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Analysis on Core Technologies and Cutting-edge Technologies of New Energy Based on Input-output Method
Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 174 (2017) 1036 – 1045
13th Global Congress on Manufacturing and Management, GCMM 2016
Analysis on core technologies and cutting-edge technologies of new energy based on input-output method Jian-hua Liua, Zhan Menga,*,Zhao-hua Jiangb a
School of Management Engineering, Zhengzhou University, Zhengzhou 450001,China
b
Institute of Science of Science and Management of S.& T, Dalian University of Technology, Dalian 116024,China
Abstract In this paper, taking the patent for the study and using input-output analysis method distinguish the advanced technology and the core technology in the field of new energy, which makes the number of cited patents as input, and the number of published patents as output. Patent data for this paper comes from Derwent Innovation Patents Citation Index (DII), using the Python programming language to extract the patent information in PN field and CP field for each time period and each energy sector, then matching this information in SQL database, whereby the number of one energy sector cited from another energy field. Construct the patent citations matrices to identify core technologies filed and cutting-edge technologies field by induction coefficient and influence coefficient, on this basis analyze the degree of sensitivity, to further determine which energy field makes the greater impact for the development of whole new energy field. The results show that the cutting-edge technologies field is marine energy technology research and development, the core technologies field is solar technology field, the solar technology makes the greater impact for the development of whole new energy field. 2016The TheAuthors. Authors. Published by Elsevier © 2017 © Published by Elsevier Ltd. Ltd. This is an open access article under the CC BY-NC-ND license Peer-review under responsibility of the organizing committee of the 13th Global Congress on Manufacturing and Management. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 13th Global Congress on Manufacturing and Management Keywords: New energy; Induction coefficient; Influence coefficient; Sensitivity analysis; Cutting-edge technology; Core technology;
1. Introduction Rational development and efficiently use of energy in relation to the future of the world, today, the world is facing the challenge of population, resources, social development and environmental protection and other multiple pressures, but the traditional energy reserves are getting fewer, therefore, the national government have focus on the
* Corresponding author. Tel.: +86-15638863054. E-mail address: [email protected]
1877-7058 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 13th Global Congress on Manufacturing and Management
doi:10.1016/j.proeng.2017.01.256
Jian-hua Liu et al. / Procedia Engineering 174 (2017) 1036 – 1045
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development of new energy and renewable energy, gradually reduce fossil energy use. In the perspective of globalization, the energy issue has become a key problem in international politics, economy, environmental protection and many other fields, and even become the focus of international politics. Among the world's energy hegemony has fierce competition around the world, the core interest of the country have to maintain the focus on energy security strategy to develop. Governments are actively leading the development of alternative energy sources, so energy problem is increasingly becoming the focus of international attention. Oil prices continue to fluctuate, the national focus on low-carbon economy, climate change and environmental problem, government think-tank scholars also pay close attention to people's livelihood. In the energy fields, China's international cooperation is also expanding, at the begin, oil and natural gas play an important roles, and then extended to coal, electricity, wind, biomass fuels, nuclear and other new energy sources. Chinese state-owned oil companies, assume and fulfill an important mission of political, economic and social development, and also ensure national energy security; it is also made great achievements in opening up the domestic and foreign markets. However, the energy issue is no longer a simple economic problem; it is often accompanied by complex international political, economic, social and environmental factors at the overseas development. In the past, mainly based the CITESPACE software by cited frequency, intermediary, emergent and other indicators to identify core technologies and advanced technologies. Input-output analysis is widely used in industrial economic research, which use of the various types of indicators, to portray the input-output relationship between the various departments, reveal their interdependence, affect and interaction mode [1]. H.Inhaber and M.Alvo from the input-output analysis perspective use published papers as an input-output system or product, and H.Eto from journal literature citations perspectives analysis the relationship between the subjects [2]. Nomaler and Verspagen is applied the input-output analysis to the flow of knowledge, analysis the strength of different industries difference by patent reference matrix decompose into the flow of knowledge between industry and the scientific [3]. Junna Yan, Tao Zhao through establishment of input-output model to analyze the effects depth of different industries production technology change to High energy-consuming industries CO2 emissions intensity[4]. García and Vicentethe have applied input-output method to the analysis of technology diffusion and economic growth in Europe in the field of information and communication technology [5]. Jingqin Su has established the analysis framework by use of inputoutput analysis of APL and other methods to identify the core technology chain [6]. Zhaohua Jiang who calculated the technical maturity of new energy vehicles used input-output analysis [7]. Zhiqi Wang et al. Taking hybrid vehicles as an example, using input-output analysis, identification of its cutting-edge technology and core technology, and the development trend of key technology areas were analyzed[8].In this paper, take patent as our research target, which reference other patents as inputs or consume, published patent as output, use input-output analysis method, induction coefficient and influence coefficient discuss core technologies and advanced technologies of the new energy, at last, analysis patent changes of the technical field have sensitivity to the whole new energy field. 2. Technical principles and quantitative analysis method According to Jingqin Su et al. about the core technology chain and other input-output analysis method as summarized the technical principles, use influence and induction coefficient etc. calculation model, introduction of technology diffusion theory, Construction diffusion effect, absorption effect calculation model, to further improve the input-output method of patented technology. 2.1. Technical induction principle The technical field achievements, one hand come from the field itself into research, equipment, personnel and time for the results to create original and innovative; on the other hand, depending on the network technology in other technical fields of study, imitation, digestion absorption and re-innovation, it is the result of induction technology, which can be called the principle of induction technology. The technology induction principle can be used the input-output analysis method to quantitative described, assuming technology networks in the i-th fields patent number Xi, the i-th field cited j-th field patents number is Xij;
