Technological trajectories provide valuable information on technological development as well as its potential impact. Using 3D printing technology as a case study, this paper maps the trajectory of technological development and explores the contribution of various knowledge sources (from both geographical and technological perspectives). Based on patent citation analysis, our results show that there was a main concentrated technological trajectory between 1998 and the early 2000s, indicating a technology lock-in situation. However, a great diversification can be observed after the mid-2000s. The U.S. and Japan were the pioneer countries to develop core 3DP technologies, while China and South Korea contributed relatively more to the recent core 3DP technologies. By tracking technology domains in the patents cited by 3DP technologies, we also detect contributions from different technology categories in the process of 3DP technology development. At a disaggregated level, this study provides insights on how technologies from various fields contributed to the development of 3D printing technology. The diversified knowledge contributions from different countries and different fields indicate not only a broader range of future business opportunities in various domains, but also a far-ranging social impact in various nations.

1. Contents lists available at ScienceDirect
Technological Forecasting & Social Change
journal homepage: www.elsevier.com/locate/techfore
Mapping technological trajectories and exploring knowledge sources: A case
study of 3D printing technologies
Lili Wanga
, Shan Jiangb
, Shiyun Zhangc
a
UNU-MERIT, Maastricht University, Maastricht, the Netherlands
b
Wuhan Library, Chinese Academy of Sciences, China
c
Beijing Institute of Science and Technology Information, Beijing Academy of Science and Technology, China
A R T I C L E I N F O
Keywords:
Technological trajectory
Patents
Citations
Knowledge sources
Three dimensional printing
A B S T R A C T
Technological trajectories provide valuable information on technological development as well as its potential
impact. Using 3D printing technology as a case study, this paper maps the trajectory of technological devel­
opment and explores the contribution of various knowledge sources (from both geographical and technological
perspectives). Based on patent citation analysis, our results show that there was a main concentrated techno­
logical trajectory between 1998 and the early 2000s, indicating a technology lock-in situation. However, a great
diversification can be observed after the mid-2000s. The U.S. and Japan were the pioneer countries to develop
core 3DP technologies, while China and South Korea contributed relatively more to the recent core 3DP tech­
nologies. By tracking technology domains in the patents cited by 3DP technologies, we also detect contributions
from different technology categories in the process of 3DP technology development. At a disaggregated level,
this study provides insights on how technologies from various fields contributed to the development of 3D
printing technology. The diversified knowledge contributions from different countries and different fields in­
dicate not only a broader range of future business opportunities in various domains, but also a far-ranging social
impact in various nations.
1. Introduction
Technological advance is an accumulative progress which involves
various possible technological directions and continuous changes.
Towards a good understanding of technological development as well as
its potential impact, existing literature emphasises the importance of
insights on technological trajectories (Robinson et al., 2013, 2018;
Berg et al., 2018; Verspagen 2007). Technological development is
fuelled by knowledge, and knowledge elements embodied on the evo­
lutionary trajectory provide an important foundation for technology
forecasting (Watts and Porter 1997; Daim et al., 2006; Robinson et al.,
2018).
A technological trajectory presents the direction of advance toward
progressive exploitation of latent economic or technological opportu­
nities (Nelson and Winter, 1975; Dosi 1982). Knowledge accumulated
in the technological trajectory provides the momentum to enable or
constrain further technological development, which also lays an im­
portant foundation for technology forecasting (Garud and Karnøe 2003;
Robinson et al., 2018; Watts and Porter 1997; Daim et al., 2006). There
can be technological convergence shaped by standards (Kim et al.,
2017), fusion of cross-disciplinary technology (No and Park 2010), or
diversification driven by new technological combinations
(Cantwell and Vertova 2004) or divergent patenting strategies
(David et al., 2011). Emerging technological branches can be driven by
the combination of knowledge from various sources (Nakamura et al.,
2015). Identifying and understanding knowledge formation is an es­
sential step to forecast innovation process (Berg et al., 2018;
Robinson et al., 2013; Robinson et al., 2018). Building upon the tech­
nological evolution theories and aiming at detecting knowledge re­
sources, this paper empirically looks at the development of 3D printing
technologies and examine what types of trajectories 3D printing tech­
nologies have followed in the past decades.
The paper is organized as follows. Section two presents the theo­
retical background and literature review related to technological tra­
jectory, knowledge sources and 3DP technology development. Section
three describes the data collection and methodology. Results are pro­
vided in Section four. This consists of mapping the 3DP trajectory (in­
cluding countries and time stage), comparison of knowledge contribu­
tions from different countries and different technological branches.
Conclusions and discussions are provided in the last section.
https://doi.org/10.1016/j.techfore.2020.120251
Received 15 December 2019; Received in revised form 1 August 2020; Accepted 10 August 2020
E-mail addresses: wang@merit.unu.edu (L. Wang), jiangs@whlib.ac.cn (S. Jiang), zhangsy@bjstinfo.com.cn (S. Zhang).
Technological Forecasting & Social Change 161 (2020) 120251
Available online 26 August 2020
0040-1625/ © 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
T

2. 2. Theoretical background and hypotheses
2.1. Technological trajectory and lock-in
A technological trajectory presents a cluster of problem solving
activities and captures continuous changes related to the technological
progress (Dosi 1982). With connected technological changes, a trajec­
tory can indicate the direction of technological progress. A trajectory
can present different types of technological development, e.g. stable
path and emerging and branching innovation pathways
(Robinson et al., 2018). The formation of a technological trajectory is
usually shaped by various technological, social and economic factors
(Kim et al., 2017; Cantwell and Vertova 2004; David et al., 2011).
Taking the trajectory in the automobile and airplane industries as an
example, a high level of variation existed in the earlier stage of de­
velopment but a stable path appeared after one dominant technology
emerged and industry standards were introduced (Anderson and
Tushman, 1990). In such a trajectory, more incremental changes are
expected (Kaplan and Vakili).
Due to the influence of earlier technologies on subsequent ones,
technological changes captured by a trajectory are characterized by the
path-dependent nature (Momeni and Rost, 2016; Kim et al., 2017;
Verspagen 2007). In the literature, many have demonstrated the path
dependent and lock-in feature of technological development
(Rothmann and Koch, 2014; Autant-Bernard et al., 2013; Fleming and
Sorenson, 2001; Kim et al., 2017; Diaz et al., 2016; Arthur, 1989).
Technologies can be locked into established patterns due to many
reasons, e.g. the interdependent nature of technological elements
(Fleming and Sorenson, 2001; Arthur, 1989), high switching costs
(Arthur, 1989; Hillman, K. M. and Sandén), or the selection of certain
standards (D. Kim et al., 2017). Such lock-in situations are observed not
only in the technological domains (Kaplan and Vakili, 2013) but also in
a regional context (Autant-Bernard et al., 2013). Accordingly, we pre­
dict:
Hypothesis 1. There was a stage of a technological lock-in situation in
the 3D printing technological trajectory.
