Document [original]

ORIGINAL ARTICLE

Technology strategies in converging technology systems:

Evidence from printed electronics

Annika Wambsganss

1,2

| Stefanie Bröring

| Søren Salomo

2,4

Nathalie Sick

Centre for Advanced Manufacturing,

Faculty of Engineering and IT, University

of Technology Sydney, Sydney,

New South Wales, Australia

Chair of Technology and Innovation

Management, Faculty of Economics and

Management, Technical University Berlin,

Berlin, Germany

Chair for Entrepreneurship and

Innovative Business Models, Faculty of

Management and Economics, Ruhr-

University Bochum, Bochum, Germany

Center for Entrepreneurship, Technical

University of Denmark, Copenhagen,

Denmark

Correspondence

Annika Wambsganss, UTS Faculty of

Engineering and IT, Broadway, NSW

2007, Australia.

Email: annika.wambsganss@uts.edu.au

Abstract

Novel technology systems, such as “fiber optics”and “printed electronics,”

increasingly emerge at the interface of hitherto unrelated technology areas. As

such, new technology systems often arise through technology convergence,

characterized by integrating technology components and knowledge from dif-

ferent technology systems, resulting in a novel system architecture. This phe-

nomenon is of utmost societal relevancy but simultaneously poses tremendous

challenges for firms' technology strategies. Firms must not only cope with

unrelated knowledge rooted in hitherto different technologies but also have to

decide deliberately how systemic (i.e., complete technology system) versus

focused (i.e., single component of the technology system) their engagement in

technology development in the converging technology system ought to be. In

addition, firms need to decide strategically to what extent to develop special-

ized or design knowledge. Extant concepts of technology strategy fall short of

capturing this complexity inherent in converging technology systems. There-

fore, to address how technology strategies co-evolve along with the emergence

of new technology systems, this study adds a systems perspective to technology

strategy by developing the concept of technology system coverage. This novel

dimension of technology strategy is formed by the scope (i.e., focused

vs. systemic coverage of the technology system) and type of technological

knowledge (i.e., specialized or design knowledge).We empirically apply this

novel angle of technology strategy to the convergence field of printed electron-

ics. Based on a longitudinal set of 828 patents over 30 years, 74 relevant corpo-

rate actors are identified. The underlying taxonomy enables us to reveal four

technology strategies and develop five propositions. The results indicate that

all firms build design knowledge over time, whereas not all firms build special-

ized knowledge, no matter what technology strategy is pursued. In sum, this

work advances literature by understanding technology strategy in emerging

complex technology systems, introducing a systems perspective.

Received: 6 September 2021 Revised: 3 April 2023 Accepted: 11 June 2023

DOI: 10.1111/jpim.12693

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided

the original work is properly cited.

J Prod Innov Manag. 2023;40:705–732. wileyonlinelibrary.com/journal/jpim 705

KEYWORDS

complex technology system, technology convergence, technology strategy, technology system

coverage

1|INTRODUCTION

Technology convergence, which builds on the integration

of hitherto distant technology systems, presents an

increasingly pertinent phenomenon that has huge poten-

tial to trigger novel technology-based solutions with

strong societal relevancy (Bröring & Leker, 2007; Choi &

Valikangas, 2001; Curran et al., 2010; Curran & Leker,

2011; Hacklin, 2008). We are currently witnessing differ-

ent examples of technology convergence, such as syn-

thetic biology, “nanobioinfotech,”or fiber optics, which

all emerge at the interface of formerly unrelated technol-

ogy systems (Kim et al., 2019a; Klarin et al., 2023;

Kodama, 1992; Maine et al., 2014; Shmulewitz et al.,

2006; Sick & Bröring, 2022). Generally speaking, a tech-

nology system consists of different components and an

underlying architectural design that links involved com-

ponents (Henderson & Clark, 1990). In line with prior

research, we argue that a converging technology system

integrates not only different and formerly unrelated com-

ponents but also forms a novel architectural design

(Henderson & Clark, 1990; Jaspers et al., 2012; Metcalfe,

1995; Staudenmayer et al., 2005).

All the aforementioned examples of technology con-

vergence are built on cross-sectoral research and develop-

ment (R&D) activities and involve a novel inter-industry

architectural design that implicates a co-evolution of com-

ponents to ensure interoperability with the overall con-

verging technology system (Jaspers et al., 2012). Fiber

optics, for example, which presents a well-understood case

of a converging technology system, emerges from the

fusion of distinct technology systems and thus integrates

components stemming from glass, cable, and electronics

technologies converging into a novel architectural design

(Kodama, 1992). More precisely, this implies that compo-

nents originating from the technology system of materials,

such as flexible glass systems, are merged with those stem-

ming from the field of electronics, such as cable systems.

Together, these are forming the novel converging technol-

ogy system of fiber electronics (Kodama, 1992).

Technology convergences come with inherent complex-

ities, uncertainties, and dynamics, which present firms

with significant challenges. Complexity is of structural

nature, as converging technology systems are requiring

firms to combine knowledge of fundamentally different

technological fields, including a multitude of different and

novel interfaces (Kapoor & Furr, 2015). In addition, firms

are confronted with uncertainties stemming from

unknown specifications, lacking industry standards, and

time frames (Rotolo et al., 2015;Su



arez & Utterback, 1995).

Finally, the emergence of converging technology systems is

an inherently dynamic phenomenon, which evolves as a

highly decentralized process with newly developing com-

ponents and dominant designs, new actors and network

structures, and finally, changing interdependencies

Practitioner points

•Technology convergences create complex tech-

nology systems that emerge through recombin-

ing and integrating components from

previously unrelated technology areas. It is cru-

cial for managers to recognize that these com-

plex technology systems present new

challenges impacting their technology strategy.

•Engaging in the development of technology

convergence presents managers with the

dilemma of whether to prioritize individual

components or adopt a comprehensive

approach addressing the entire technology

system. Accordingly, they need to determine

the knowledge base (i.e., degree of design

knowledge) to invest in, and establish mecha-

nisms for dynamic adjustment throughout the

technology development.

•Another important insight for managers is that

all companies that initially engaged in special-

ized knowledge components have been

observed to accumulate design knowledge over

time. Thus, our findings emphasize the signifi-

cance of design knowledge as a facilitator in

understanding the interdependencies between

components, enabling sustained participation,

and potentially allowing for the orchestration

of development.