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and because the R&D expenditures reasons, technical field i original innovation is obtained patent number is Y i, then the following relationship: n
¦D
ij
X ij Yi
Xi
(1)
j 1
Among them, D ij represents technical field i reference technical field j induction effect coefficient. Referring to the input-output analysis of direct consumption coefficient, total consumption coefficient, and the corresponding matrix, the direct inductance calculated method is: the i-th technical field reference j-th technical field number of patents and the i-th technical field patent total number ratio, with the formula:
D ij=Xij / Xi (i,j=1,2,….,n)
(2)
Completely inductance denoted as bij, it is mean the i-th technical field output per of a patent, the j-th technical field the direct induction plus the indirect induction. By direct induction coefficient matrix A to compute completely inductance matrix B of formula:
B
I A
1
I
(3)
Accordingly, the induction coefficient is calculated as follows: n
¦b Uj
ij i 1 n n
(4)
1 ¦¦ bij n j1i1 n
Among them,
¦ bij represents the j-th column elements of the completely inductance matrix; i 1
1 n ¦ n j1
n
¦b
ij
i 1
represents the completely inductance matrix of columns and averaged. Induction coefficient of the induction on behalf of the network technology and other technical areas of new technology in their fields of a Technical field of, learn and absorb and re-innovation ability, we can use the induction coefficient of size identification advanced Technologies of the new energy. 2.2. Technical principle influence The technical field have impact to technical network, the hand is to other fields and self, their influence on the performance of the other members of the network technology; on the other hand, is influence the out of network technology. Technical principle influence can be used for quantitative input-output analysis method described, assuming technology field i-th patent number is Xi, technology field j-th cited by field i-th is Xij; patented technology n
reference, on the one hand is the impact on other technologies within the network
¦G j 1
the network technology; on the other hand, is out of network technology Oi Ei . Thus,
ij
X ij , to other members of
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Jian-hua Liu et al. / Procedia Engineering 174 (2017) 1036 – 1045 n
¦G
ij
X ij +Oi Ei =Ui X i
(5)
j 1
Ui X i Representative technology filed i-th overall impact inside and outside the network effect. Referring to the definition of input-output analysis method of direct consumption coefficient, the direct influence coefficient as follows: the j-th technical field reference i-th technical field number of patents and the j-th technical field patent total number ratio, with the formula: Kij
Eij X ij / X j
(i,j=1,2,….,n)
(6)
E ij represents coefficient of patent effect that the i-th technical field of effect patent j-th technical field. Similarly, we can use direct influence matrix K measure out exact complete influence coefficient matrix D, as follows: D
I K
1
I
(7)
Thus, the influence coefficient is calculated as follows: n
¦d Vi
ij
j 1 n n
1 ¦¦ dij ni1 j1 n
Among them,
¦ d ij represent complete influence coefficient matrix elements of the i-th row˗ j 1
(8)
1 n n ¦¦ d ij ni1 j1
represents the average of the complete influence coefficient. The influence coefficient represent a specific technology field have push and guiding role to others technology field or self, we can use the influence coefficient to identification core technology. 2.3. Sensitivity Analysis Sensitivity analysis is usually used to find the most critical factor, Tarancon et al. put forward a new approach by combine input-output model and the sensitivity analysis, which used to determine the impact of the most relevant in an economy the most contaminated production sector CO 2 emissions factors[9]. In 2012ˈTarancon et al. from the perspective of final demand, used sensitivity analysis based on the Leontief input - output model, the factors which influence the Spanish manufacturing industry emissions of carbon dioxide into the structural factors and technical factors, and analyze the impact of different sectors of carbon dioxide the key factor in emissions[10]. In this paper, based on the induction principle and the principle influence, reference sensitivity analysis based on input-output by Tarancon et al. proposed, study of new energy for the entire industry in the areas of sensitivity level. According to the patent cited matrix, the technical induction principle and the technical principle influence to define the most critical technology areas. For example, the impact on the entire field of nuclear technology can be divided into nuclear patent change for it impact in the next period of time and the degree of change on the patent technology in the field of wind energy, solar energy. Between two adjacent time periods, the original innovation in the field of a patent through its own technology into the formation, the change amount can be described as:
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'Xi=Xi+1-Xi (i=0,1,…,8)
(9)
Between two adjacent time periods, a technical field through technological changes affect the amount cited other technical areas; the change amount can be described as:
'Xij=X˄i+1ˈj+1˅-X˄iˈj˅(i,j=0,1,…,8)
(10)
Between two adjacent time periods, Changes in the number of patents in the field of the new energy can be expressed as:
'Yi=|Yi+1-Yi| (i =0,1,…,8)
(11)
According to the formula (9) - (11) can be draw a technical field a number of patents the new energy changes lead to the changes in the technical field of the new energy technology, the sensitivity level is calculated as follows:
H i=˄'; +'; ˅'< (i,j =0,1,…,8) i
ij
(12)
i
The formula (12) can be simplified, the sensitivity level can be drawn is calculated as follows: 8
8
8
8
H i=¦¦˄; i+j+˅; i,j˅˅|¦¦ (< i+j+˅< i,j˅)| i 0 j 0
8
Among them,
(13)
i 0 j 0
8
¦¦˄;
; iˈj˅˅representative a technical field adjacent to two periods of change in
i+ˈj+˅
i 0 j 0
8
the number of patents,
8
|¦¦ (< i+ˈj+˅< iˈj˅˅ | representative the number of patents all the changes in the new i 0 j 0
field of energy in two adjacent periods. Sensitivity analysis is a certain degree of technical change in the number of patents in the field led to the whole new energy field of changes in the number of patents, the degree of sensitivity can be used to analyze the main technical areas of impact of the new energy and the specific impact of the size. 3. Data Sources and data processing 3.1. Data sources In this paper, the patent data comes from Derwent Innovation Index(DII)patent database, which contains more than 40 patent office authorized the basic invention, which has more than 10 million patents and more than 20 millions patent information data, so it can display a comprehensive and objective patent development in various countries around the world. The definition and classification of new energy has always been closer. United Nations Development Programme (UNDP) put new energy into the following three categories: (1) large and medium hydropower; (2) new renewable energy, including small-hydro, solar, wind energy, modern biomass, geothermal, ocean energy (tidal energy); (3) traditional biomass. According to the National Science and Technology Approval Committee announced terms, new energy resources means based on the new technology, which can be systematic exploitation of renewable energy sources, such as nuclear, solar, wind, biomass, geothermal energy, ocean energy, hydrogen etc. “12th Five-Year national strategic emerging industry development plan” define the contents of the new energy use including new energy, nuclear, wind, solar photovoltaic and thermal, gas shale, biomass, geothermal and geothermal energy, biogas, biomass gasification, bio fuels and ocean energy etc.