While the path-dependence and catching up theories tend to suggest
a concentrated technological trajectory, there have been studies pro­
posing more diversified development patterns in the technology-
economy domain. First, based on a revisited evolutionary growth
model, Fagerberg and Verspagen (2002) emphasize the mixed impact of
technology diffusion and innovation. If technology diffusion or tech­
nology learning is regarded as an importance source for convergence,
then (radical) innovation is the source to increase the technology gap
and lead to uneven growth paths and divergence (Silverberg &
Verspagen, 1995; Fagerberg and Verspagen, 2002; Gkypali et al.,
2019). Whether there is convergence or divergence depends on the
balance between the rate of technological advances in the lead coun­
tries/regions and technology diffusion to the less advanced countries/
regions (Verspagen, 1991; Wang and Szirmai, 2013). Second, from a
micro perspective, a group of literature emphasizes the nature of het­
erogeneity in the process of evolutionary change (Dosi and
Nelson, 2010; Dosi et al., 2010; Dosi, 1988; Gkypali et al., 2019). As
stressed by Dosi et al. (2010), there is persistent heterogeneity in all
dimensions of business firms’ characteristics. Technologies captured in
technological trajectories present “specific patterns of solution to se­
lected techno-economic problems”, to meet the needs and technical
requirements of the users (Dosi and Nelson, 2010, p. 66). Hence, re­
sponding to such potential demand requirements, technology advances
are inevitably influenced by firms’ heterogenous activities, compe­
tencies, capabilities, and specific markets, which will in turn lead to
more specific development Acosta and Coronado, 2003routes (Dosi and
Nelson, 2010; Dosi, 1988; Gkypali et al., 2019). Third, in the con­
vergence and divergence debate, it is worthy to note that it is not ne­
cessary to have one monotonous pattern. Convergence and divergence
can go hand in hand. By exploiting a dataset of 17 European countries
and 13 industries, Gkypali et al. (2019) find that a within-group con­
vergence process is linked to the between-group divergence process.
Different patterns can also be observed in different technological do­
mains and different development stages (Karvonen and Kässi, 2013;
Fagerberg and Verspagen, 2002).
In the development of technological trajectory, due to certain spe­
cific needs and competencies, there are possibilities that technologies
break out from one trajectory (Kaplan and Vakili, 2013; Dolfsma and
Leydesdorff, 2009). Locked-in technological regimes can also develop
to more diversified paths and create an irregular burst of technological
change, when a “tipping point” is achieved (Diaz et al., 2016). The
question is, for the 3D printing technology, whether the changing point
has been reached. According to the wide application of 3DP ranges from
prototypes (Mahindru and Mahendru 2013), creative industries
(Leigh et al., 2012) to medical implants (Lee 2016; Murphy and Atala
2014), we expect that 3D printing technologies are getting more and
more diversified. Hence the following hypothesis is developed:
Hypothesis 2. A “tipping point” has emerged in 3D printing technological
trajectory to lead to diversified technological changes.
2.2. Tracing knowledge flows in the trajectory
It has been well recognized that it is difficult to trace knowledge
flows. By providing a paper trial in linking up different inventions, ci­
tations documented in patents provide an efficient approach to solve
this problem (Jaffe et al., 1993; Jaffe and Trajtenberg 2002). As stated
by Jaffe and Trajtenberg (2002), “the large volume and wide coverage
of patent citations data make them extremely useful” for innovation
studies. Patent citations provide evidence of the links between in­
novation and (scientific and technological) knowledge that preceded it
(Trajtenberg et al., 1992).
Citations in one patent reveal that the knowledge in this patent has
developed from (or is related to) the knowledge described in other
patents published earlier. The availability of patent citation data makes
it possible to measure and track knowledge flows (Jaffe et al., 1993;
Jaffe and Trajtenberg, 2002; Verspagen 2007; Wang and Li, 2020;
Wang and Li, 2018; Hummon and Doreian, 1989). Patent references
cited by the inventor represent the knowledge flows from the cited
work to the new invention. On the one hand, knowledge flows can be
linked between individual inventions. On the other hand, by tracing the
inventor's name, country and year in which the patents were granted,
one can also view the locations where the technological innovation took
place and the year when the patent was publicly announced.
There are clusters or sub-streams in the development of technolo­
gical trajectories. The main path, however, provides the most important
information on the major stream of knowledge flows and represents the
greatest connectivity of different technologies (Verspagen 2007; ;
Fontana et al., 2009).
In many technological fields, core technologies were mostly (or al­
most all) developed by advanced countries, such as the U.S. or
European countries. Consequently, many studies on technology plan­
ning and forecasting were conducted based only on the U.S. patent
database (Daim et al., 2006; Kim et al., 2016). In recent years, less
developed countries have become more and more involved in devel­
oping emerging technologies, such as 3D printing. However, it is be­
lieved that technological knowledge stemmed mainly from advanced
countries (Mahindru and Mahendru, 2013). Accordingly, we predict:
Hypothesis 3. Developed countries have been dominating the main stream
of knowledge flows in 3D printing technologies.
2.3. Knowledge variation, technological and geographical perspectives
Invention has been seen as a process of recombinant search over
technology domains, and technological evolution is regarded as a
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
2

3. recombination of new and existing technological components
(Fleming and Sorenson 2001; Karvonen and Kässi 2013). Inventors
combine elements purposely to solve certain problems. If some ele­
ments from other domains are potentially valuable, as stated by
Hargadon and Sutton (1997, p.746), “individuals and organizations can
create innovative new concepts by acquiring, storing, and retrieving
these ideas in new combinations and by transferring these combinations
to new audiences.”
A combination of diverse technological components can help avoid
technology lock-in and lead to creative ideas or breakthroughs
(Kaplan and Vakili, 2013; Fleming 2001; Rosenkopf and Nerkar 2001)
and have higher social impact ( Keijl et al., 2016).
With the increase of the interdisciplinary character in science and
technology (Su and Moaniba 2017; Wang et al., 2013), it is expected
that there will be more and more overlapping concepts, skills or tools
across different fields (Harianto and Pennings 1994; No and Park 2010).
Hypothesis 4. Knowledge variety increases along with technological
development.
Besides the technological dimension, the evolution of technology
should also be explored from its geographic dimension. The distribution
of knowledge has always been uneven and high technologies have been
dominated by a few advanced countries. Patent citation provides a
helpful measure to detect the knowledge flows between geographic
units (Jaffe et al., 1993; Jaffe and Trajtenberg, 1999). Using patent
citation data, Jaffe and Trajtenberg (1999) investigate the patterns of
patent citation among the U.S., U.K., France, Germany, and Japan, and
find that there are country-specific citation tendencies and that in­
ventors are more likely to cite patents from the same country. Yet the
geographical localization fades over time and it is expected that
“eventually the probability of an antecedent benefiting a remote des­
cendant may be no lower than the probability of benefiting one nearby”
(Jaffe and Trajtenberg, 1999, p.108). Using a similar method, Hu and
Jaffe (2003) analyze the pattern of knowledge flows from the U.S. and
Japan to Korea and Taiwan, and conclude that it is much more likely for
Korean patents to cite Japanese patents than U.S. patents, whereas
Taiwanese inventors tend to learn evenly from both. Acosta and
Coronado (2003) also point out that social determinants of innovation –
including political, economic and industrial institutions, etc. – cause
profound differences between regions. Accordingly, we have the fol­
lowing hypothesis:
Hypothesis 5. There exist significant differences in developing 3D printing
technologies between developed and less developed regions.
