4.5 Article

Enhancing Digital Innovation for the Sustainable Transformation of Manufacturing Industry: A Pressure-State-Response System Framework to Perceptions of Digital Green Innovation and Its Performance for Green and Intelligent Manufacturing

期刊

SYSTEMS
卷 10, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/systems10030072

关键词

digital green innovation; manufacturing industry; carbon neutral; carbon peak; innovation-driven development

资金

  1. office of Research, Innovation, and Commercialization (ORIC) of Riphah International University Lahore [Riphah-ORIC-21-22/FEAS-20]
  2. Philosophy and Social Sciences Planning Project of the Ministry of Education [21YJCZH203]
  3. Soft Science Special Project of Hebei Innovation Capability Enhancement Program [21557635D]
  4. Social Science Fund project of Hebei Province [HB21YJ003]
  5. Top Young Talents Scientific Research Project of Higher Education in Hebei Province [BJ2021084]
  6. Baoding Philosophy and Social Science Planning Project [2020047]
  7. Teaching and Research Project of Hebei Agricultural University [2021C-39]
  8. Scientific Research Foundation for the Talents of Hebei Agricultural University [YJ2020017]
  9. Heilongjiang University Special Fund Project [2020-KYYWF-0969]
  10. Philosophy and Social Science research Planning project of Heilongjiang Province [20JYB030]
  11. Hebei Agricultural Industry System Project [HBCT2021230301]

向作者/读者索取更多资源

Low carbon and digitalization are general trends in the upgrading and transformation of manufacturing. Digital technology enables green innovation in manufacturing and breaks spatial barriers. This study analyzes the pressure-state-response model of digital green innovation in the manufacturing industry and constructs an evaluation model to measure its level. The study finds regional differences in the level of digital green innovation in the Chinese manufacturing industry and identifies key factors that influence it.
Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables the green innovation of the manufacturing industry, was theoretically analyzed in this study. The measurement system of the digital green innovation (DGI) in the manufacturing industry was constructed according to the PSR framework. An evaluation model based on the analytic hierarchy process and the deviation maximization technique for order preference by similarity to an ideal solution method was constructed to measure the level of DGI. The results of this study from Chinese manufacturing are as follows. (i) The measurement system of the level of DGI in manufacturing industry includes a pressure system, state system and response system. (ii) In the past five years, the comprehensive index of the DGI in manufacturing industry has generally shown a trend of fluctuating rise. There are overall low and unbalanced phenomena in all regions. The gap decreased from 0.1320 to 0.1187, showing a gradually narrowing trend. (iii) Compared with other regions, the composite index of DGI is generally higher in the regions with a better ecological environment in the east and a more developed economy in the north. State parameters are higher than pressure and response parameters in most areas. (iv) Compared with other regions, the composite index of DGI in western and southern regions is lower, and the parameters of pressure, status and response are basically coordinated. (v) The application degree of digital technology, the emission intensity of waste water/exhaust gas of output value of one hundred million yuan and the expenditure intensity of digital technology adopted by enterprises are the key influencing factors of DGI in the manufacturing industry. This study not only proposed an evaluation index system of the digital green innovation level, but also puts forward policy guidance and practical guidance of digital technology to accelerate the green and intelligent manufacturing industry.

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