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This paper argues that the new energy refers to new technology, there is no large-scale use, are actively research and development of energy sources, including both nuclear and unconventional fossil energy sources such as: shale gas, gas hydrates (also known as flammable ice), etc., also contains solar, wind, biomass, geothermal energy, ocean energy, hydrogen energy etc. renewable energy sources, in addition to water. So, set of nine areas of new energy and the corresponding search queries are: solar (TS = Solar energy ), nuclear power (TS = nuclear energy), wind energy (TS = Wind energy), ocean energy (TS = Ocean energy ), biomass (TS = biomass energy OR TS = bio fuels), geothermal energy (TS = geothermal energy), shale gas (TS = shale gas), hydrogen (TS = hydrogen energy), combustible ice (TS = gas Hydrate). Then every three years in the Derwent database to be searched separately as a time unit from 1991 to 1993, 1994 to 1996, 1997 to 1999, 2000 to 2002, 2003 to 2005, 2006 to 2008, 2009 to 2011 and 2012 to 2014 patent data. Specific retrieval methods are: for example, retrieving the number of patents of the nuclear energy in 2012 to 2014 , in the Derwent patent database, select advanced search, retrieval formula is (TS=nuclear energy), time is set to 2012 to 2014,retrieve the corresponding period in the number of patents in the field of nuclear energy. 3.2. Data processing In this paper, the induction coefficient and influence coefficient was calculated, we need to do some processing on the data to construct the patent citations matrices. The patent information from Derwent data downloaded including patent number (PN) field, if the patent has cited patent, the patent will also contain references to information (CP) field. Based on this, the data processing principles described as follows: Using the Python programming language to extract PN and CP field, and then in SQL database matching a technical field CP patent number and at the same time another technical field PN patent number, resulting the number of patents in a technical field cited another technology. Taking 2012 to 2014 as an example, to get the data which nuclear energy field reference wind energy field needed matching the nuclear energy field CP data and wind energy field PN data. Similarly, the availability of patent citations among other areas. Thus there can be get 2012 to 2014 patents cited matrix, shown in Table 1. The data in Table 14 of the second row of the fifth column indicates the amount of nuclear energy cited patents in the field of biomass energy is 14, and the data matrix diagonal indicates self cited patent amount of each new energy, such as the second row and second column the table 623 representatives of nuclear energy patents self cited patent amount. Table 1 2012 to 2014 various technical areas cited patents matrix a b c d e f g h i
a 623 64 76 14 9 21 1 55 0
b 69 5028 1020 45 122 69 5 103 3
c 77 1004 8598 102 27 126 0 258 2
d 14 43 102 1391 7 24 5 167 0
e 10 110 26 8 461 8 0 7 0
f 23 70 133 27 11 373 6 29 1
g 1 6 0 5 0 6 409 3 2
h 57 100 252 162 6 30 1 3130 5
i 0 3 3 1 0 1 2 5 365
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
Next, using MATLAB were calculated complete induction coefficient matrix and complete influence coefficient matrix for each new energy field. Especially, the results appear in some years in the negative when complete coefficient matrix. With careful thought and trial and error, considering this paper based on the extraction of the PN field in all patent number as the PN data sets, while PN field contains patent number one cluster. Finally, the denominator is set to 3×PN when calculation direct inductance and direct influence coefficient, that is mean use number of intervals years 3 multiplied i-th technical field of total PN. In this paper, these scenarios is calculated as a direct induction coefficient matrix and direct influence matrix, and then get complete induction coefficient matrix
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and complete influence coefficient matrix, and accordingly estimates from 1991 to 2014 every three years between the various energy technologies induction coefficient, influence coefficient and the degree of sensitivity. 4. Calculation Results 4.1. Induction coefficient: Identifying advanced technologies As mentioned above, induction coefficient representing a field to other fields or its own field induction, learn, absorb and re-innovation to ability, which we can take size of the induction coefficient identify which areas are advanced technology fields. After calculation, the new energy field induction coefficient as shown in Table 2. It can be seen in the first three years (1991 to 1993), ocean energy, nuclear energy, biomass energy, shale gas and hydrogen sensitivity, the area of induction coefficient greater than 1, the top five, indicating a higher activity, higher than the average in other areas of the induced forces. The next twenty-one years (1994 to 2014), the ocean energy, geothermal energy, biomass and nuclear energy induction coefficient basically greater than 1 and came in front of the location. Although in 19911993 and 1997-1999 geothermal energy has been ranked relatively rearward position, and are below average, but in 2006, the induction coefficient geothermal field has been dominated by the top, shows that the geothermal energy get attention in the research and development; it can be clearly seen that most of the energy technology field induced forces rankings over time there is a change, but only in the field of marine energy induced forces remain at the level of the first three, and higher than the average level of other technical areas. It showed that in the development and research of new energy, which have been in the forefront of technology in the field of marine energy technologies. Table 2 1991--2014 induction coefficient of each new energy fields No. 1
1991-1993
1994-1996
1997-1999
2000-2002
e
1.4998
i
1.4387
g
1.4635
f
1.4243
2
a
1.1972
d
1.3552
d
1.2769
e
1.1096
3
d
1.1781
e
1.2327
e
1.2577
a
1.0278
4
g
1.1079
f
1.2191
a
1.0256
d
0.9925
5
h
1.0463
a
0.9833
h
1.0256
c
0.9812
6
b
0.9656
c
0.9383
b
1.0229
h
0.9167
7
c
0.8713
h
0.9356
c
1.0216
b
0.9127
8
f
0.7339
b
0.8971
i
0.744
i
0.8449
9
i
0.3999
g
0
f
0.1622
g
0.7903
No.