3. Three-dimensional (3D) printing technology: history and
impact
Three-dimensional printing (3DP), known as additive manu­
facturing, is a process of creating physical objects from a digital design.
The 3D printing process starts from a digital 3D model measured by
computer aided design (CAD) software. The printing process is to lay
down and fuse successive fine layers – which are in the x, y and z di­
rections – to construct geometries (Berman 2012; Vaezi et al., 2013;
Wohlers and Gornet 2014).
In 1984, Charles Hull, co-founder and chief technical officer of 3D
Systems, applied for a U.S. patent titled Apparatus for Production of
Three-Dimensional Objects by Stereolithography (SLA) ,1
which de­
scribes a process of photo-hardening a series of cross sections using a
computer-controlled beam of light. SLA is a technique using ultraviolet
(UV) light to solidify liquid resin and create models, prototypes etc.
(Bogers et al., 2016; Sætre 2013).
In the late 1980s, various non-SLA technologies developed. In 1989,
Carl Deckard and Joe Beaman at the University of Texas at Austin in­
vented Selective Laser Sintering (SLS). SLS uses a laser beam as the
power source to sinter powdered material (typically nylon or poly­
amide) to create 3D structure as the 3D model. The SLS technique was
commercialized by DTM Co., a start-up of University of Texas at Austin
(Liu and Lin 2014).2
Other non-SLA technologies also include Fused
Deposition Modeling (FDM) from Stratasys and Laminated Object
Manufacturing (LOM) from Helisys (Wohlers and Gornet 2014). These
techniques enabled the emergence of low-cost 3D printing machines
(Leigh et al., 2012; Xu et al., 2018). Based on the technology developed
at IBM's Watson Research Center, Stratasys introduced its low-cost 3D
printer in 1996.3
In the same year, both 3D Systems and Z Corp. also
launched their own 3D printing machines (Wohlers and Gornet 2014),
and the term “3D Printer” was used to refer to all the additive manu­
facturing (Chua and Leong 2015).
After 2000, along with the further development of 3D printing
technologies, more and more competitive companies from outside of
the U.S. (e.g. Japan, Germany and Israel) participated in the process of
commercializing 3D printing technologies (Wohlers and Gornet 2014).
This not only increased the variety of available 3D printers in the
market, but also improved the printing techniques and equipment re­
markably in different ways. For instance, following DTM's laser sin­
tering techniques, Electro Optical Systems (EOS) from Germany in­
troduced its direct metal laser sintering machine which uses a fiber
laser rather than a CO2 laser. Israel-based Cubital commercialized 33
3D printing processes over a short period of time (Wohlers and Gornet
2014).
In recent years, the 3D printing business has expanded to a wider
range of countries, including latecomers such as Korea and China. In
particular in China, 3D printing business has been growing at an annual
rate of 100%.4
Due to the wide involvement of various countries and various in­
dustries related to 3D printing, in the digital era, 3D printing is re­
garded as socially transformative technology with great socioeconomic
implications (Ratto and Ree 2012). With 3D printers, economies of
scale no longer matter (Baumers et al., 2016) and factories in the future
will change from traditional mass manufacturing to more personalized
products with a small production volume (The Economist 2011;
Sætre 2013).
4. Data and methodology
4.1. Data collection
Patent data have been collected through the Thomson Innovation
(TI) platform from Derwent World Patent Index (DWPI).5
Given that
there is no pre-classified international patent classification (IPC) for
3DP patents, searching by keywords is a commonly adopted method
(Kim et al., 2016; Liu and Lin 2014; Huang et al., 2017). In line with
Huang et al. (2017) and Kim et al. (2016), we extracted 3DP patents
based on series of keywords, including 3D print, Additive Manu­
facturing, Rapid prototyping, and the key 3D printing techniques, i.e.
Stereolithography, Fused Deposition Model, Laser sintering, Direct
metal deposition, Bioprinting, Layered object manufacturing, Selective
laser melting and Electron beam melting. The query we used in the
searching, which takes wording variation into account is: TI=(((3d) or
(three ADJ dimension*) or (3 ADJ dimension*)) adj (print* or
1
Charles Hull. Apparatus for production of three-dimensional objects by
stereolithography. US4575330A
2
DTM was acquired by 3D Systems in 2001.
3
Known as the “Genisys” machine (Wohlers and Gornet, 2014; Chua and
Leong, 2015).
4
https://www.statista.com/statistics/870778/china-3d-printing-market-
size/
5
Thomson innovation guide. http://info.thomsoninnovation.com/sites/
default/files/assets/ti_user_guide_zh.pdf.
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
3

4. manufact*)) OR AB=(((3d) or (three ADJ dimension*) or (3 ADJ di­
mension*)) adj (print* or manufact*)) OR TI=((Rapid ADJ protyp*) or
(Rapid ADJ manufacturing) or (Addictive ADJ manufacturing) or bio­
print* or Stereolithograph* or (Fused ADJ Deposition ADJ Model*) or
(Laser ADJ Sinter*) or (Direct ADJ Metal ADJ Deposition) or (Layered
ADJ Object ADJ Manufact*) or (Select* ADJ laser ADJ melt*) or
(Electron ADJ beam ADJ melt*)) OR AB=((Rapid ADJ protyp*) or
(Rapid ADJ manufacturing) or (Addictive ADJ manufacturing) or bio­
print* or Stereolithograph* or (Fused ADJ Deposition ADJ Model*) or
(Laser ADJ Sinter*) or (Direct ADJ Metal ADJ Deposition) or (Layered
ADJ Object ADJ Manufact*) or (Select* ADJ laser ADJ melt*) or
(Electron ADJ beam ADJ melt*)).6
Based on this query, we extracted in total 37,803 granted patents,
which were further distributed into 19,961 patent families. The dataset
covers all available patents from any year and any patent authorities
covered by DWPI.
Citations were gathered from Derwent Patents Citations Index
(DPCI). For all the 3D printing patents collected above, we have in total
217,109 patent citations,7
which are from 44,664 patent families.
4.2. The main path of 3DP technology
Citation links are used to trace knowledge flows or connectivity
between patents. We label year and country for each patent family, in
order to track knowledge flows according to time and location. The year
is defined by the earliest publication year of all the patents in the same
patent family. Country label is defined by the nation of inventor(s). If
there are multiple inventors in one patent publication, we label only the
country of the first inventor. In creating the main technological path of
technological development in the long run, we follow the method
proposed by Liu et al., (2013). Technological trajectories are mapped
with software Pajek.
By tracing the citation links between different patents, we construct
a citation network in which the nodes represent 3DP patents. The link
between two nodes represents the citation relationship, and knowledge
flows from the cited node to the citing node. In a citation network,
sources are the nodes that are cited but cite no others and sinks are those
citing other nodes but not cited. Sources and sinks are usually located at
the edges. The nodes with both citing and cited links are crucial for
connecting the network.