•This study introduces the concept of technol-

ogy system coverage and its dynamics as a rele-

vant dimension of the technology strategy. It

can assist managers in navigating the increas-

ingly complex and uncertain environment sur-

rounding converging technology systems

effectively.

706 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

between different components (Cho et al., 2015;

Staudenmayer et al., 2005; Sukri & Yusoff, 2019).

We argue that the context of converging technology

systems poses tremendous challenges for firms seeking to

develop technology strategies to position themselves in

these emerging yet, often fast-growing sectors. However,

it remains unclear how firms shape their technology

strategies to approach such an emerging, complex tech-

nology system. Especially the scope of the knowledge that

firms develop regarding the emerging technology system

over time presents a space to uncover. It remains a cen-

tral strategic question whether firms should focus on

their potentially existing position reflected by component

knowledge or aim at a broader approach, potentially cov-

ering the entire system.

Extant literature so far neglects this systems perspec-

tive but rather conceptualizes technology strategy as a

plan guiding the development of technological capabili-

ties and knowledge along the classic lines of “timing of

entry,”“R&D portfolio,”or “IP strategy”(Bayus &

Agarwal, 2007; Ford, 1988; Schilling & Hill, 1998; Zahra,

1996). However, these concepts fall short of reflecting the

particularities of evolving technology systems, for exam-

ple, how firms can maneuver such a complex system of

different components and architectures with changing

interfaces (Henderson & Clark, 1990). Moreover, the

question arises of how technology strategies can co-

evolve with, and adapt to, the dynamics of a converging

technology system. As such, to our best knowledge, liter-

ature has not dealt with the question of how firms' tech-

nology strategies evolve with regard to building relevant

knowledge in parallel to the emergence of a new converg-

ing technology system. This is striking since the context

of complex technology systems triggered by the integra-

tion of different technologies seems to be highly relevant

beyond the setting of convergence (Jaspers et al., 2012).

Especially the idea of digital technology systems, where

value creation only materializes if interfaces are well-

defined and system designs are understood (Yoo et al.,

2012), underscores the need for exploring technology

strategy in complex technology systems.

To advance theorizing on technology strategies, this

study offers a systems perspective on technology strategy

development. The paper, therefore, relates well-established

technology strategy approaches (Ford, 1988;Zahra,1996)

to the concept of technology systems and their underlying

architectural design (Baldwin et al., 2014; Henderson &

Clark, 1990; Metcalfe, 1995)inthetopicalcontextofcon-

verging technology systems (Kim, Jung, & Hwang, 2019).

Drawing on the seminal concepts of architectural innova-

tion (Henderson & Clark, 1990) and systemic innovation

(Chesbrough & Teece, 2002), we, thus, develop a novel

dimension to technology strategy that considers the

systems perspective. In recognizing the different compo-

nents of a technology system, which stem from different

hitherto distinct technology systems and are integrated

based on a novel systems architecture, we introduce the

concept of technology system coverage (TSC). This novel

dimension enables deciphering not only the scope of a tech-

nology strategy but also the type of knowledge development

pursued. From a knowledge type perspective, firms may

target components rich in design knowledge, or focus on

specialized components, which require less systems under-

standing (Baldwin et al., 2014).

Against this backdrop, this paper follows an explor-

atory theory-building approach (Strauss, 1987) and builds

on a longitudinal study on firm-level data, using a com-

prehensive patent data sample reflecting the converging

technology system of printed electronics. Based on a set

of 828 patent families comprising a period of 30 years,

74 relevant corporate actors are identified. By seeking to

extend our understanding of technology strategy in the

context of converging technology systems, this study

offers two main contributions to the technology and

innovation management literature.

First, by drawing on the literature of inter-industry

architectural innovations (Jaspers et al., 2012), more par-

ticularly on the complex design of converging technology

systems (Baldwin et al., 2014) and the related technologi-

cal knowledge base (Fleming, 2001; Henderson & Clark,

1990; Yayavaram et al., 2018), we introduce technology

systems coverage as a novel dimension of technology

strategy. In doing so, we develop an understanding of

technology strategies that firms employ to respond to the

uncertainties posed by converging technology systems.

We explore how firms encounter converging technology

systems based on how comprehensively they cover the

different technological knowledge bases—that is,

the scope of their technological engagement. Moreover,

in distinguishing different types of knowledge along their

degree of embeddedness in specialized versus design

knowledge (Henderson & Clark, 1990; Yayavaram et al.,

2018), technology systems coverage adds to the extant

conceptualization of technology strategy.

Our second contribution is related to understanding

the dynamics of firms' co-evolution with the converging

technology system. As we observe technology strategies

over the technology life cycle (Ernst, 1997), we are able

to empirically identify different development patterns.

Thus, our research integrates a dynamic perspective to

technology strategy, accounting for the dynamics inher-

ent in evolving technology systems.

By rendering a novel theoretical construct, TSC, and

its empirical application to the convergence setting of

printed electronics, we offer a taxonomy of technology

strategies that enable managers to reflect upon and

WAMBSGANSS ET AL.707

deliberately configure their technology strategy and related

investments in either specialized and/or design knowl-

edge. This seems particularly relevant for contexts of inter-

industry architectural innovation (Jaspers et al., 2012),

such as technology convergence (Kodama, 1992). But it is

also relevant for any field characterized by rapid techno-

logical progress that leads to the emergence of complex

technology systems (Baldwin et al., 2014). Hence, our tax-

onomy also informs managers confronted with the emer-

gence of complex technology systems arising from any

inter-industry joint value creation, where different actors

form novel but complex value propositions (Talmar et al.,

2020) emerging from the integration of hitherto distant

fields of technological knowledge (Fleming, 2001).

1.1 |Converging technology systems and

the related knowledge base

Firms are facing increasingly complex technological envi-

ronments, which require them to advance their technologi-

cal knowledge base (Wang & Von Tunzelmann, 2000).

This holds especially true in the context of technology con-

vergence, triggering the emergence of novel technology sys-

tems (Hacklin et al., 2013). Technology systems, as such,

are complex (Baldwin et al., 2014) and comprise a nested

hierarchy of design elements (Clark, 1985; Marples, 1961),

encompassing a set of different components and an archi-

tectural design that defines “the way in which the compo-

nents […] are linked together”(Henderson & Clark, 1990,

p. 10). As illustrated in Figure 1, all converging technology

systems share the peculiarity that their technology compo-

nents, as well as their architectural design, stem from

formerly unrelated technology systems (Giachetti &

Dagnino, 2017; Jaspers et al., 2012). This involves the (re-)

definition as well as the recombination of different compo-

nents stemming from any of the incumbent systems and

their integration through a new inter-industry architectural

design (Baldwin & Clark, 2000; Jaspers et al., 2012). Thus,

converging technology systems are characterized by

increased levels of uncertainty and ambiguity (Rotolo et al.,

2015) as a dominant design only gradually emerges

(Su

arez & Utterback, 1995).