2003-2005
2006-2008
1
e
1.1012
f
1.6883
2
d
1.0728
e
3
f
1.0481
a
4
a
1.0161
5
g
6 7
2009-2011
2012-2014
f
1.3601
f
1.4531
1.2964
e
1.1001
a
1.1284
0.9637
d
1.0152
e
1.0823
d
0.889
a
1.0012
h
1.0492
1.0132
h
0.8842
h
0.9958
d
1.0232
b
0.9746
g
0.8459
b
0.9344
g
0.964
h
0.9412
i
0.8445
i
0.9237
b
0.8538
8
c
0.9339
b
0.8337
g
0.8394
i
0.8368
9
i
0.899
c
0.7543
c
0.8301
c
0.6093
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
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4.2. Influence coefficient: Identifying core technologies Similarly, the influence coefficients represent a field to other fields or its own field push, guiding role, so we can use the influence coefficient to identification core technology. Accordingly, the main components of the new fields of influence coefficient as shown in Table 3.From table 3,we can be found, influence coefficient and induction coefficient have a very significant difference, look at this 24 years (1991-2014), solar and hydrogen energy influence coefficient greater than 1, higher than the average in other areas; in addition to 1991-1993 and 1997-1999, the solar energy field influence coefficient in the first, which can be seen in the whole field of research and development of new energy sources, how to exploit solar energy and related technology research began early stage and more mature, so the solar energy is the core technology. Table 3 influence coefficient of each new energy fields in 1991--2014 No.
1991-1993
1994-1996
1997-1999
2000-2002
1
h
1.4217
c
1.4901
h
1.3748
c
1.3967
2
c
1.3606
h
1.115
b
1.2009
d
1.1515
3
a
1.1757
b
1.0535
i
1.1986
b
1.0924
4
d
1.0599
a
0.9982
a
1.1731
e
1.0005
5
i
0.9794
d
0.9818
c
1.1662
h
1.0005
6
b
0.8797
f
0.8895
d
1.0943
i
1.0005
7
g
0.7816
i
0.8834
g
0.9204
a
0.9742
8
e
0.7591
g
0.8813
e
0.8717
f
0.9676
9
f
0.5822
e
0.7071
f
0
g
0.416
No.
2003-2005
2006-2008
2009-2011
2012-2014
1
c
1.3144
c
1.5073
c
1.6843
c
1.7373
2
h
1.2312
h
1.1891
b
1.5039
b
1.5665
3
i
1.2312
b
1.1871
h
1.0983
h
1.0481
4
b
1.2238
i
1.1016
i
0.9314
i
0.9589
5
d
1.0378
f
1.0798
d
0.9043
d
0.8734
6
a
0.9546
d
0.8928
a
0.8558
a
0.8127
7
f
0.9374
a
0.8093
f
0.7529
e
0.7994
8
e
0.7563
e
0.8093
e
0.718
f
0.6323
9
g
0.3133
g
0.4236
g
0.5511
g
0.5715
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
4.3. Sensitivity Analysis As described above, use formula (13) measured the degree of sensitivity of the adjacent two time periods, as well as measured the degree of 1994--2014, as well as measured a specific technical field in 21 years for the entire new energy field the average degree of sensitivity, because it’s based on the 1991-1993 expanded on an annual basis, so in table 4 there is not include degree of sensitivity in 1991-1993.The degree of sensitivity of the results shown in Table 4. Table 4 degree of sensitivity in 1994-2014 1994-1996
1997-1999
2000-2002
2003-2005
2006-2008
2009-2011
2012-2014
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a
-0.7380
0.1308
0.0372
0.0083
0.0387
0.0211
-0.0659
b
0.6725
0.2710
0.2446
0.3735
0.2123
0.2750
0.3264
c
1.5764
0.3405
0.1871
0.1959
0.3413
0.4497
0.4870
d
0.2926
-0.0107
0.0521
0.0732
0.0960
0.0977
0.1022
e
-0.0087
0.0347
0.0127
0.0460
0.0524
0.0156
0.0247
f
0.0568
-0.0761
0.0580
-0.0094
0.0612
0.0207
0.0195
g
-0.2489
0.0280
0.0326
-0.0142
0.0157
0.0117
-0.0245
h
-0.5197
0.3405
0.3314
0.2820
0.1505
0.1045
0.1282
i
-0.0830
-0.0587
0.0444
0.0448
0.0320
0.0040
0.0024
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
According to table 4, calculation the degree of sensitivity of average that a particular area for the whole new energy field in 1994-2014, show in table 5. Table 5 average degree of sensitivity in 1994-2014 field a b c d e f g h i average -0.0811 0.3393 0.5111 0.1004 0.0253 0.0187 -0.0285 0.1168 -0.0020 Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
By Table 4 and 5,we can seen in the past 21 years solar, wind, hydrogen technology play a grater role in promoting the new energy field, especially solar technology field, the average degree of influence in 21 years was 48.6964%, means it’s a huge role in the new energy field. In the table 4 and 5 have appear negative, it’s mean the technology field have having a small role in promoting the whole field of new energy or no effect. 5. Conclusion High-end equipment manufacturing industry is a leaded by high-tech, in the value chain of high-end and is the core part of the industrial chain, is the backbone of modern industrial system, is the engine to promote industrial restructuring and upgrading. With the depth of integration of the new generation of information technology and industrialization, combined with high-end equipment manufacturing industry and the Internet is the future direction of development, high-end equipment manufacturing industry has become the focus of research. By using the inputoutput analysis of nine major energy field of new energy induction coefficient, influence coefficients are calculated, to identify areas of marine energy is its advanced technology, solar energy is the core technology, and than through sensitive analysis of changes in the number of patents obtained for the entire new field of solar energy has a greater degree of influence. The results of this paper more realistic, and input-output analysis method is relatively mature, and therefore can be widely used in various industries frontier patented technology networks, and other core areas of identification and prediction, and for China to develop new energy and other related fields provide policy recommendations. Acknowledgements This study was supported by the grants of National Natural Science Foundation of China (No. 71540006). The authors would like to express their appreciation to the agencies. References [1] Z.H. Jiang, H.L. Wang, Y.W. M, et al., Interrelationship of Management, Economics, Systems Science and Mathematics: An InputˉOutput Analysis Based on Chinese Journal Articles, Science of Science and Management of S. & T. 2010(5):131-134. (in Chinese) [2] Inhaber H., Alvo M., World science as an input-output system, Scientometrics, 1978(1): 43-64. [3] Nomaler O, Verspagen B., Knowledge Flows, Patent Citations and the Impact of Science on Technology, Economic Systems Research,
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ScienceDirect Procedia Engineering 174 (2017) 1036 – 1045
13th Global Congress on Manufacturing and Management, GCMM 2016
Analysis on core technologies and cutting-edge technologies of new energy based on input-output method Jian-hua Liua, Zhan Menga,*,Zhao-hua Jiangb a
School of Management Engineering, Zhengzhou University, Zhengzhou 450001,China
b
Institute of Science of Science and Management of S.& T, Dalian University of Technology, Dalian 116024,China