In our work, we use Search Path Count (SPC) to measure the sig­
nificance of a link. The SPC measurement was first proposed by
Batagelj (2003) and has been widely used ever since then. A link's SPC
is the number of times the link is traversed if one runs through all
possible paths from all the sources to all the sinks. Fig. 1 presents an
example of calculating SPC values for links in a citation network. The
SPC value for the link (B, D) is 5 because there are five paths (B-D-F-H-
K, B-D-F-I-L, B-D-F-I-M-N, B-D-I-L, and B-D-I-M-M) traverse through it.
Based on the traversal counts of each links in the citation network, we
use Global Search to find out the most significant path(s).8
Global
Search method suggests the citation chain(s) with the largest overall
SPC. In Fig. 1, for instance, the global main path of the sample citation
network based on SPC is B-D-F-I-M-N, which has the largest sum of all
the SPC values among all possible paths. More discussions on the search
path can be found in David et al. (2011). Different from the existing
literature (Hummon and Doreian, 1989; Verspagen 2007; Liu et al.,
2013; David et al., 2011), this study pays special attention to the
country origin of knowledge sources and the emergence of latecomer
countries.
4.3. Knowledge variation index
Using the citation information collected above, we further in­
vestigate knowledge variation from two perspectives: (a) knowledge
origin variety and (b) technological domain variety.
The variety level is measured by the following equation:
=
=
P
Var 1 ( )
i
N
i
P
1
2
i
(1)
Where Pi is the number of patents in i category, i.e. by country group or
by technological group. Hence the variety level can be understood as 1
minus Herfindahl–Hirschman index (Hirschman, 1964), i.e. =
( )
i
N P
1
2
i
Pi
.
The variety level ranges from 0 to 1. A high variety indicates a wide
range of knowledge sources, while a low variety indicates a high con­
centration of knowledge sources. Among the 19,961 3DP patent fa­
milies and cited 44,664 patent families, technology fields are examined
based on the DWPI Manual Code, which was assigned by teams of
Thomson Reuters analysts who have been specially trained in the ap­
plication of these codes (Larner 2013).
We collect the DWPI codes at the second level (e.g. A11 or A12).9
Based on the cited frequency, we rank the citation groups according to
the second level DWPI codes. Thus we derive the top technology fields
contributing as knowledge sources to the development of 3DP tech­
nology.
5. Results and discussions
This section provides empirical studies from three perspectives.
First, we provide the general information of 3DP development and
country differences. Second, we map technological trajectories of 3DP
inventions,10
illustrating the core technologies contributed by different
countries. Third, by tracking the detailed information of patents cited
by 3DP inventions, we investigate the knowledge sources for the de­
velopment of 3D printing technologies. Knowledge sources are de­
composed into both geographical and technological dimensions.
5.1. Development of 3D printing (3DP) technologies
The development of 3D printing technologies can be dated back to
the 1980s in the U.S., marked by the publication of patent family
EP171069A2. In this patent family, according to the application year,
the earliest patent was US4575330A filed in 1984, which proposed a
type of technology named Stereolithography. In 1986, the inventor of
this patent, Charles Hull, co-funded 3D systems – the first 3D printing
Fig. 1. Example of path count search.
Source: https://en.wikipedia.org/wiki/Main_path_analysis.
6
The final data collection was done on 7 March 2017.
7
Backward citations.
8
We have also testes Global Search and the result stays similar to that of
Global Search.
9
Which is also called 3-digit DWPI code.
10
Based on patent analysis, needless to say, 3DP inventions mention in this
study refers to patented 3DP inventions.
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
4

5. company in the world.11
In the past decades, 3D printing technologies
have increased dramatically. The volume of granted patent families
increased at a rate of 23 percent per year, from 17 in 1985 to 6951 in
2015.
In the analysis on patents decomposed by geographical locations,
we focus on the top 20 countries with the highest patent numbers until
2015. To ensure a comparable basis, Fig. A1 (in the appendix) presents
the performance of four regional groups, i.e. the U.S. Europe,12
China
and the remaining top 20 countries. In the earlier years, not surpris­
ingly, U.S. kept the dominant position. For instance, in the period of
1991–95, the U.S. accounted for 77 percent of the total patents in the
top 20 countries (see Fig. A1). After 1995, Europe and Japan start to
witness the development of 3DP technologies, following which, the
U.S.’s share went down by 10 percent in the late 1990s. However, the
U.S. showed an obvious increase in the early 2000s, with a share of
more than 77 percent again during 2000 and 2005. Compared to the
other three regional groups, China stayed in the lowest position for
most of the years. After 2012, however, China's 3DP patents out­
performed European countries and reached to a number similar to the
U.S.. It worth noting that there is a drop in the patent number in 2015,
mainly due to the delay in filing patent publications, i.e. the 2015 pa­
tent data in the system was not complete yet.
5.2. Main path of 3D printing (3DP) technologies
The creation of a new technology usually begins from the places
where the innovation capability is high. The same rule also applies to
the development of 3D printing technologies and it is not surprising
that the advanced countries played an important role in its initial stage
of technological development.
Patent citations are used to connect different patents and trace the
knowledge flows in the development of 3D printing technologies. For
the collected 19,961 3D patent families and the 44,664 cited patent
families, we have in total 85,484 citing-cited pairs. Citing patents are
the knowledge recipients and cited patents represent the knowledge
resources.
In theory, the year of citing patent families should be later than the
cited ones. However, due to the fact that a patent family includes a
series of patents with different publication dates, and that the year la­
belled on the map is defined only by the earliest publication year of all
the patents in the same patent family, it can happen that a patent family
seemingly cited one from an even later publication year. For instance,
the earliest patent (A1) in a patent family was published in 2006. Thus
we labelled the publication year of patent family A as 2006. In patent
family B, the earliest patent was published in 2004 and we labelled the
publication year of patent family B as 2004. However, there is one
patent (B2) published in 2007 that cited A1. Thus at the patent family
level, we will have patent family A (labelled in the year of 2006) that
was cited by patent family B (labelled in the year of 2004). Fig. 2 il­
lustrates the misalignment citations between patent families.13
Apart
from the few exceptional cases with misalignment citations, the re­
maining citation links in the main path are all with logical years.
Based on the citation linkages, we use Search Path Count (explained
in Section 3.3) to map the main path of 3D printing technologies (see
Fig. 3). In the trajectory map, the arrow line illustrates citation relations
between patent families, while the arrow head is directed from the cited
to the citing ones. This trajectory map provides important information
from two perspectives, i.e. both technological and geographical com­
positions.