The knowledge base behind any component of a tech-

nology system may exhibit different characteristics rela-

tive to the type of knowledge required. In particular, we

can distinguish between specialized and design knowl-

edge. Some technology components are richer in design

knowledge and, thus, contribute directly to the entire sys-

tem architecture and their interdependencies. Other com-

ponents are more specific and need to adjust to the

overall system architecture and their interdependencies

(Baldwin et al., 2014). In the case of fiber optics, for

example, the coating of the cable is rather peripherical

knowledge (more specialized and less design knowledge),

whereas the glass fibers and their composition in the

cable is a component rich in design knowledge defining

the overall cable architecture.

Following Baldwin et al. (2014), we argue that all

components need to incorporate a limited level of design

knowledge to ensure systems fit. However, the level of

embedded design knowledge may vary significantly in

depth. Consequently, we conceptualize technology sys-

tem as consisting of components that are rather special-

ized (involve a higher degree of specialized knowledge

and limited design knowledge) and those that are rich in

FIGURE 1 The emergence of a converging technology system consisting of components with different knowledge stocks.

708 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

design knowledge (compare Figure 1) with a higher

impact on the overall systems architecture.

1.2 |Technology strategy in the context

of converging technology systems

In a setting of technology convergence, firms need to

build the underlying knowledge base to be able

to develop a position in the novel technology system

(Hacklin et al., 2013). This requires firms to adjust their

technology strategy to an evolving competitive environ-

ment (Hacklin et al., 2013). More specifically, this

includes decisions to align extant competencies with the

dynamic technology environment (Sukri & Yusoff, 2019;

Zahra & Bogner, 2000). Technology strategy, in its

generic sense, encompasses plans and management deci-

sions on resource allocation for the development, mainte-

nance, and use of technology capabilities (Friar &

Horwitch, 1985; Zahra, 1996). Ideally, a deliberate tech-

nology strategy allows to develop and nurture those

technologies that will be crucial for the long-run competi-

tive position of a firm (Schilling & Hill, 1998). Thus, tech-

nology strategies provide firms with guidance in

determining the attractiveness of technology investment

opportunities and may assist in targeted accumulation of

knowledge (Ford, 1988; Malerba & Orsenigo, 1996). As

such, a technology strategy shapes an important part of

firms' competitiveness in settings relying strongly on

technological foundations (Bonnet & Yip, 2009; Sukri &

Yusoff, 2019; Zahra & George, 2002).

Firms' technology strategies become particularly rele-

vant when facing high environmental turbulence, such as

technology convergence, as they determine if and how

firms may participate in evolving technology systems

(Golder & Tellis, 1993;Hacklinetal.,2013;Zahra,1996).

Here, the extant dimension such as the use of internal and

external R&D resources (Hagedoorn & Duysters, 2002;

Veugelers, 1997), R&D spending (Zahra, 1996), pioneer ver-

sus follower (Lieberman & Montgomery, 1988), balance of

technology exploration and exploitation (Clarke et al., 1989;

Tushman & O'Reilly, 1996), as well as related IP protection

strategies (Drechsler & Natter, 2012), make up multiple

dimensions of technology strategy. However, these dimen-

sions may not suffice to capture the uncertainty and com-

plexityofstrategydevelopment in the context of converging

technology systems. Hence, to advance theorizing regarding

technology strategies, we expand existing concepts with a

novel dimension that enables to navigate complex technol-

ogy systems. Accordingly, we conceptualize technology

strategies along the following four dimensions and intro-

duce TSC as a central technology strategy dimension, sum-

marized in Table 1andelaboratedbelow.

1.2.1 | Scope: Focused versus systemic

A central aspect of a technology strategy in the context of

convergence concerns the scope of engagement in the

emerging technology system. This dimension seems par-

ticularly relevant in such a context of high technology

dynamics, as technology components merge from previ-

ously unrelated technology systems. Firms can seek to

develop a single or multiple components of the converg-

ing technology system, implying to either remain within

their knowledge base or expanding into novel areas. The

decision on the scope is informed by the dichotomy of

autonomous (focused) and systemic innovation, as intro-

duced by Chesbrough and Teece (2002).

Afocused scope reflects a technology strategy that

directs its development efforts toward a single component

of the evolving technology system (e.g., only x

a,b

Figure 1). Firms entering a converging technology system

with a focused scope may benefit from a very targeted

TABLE 1 Theoretical framework for the extended conceptualization of technology strategy.

Dimension Characteristics

Conceptually informed by

Technology system coverage

Scope Focused Systemic Chesbrough and Teece (2002)

Taylor and Levitt (2004)

Knowledge base Specialized Design Henderson and Clark (1990)

Yayavaram et al. (2018)

Timing Pioneer Follower Lieberman and Montgomery (1988)

Golder and Tellis (1993)

Dynamics Steady Evolving Porter (1991)

D'Aveni (1994)

Following extant literature, we choose to highlight extreme or dichotomous positions in each dimension to allow for a clear distinction of technology strategy

approaches.

WAMBSGANSS ET AL.709

R&D activity concentrating on that particular component

only (Staudenmayer et al., 2005), potentially remaining

in their core knowledge base. In contrast, the converging

technology system can be approached more comprehen-

sively by covering more than one component, which

we label as systemic. Firms following a systemic

scope develop knowledge around multiple components

(e.g., y

a,b

and z

a,b

in Figure 1), which puts them in

a position to potentially better understand the entire

system, including the interdependencies and linkages

between components, and presumably expanding their

core knowledge scope (Bröring, 2008; Henderson &

Clark, 1990; Taylor & Levitt, 2004).

1.2.2 | Knowledge base: Specialized versus

design knowledge

Drawing upon Henderson and Clark (1990) and

Yayavaram et al. (2018), we distinguish between different

forms of knowledge that firms can build as part of

deliberate technology strategies. Accordingly, firms can

engage in knowledge development regarding those

components of the evolving technology system that are

either rich in specialized or rich in design knowledge (see

Figure 1). We argue that firms either build specialized

knowledge needed for specific, rather peripherical compo-

nents (Baldwin et al., 2014; Yayavaram et al., 2018)

and/or build design knowledge needed for the overall

architectural design.