Abstract In this paper, taking the patent for the study and using input-output analysis method distinguish the advanced technology and the core technology in the field of new energy, which makes the number of cited patents as input, and the number of published patents as output. Patent data for this paper comes from Derwent Innovation Patents Citation Index (DII), using the Python programming language to extract the patent information in PN field and CP field for each time period and each energy sector, then matching this information in SQL database, whereby the number of one energy sector cited from another energy field. Construct the patent citations matrices to identify core technologies filed and cutting-edge technologies field by induction coefficient and influence coefficient, on this basis analyze the degree of sensitivity, to further determine which energy field makes the greater impact for the development of whole new energy field. The results show that the cutting-edge technologies field is marine energy technology research and development, the core technologies field is solar technology field, the solar technology makes the greater impact for the development of whole new energy field. 2016The TheAuthors. Authors. Published by Elsevier © 2017 © Published by Elsevier Ltd. Ltd. This is an open access article under the CC BY-NC-ND license Peer-review under responsibility of the organizing committee of the 13th Global Congress on Manufacturing and Management. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 13th Global Congress on Manufacturing and Management Keywords: New energy; Induction coefficient; Influence coefficient; Sensitivity analysis; Cutting-edge technology; Core technology;
1. Introduction Rational development and efficiently use of energy in relation to the future of the world, today, the world is facing the challenge of population, resources, social development and environmental protection and other multiple pressures, but the traditional energy reserves are getting fewer, therefore, the national government have focus on the
* Corresponding author. Tel.: +86-15638863054. E-mail address: [email protected]
1877-7058 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 13th Global Congress on Manufacturing and Management
doi:10.1016/j.proeng.2017.01.256
Jian-hua Liu et al. / Procedia Engineering 174 (2017) 1036 – 1045
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development of new energy and renewable energy, gradually reduce fossil energy use. In the perspective of globalization, the energy issue has become a key problem in international politics, economy, environmental protection and many other fields, and even become the focus of international politics. Among the world's energy hegemony has fierce competition around the world, the core interest of the country have to maintain the focus on energy security strategy to develop. Governments are actively leading the development of alternative energy sources, so energy problem is increasingly becoming the focus of international attention. Oil prices continue to fluctuate, the national focus on low-carbon economy, climate change and environmental problem, government think-tank scholars also pay close attention to people's livelihood. In the energy fields, China's international cooperation is also expanding, at the begin, oil and natural gas play an important roles, and then extended to coal, electricity, wind, biomass fuels, nuclear and other new energy sources. Chinese state-owned oil companies, assume and fulfill an important mission of political, economic and social development, and also ensure national energy security; it is also made great achievements in opening up the domestic and foreign markets. However, the energy issue is no longer a simple economic problem; it is often accompanied by complex international political, economic, social and environmental factors at the overseas development. In the past, mainly based the CITESPACE software by cited frequency, intermediary, emergent and other indicators to identify core technologies and advanced technologies. Input-output analysis is widely used in industrial economic research, which use of the various types of indicators, to portray the input-output relationship between the various departments, reveal their interdependence, affect and interaction mode [1]. H.Inhaber and M.Alvo from the input-output analysis perspective use published papers as an input-output system or product, and H.Eto from journal literature citations perspectives analysis the relationship between the subjects [2]. Nomaler and Verspagen is applied the input-output analysis to the flow of knowledge, analysis the strength of different industries difference by patent reference matrix decompose into the flow of knowledge between industry and the scientific [3]. Junna Yan, Tao Zhao through establishment of input-output model to analyze the effects depth of different industries production technology change to High energy-consuming industries CO2 emissions intensity[4]. García and Vicentethe have applied input-output method to the analysis of technology diffusion and economic growth in Europe in the field of information and communication technology [5]. Jingqin Su has established the analysis framework by use of inputoutput analysis of APL and other methods to identify the core technology chain [6]. Zhaohua Jiang who calculated the technical maturity of new energy vehicles used input-output analysis [7]. Zhiqi Wang et al. Taking hybrid vehicles as an example, using input-output analysis, identification of its cutting-edge technology and core technology, and the development trend of key technology areas were analyzed[8].In this paper, take patent as our research target, which reference other patents as inputs or consume, published patent as output, use input-output analysis method, induction coefficient and influence coefficient discuss core technologies and advanced technologies of the new energy, at last, analysis patent changes of the technical field have sensitivity to the whole new energy field. 2. Technical principles and quantitative analysis method According to Jingqin Su et al. about the core technology chain and other input-output analysis method as summarized the technical principles, use influence and induction coefficient etc. calculation model, introduction of technology diffusion theory, Construction diffusion effect, absorption effect calculation model, to further improve the input-output method of patented technology. 2.1. Technical induction principle The technical field achievements, one hand come from the field itself into research, equipment, personnel and time for the results to create original and innovative; on the other hand, depending on the network technology in other technical fields of study, imitation, digestion absorption and re-innovation, it is the result of induction technology, which can be called the principle of induction technology. The technology induction principle can be used the input-output analysis method to quantitative described, assuming technology networks in the i-th fields patent number Xi, the i-th field cited j-th field patents number is Xij;
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and because the R&D expenditures reasons, technical field i original innovation is obtained patent number is Y i, then the following relationship: n
¦D
ij
X ij Yi
Xi
(1)
j 1
Among them, D ij represents technical field i reference technical field j induction effect coefficient. Referring to the input-output analysis of direct consumption coefficient, total consumption coefficient, and the corresponding matrix, the direct inductance calculated method is: the i-th technical field reference j-th technical field number of patents and the i-th technical field patent total number ratio, with the formula:
