Page 152 - IJOCTA-15-4

Mengxue Li et al. / IJOCTA, Vol.15, No.4, pp.686-705 (2025)
Secondly, the patent title and abstract are sup- 3.3.4. Analysis of the reasons for the results
plemented with green technology keywords, such of green innovation efficiency
as hydrogen fuel, biodiesel, and smart grid, for measurement of SNEs
secondary checking, and setting the condition Further analysis of the reasons for the low level
of “legal status=authorized” to retain only the
of GIE shows that, from the perspective of green
authorized patents that have passed the exami-
patent output, 33% of the sample enterprises have
nation of the State Intellectual Property Office,
no green patent output, which is an important
to avoid the interference of the lag period of 1–2
reason that leads to the low level of GIE within
years from application to authorization. Finally,
listed companies in China. In addition, under
the data uniqueness and classification accuracy
China’s current environmental regulation policy,
are ensured through de-duplication and manual
enterprises will actively conduct green innova-
sampling. In addition, this paper also selected
tion activities only when the cost of violating the
the ratio of enterprise R&D expenses to operat-
environmental regulation policy is much greater
ing income and operating profit as an important
than the cost of innovation activities. Other-
measurement basis of economic output indicators. wise, to chase short-term profits, enterprises often
The construction of the specific index system is choose to accept economic sanctions, such as en-
shown in Table 2.
vironmental taxes for polluting the environment,
rather than conducting innovation activities, and
therefore lack the incentive to implement green
innovation.
3.3.3. Analysis of the results of green Besides, there are many other reasons affect-
innovation efficiency measurement of ing the low level of GIE within the listed compa-
SNEs nies of SNEs in Zhejiang, such as insufficient scale
of R&D expenditures and R&D personnel, as
This paper adopts the DEA method and utilizes
well as inefficient resource allocation. The declin-
MaxDEA software (MaxDEA 5.2, MaxDEA soft-
ing trend of CRS presented by SNEs throughout
ware Ltd., China) to evaluate and decompose the
2017–2021 may be the result of China’s overall
GIE of 40 SNEs in Zhejiang. The general GIE of
downward adjustment of economic growth rate
SNEs and its decomposition items are shown in under the new normal, with elevated inputs ac-
Table 3.
companied by insufficient demand on the output
First, comprehensive technical efficiency side, which hinders efficiency.
(CRS) is a comprehensive indicator that reflects
the ability of decision-making units to allocate The overall GIE of SNEs in Zhejiang is low. It
and utilize resources. According to the mea- has been declining in recent years, and few of the
surement results, the CRS of SNEs in the years enterprises are in a state of inefficiency. Moreover,
2017–2021 were 0.807, 0.773, 0.779, 0.724, and VRS and scale have not reached the optimal level,
0.704, respectively, with an overall downward which is the main cause of the low level of GIE.
trend. This indicates that the allocation and uti- The GIE is also declining throughout 2017–2021,
lization of innovation resources by the SNEs have which may be due to the overall downward ad-
declined, and there is still some room for upward justment of China’s economic growth rate under
movement. the new normal, resulting in insufficient output
demand, and may also be related to the COVID-
Second, pure technical efficiency (VRS) re- 19 pandemic in recent years. The epidemic led
flects the part affected by enterprise management to shrinking market demand and supply chain
and technology. The VRS in the years 2017–2021 disruptions, resulting in cash flow constraints for
were 0.973, 0.919, 0.880, 0.852, and 0.836, respec- SNEs, which ultimately limited R&D investment.
tively. The average values of scale efficiency in the R&D investment, as a positive influence on GIE,
years 2017–2021 were 0.829, 0.841, 0.885, 0.850, directly impacted the financial support of green
and 0.842, respectively. The scale and VRS in technology R&D and the resulting transforma-
each year were greater than the CRS, but neither tion capacity. At the same time, enterprises need
has reached the optimal level, resulting in a low to cope with the uncertainty of the contraction of
level of GIE. Therefore, it is necessary to focus on the scale of possible involuntary or idle resources,
improving the management and technical level, which leads to a further decline in the efficiency of
as well as the scale efficiency of SNEs. resource allocation. Moreover, to maintain their
survival, environmental protection inputs, which
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