Efficiency Evaluation of Chinese Patent Medicine Listed Companies in China – A Stock Market Based on DEA Model
- DOI
- 10.2991/icesem-18.2018.45How to use a DOI?
- Keywords
- Operating efficiency; Chinese patent medicine listed companies; DEA model; Suggestion
- Abstract
In order to improve the level of business decision-making and promote the development of Chinese patent medicine companies, this paper selects 8 indicators in the financial statements of 23 related listed companies in China A stock market in 2016 as examples. By constructing the Chinese patent medicine performance efficiency index system, our research chooses to use DEA model to estimate the comprehensive technical efficiency, pure technical efficiency, scale efficiency and scale efficiency characteristics. The results show that the overall efficiency of Chinese patent medicine listed companies is at a medium high level and the input-output ratio is generally higher. However, most companies have different degrees of DEA ineffective which have relatively stable scale efficiency and poor pure technical efficiency. We report here that the corporate managers should optimize the allocation of enterprise resources and increase investment in R&D and innovation to promote the improvement of corporate economies of scale and profit growth on the basis of maintaining the current level of fiscal management.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Kanlun Chen AU - Wuyi Song AU - Sheng Li PY - 2018/08 DA - 2018/08 TI - Efficiency Evaluation of Chinese Patent Medicine Listed Companies in China – A Stock Market Based on DEA Model BT - Proceedings of the 2018 2nd International Conference on Education Science and Economic Management (ICESEM 2018) PB - Atlantis Press SP - 205 EP - 210 SN - 2352-5398 UR - https://doi.org/10.2991/icesem-18.2018.45 DO - 10.2991/icesem-18.2018.45 ID - Chen2018/08 ER -