D ij=Xij / Xi (i,j=1,2,….,n)
(2)
Completely inductance denoted as bij, it is mean the i-th technical field output per of a patent, the j-th technical field the direct induction plus the indirect induction. By direct induction coefficient matrix A to compute completely inductance matrix B of formula:
B
I A
1
I
(3)
Accordingly, the induction coefficient is calculated as follows: n
¦b Uj
ij i 1 n n
(4)
1 ¦¦ bij n j1i1 n
Among them,
¦ bij represents the j-th column elements of the completely inductance matrix; i 1
1 n ¦ n j1
n
¦b
ij
i 1
represents the completely inductance matrix of columns and averaged. Induction coefficient of the induction on behalf of the network technology and other technical areas of new technology in their fields of a Technical field of, learn and absorb and re-innovation ability, we can use the induction coefficient of size identification advanced Technologies of the new energy. 2.2. Technical principle influence The technical field have impact to technical network, the hand is to other fields and self, their influence on the performance of the other members of the network technology; on the other hand, is influence the out of network technology. Technical principle influence can be used for quantitative input-output analysis method described, assuming technology field i-th patent number is Xi, technology field j-th cited by field i-th is Xij; patented technology n
reference, on the one hand is the impact on other technologies within the network
¦G j 1
the network technology; on the other hand, is out of network technology Oi Ei . Thus,
ij
X ij , to other members of
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Jian-hua Liu et al. / Procedia Engineering 174 (2017) 1036 – 1045 n
¦G
ij
X ij +Oi Ei =Ui X i
(5)
j 1
Ui X i Representative technology filed i-th overall impact inside and outside the network effect. Referring to the definition of input-output analysis method of direct consumption coefficient, the direct influence coefficient as follows: the j-th technical field reference i-th technical field number of patents and the j-th technical field patent total number ratio, with the formula: Kij
Eij X ij / X j
(i,j=1,2,….,n)
(6)
E ij represents coefficient of patent effect that the i-th technical field of effect patent j-th technical field. Similarly, we can use direct influence matrix K measure out exact complete influence coefficient matrix D, as follows: D
I K
1
I
(7)
Thus, the influence coefficient is calculated as follows: n
¦d Vi
ij
j 1 n n
1 ¦¦ dij ni1 j1 n
Among them,
¦ d ij represent complete influence coefficient matrix elements of the i-th row˗ j 1
(8)
1 n n ¦¦ d ij ni1 j1
represents the average of the complete influence coefficient. The influence coefficient represent a specific technology field have push and guiding role to others technology field or self, we can use the influence coefficient to identification core technology. 2.3. Sensitivity Analysis Sensitivity analysis is usually used to find the most critical factor, Tarancon et al. put forward a new approach by combine input-output model and the sensitivity analysis, which used to determine the impact of the most relevant in an economy the most contaminated production sector CO 2 emissions factors[9]. In 2012ˈTarancon et al. from the perspective of final demand, used sensitivity analysis based on the Leontief input - output model, the factors which influence the Spanish manufacturing industry emissions of carbon dioxide into the structural factors and technical factors, and analyze the impact of different sectors of carbon dioxide the key factor in emissions[10]. In this paper, based on the induction principle and the principle influence, reference sensitivity analysis based on input-output by Tarancon et al. proposed, study of new energy for the entire industry in the areas of sensitivity level. According to the patent cited matrix, the technical induction principle and the technical principle influence to define the most critical technology areas. For example, the impact on the entire field of nuclear technology can be divided into nuclear patent change for it impact in the next period of time and the degree of change on the patent technology in the field of wind energy, solar energy. Between two adjacent time periods, the original innovation in the field of a patent through its own technology into the formation, the change amount can be described as:
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'Xi=Xi+1-Xi (i=0,1,…,8)
(9)
Between two adjacent time periods, a technical field through technological changes affect the amount cited other technical areas; the change amount can be described as:
'Xij=X˄i+1ˈj+1˅-X˄iˈj˅(i,j=0,1,…,8)
(10)
Between two adjacent time periods, Changes in the number of patents in the field of the new energy can be expressed as:
'Yi=|Yi+1-Yi| (i =0,1,…,8)
(11)
According to the formula (9) - (11) can be draw a technical field a number of patents the new energy changes lead to the changes in the technical field of the new energy technology, the sensitivity level is calculated as follows:
H i=˄'; +'; ˅'< (i,j =0,1,…,8) i
ij
(12)
i
The formula (12) can be simplified, the sensitivity level can be drawn is calculated as follows: 8
8
8
8
H i=¦¦˄; i+j+˅; i,j˅˅|¦¦ (< i+j+˅< i,j˅)| i 0 j 0
8
Among them,
(13)
i 0 j 0
8
¦¦˄;
; iˈj˅˅representative a technical field adjacent to two periods of change in
i+ˈj+˅
i 0 j 0
8
the number of patents,
8
|¦¦ (< i+ˈj+˅< iˈj˅˅ | representative the number of patents all the changes in the new i 0 j 0
field of energy in two adjacent periods. Sensitivity analysis is a certain degree of technical change in the number of patents in the field led to the whole new energy field of changes in the number of patents, the degree of sensitivity can be used to analyze the main technical areas of impact of the new energy and the specific impact of the size. 3. Data Sources and data processing 3.1. Data sources In this paper, the patent data comes from Derwent Innovation Index(DII)patent database, which contains more than 40 patent office authorized the basic invention, which has more than 10 million patents and more than 20 millions patent information data, so it can display a comprehensive and objective patent development in various countries around the world. The definition and classification of new energy has always been closer. United Nations Development Programme (UNDP) put new energy into the following three categories: (1) large and medium hydropower; (2) new renewable energy, including small-hydro, solar, wind energy, modern biomass, geothermal, ocean energy (tidal energy); (3) traditional biomass. According to the National Science and Technology Approval Committee announced terms, new energy resources means based on the new technology, which can be systematic exploitation of renewable energy sources, such as nuclear, solar, wind, biomass, geothermal energy, ocean energy, hydrogen etc. “12th Five-Year national strategic emerging industry development plan” define the contents of the new energy use including new energy, nuclear, wind, solar photovoltaic and thermal, gas shale, biomass, geothermal and geothermal energy, biogas, biomass gasification, bio fuels and ocean energy etc.
