Education, Science, Technology, Innovation and Life
Open Access
Sign In

"Big data" Analysis for Inventory Diagnosis on A Publishing House

Download as PDF

DOI: 10.23977/infkm.2021.020101 | Downloads: 1 | Views: 175

Author(s)

Li Zhou 1

Affiliation(s)

1 Chongqing University Press, Chongqing, China

Corresponding Author

Li Zhou

ABSTRACT

According to the statistics of the State Administration of Press, Publication, Radio, Film and Television, the national Xinhua Bookstore system and publishers self-run publishing units are facing an increasing inventory year by year. At the end of the year 2014, inventories have exceeded the 100 billion yuan mark. Big data analysis is beginning to attract the attention of all walks of life. Publishing house inventory data is also a kind of big data, which can be used as small data in big data for definition and characteristic analysis. This work analyzed the ultimate data of A Publishing House-inventory "big data", and subdivided its inventory composition data into four aspects including textbooks, books, topic selection sections and inventory turnover rate. With the help of reverse inference, problems in various links of the publishing house were diagnosed, such as market research, topic selection planning, production, marketing, etc. The decision of optimizing the publishing house was then adjusted accordingly, making it possible for the publishing house with its inventory to develop in a healthy way.

KEYWORDS

Publishing House Inventory; Data; Turnover Rate; Reverse Analysis and Diagnosis; Sound Development

CITE THIS PAPER

Li Zhou. "Big data" Analysis for Inventory Diagnosis on A Publishing House. Information and Knowledge Management (2021) Vol. 2: 1-9. DOI: http://dx.doi.org/10.23977/infkm.2021.020101

REFERENCES

[1] Likun L. (2017) You Xindong. Research on the application of big data technology in the publishing industry. Publishing Science, 6, 20-23.
[2] Yufen S. (2016) Zhao Min. Inventory management of publishing houses in a big data environment. Science and Technology and Publishing, 5, 70-72.
[3] Xiaoming L. (2016). Some applications of big data in publishing industry. 09-17+29. http://media.people.com.cn/n1/2016/0929/c4074
[4] Zhihong Z. (2016) "Twelfth Five-Year" Publishing Industry in Numerical Reading. China News and Publication News, 09-12(9).

Downloads: 6
Visits: 1387

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.