By understanding technology systems as hierarchical

(compare Clarke et al., 1989 or Marples, 1961), we concep-

tualize design knowledge as relevant for understanding

and determining the systems architecture at a higher level.

Baldwin et al. (2014) also refer to “core”components in

this regard, as components rich in design knowledge deter-

mine many subsequent configurations of the system

(Henderson & Clark, 1990). The following assumption

seems important in this regard: in line with Persoon et al.

(2021) and Malerba and Orsenigo (1996), we understand

technological knowledge as cumulative, thus a stock of

knowledge of the firm that grows over time.

The involvement in a technology system always

comes with two decisions: firstly, regarding scope, how

many components should be developed: focused versus

systemic and, secondly, regarding the knowledge base of

a particular component: specialized versus design knowl-

edge (see Figure 1). Thus, the integration of both dimen-

sions leads to the novel construct of technology systems

coverage that we conceptualize as a dimension relevant

to the development of technology strategy, in particular

relevant for firms engaged in emerging complex technol-

ogy systems (see Table 1).

1.2.3 | Timing: Pioneer versus follower

As technology convergence is an evolving phenomenon—

with a novel technology system and dominant design

emerging only over time—to ensure a systems fit, the re-

design of a component or the entire technology system

might be required (Metcalfe, 1995). In this regard, a

relevant and well-established dimension of technology

strategy concerns the timing of entry (García-Cabrera et al.,

2019; Golder & Tellis, 1993; Langerak & Hultink, 2006;

Lieberman & Montgomery, 1988;Su



arez & Utterback,

1995). However, often this is not a deliberate strategy but

rather emerges (Mintzberg & Waters, 1985). Despite the

question of whether timing of entry is a deliberate strategic

decision or emerges, it seems important to observe and

realize the implications of an early entry versus a late fol-

lowing position. In this regard, a pioneering or following

position seems particularly relevant with respect to the

progression of the system's development. Early participa-

tion and, therefore, a positioning as a pioneer enables a

firm to build knowledge from the very beginning. This

potentially allows for setting a dominant design, which

later entrants must follow (Golder & Tellis, 1993).

However, when technology systems converge, hith-

erto unlinked components need to be interlinked with

each other, potentially for the very first time or in a novel

manner. This involves considerable complexity concern-

ing components outside a firm's core technological

knowledge. So, moving first comes with the risk that

efforts might be prioritized unfavorably, and a fast-

evolving technology bears the difficulty to sustain a dura-

ble competitive advantage (Leten et al., 2016;

Lieberman & Montgomery, 1988;Su



arez & Lanzolla,

2005). Additionally, the investment in early-stage tech-

nologies always bears the risk of not meeting the

expected return on investment (Porter & Chubin, 1985;

Zahra, 1996).

1.2.4 | Dynamics of TSC: Steady versus

evolving

Converging technology systems are particularly dynamic

and companies potentially need to deepen and broaden

their technological knowledge continuously (Yayavaram

et al., 2018). Therefore, we argue that firms may seek to

adapt their technological knowledge as the technology

system evolves (D'Aveni, 1994; Sanchez & Mahoney,

1996). Hence, when examining participation in a technol-

ogy system, covering dynamics seems to be critical

(Thomke et al., 1998). Firms participating in such an

environment might continuously be pressured to keep up

with these dynamics if they want to sustain their

710 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

participation (D'Aveni, 1994; Porter, 1991). But the ques-

tion remains if all firms engage in a dynamic approach or

if some rather follow a steady approach. Against this

backdrop, we argue that technology strategy can either

be evolving or steady. In contrast to evolving, that is,

adapting, we conceptualize steady as not adapting the

scope, that is, number of components covered, and

knowledge base, that is, specialized or design knowledge.

2|CONTEXT AND METHOD

2.1 |Research context

To explore technology strategies during the development

of complex technology systems, we choose the well-

defined convergence field of printed electronics (Bröring,

2010; Cho et al., 2015). It represents an established and

rich empirical site to uncover technology strategy devel-

opment in the context of converging technology systems,

as the convergence phenomenon is salient here (Strauss,

1987). The convergence of printed electronics derives

from the two formerly distinct technological fields of con-

ventional printing and electronics. Both original fields

have long histories of established technological knowl-

edge (Cho et al., 2015; Karvonen et al., 2010; Karvonen

et al., 2012).

When the knowledge in conventional printing, for

example, printing newspapers, merged with knowledge

on electrical properties in inks, the production of printed

electronics such as printed microchips, printed electronic

circuits, or printed semiconductors was enabled (Cui

et al., 2016; Hu et al., 2018; Huang & Zhu, 2019). The

main procedural difference in the production of tradi-

tional electronics and printed electronics is that the for-

mer uses a subtractive procedure, while the latter

involves an additive process. This gives printed electron-

ics the advantage of lower production costs while offering

increased flexibility and robustness (Cho et al., 2015;

Huang & Zhu, 2019). Consequently, this converging tech-

nology system is developing fast. It started with the pro-

duction of printed circuit boards and evolved into areas

such as radio-frequency identification (RFID), organic

light-emitting diodes (OLED), flexible displays, or flexible

photovoltaics (PV) (Hu et al., 2018; Huang & Zhu, 2019).

Applying our simplified model of converging

technology systems (introduced in Figure 1) to the

printed electronics field, the underlying technology sys-

tem is built by the integration of four components: sub-

strate, ink, manufacturing device, and electronic

application, see Figure 2.

The first component of a typical printed electronics

technology system is the substrate, which is the surface

material onto which the ink is printed. The substrate can

be made of various materials and layers, such as flexible

polymeric materials, including properties such as being

conductive. The second component, ink, refers to func-

tional inks, such as semi-conductive, conductive, and

insulative pastes. They are printed onto the substrate to

produce the circuits (Cui et al., 2016). These first two

FIGURE 2 Printed electronics converging technology system (based on Cho et al., 2015). OLED, organic light-emitting diodes; RFID,

radio-frequency identification.