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This paper argues that the new energy refers to new technology, there is no large-scale use, are actively research and development of energy sources, including both nuclear and unconventional fossil energy sources such as: shale gas, gas hydrates (also known as flammable ice), etc., also contains solar, wind, biomass, geothermal energy, ocean energy, hydrogen energy etc. renewable energy sources, in addition to water. So, set of nine areas of new energy and the corresponding search queries are: solar (TS = Solar energy ), nuclear power (TS = nuclear energy), wind energy (TS = Wind energy), ocean energy (TS = Ocean energy ), biomass (TS = biomass energy OR TS = bio fuels), geothermal energy (TS = geothermal energy), shale gas (TS = shale gas), hydrogen (TS = hydrogen energy), combustible ice (TS = gas Hydrate). Then every three years in the Derwent database to be searched separately as a time unit from 1991 to 1993, 1994 to 1996, 1997 to 1999, 2000 to 2002, 2003 to 2005, 2006 to 2008, 2009 to 2011 and 2012 to 2014 patent data. Specific retrieval methods are: for example, retrieving the number of patents of the nuclear energy in 2012 to 2014 , in the Derwent patent database, select advanced search, retrieval formula is (TS=nuclear energy), time is set to 2012 to 2014,retrieve the corresponding period in the number of patents in the field of nuclear energy. 3.2. Data processing In this paper, the induction coefficient and influence coefficient was calculated, we need to do some processing on the data to construct the patent citations matrices. The patent information from Derwent data downloaded including patent number (PN) field, if the patent has cited patent, the patent will also contain references to information (CP) field. Based on this, the data processing principles described as follows: Using the Python programming language to extract PN and CP field, and then in SQL database matching a technical field CP patent number and at the same time another technical field PN patent number, resulting the number of patents in a technical field cited another technology. Taking 2012 to 2014 as an example, to get the data which nuclear energy field reference wind energy field needed matching the nuclear energy field CP data and wind energy field PN data. Similarly, the availability of patent citations among other areas. Thus there can be get 2012 to 2014 patents cited matrix, shown in Table 1. The data in Table 14 of the second row of the fifth column indicates the amount of nuclear energy cited patents in the field of biomass energy is 14, and the data matrix diagonal indicates self cited patent amount of each new energy, such as the second row and second column the table 623 representatives of nuclear energy patents self cited patent amount. Table 1 2012 to 2014 various technical areas cited patents matrix a b c d e f g h i
a 623 64 76 14 9 21 1 55 0
b 69 5028 1020 45 122 69 5 103 3
c 77 1004 8598 102 27 126 0 258 2
d 14 43 102 1391 7 24 5 167 0
e 10 110 26 8 461 8 0 7 0
f 23 70 133 27 11 373 6 29 1
g 1 6 0 5 0 6 409 3 2
h 57 100 252 162 6 30 1 3130 5
i 0 3 3 1 0 1 2 5 365
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
Next, using MATLAB were calculated complete induction coefficient matrix and complete influence coefficient matrix for each new energy field. Especially, the results appear in some years in the negative when complete coefficient matrix. With careful thought and trial and error, considering this paper based on the extraction of the PN field in all patent number as the PN data sets, while PN field contains patent number one cluster. Finally, the denominator is set to 3×PN when calculation direct inductance and direct influence coefficient, that is mean use number of intervals years 3 multiplied i-th technical field of total PN. In this paper, these scenarios is calculated as a direct induction coefficient matrix and direct influence matrix, and then get complete induction coefficient matrix
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and complete influence coefficient matrix, and accordingly estimates from 1991 to 2014 every three years between the various energy technologies induction coefficient, influence coefficient and the degree of sensitivity. 4. Calculation Results 4.1. Induction coefficient: Identifying advanced technologies As mentioned above, induction coefficient representing a field to other fields or its own field induction, learn, absorb and re-innovation to ability, which we can take size of the induction coefficient identify which areas are advanced technology fields. After calculation, the new energy field induction coefficient as shown in Table 2. It can be seen in the first three years (1991 to 1993), ocean energy, nuclear energy, biomass energy, shale gas and hydrogen sensitivity, the area of induction coefficient greater than 1, the top five, indicating a higher activity, higher than the average in other areas of the induced forces. The next twenty-one years (1994 to 2014), the ocean energy, geothermal energy, biomass and nuclear energy induction coefficient basically greater than 1 and came in front of the location. Although in 19911993 and 1997-1999 geothermal energy has been ranked relatively rearward position, and are below average, but in 2006, the induction coefficient geothermal field has been dominated by the top, shows that the geothermal energy get attention in the research and development; it can be clearly seen that most of the energy technology field induced forces rankings over time there is a change, but only in the field of marine energy induced forces remain at the level of the first three, and higher than the average level of other technical areas. It showed that in the development and research of new energy, which have been in the forefront of technology in the field of marine energy technologies. Table 2 1991--2014 induction coefficient of each new energy fields No. 1
1991-1993
1994-1996
1997-1999
2000-2002
e
1.4998
i
1.4387
g
1.4635
f
1.4243
2
a
1.1972
d
1.3552
d
1.2769
e
1.1096
3
d
1.1781
e
1.2327
e
1.2577
a
1.0278
4
g
1.1079
f
1.2191
a
1.0256
d
0.9925
5
h
1.0463
a
0.9833
h
1.0256
c
0.9812
6
b
0.9656
c
0.9383
b
1.0229
h
0.9167
7
c
0.8713
h
0.9356
c
1.0216
b
0.9127
8
f
0.7339
b
0.8971
i
0.744
i
0.8449
9
i
0.3999
g
0
f
0.1622
g
0.7903
No.