First, from the technological perspective, according to the content
and the relatedness of different technologies, the trajectory of 3D
printing technologies can be further classified into five development
stages. The first one, shown in red squares, presents the earliest 3DP
technologies, related to basic techniques in Additive manufacturing and
Stereolithography. At this development stage, representative technol­
ogies include WO1989008021A1_1989_US14
documenting a Stereo­
lithography (SLA) technique on solidifying liquid resin and using
composition providing reduced distortion, and US4844144A_1988_US
presenting a method of investment casting utilizes a pattern produced
by stereolithography in which a three-dimensional specimen is pro­
vided by light cure of ethylenically unsaturated liquid material. A set of
core technologies on Selective Laser Sintering (SLS) emerged in the late
1980s and early 1990s. This includes three core patent families from
The University of Texas System,15
and one from the Massachusetts In­
stitute of Technology (CA2031562A1_1990_US) on fabricating
moulds and prototypes; and one from DTM Corporation
(WO1994015265A1_1993_US) on automated scanning
calibration for selective laser sintering. Patent families
represented by US4938816A_1989_US, US5053090A_1990_US,
WO1992010343A1_1991_US and WO1994015265A1_1993_US demon­
strate the remarkable contribution from the University of Texas at
Austin and DTM Corporation in this stage of 3D printing development.
The second development stage, shown in blue squares, includes
patents that mainly introduced methods to derive data for forming high
resolution three-dimensional object. This includes a series of inventions
from 3D Systems16
and one joint invention (EP606627A1_1993_US)
from IBM Corporation and Stratasys Inc. The latter seems to have
provided an important knowledge basis for the development of Genisys
printer – as mentioned in Section 3 – which was introduced by Stra­
tasys.
The third one, in green, indicates a group of patents applying
technologies such as beam Stereolithography equipment and Optical
molding apparatus etc. The main contribution at this stage comes from
techniques related to calibration and improvement of printing equip­
ment. Different from earlier technological development, stage 3 wit­
nessed the emergence of inventions from non-US countries. For in­
stance, Toyota Jidosha KK and Matsushita Electric Works LTD from
Japan contribute to the main-path by improving the deviation control
and positioning system in 3D printing.17
Evonik-Degussa from Germany
Fig. 2. Example of misalignment citations between patent families.
11
https://www.3dsystems.com/our-story.
12
This refers to the European countries in the top 20 with highest 3D printing
patent numbers, including Germany, UK, Switzerland, the Netherlands, France,
Italy, Belgium, Denmark and Sweden
13
Among the 86 nodes in the main path, there are five such citation pairs, e.g.
CA2031562A1_1990_US cited WO1992020505A1_1992_US;
US20060032838A1_2004_US cited JP2008037024A_2006_JP;
WO2005090055A1_2005_DE cited DE201010005162U1_2010_DE;
US20110282482A1_2010_US cited WO2012143786A1_2012_IT ; and
KR2015069403A_2013_KR cites WO2015026201A1_2014_KR.
14
Each patent ID mentioned in this section represents a patent family.
15
They are US4938816A_1989_US on technologies related to selective laser
sintering with assisted powder handling, US5053090A_1990_US on component
manufacture by powder metallurgy with several selectively laser sintered
layers, and WO1992010343A1_1991_US on producing parts by compound
formation of precursor powders.
16
Including WO1989010801A1_1989_US, WO1992008200A1_1991_US,
WO1995029053A2_1995_US, US5999184A_1995_US,
WO1996023647A2_1996_US, WO1998048997A1_1998_US,
EP1025980A2_2000_US, EP1025981A2_2000_US.
17
JP2002210835A_2001_JP and JP2004162095A_2002_JP.
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5

6. presents core inventions to improve the selective heating system.18
EOS, who was one of the precursors in commercializing direct metal
laser sintering machines – as mentioned in Section 3 – also contributed
in this group, see patent ID: EP1048441A1_2000_DE.
An interesting observation is that there is only one main path
without other different directions through this development stage,
suggesting that technology lock-in took place. However, after this stage,
more diversified directions can be seen. A close look at the cross section
reveals that three patents developed based on a substantially large
amount of knowledge resources. They are WO2004113042A2_2004_US,
US20080138515A1_2007_US, WO2008086033A1_2008_US, with red
underlining in Fig. 3. On average, each 3DP patent on the main path
cites 37 patents (see Table 1, first column). These three patents, how­
ever, were developed based on a substantially high number of knowl­
edge resource, citing 406, 396 and 372 patents respectively. If we look
at the technology category information, the number of DWPI category
of these three patents does not seem to differ from the average number
of all patents on the main path (see second column in Table 1). From
the knowledge supply side, however, there is again a substantial dif­
ference between these three patents and the average (see the last
column in Table 1). For instance, WO2008086033A1_2008_US and
US20080138515A1_2007_US cited patents from 92 different technology
categories, which is substantially higher than the main path average
(20.2).
The high number of backward citations and the high number of
technology categories in cited citations indicate a high level of
knowledge combination captured by these three patents. In accordance
with their positions in the trajectory map (Fig. 3), these three patents
seem to play a role as “tipping-point” to usher in a more diversified era.
After the cross-section in the trajectory map, there are two tech­
nology groups heading in different directions. After going through the
abstracts of patents on the main path and classifying the patents in the
path into different groups, based on the content of each patent (family),
we classify them into two groups. The purple group, consists of tech­
nologies related to 3D printing materials. At this stage, we can observe
the variation not only in contributing countries but also in technolo­
gical themes (branches). There are inventions not only from long-ex­
isting technological leaders such as 3D Systems and Z Corporation,19
but also from latecomers from China (e.g. Guangzhou Aoqu Electronic
Technology Co., Beijing Inst Petrochemical Technology, etc.). These
Fig. 3. Technological trajectories of 3DP technologies.
Table 1: Comparison
of tipping-point patents and other patents on the main path.
No. of
backward
citations
No. of 3-
digit DWPI
code
No. of backward
citation’ 3-digit
DWPI
Main path patents (average) 37 3.4 20.2
WO2008086033A1_2008_US 406 3 92
US20080138515A1_2007_US 396 7 92
WO2004113042A2_2004_US 372 4 88
18
DE202010005162U1_2010_DE, WO2005090055A1_2005_DE and
WO2005105412A1_2005_DE.
19
WO2004113042A2_2004_US, US20070241482A1_2007_US,
WO2008086033A1_2008_US, and US20080138515A1_2007_US.
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
6

7. inventions are related to a wide range of new methods, e.g. forming
electrically conductive structure in 3D surface
(US20100055895A1_2008_US), printing with wood materials
(CN103665905A_2013_CN) and soft elastic rubber materials
(CN104004377A_2014_CN, CN104292850A_2014_CN), and handling
environmentally friendly materials (CN104744869A_2015_CN), etc.
They represent a gradual increase in the types of additive manu­
facturing materials. These techniques (e.g. covered by
US20100055895A1_2008_US and US20130170171A1_2012_US) not
only enable small scale additive manufacturing with highly complex
electronic structures, but also reduce the material waste, energy, pro­
totyping time and other related costs.
And the last group, in brown, is comprised of technologies related to
3D printers. The inventions related to the materials, process and
equipment from 3D Systems and Z Corporation – on melting and ad­
hering particulate (including loose and dry) material20
– played an
important role not only in developing 3D printing materials (purple
group) but also in shaping 3D printers (brown group) (see Fig. 3).