WAMBSGANSS ET AL.711

components derive from material science and need to be

integrated into the architectural design of the technology

system, originating in the electronics domain. Thus, these

components mainly contain specialized knowledge but

still need to embed some design knowledge on interface

definitions to enable compatibility and systems fit

(Baldwin et al., 2014; Henderson & Clark, 1990). For

example, ink can be developed primarily remaining

within its specialized knowledge base but cannot be

developed completely autonomously, as it needs to align

with the overall systems architecture. Such design knowl-

edge may entail insights on the needed viscosity of the

ink to enable a fit to the manufacturing (printing) device

(Cho et al., 2015).

The third component, manufacturing device,comprises

the printing and patterning processes, that is, the additive

manufacturing technique of how to apply layers of inks to

a given substrate. This component is rich in design knowl-

edge to enable not only compatibility between the printing

materials (ink and substrate) but also ensure that inter-

faces align with the specific requirements of different

electronic applications. The final component, electronic

application, further adds to previous components by

including application-specific design elements of printed

electronics, enabling the development of the final printed

RFID, OLED, printed (semi-)conductors, printed battery

cells, and flexible photovoltaic cells (Cho et al., 2015;

Das & Harrop, 2013; Marketsandmarkets, 2021). Develop-

ing the printed electronic application resembles a success-

ful synergy of all components of the technology system. As

the final component can only be developed through the

interoperability of all components, a vast amount of design

knowledge is required to master the complexity of the con-

verging technology system.

In contrast to the first two components, manufactur-

ing device and electronic application are both rich in

design knowledge and thus have a stronger impact on

the overall system architecture (Baldwin et al., 2014).

These two components necessitate a more diverse set of

knowledge previously rooted in different industries.

Although the printed electronics technology system has

been developing over several decades, components, as

well as their overarching architectural system design, are

still evolving: This is also reflected by ongoing develop-

ment and standardization efforts, yet so far, without

reaching a dominant design.

2.2 |Method and data collection

This study seeks to empirically explore patterns of tech-

nology strategies during a dynamically evolving technol-

ogy system. To this end, we analyze an extensive set of

actively participating firms in the printed electronics field

to capture their different technology strategies. We fur-

thermore investigate how such approaches dynamically

change over time, which demands a longitudinal

approach covering a substantial part of the emergence of

the new technology system. To this end, we use longitu-

dinal patent data, reflecting the development of firm-

specific knowledge stocks in the different domains of the

evolving technology system.

In high-technology fields, such as printed electronics,

intellectual property protection through patents is highly

relevant, as it offers a detailed description and protection

of new and nontrivial technological developments

(Persoon et al., 2021). For this reason, value creation

from technological development activities is usually pro-

tected through patents (Belderbos et al., 2010). When a

dominant design is yet to emerge, protection through pat-

ents is essential for firms, as patents allow firms to block

potential competitors and signal their activities to the

market (Blind et al., 2022). Hence, patents serve as a valid

indicator for companies' strategic technological activities

in the field and deliver a detailed picture of knowledge

stocks developed by firms over time (Andries & Faems,

2013; Blind et al., 2022). Additional benefits of analyzing

patents are their highly structured nature and, thus, high

comparability, as well as the fact that information, for

example, ownership, is validated by skilled patent exam-

iners and available at a detailed level (Ernst, 2003).

To achieve a relevant and comprehensive patent

sample, a stepwise approach was applied to define key

search terms for printed electronics. First, we selected

search terms from seminal scientific publications on

printed electronics and added keywords used in relevant

industry reports (Das & Harrop, 2013; Marketsandmarkets,

2021). To validate the initial search string, we interviewed

four technology domain experts from industries centrally

involved in printed electronics. Industry experts were asked

to validate, compare, and complement a proposed search

string with their endeavors in this field. The final search

string comprises keywords referring to the four compo-

nents. To reach a higher precision, frequently occurring

terms that are not related to printed electronics, but mis-

leading to neighboring fields, were excluded (see Table 2

for search string).

The search string was applied to the Derwent World

Patents Index (DWPI), which is maintained by Thomson

Reuters and offers a collection of over 61 different

sources covering over 105 million global patent publica-

tions (Clarivate, 2022). To prevent overrepresentation

through multicountry filing, this study uses International

Patent Documentation (INPADOC) family IDs (World

Intellectual Property Organization, 2015). INPADOC

families comprise a set of patent documents that relate to

712 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

the same technological content over patent offices in mul-

tiple jurisdictions (Vicente-Gomila et al., 2017). The use of

patent families increases comparability and accuracy

(Barbieri et al., 2020;Clarivate,2018; Persoon et al., 2021)

and is, therefore, an appropriate way to analyze strategic

behavior (Martinez, 2010; World Intellectual Property

Organization, 2015). From now on, and for simplicity, we

will refer to “patent,”although we use patent families.

The first patent in the field was submitted in 1924,

followed by very limited activity over the subsequent

decades. A steadily rising trend can be observed only

from 1990 onwards. Thus, this date is chosen as the start-

ing point for our analysis. The last year included is 2019

due to a gap of 18 months between patent application

and publication in the database.

The sample comprises 3223 patents between 1990 and

2019 (see Figure 3). Each patent is assigned to a com-

pany, that is, Derwent's so-called “Ultimate Parent,”

which refers to the top company in the patent family

hierarchy. They have the ultimate and current responsi-

bility for the patent, including the ability to exploit it

(Stembridge, n.d.).

We excluded patents that provided incomplete infor-

mation (i.e., lacking INPADOC family ID, application

date, ultimate parent, title, abstract, or claims; comprised

around 6% of the sample), and patents filed by universi-

ties or research institutions (comprised around 7% of the

sample), leaving 2800 patents.

We only included firms with a considerable and sus-

tained interest in the field. Thus, firms not participating

intensively in technology development were excluded.

For that reason, only patent assignees with an above-

average number of patents remained in the sample (aver-

age number of patents =4.5; the threshold for inclusion:

min. 5 patents

), leaving 1850 patents.

In the next step, a detailed assessment of the patents'

relevancy was applied by analyzing the patents based on

a textual analysis, which is especially relevant in the con-

text of this convergence due to the similarity of keywords

in printed electronics and conventional printer electron-

ics. Each of the 1850 patents was semantically evaluated

based on abstract and claims to secure that only patents

pertaining to the printed electronics field were included.

Two researchers reviewed the individual patents inde-

pendently, results were compared, differences discussed,

and finally arbitrated. Eight hundred and twenty-eight

patents from 74 corporate assignees remained in the final

sample for printed electronics.