2003-2005
2006-2008
1
e
1.1012
f
1.6883
2
d
1.0728
e
3
f
1.0481
a
4
a
1.0161
5
g
6 7
2009-2011
2012-2014
f
1.3601
f
1.4531
1.2964
e
1.1001
a
1.1284
0.9637
d
1.0152
e
1.0823
d
0.889
a
1.0012
h
1.0492
1.0132
h
0.8842
h
0.9958
d
1.0232
b
0.9746
g
0.8459
b
0.9344
g
0.964
h
0.9412
i
0.8445
i
0.9237
b
0.8538
8
c
0.9339
b
0.8337
g
0.8394
i
0.8368
9
i
0.899
c
0.7543
c
0.8301
c
0.6093
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
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4.2. Influence coefficient: Identifying core technologies Similarly, the influence coefficients represent a field to other fields or its own field push, guiding role, so we can use the influence coefficient to identification core technology. Accordingly, the main components of the new fields of influence coefficient as shown in Table 3.From table 3,we can be found, influence coefficient and induction coefficient have a very significant difference, look at this 24 years (1991-2014), solar and hydrogen energy influence coefficient greater than 1, higher than the average in other areas; in addition to 1991-1993 and 1997-1999, the solar energy field influence coefficient in the first, which can be seen in the whole field of research and development of new energy sources, how to exploit solar energy and related technology research began early stage and more mature, so the solar energy is the core technology. Table 3 influence coefficient of each new energy fields in 1991--2014 No.
1991-1993
1994-1996
1997-1999
2000-2002
1
h
1.4217
c
1.4901
h
1.3748
c
1.3967
2
c
1.3606
h
1.115
b
1.2009
d
1.1515
3
a
1.1757
b
1.0535
i
1.1986
b
1.0924
4
d
1.0599
a
0.9982
a
1.1731
e
1.0005
5
i
0.9794
d
0.9818
c
1.1662
h
1.0005
6
b
0.8797
f
0.8895
d
1.0943
i
1.0005
7
g
0.7816
i
0.8834
g
0.9204
a
0.9742
8
e
0.7591
g
0.8813
e
0.8717
f
0.9676
9
f
0.5822
e
0.7071
f
0
g
0.416
No.
2003-2005
2006-2008
2009-2011
2012-2014
1
c
1.3144
c
1.5073
c
1.6843
c
1.7373
2
h
1.2312
h
1.1891
b
1.5039
b
1.5665
3
i
1.2312
b
1.1871
h
1.0983
h
1.0481
4
b
1.2238
i
1.1016
i
0.9314
i
0.9589
5
d
1.0378
f
1.0798
d
0.9043
d
0.8734
6
a
0.9546
d
0.8928
a
0.8558
a
0.8127
7
f
0.9374
a
0.8093
f
0.7529
e
0.7994
8
e
0.7563
e
0.8093
e
0.718
f
0.6323
9
g
0.3133
g
0.4236
g
0.5511
g
0.5715
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
4.3. Sensitivity Analysis As described above, use formula (13) measured the degree of sensitivity of the adjacent two time periods, as well as measured the degree of 1994--2014, as well as measured a specific technical field in 21 years for the entire new energy field the average degree of sensitivity, because it’s based on the 1991-1993 expanded on an annual basis, so in table 4 there is not include degree of sensitivity in 1991-1993.The degree of sensitivity of the results shown in Table 4. Table 4 degree of sensitivity in 1994-2014 1994-1996
1997-1999
2000-2002
2003-2005
2006-2008
2009-2011
2012-2014
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Jian-hua Liu et al. / Procedia Engineering 174 (2017) 1036 – 1045
a
-0.7380
0.1308
0.0372
0.0083
0.0387
0.0211
-0.0659
b
0.6725
0.2710
0.2446
0.3735
0.2123
0.2750
0.3264
c
1.5764
0.3405
0.1871
0.1959
0.3413
0.4497
0.4870
d
0.2926
-0.0107
0.0521
0.0732
0.0960
0.0977
0.1022
e
-0.0087
0.0347
0.0127
0.0460
0.0524
0.0156
0.0247
f
0.0568
-0.0761
0.0580
-0.0094
0.0612
0.0207
0.0195
g
-0.2489
0.0280
0.0326
-0.0142
0.0157
0.0117
-0.0245
h
-0.5197
0.3405
0.3314
0.2820
0.1505
0.1045
0.1282
i
-0.0830
-0.0587
0.0444
0.0448
0.0320
0.0040
0.0024
Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
According to table 4, calculation the degree of sensitivity of average that a particular area for the whole new energy field in 1994-2014, show in table 5. Table 5 average degree of sensitivity in 1994-2014 field a b c d e f g h i average -0.0811 0.3393 0.5111 0.1004 0.0253 0.0187 -0.0285 0.1168 -0.0020 Notice: a to i representative nuclear energy, wind energy, solar energy, biomass, ocean energy, geothermal energy, shale gas, hydrogen, combustible ice.
By Table 4 and 5,we can seen in the past 21 years solar, wind, hydrogen technology play a grater role in promoting the new energy field, especially solar technology field, the average degree of influence in 21 years was 48.6964%, means it’s a huge role in the new energy field. In the table 4 and 5 have appear negative, it’s mean the technology field have having a small role in promoting the whole field of new energy or no effect. 5. Conclusion High-end equipment manufacturing industry is a leaded by high-tech, in the value chain of high-end and is the core part of the industrial chain, is the backbone of modern industrial system, is the engine to promote industrial restructuring and upgrading. With the depth of integration of the new generation of information technology and industrialization, combined with high-end equipment manufacturing industry and the Internet is the future direction of development, high-end equipment manufacturing industry has become the focus of research. By using the inputoutput analysis of nine major energy field of new energy induction coefficient, influence coefficients are calculated, to identify areas of marine energy is its advanced technology, solar energy is the core technology, and than through sensitive analysis of changes in the number of patents obtained for the entire new field of solar energy has a greater degree of influence. The results of this paper more realistic, and input-output analysis method is relatively mature, and therefore can be widely used in various industries frontier patented technology networks, and other core areas of identification and prediction, and for China to develop new energy and other related fields provide policy recommendations. Acknowledgements This study was supported by the grants of National Natural Science Foundation of China (No. 71540006). The authors would like to express their appreciation to the agencies. References [1] Z.H. Jiang, H.L. Wang, Y.W. M, et al., Interrelationship of Management, Economics, Systems Science and Mathematics: An InputˉOutput Analysis Based on Chinese Journal Articles, Science of Science and Management of S. & T. 2010(5):131-134. (in Chinese) [2] Inhaber H., Alvo M., World science as an input-output system, Scientometrics, 1978(1): 43-64. [3] Nomaler O, Verspagen B., Knowledge Flows, Patent Citations and the Impact of Science on Technology, Economic Systems Research,
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