinese Version)
Keywords
data elements, market allocation efficiency, network DEA, Malmquist index, total factor productivity
Document Type
Research on Market-oriented Allocation of Data Elements
Abstract
Promoting the market allocation of data elements is the key to realize the value of data resources, which drives the high-quality development of digital economy. Based on the literature review, this study first analyses the theoretical process of market allocation of data elements, and divides the whole process into two stages: market-based construction and value-based allocation. According to the proposed theoretical model, this study designs the network DEA model with additional intermediate inputs to calculate the market allocation efficiency of data elements of 30 provincial administrative regions in China from 2019 to 2020. Moreover, by Malmquist index analysis, we further investigate the dynamic changes of both market allocation efficiency of data elements and total factor productivity in China. The study finds that during the period of 2019 to 2020, the market allocation efficiency of data elements in China is on an upward trend. The efficiency of value-based allocation stage reached a higher level than that of the market-based allocation stage. This finding suggests that the orderly opening of public data and the construction of data trading platform will still be the focus in improving the market allocation efficiency of data elements in the future. The results of the study further indicates that China’s total factor productivity increased significantly—both the technology progress and the improvement of market allocation efficiency of data elements had a positive effect on improving total factor productivity, and the latter driving force is more critical to promoting the improvement of total factor productivity.
First page
1444
Last Page
1456
Language
Chinese
Publisher
Bulletin of Chinese Academy of Sciences
References
1 蔡跃洲, 马文君. 数据要素对高质量发展影响与数据流动制约. 数量经济技术经济研究, 2021, 38(3): 64-83.
Cai Y Z, Ma W J. How data influence high-quality development as a factor and the restriction of data flow. The Journal of Quantitative & Technical Economics, 2021, 38(3): 64-83. (in Chinese)
2 黄少安, 张华庆, 刘阳荷. 数据要素的价值实现与市场化配置. 东岳论丛, 2022, 43(2): 115-121.
Huang S A, Zhang H Q, Liu Y H. Value realization and market allocation of data production factors. Dong Yue Tribune, 2022, 43(2): 115-121. (in Chinese)
3 Pantelis K, Aija L. Understanding the value of (big) data//2013 IEEE International Conference on Big Data. IEEE, 2013: 38-42.
4 杨艳, 王理, 廖祖君. 数据要素市场化配置与区域经济发展——基于数据交易平台的视角. 社会科学研究, 2021(6): 38-52.
Yang Y, Wang L, Liao Z J. Market allocation of data production factors and regional economic development— From the perspective of data trading platform. Social Science Research, 2021(6): 38-52. (in Chinese)
5 陈德球, 胡晴. 数字经济时代下的公司治理研究: 范式创新与实践前沿. 管理世界, 2022, 38(6): 213-240.
Chen D Q, Hu Q. Corporate governance research in the digital economy: New paradigms and frontiers of practice. Journal of Management World, 2022, 38(6): 213-240. (in Chinese)
6 Jones C I, Tonetti C. Nonrivalry and the economics of data. American Economic Review, 2020, 110(9): 2819-2858.
7 Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research, 1978, 2(6): 429-444.
8 Färe R, Grosskopf S, Whittaker G. Network DEA// Zhu J, Cook W D, eds. Modeling data irregularities and structural complexities in data envelopment analysis. Boston: Springer, 2007: 209-240.
9 Kao C, Hwang S N. Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research, 2008, 185(1): 418-429.
10 马建峰, 戚丽囡, 邓立治. 考虑追加投入的混联两阶段DEA 效率评价. 系统工程学报, 2020, 35(2): 276-288.
Ma J F, Qi L N, Deng L Z. DEA efficiency evaluation of hybrid two-stage system with additive inputs. Journal of Systems Engineering, 2020, 35(2): 276-288. (in Chinese)
11 黄丽华, 窦一凡, 郭梦珂, 等. 数据流通市场中数据产品的特性及其交易模式. 大数据, 2022, 8(3): 3-14.
Huang L H, Dou Y F, Guo M K, et al. Features and transaction modes of data products in data markets. Big Data Research, 2022, 8(3): 3-14. (in Chinese)
12 Färe R, Grosskopf S, Norris M, et al. Productivity growth, technical progress, and efficiency change in industrialized countries. The American Economic Review, 1994: 66-83.
13 郑京海, 刘小玄, Bigsten A. 1980—1994期间中国国有企业的效率、技术进步和最佳实践. 经济学(季刊), 2002(2): 521-540.
Zheng J H, Liu X X, Bigsten A. Efficiency, technical progress, and best practice in Chinese state enterprises (1980–1994). China Economic Quarterly, 2002(2): 521-540. (in Chinese)
14 蔡昉. 以提高全要素生产率推动高质量发展. 人民日报, 2018-11-09(07). Cai F. Promote high-quality development by improving total factor productivity. People’s Daily, 2018-11-09(07). (in Chinese)
15 Jones M D, Hutcheson S, Camba J D. Past, present, and future barriers to digital transformation in manufacturing: A review. Journal of Manufacturing Systems, 2021, 60: 936-948.
Recommended Citation
QIAO, Han and LI, Zhuolun
(2022)
"Research on Market Allocation Efficiency of Data Elements,"
Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 37
:
Iss.
10
, Article 10.
DOI: https://doi.org/10.16418/j.issn.1000-3045.20220629001
Available at:
https://bulletinofcas.researchcommons.org/journal/vol37/iss10/10