Following these core technologies, more diversified technological
branches are observed in 2010s. This includes a set of inventions from
China related to print heads, nozzles and other components of the
printing equipment21
and hybrid printing apparatus that can mix and
print multiple materials.22
At this stage, there is also integration of
various elements, e.g. additive manufacturing equipment, computing
equipment, networked sales model of additive manufacturing products,
data modelling system of additive manufacturing, and management
model of additive manufacturing, etc.23
New methods related to bio­
logical cell planting shell printing also appeared in this technology
group,24
which indicates that additive manufacturing technology has
been applied to the biological field, and cell tissues can be used as raw
materials for bioprinting. This group of inventions represent the refined
and complicated development trend of printing equipment.
The main path (Fig. 3) shows that, the development of 3D printing
technologies followed one mainstream path without other obvious sub-
branches between 1998 and 2007. This seems to support our hypothesis
I that 3D printing technology developed to a lock-in situation. However,
the tipping-point emerged around 2008, notably led by three influential
patent families, following which forked technological streams are ob­
served. Printing materials and printing machines are the two main
groups that developed simultaneously in the later stage. Within either
group, there are also sub-branches with special technological focus.
This indicates that 3D printing technologies have become more and
more diversified, which supports the expectation that 3DP is enabling a
broader range of applications (Jiang et al., 2017). This verifies out
hypothesis II.
Second, from the geographical perspective, the U.S., Germany,
England and Japan have been the pioneer countries taking the leading
role in pursuing technological inventions in the 3DP field. Follower
countries, such as China, appeared in Fig. 3 only in recent years.
The earliest 3D printing technology is represented by
EP171069A2_1985_US. The technological path is dominated by the
U.S., with an incidental presence of Japan (JP) and Germany (DE).
China (CN) appeared on the map only after 2012, in both technology
group dealing with printing materials (in purple squares) and printing
machines (in brown squares). South Korea (KR) showed up also rela­
tively late on the path, in particular in the track of printing machine
related technologies (in the end of brown branch).
The progress upon a technological trajectory is a cumulated effect
and later technological advances are developed based on the earlier
technological frontier (Dosi 1982). China's emergence in the main path
reflects the fact that China, partly via learning from earlier technolo­
gical leaders, has gradually built its innovation capability and starts to
play a role in pushing the 3DP technology development. As the forward
citations for later nodes (e.g. after 2010) are relatively few, it is in­
appropriate to value nodes equally in the main path in Fig. 3. Due to the
time lag involved in citations, the later nodes are more sensitive than
the earlier nodes. Whether those nodes (e.g. patents from China) would
stay on the main path depends on the number of forward citations in
the future. Nevertheless, it is clear that China has gotten in on the ac­
tion with additive manufacturing (Styles 2018).
5.3. Knowledge variation
This study considers two types of knowledge resources, i.e. tech­
nological and geographical resources.
As explained in the methodology section, we rely on DWPI codes at
the second level (e.g. A11 or A12) to examine the knowledge con­
tribution from the technological perspective. Table 2 lists the share of
top technology categories for both the 3DP patents and cited patents. It
reveals that the 3DP patents from the U.S. are mainly from A11 (Pro­
cessing polymers including equipment) and A12 (Polymer applica­
tions). In China and South Korea, besides these two basic categories, a
relative concentration can be found in X25 (Industrial electrical
equipment). However, Japan's 3DP technologies are widely distributed
in different categories, e.g. L04 (Seminconductors), L03 (Electro-(in)
organic), G02 (Coatings, paints, inks, natural resins, polishes), G06
(Photographic materials and processes), V04 (Printed circuits and
connectors), etc.
From the knowledge contribution aspect, Japan again shows a wide
distribution across the DWPI categories, notably with the aforemen­
tioned A12, A08, L03, G06. In the U.S. and the U.K., besides the basic
A11 and A12 categories, knowledge from T01 (Digital computers)
seems to contribute to a relatively high share, accounting for 20% of the
total knowledge in developing 3DP patents. In China and South Korea,
although a large share of 3DP patents are in X25 (Industrial electrical
equipment), the share of knowledge adopted from this category is re­
latively low, at 12% and 8% respectively. This means that China and
South Korea have been using relatively more knowledge from other
technology fields to develop 3DP patents in X25. Such a misalignment
can also be found in Germany related to technology category M22.
Merely 2% of German 3DP patents are from M22 (Casting, powder
metallurgy) field, but the knowledge adopted from this field accounts
for 18% of the total knowledge used by Germany. This indicates that
Germany has been using knowledge from M22 to develop patents be­
longing to other technology categories.
Using the knowledge variation index introduced in Section 4, Fig. 4
presents the changes of knowledge variation over the years. First, we
look at the knowledge variation measured from the technological per­
spective, i.e. by examining the knowledge contribution from various
technological domains. The blue dotted line (named “knowledge var­
iety_DWPI”) presents the variation index calculated by the DWPI tech­
nology categories of each cited patent. There is a clear increase of
variation level in the earlier years, from 0.82 in 1985 to 0.95 in 1990.
However, this index stayed relatively unchanged in the following years.
However, there seems to have a different story in the variation index
measured by the knowledge contribution from different geographical
groups. In 1985, the variation index (green dotted line in Fig. 4) was
very low, being around 0.2, far below the technological variation index
captured by the blue dotted line. This can be explained by the fact that
3DP technologies were dominated mainly by a couple of leading
countries in the earlier years. For instance, 3DP inventions developed in
1985 and 1987 only cited patents from the U.S., Germany and Japan. In
20
Represented by US20070241482A1_2007_US and
WO2008086033A1_2008_US.
21
For instance, WO2013038413A2_2012_IL, CN103350509A_2013_CN,
CN103600407A_2013_CN, CN103895223A_2014_CN and
CN104191612A_2014_CN from China.
22
US20110282482A1_2010_US and WO2012143786A1_2012_IT.
23
US20130215454A1_2012_US, WO2015026201A1_2014_KR,
KR2015069403A_2013_KR and KR1686882B1_2015_KR.
24
See patent CN105238690A_2015_CN.
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
7

8. other words, knowledge contribution in those years were 100 percent
from these three countries. The fluctuation between 1985 and 1988 is
due to the very low number of 3DP patents, and accordingly, the
number of cited patents was only between 8 and 32 in those years. After
1989, the numbers of 3DP citing and cited patents were both much
higher, and the knowledge variation index was also smoothed out after
that. The red line in Fig. 4 exhibits that the share of knowledge con­
tributions from the top three countries (U.S., DE and JP) decreased
gradually after 1999. In accordance with this, not surprisingly, the
knowledge variation index (blue line) increased steadily to 0.76 in
2015.
This result partially supports Hypothesis 4. There is an increase in
knowledge variety. Nevertheless, that occurred in the very early stage,
if we look at knowledge contribution from a technological perspective.
While technological knowledge variation has become more stable,
geographical knowledge is still changing over the years. More and more
knowledge contribution can be found from latecomer countries.
Table 2
Top 20 technology categories in 3DP patents and cited patents.