Lastly, the remaining 828 patents were analyzed

semantically to allow a detailed examination of the con-

tent and a classification into the four previously identi-

fied technology components (Persoon et al., 2021).

Analog to the previous step, this was done by building on

the independent, qualitative assessment by two

researchers. Table 3offers a list of central reference terms

that have been used to assign patents to the components.

The list is not complete, as the classification of each of

the components includes the identification and under-

standing of descriptions and synonyms, as well as the

understanding of the patent as a whole.

2.3 |Data analysis

In our analysis, we identified 74 firms as relevant actors

showing sustained interest in the field. To explore their

TABLE 2 Applied search string for printed electronics.

CTB=((PRINT* NEAR2 ELECTRO*) OR (PRINT* NEAR2 ELECTRIC*)) AND CTB=((CONDUCT* ADJ INK*) OR (CONDUCT* ADJ

SUBSTRAT*) OR (FLEX* ADJ CIRCUIT*) OR (FLEX* ADJ DISPLAY*) OR (PRINT* ADJ SCREEN*) OR (PRINT* ADJ TRANSIST*)

OR (OLED*) OR (ORGANIC* ADJ LIGHT* ADJ EMITTING* ADJ DIODE*) OR (RFID) OR (RADIO ADJ FREQUENCY ADJ

IDENTIFICATION) OR (SEMICONDUCT*) OR (SEMI ADJ CONDUCT*) OR (SEMI-CONDUCT*) OR (PRINT* ADJ CONDUCT*)

OR (LED) OR (LIGHT*EMITTING*DIODE*) OR (PRINT* ADJ PHOTOVOLTAIC) OR (PRINT* ADJ SOLAR* ADJ CELL*) OR

(PRINT* ADJ SENSOR*) OR (PRINT* ADJ BATTER*) OR (PRINT* ADJ MEMOR*) OR (FLEX* ADJ SCREEN*) OR (PRINT* ADJ

DISPLAY*) OR (PRINT* ADJ SOLAR*) OR (PRINT* NEAR ELECTROLUMIN*) OR (ORGANIC* ADJ PHOTOVOLT*) OR (OPV))

NOT CTB=((IMAG* ADJ FORMAT*) OR (IMAGE-FORM*) OR (ELECTRO* ADJ PHOTOGRA*));

FIGURE 3 Data-cleaning process.

It should be noted that five patents as a threshold might cause the

impression of underrepresentation of participation, but our basis

remains to rely on patent families. Therefore, the investment made by

an organization for five patent families serves as an indicator of

sustainable interest in the field.

WAMBSGANSS ET AL.713

technology strategy, we measured each firm's scope of

engagement and knowledge base, that is, TSC, as well as

the timing of entry and the dynamic alteration of the TSC

over time (see Table 4for an overview).

Based on the components (four in the printed electron-

ics case) forming the technology system, participation in

technology development is distinguished based on the

numerical indicator “technology system coverage”.TSC

differentiates between a focused and systemic scope of

engagement and the integration of knowledge base. A

focused approach (engagement in only one technological

component) translates into the lowest TSC score of 1. The

more systemic a company approaches technology develop-

ment, that is, the more comprehensively it embraces the

technology system, the higher its TSC score (Table 5). To

be exact, a systemic approach in two different components

but within either specialized knowledge (ink or substrate)

or within design knowledge (manufacturing device or elec-

tronic application) is labeled as a narrow systemic

(TSC =2). When both, specialized and design knowledge

components, are developed, the TSC score increases to 3,

“broad systemic,”and if all four components are covered,

to 4 and “complete systemic.”

Firms can extend their TSC and the underlying base

of technological knowledge with every additional patent.

To analyze and reflect on how a company's TSC changes

over time, a dynamic perspective is included in the analy-

sis. To this end, we distinguish between steady

(no change in TSC) and evolving (increasing TSC). For

that matter, we determine the TSC of each firm twice: in

the very first year of their engagement and at the time of

their last patent application in printed electronics. Due to

the basic assumption of knowledge accumulation

(Persoon et al., 2021), a firm's TSC can only increase and

not decrease over time.

The assessment of the observed timing of entry is

based on Ernst's (1997) model of patenting activity over

the technology life cycle. Ernst's generic model

distinguishes three stages of patenting activity. At first, a

small number of actors initiate the new technology devel-

opment cycle by increasing patenting activity, followed

by a stage of consolidation with declining patenting

activity. Both stages can be considered as the early phase

in the technology life cycle. This is followed by a

maturity stage, which shows a steep increase in patenting

activity (Ernst, 1997). This stage, combined with a decline

toward the end of the life cycle, can be considered as late

phase. Firms to be observed as entering the printed elec-

tronics field after the early phase are classified as follower

firms.

TABLE 3 Reference terms used to assign patents to the corresponding component.

Component Central reference terms

Number of

patents

Substrate Base, pad, plate, sheet, substrate, surface, surface film, surface material 35

Ink Ink, dye, paste, coating material, liquid material, (semi)conductive traces, (semi)conductive

composition, (semi)conductive toner, (semi)conductive film

107

Manufacturing

device

Printing process, printing technique, printing patterning, printing method, patterning processes,

technique, manufacturing method, manufacturing process, printing system, printing device,

methodology

286

Electronic

application

Printed RFID, OLED, printed (semi)conductors, printed battery cells, flexible photovoltaic, printed

solar panel, printed solar cell, printed connectors, printed display, printed monitor, printed

sensor, printed lighting device, printed circuitry, flexible devices, printed wearable

435

Note: A patent could be assigned to two components if the claim was covering the content of two different components. This is the case for 4% of all patents.

Abbreviations: OLED, organic light-emitting diodes; RFID, radio-frequency identification.

TABLE 4 Operationalization of technology strategy variables

relevant in emerging technology fields.

Dimension Measure

Technology system coverage (TSC)

Scope Number of components

•Focused—covering one component

•Systemic—covering more than one

component

Knowledge

base

Type of components

•Components rich in specialized

knowledge

•Components rich in design knowledge

Timing Timing of entry

•Entry in the early phase of technology

system emergence

•Entry in the late phase of technology

system emergence

Dynamics Change of TSC over time

•Steady with constant TSC to deepen

knowledge

•Evolving with increasing TSC to broaden

knowledge

714 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

3|RESULTS

The patenting activity in the converging technology sys-

tem of printed electronics is visualized in Figure 4. In the

early phase between 1990 and 2004, a slow but continu-

ously increasing development can be observed. From

2005 onwards, a strong increase in development activities

follows, which in line with Ernst (1997), points to the

start of the late phase.

