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Green innovation efficiency measurement and its influencing factors in specialized and new enterprises
and market position, to ensure that the sam- The method used to calculate the R&D capital
ple fully reflects the diversity of the group as a stock of an enterprise was the perpetual inven-
whole. For example, in terms of innovation abil- tory method. 43 The specific formula is shown in
ity, Wolwo Bio-Pharmaceutical (300357.SZ), and Equation (5).
Canaan Technology (300412.SZ) possess signifi-
cant R&D strength and innovation ability in their
RD it = K + (1 − δ) RD (5)
respective fields; for R&D investment, Hangzhou i(t−1) i(t−1)
Changchuan Technology (300604.SZ), and Inven-
where RD it is the R&D capital stock of an enter-
tronics (300582.SZ) have continued to increase
prise i in year t, RD i(t−1) is the R&D capital stock
R&D investment and promote technological in-
in year t−1, K i(t−1) is the R&D investment input
novation and product upgrading; and in terms of
after discounting in the early year t − 1 (the dis-
market position Jinggong Integration Technology
count rate used here was 8%), and δ is the depreci-
(002006.SZ) and Dali Technology (002214.SZ) ex- ation rate of the R&D capital stock. We assumed
hibit high visibility and competitiveness in both that the R&D capital stock at the beginning of
domestic and international markets.
the period could be expressed with Equation (6),
Collectively, these 40 enterprises are broadly
and the rise in the ratio of the R&D investment
representative in terms of industry, scale, and
inputs K and the R&D capital stock were equal.
other major features, and truly reflect the overall
strength and diversity of SNEs in Zhejiang.
RD i0 = K i0 /δ + g (6)
According to the scope and availability of
data, this paper selected information from 40 where g is the average growth rate of K. The data
SNEs in Zhejiang from 2017 to 2021. Most of used in this paper range from 2017 to 2021, and
the data were obtained from the “China Urban a 15% depreciation rate was applied to R&D ex-
Statistical Yearbook,” the Wind Database, and penditures, which is the value according to most
the Science and Technology Department websites previous studies.
of each city. The collected data were then prepro-
cessed by removing outliers and filling in missing Output indexes, according to Wang et al., 43
values, which improved the quality and usability the revenue from new product sales was gener-
of the data. Among these, the linear interpolation ally chosen as the economic output indicator.
approach was used to adjust for certain incom-
However, since enterprises did not disclose this
plete data. Linear interpolation is a simple and
indicator, the main business income of listed
easy-to-implement method. Due to its simplic-
companies was used as the alternative indica-
ity, the computational cost of linear interpolation 44
tor, referring to the practice of Qu et al. The
is relatively low, which is suitable for real-time
green innovation output indicators in the existing
applications or data processing scenarios that re- literature generally used the number of patent
quire frequent updates. 41
applications or authorizations directly, and rarely
applied green patents to measure green innova-
3.3.2. Selection of green innovation efficiency
tion output directly. The current study obtained
index of SNEs
and screened patents according to the “Green
The “input index” and “output index” categories List of International Patent Classification” issued
were chosen as the first-level indexes for evalua- by the International Intellectual Property Office.
tion when selecting the input–output index sys- Due to the delay in granting patents, it often
tem to assess the GIE in Zhejiang SNEs. Simul- took 1–2 years from the application to the grant-
taneously, considering the availability of data and ing of a patent. Therefore, the number of green
the scientific basis of the indexes, we evaluated the patents awarded can better represent the level
environmental and innovation variables based on of green innovation compared to the number of
the research findings of previous studies. 42,43 green patent applications. The authorized green
Among input indices, such as labor and capi- patents were accurately screened in the following
tal inputs, the total number of employees and the three steps: firstly, the international patent clas-
R&D personnel of enterprises were chosen as indi- sification numbers of seven major green technol-
cators of labor input, according to the custom of ogy fields, such as alternative energy production,
Yan and Zhang. 39 The capital input was selected energy efficiency improvement, and waste man-
as a measure of R&D capital stock and net fixed agement, were extracted from the list of the In-
assets of enterprises, and the annual changing rate ternational Intellectual Property Office, and the
of R&D investment input of enterprises was added scope of the target patents was locked through
as a significant reference for the capital input. 42 the combination of classification number search.
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