3DP – technology category Citation – technology category
CN DE GB JP KR US CN DE GB JP KR US
A11 0.41 0.53 0.36 0.45 0.55 0.37 A11 0.34 0.35 0.26 0.26 0.34 0.28
A12 0.34 0.33 0.41 0.46 0.43 0.39 A12 0.30 0.31 0.28 0.38 0.30 0.26
T01 0.15 0.12 0.26 0.08 0.23 0.26 T01 0.16 0.13 0.21 0.08 0.23 0.20
X25 0.28 0.14 0.13 0.12 0.37 0.14 X25 0.12 0.12 0.11 0.04 0.08 0.12
A09 0.18 0.10 0.16 0.05 0.23 0.10 A09 0.12 0.08 0.07 0.05 0.13 0.07
S06 0.23 0.08 0.07 0.13 0.15 0.08 S06 0.13 0.02 0.03 0.05 0.08 0.02
U11 0.02 0.02 0.12 0.24 0.03 0.14 U11 0.03 0.03 0.06 0.15 0.06 0.11
A08 0.11 0.11 0.10 0.35 0.08 0.06 A08 0.10 0.09 0.07 0.22 0.07 0.05
M22 0.17 0.18 0.02 0.06 0.03 0.07 M22 0.14 0.18 0.07 0.05 0.05 0.09
L03 0.05 0.05 0.10 0.37 0.06 0.06 L03 0.05 0.05 0.07 0.18 0.07 0.06
T04 0.02 0.02 0.07 0.09 0.05 0.08 T04 0.06 0.04 0.07 0.07 0.07 0.07
L04 0.01 0.02 0.08 0.27 0.02 0.07 L04 0.02 0.02 0.05 0.11 0.04 0.05
A05 0.10 0.07 0.07 0.07 0.03 0.04 A05 0.08 0.08 0.04 0.10 0.04 0.04
S05 0.04 0.07 0.08 0.04 0.06 0.07 S05 0.04 0.05 0.05 0.02 0.05 0.04
D09 0.05 0.03 0.03 0.03 0.05 0.06 D09 0.05 0.03 0.04 0.03 0.04 0.05
G02 0.01 0.04 0.09 0.29 0.03 0.03 G02 0.02 0.05 0.04 0.12 0.04 0.03
A04 0.07 0.04 0.07 0.18 0.03 0.03 A04 0.06 0.04 0.04 0.10 0.04 0.03
A10 0.06 0.05 0.01 0.08 0.01 0.04 A10 0.05 0.06 0.05 0.10 0.03 0.04
G06 0.02 0.03 0.05 0.35 0.00 0.03 G06 0.01 0.03 0.05 0.24 0.02 0.05
V04 0.01 0.02 0.01 0.22 0.02 0.04 V04 0.02 0.03 0.02 0.06 0.03 0.05
Note: 1) The intensity for “3DP – technology category” is calculated by the number of 3DP patents in each category divided by the total number of 3DP patents in all
categories. 2) The intensity for “Citation – technology category” is calculated by the number of cited patents in each category divided by the total number of cited
patents in all categories.
Fig. 4. Knowledge variation indexes.
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
8

9. 5.4. Comparison of geographical differences
Following the trajectory detected earlier, this section statistically
tests the differences between countries that were involved in con­
tributing to the main path.
In forming technological trajectories, there are two types of con­
tributing elements. One is the inventions appearing on the trajectory,
representing the core 3DP technologies in this domain. The other is the
knowledge sources (cited patents) that lead to the development of
subsequent 3DP patents. These two elements are examined in the five
major players appearing on the main path illustrated in Fig. 3, i.e. the
U.S., Germany, Japan, South Korea and China.
Comparisons are made in two databases, i.e. full sample of 3DP
patents and sub-sample of core 3DP patents25
and three variables (i.e.
3DP_patent_year, Citation_year and Time_lag) are taken into considera­
tion. 3DP_patent_year is the mean of granted years of 3DP patents in
each country, and Citation_year is the mean of cited patent years from
each country. These to some extent represent the average years of 3DP
inventions and cited knowledge. Time_lag is the year difference between
the 3DP patent year and the cited patent year. A higher Time_lag value
means that relatively old (or longer existing) knowledge from this
country was used before the prevalent 3DP patents developed in this
country. Similarly, a lower Time_lag value means that more recent
knowledge from this country was adopted to develop 3D printing
technologies.
An ANOVA test shows that there is a statistically significant differ­
ence across countries in terms of 3D patenting, citation and time lag.
In the first database – the full sample covering all the patents, the
mean of 3DP_patent_year is smallest in the U.S. (2007.1), followed by
Japan (2007.6). China and South Korea have the highest years, 2013.8
and 2013.0 respectively. This suggests that the U.S. and Japan started
3D printing technologies earlier than the other three countries, in
particular around 6 years earlier than China and South Korea. In the
second database, covering only the core patents on the main path, the
mean of 3DP_patent_year is again lower in the U.S. and Japan and higher
in China and South Korea. It is not surprising that the U.S. and Japan
were the pioneer countries to develop core 3DP technologies.
Comparing both databases, an obvious difference in 3DP_patent_year
can be observed in the U.S. and Japan. That is, in these two countries,
the average year of 3DP patents appearing on the main path is some­
what lower than that of all 3DP patents. Interesting, however, the va­
lues of this variable for China and South Korea are both higher in the
sub-database than the full sample. This observation indicates a different
pattern between two geographical groups. In the group of patents by
the U.S., Germany and Japan, a higher share of earlier patents con­
tributed to the main 3DP technological trajectories, while a higher
share of later patents contributed as the non-main stream technology
not included in the main path. Contrary to this, among all the patents
from China and South Korea, a higher share of later patents contributed
to the core 3DP technologies.
For the knowledge sources, represented by citation, different pat­
terns are also observed across countries. The U.S. has the lowest mean
in Citation_year, with 1996 in the full sample and 1991 in the sub-
sample. Following that, the means for Germany and Japan are between
1996 and 2000. Again, China and South Korea have the highest values.
However, the pattern of these two countries in this variable (serving as
knowledge sources) are different from the aforementioned
3DP_patent_year variable. In the full-sample of all patents, South Korea
has a mean of 2004.9, much earlier than that of China (2007.9). This
shows that, although South Korea and China share a common feature in
the time of developing 3DP inventions, knowledge from South Korea
used in this technological domain was on average 3 years earlier than
knowledge from China.
In terms of the development of main path, the U.S. provided the
earliest knowledge, with an average year of 1991 (see Table 3: the
Citation_year row in the sub-sample), while South Korea provided the
newest knowledge source, with a mean of 2011.8, which is 20 years
later than the U.S. and one year later than China.
With regard to the Time_lag variable, the U.S. has the highest mean,
indicating that U.S.’ knowledge used to develop 3DP patents was on
average 11 years earlier than U.S.’ 3DP inventions. Comparing patents
in both samples, except the U.S., all other countries have a lower value
in the sub-sample than in the full-sample. This means that four coun­
tries on the main path (Germany, Japan, South Korea and China) all
developed the core 3DP technologies closely following their existing
background knowledge.