Building on these two conceptually established and

empirically observed phases, we classify companies start-

ing their technology development in the early phase, until

2004, as pioneers. Those companies that can be observed

to engage in technology development (i.e., reflected by

patenting behavior) in the late phase, from 2005, are clas-

sified as followers (Golder & Tellis, 1993).

The distribution of patents, as depicted in Figure 5,

reveals that components that inherit design knowledge

(i.e., manufacturing device and electronic application)

lead the technological development in the early phase,

while a continuous and substantial development of the

specialized components (i.e., ink and substrate) mainly

takes place in the late phase. To enable an assessment of

the timing strategies (pioneering vs. following) as well as

TSC dynamic per firm, Figure 5renders a mapping of

each company's initial and final year of participation. A

company's initial TSC is depicted by a blue triangle, while

the final TSC is depicted by an orange bubble. The size of

the triangle/bubble and the number below depicts the

number of firms in this TSC. Overall, 54 out of 74 firms

start as pioneers (73%), while only 20 firms pursue a fol-

lower strategy (27%). Looking at firms' initial approach to

technological system coverage, the majority (91%) of all

pioneers and 80% of all followers start with a focused

approach (TSC =1). Thus, only 5 out of the 54 pioneers

(9%), and 4 out of the 20 followers (20%), start with a sys-

temic approach (TSC > 1).

Regarding TSC dynamics, a general shift toward more

systemic approaches can be observed. The Sankey diagram

TABLE 5 Technology system coverage (TSC) matrix based on

components.

FIGURE 4 Technology system development distinguished by components over time.

WAMBSGANSS ET AL.715

in Figure 6provides insights into the firms' shifts from

their initial to their final TSC and allows us to distinguish

several streams: while most firms dynamically evolve

toward a broader TSC, some remain steady within their

initial TSC. In detail, five firms that start with a TSC of

1 remain focused, but the majority starts focused and

evolves toward a narrow, broad, or complete systemic

TSC. This holds true for 81% of all firms (60 in total). Eight

firms start narrow systemic, of which five firms remain

narrow systemic, and three firms evolve their TSC to

broad systemic. One firm could be observed to start with a

broad systemic approach, remaining in this TSC of 3.

In total, 11 firms remain steady in their TSC. This is

especially noticeable when we take the timing of entry

into perspective—while 11% of all pioneers remain in

their initial TSC, 25% of the followers can be observed to

remain steady (see Figure 7). The remaining 63 firms

evolve to a more systemic stream, of which 48 are pio-

neers and 15 are followers (see Figure 7).

More detailed insights into the knowledge base inherent

in the initial and final TSC are offered in Table 6, illustrating

the initial and final TSC per knowledge base with the corre-

sponding number of firms. Firms' final TSC shows that no

firm pursues a strategy in specialized knowledge only, nei-

ther as a focused nor as a narrow systemic approach. But

also, no company could be observed to start narrow systemic

in specialized knowledge. Thus, all companies (no matter if

focused or systemic) build design knowledge over time.

Looking at firms' final TSC, five firms have remained

in the focused approach in the component of the

FIGURE 5 Firms' initial and final technology system coverage per year with number of firms below triangle/bubble.

FIGURE 6 Streams of technology system coverage development with number of firms in brackets.

716 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

electronic application, which is rich in design knowledge.

These firms are described as steady focused as they

remain in the knowledge base of one component

throughout the emergence of the technology system.

However, 21 companies are narrow systemic in design

knowledge (manufacturing device and electronic applica-

tion) in their final TSC. Five of those firms already

started narrow systemic, whereas 16 came from a focused

approach in design knowledge. Moreover, firms' final

TSC in broad systemic, that is, design and specialized

knowledge, resembles 37 firms in total. Out of those,

33 firms initially come from a focused TSC, 3 came from

narrow systemic, and 1 remained steady broad systemic.

Lastly, 11 firms are classified as complete systemic

(TSC =4) and, thus, have covered all four components

in their final TSC. Interestingly, all these firms come

from an initially focused approach (compare Figure 6).

4|DISCUSSION

The underlying technology convergence case of printed elec-

tronics is characterized by substantial dynamics, uncertainty,

and complexity. As such, the case serves as an insightful

example of an emerging complex technology system (Rotolo

et al., 2015). By observing the technology strategies that firms

adopt to participate in the development of such a converging

technology system, our data reveal four different technology

strategies (Figure 7): (A) steady focused,(B)steady systemic,

backdrop of the investigated case, this taxonomy enables us

to derive propositions for firms aiming at sustained positions

in emerging complex technology systems.

Interestingly, our data reveal a general trend of firms

aiming for more systemic approaches with increasing

maturity of the complex technology system. Thus, the

majority of firms, albeit entering the field of printed elec-

tronics with a focused approach in just one component,

choose to evolve across the scope of the technology sys-

tem. This indicates that firms expand their initial knowl-

edge domain, which advances Cho et al.'s (2015) study,

which found that firms' technology intensification

increases, but do not distinguish different types of

technological knowledge. Even though late entrants

have less time to evolve with the system—simply due to

their later participation—this holds true for most pio-

neers and followers alike. This emphasizes that firms

engage dynamically in broader, increasingly systemic

knowledge-building activities to ensure alignment with

the new evolving technology system. Additionally, those

knowledge-building activities might aim at understand-

ing the new architectural design and the evolution of

new interfaces (Brusoni et al., 2001; Henderson & Clark,

1990). This corresponds to Brusoni et al. (2001), who

argue that firms need to build knowledge bases beyond

their factual technology offerings to understand the

requirements of the entire system. Furthermore, our find-

ing coincides with Staudenmayer et al. (2005), who argue

that increasingly systemic approaches provide firms with

relevant maneuvering space in the evolving technology

system and potentially with direct and indirect exploita-

tion opportunities for future developments. Moreover,

our findings for complex technology systems expand pre-

vious literature on strategic behavior in classic product

development environments, such as Schilling and Hill

(1998), that a more systemic orientation is crucial for

most firms to co-evolve with complex technology sys-

tems. We therefore suggest our first proposition on the

relevance of evolving to a more systemic alignment with

the converging technology system:

Proposition 1. Firms that engage in the

development of an emerging complex technol-

ogy system over time, tend to dynamically

expand their scope and knowledge base to

embrace more components of the system.

