Research on the Innovation Efficiency of Chinese Industrial IOT Companies Based on the Three-Stage DEA Method
- DOI
- 10.2991/978-94-6463-005-3_33How to use a DOI?
- Keywords
- Industrial internet of things; Three-stage DEA model; Innovation efficiency evaluation
- Abstract
The industrial internet of things has become the key foundation to support a new round of global industrial reform because of its deep integration of the new generation of information technology and industrial systems. Its own innovation efficiency is an important factor to determine the degree of industrial integration and the competitiveness of reform. Based on the data of Chinese industrial IOT companies and using the Three-stage DEA model, this paper calculates the innovation efficiency of Chinese industrial internet of things. The results show that most industrial IOT companies in China need to focus on the improvement of pure technical efficiency while increasing R&D investment. They should not only control the amount of investment, but also pay attention to the adjustment of input-output structure. According to the research results, this paper puts forward some countermeasures and suggestions to improve the innovation efficiency of industrial IOT companies.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yitong Liu AU - Yichao Zhang PY - 2022 DA - 2022/11/10 TI - Research on the Innovation Efficiency of Chinese Industrial IOT Companies Based on the Three-Stage DEA Method BT - Proceedings of the 2022 3rd International Conference on E-commerce and Internet Technology (ECIT 2022) PB - Atlantis Press SP - 337 EP - 347 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-005-3_33 DO - 10.2991/978-94-6463-005-3_33 ID - Liu2022 ER -