In general, this section demonstrates the statistically significant
difference between countries in pursuing 3DP technologies. While the
U.S. provided the earliest backbone knowledge sources and new 3DP
invention records, China and South Korea showed influential achieve­
ments in recent years. In particular, South Korea presented the newest
knowledge source for 3DP technological development.
6. Conclusions
To forecast the development and impact of a certain technology, it is
important to understand the technological path (Robinson et al., 2018) .
Using 3D printing technology as a case study, this study maps the tra­
jectory of technological development and explores the contribution of
various knowledge sources. Different from previous studies, this paper
tracks different knowledge sources in their contributions to the devel­
opment of the under studied technology. We illustrate the contribution
of different countries in shaping the main technological trajectories,
and disentangle the contribution of knowledge sources from both
geographical and technological perspectives. As the potential of 3D
printing applications is highly diversified (Lee 2016), understanding the
components of 3D technology can help better understand the future of
this new and powerful technology (Arthur 2007; Wohlers and Gornet
2014).
Towards a better management of the 3D printing related product
innovation, manufacturing process and business models, it is crucial to
understand the evolution of this group of technologies. The linkages
between patents from different countries and different years help un­
derstand the role major nations played in various stages. Our results
show that a concentrated lock-in stage occurred in the process of 3D
printing technological development. With the contribution of broad-
scope patents, a “tipping-point” emerged around 2008, after which
more diversified technological branches started to develop.
The new directions captured in the technological main path and the
involvement of latecomer countries indicate that we have reached a
more diversified and competing stage. Momentum gained along the
development of new 3DP technologies in latecomer countries may
signal that global markets associated with 3DP technologies are likely
to change in the (near) future as well. South Korea provides the newest
knowledge for the development of core 3DP technologies. With its de­
termination and capabilities in developing emerging technologies
(Chu and Su 2014; OECD 2017), South Korea is expected to bring new
dynamics to the development 3DP technologies. China, on the other
hand, has the price advantage in printing materials, such as the in­
creasingly demanded metal powders (Styles 2018). 3D printing tech­
nologies are likely to introduce new competition between countries.
By differentiating knowledge sources from various domains, this
paper also provides insights into the internal and external knowledge
basis for technological development. Our study demonstrates that the
3D printing technology has been developed based on a broad range of
knowledge basis. The combination of high technological variation (with
diversified contributions from different domains) and geographical
variation (with increasing contributions from latecomer countries)
25
The sub-sample includes all the 3DP patents appearing on the main path of
the technological trajectory.
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
9

10. indicates new industry opportunities in different fields as well as a far-
ranging social impact in various nations.
It is worth to note that this study is devoted to exploring the de­
velopment and potential capability of 3DP from the technology side.
Our results suggest that various technologies are enabling 3DP to be
applied to a broader range of products. However, the evidence is pro­
vided only from the technology-push side, without taking the effect of
demand-pull and other factors into consideration. There are three
limitations in mapping the trajectories. First, although patents from
emerging countries like China appeared in the trajectory map in recent
years, it is difficult to judge the importance of these patents as the
number of their forward citations is still low. It will be worthwhile to
test them again in the future. Second, this study defines countries of
patents based on the first inventors. Thus a collaborated patent is as­
signed only to one country. Admittedly, various collaborations happen
across the global innovation value chain. Third, we analyse patents as a
type of technology output. However, this research does not intend to
explore the input factors (e.g. company strategies or government
policy). We believe such factors can play an important role in moti­
vating patenting and promoting technological development in certain
fields. Investigating such issues can be an interesting subject for future
research.
Acknowledgement
We thank the Associate Editor and anonymous reviewers for their
valuable comments and suggestions that helped improve our work. We
also thank the participants in the Seminars at the Chinese Academy of
Science and Technology for Development, Ministry of Science and
Technology (MOST-CASTED), and the Chinese Academy of Sciences
(CAS) for their comments. We are grateful for the financial support
from Beijing Academy of Science and Technology (BJAST) and Beijing
Research Center for Science of Science (BJSS).
Declaration of Competing Interest
The authors declare that they have no conflict of interest. This re­
search has been partially funded by Beijing Academy of Science and
Technology (BJAST) and Beijing Research Center for Science of Science
(BJSS).
Date: 11 May 2020
Authors:
Lili Wang, UNU-MERIT, Maastricht University, The Netherlands
Shan Jiang, Chinese Academy of Sciences, P.R.China
Shiyun Zhang, Beijing Academy of Science and Technology,
P.R.China
Appendix
Table 3
differences across countries.
US CN DE JP KR ANOVA
F Prob > F
Full-sample (all patents) 3DP_patent_year 2007.1 2013.8 2009.0 2007.6 2013.0 3819.6 0.0000
Citation_year 1996.0 2007.9 1998.5 1996.6 2004.9 2047.3 0.0000
Time_lag 11.0 5.9 10.5 11.0 8.1 1799 0.0000
Sub-sample (patents on the main path) 3DP_patent_year 2002.9 2014.4 2005.2 2002.6 2013.8 85.88 0.0000
Citation_year 1991.4 2010.8 2000.8 1998.6 2011.8 54.39 0.0000
Time_lag 11.6 3.5 4.4 4.0 2.0 35.98 0.0000
Fig. A1. Number of 3D printing patents in the top 20 coun­
tries.
Note: “Europe” refers to the European countries in the top 20
with the highest 3D printing patent numbers, including
Germany, UK, Switzerland, the Netherlands, France, Italy,
Belgium, Denmark and Sweden. “Others” refers to the re­
maining countries from the top 20.
L. Wang, et al. Technological Forecasting & Social Change 161 (2020) 120251
10

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Lili Wang obtained her PhD degree from Eindhoven University of Technology and cur­
rently works at UNU-MERIT, The Netherlands. Her research interests cover two main
strands: a) S&T economics, innovation systems and policy, emerging technologies, and b)
economic growth and structural change in developing countries. She has widely pub­
lished in peer-reviewed journals, such as Research Policy, Proceedings of the National
Academy of Sciences of the United States of America (PNAS), Technological Forecasting &
Social Change, Journal of Informetrics, Industrial and Corporate Change, Oxford
Development Studies, China Economic Review, Research Evaluation and Scientometrics.
Shan Jiang received his Master degree in Materials Physics and Chemistry from Shandong
University of P.R.China. He is currently an associate researcher in the Wuhan Branch of
National Science Library, Chinese Academy of Sciences. His research interests include
scientometrics research, science and technology policy studies, and technology trends
analysis.
Shiyun Zhang is a full professor at and director of the Beijing Institute of Science and
Technology Information , Beijing Academy of Science and Technology, P.R.China. He is
also Deputy Director and Academic Leader of Beijing Science and Technology Strategic
Decision Consulting Center (Beijing Think Tank). He has long been engaged in S&T
strategy and policy research, S&T statistics and analysis. In the past five years, he has
completed 8 national-level projects and 25 provincial-level projects; he has published 13
monographs and 15 academic papers.
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