Companies participating in the development of a com-

plex technology system, expand their initial knowledge to

enable a system fit. This involves accumulating knowledge

across the scope of the technology system in the long term,

which is crucial for sustained participation.

4.1 |Steady focused technology strategy

A small share of firms resists the dynamics of the sys-

temic evolution and follows a steady focused strategy by

FIGURE 7 Four empirically derived technology strategies.

WAMBSGANSS ET AL.717

TABLE 6 Firms' dynamic development from initial to final technology system coverage (TSC).

718 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

engaging in a single technology component of the con-

verging system throughout their entire engagement.

These firms abstain from building knowledge stocks

across the converging technology system and appear to

find a sustained position, nonetheless. While the environ-

ment of the converging technology system around them

is changing, these firms seize the opportunity to exploit

their focused knowledge position and concentrate their

efforts to potentially become an expert in one

component.

This observed strategy seems to contradict the find-

ings of previous studies such as Baldwin and Clark

(2000) and Staudenmayer et al. (2005), who argue that

component and system level knowledge need to be

aligned. When following a focused strategy, especially

early on in technology system development, a higher

risk of misattributed efforts would be expected. More-

over, in such dynamic environments, a focused strategy

is expected to bring high risks as relevance, industry

standards, and interface specifications are not yet

defined in the dynamics and uncertainties of the

emerging technology system (Rotolo et al., 2015;

Staudenmayer et al., 2005;Su



arez & Utterback, 1995).

Such contrasting views in literature in comparison to

our observation may be resolved by distinguishing the

underlying knowledge base of the components. Our

analysis enables the differentiation between different

knowledge bases (see Table 5), and the results indicate

that firms that participate in the converging technology

system with a steady focused technology strategy miti-

gate the underlying risks by targeting a component that

is rich in design knowledge, that is, electronic

application—and not in any of the specialized compo-

nents, that is, ink or substrate (see the upper right cor-

ner in Table 6). One explanation is that electronic

application, as a component, boasts interfaces to all

other components, those of specialized and of design

knowledge. While firms that build knowledge stocks in

this central component may have a focused scope, an

understanding of intersections and compatibilities is

nevertheless maintained (Baldwin et al., 2014). Thus,

we suggest the second proposition for the condition

under which firms are enabled to a steady focused strat-

egy and may become a component expert, possibly even

directing the overarching development of the technol-

ogy system from their focused perspective:

Proposition 2. Firms that engage in the

development of an emerging complex technol-

ogy system within a single component and

refrain from expanding their scope and their

knowledge base tend to focus on a component

that is rich in design knowledge.

4.2 |Steady systemic technology strategy

Another counter trend to the dynamics of an emerging

complex technology system is the steady systemic technol-

ogy strategy, which is characterized by a more comprehen-

sive but steady approach, that is, targeting multiple

components, potentially from different knowledge bases.

In the printed electronic case, this is empirically evidenced

by multiple firms participating in the technology develop-

ment with components in manufacturing device and elec-

tronic application, that is, multiple components in design

knowledge, and one firm starting with these two compo-

nents and additionally in substrate, that is, components in

design and specialized knowledge (see Table A1 in the

Appendix for detailed references).

Su

arez and Utterback (1995) found that flexibility

comes at high costs when investments have been

approached systemically. This is due to the underlying

risk of a directional change during the emergence of a

dominant design (Grodal et al., 2015;Su



arez et al., 2015;

Su

arez & Utterback, 1995). These findings can be sup-

ported in converging technology systems when looking at

firms that develop knowledge in components embedding

specialized knowledge only: there is no evidence of firms

in a steady systemic technology strategy that remains in

specialized knowledge only. But when we are looking at

firms that participate in components rich in design

knowledge, the steady systemic technology strategy offers

a potentially successful path. Thus, in line with findings

in the steady focused technology strategy, evidence from

this study suggests that a steady systemic technology

strategy is only viable when components rich in design

knowledge are integrated. To be precise, investing in

components embedding specialized knowledge only, does

not seem to offer sufficient coverage of interdepen-

dencies, thus, does not ensure a fit between various com-

ponents. Nonetheless, if firms initially engage in the

development of a converging technology system by

investing in multiple components rich in design knowl-

edge, a steady systemic strategy is a viable path for engag-

ing in a converging technology system. This aligns well

with Wang and Von Tunzelmann's (2000) study on com-

plexity, suggesting that a steady approach toward a tech-

nology system is only achievable if the complexity

inherent in the approached components is adequate and

allows an overall understanding of the system. Thus, the

development of the more complex design knowledge

seems to be needed to follow a steady systemic technol-

ogy strategy, as it allows maneuvering the complexity

and interdependencies of the complex technology system.

If a firm's knowledge base lies in specialized knowledge

components only, the option to remain in a steady sys-

temic technology strategy does not seem to be viable,

WAMBSGANSS ET AL.719

similar to the findings of Grodal et al. (2015) that high-

light the importance of co-evolution of firms' understand-

ing with the emerging industry. Therefore, firms that rely

solely on components reflecting specialized knowledge

may be at risk of being disrupted if they do not continu-

ously innovate and evolve with the emergence of the

complex technology system. Thus, our third proposition

suggests:

Proposition 3. Firms that engage in the

development of an emerging complex technol-

ogy system with a steady systemic technology

strategy tend to cover components rich in design

knowledge.

4.3 |Systemic evolving technology

strategy

The first dynamic technology strategy regards firms that

start with multiple components, for example, in

manufacturing device and electronic application, and

expand their scope and knowledge base over time, for

example, to also include ink. We identify these firms as

pursuing a systemic evolving technology strategy. While

this approach is adopted by the smallest group of firms in

our sample, all of them seem to follow the same pattern:

they start with multiple components embedding design

knowledge and expand to components embedding spe-

cialized knowledge. When firms participate in the devel-

opment of the converging technology system with a

broader scope, design knowledge appears to be a crucial

starting point to further co-evolve with the overarching

technology system. Building specialized knowledge

stocks then appears to be an opportunity in subsequent

development stages.

Starting with design knowledge in a converging tech-

nology system may be crucial for firms to take advantage

of the cumulativeness of a technology, which refers to

the structure of knowledge and how different knowledge

bases build on each other (Persoon et al., 2021). This

approach might enable firms to later branch out to spe-

cialized knowledge bases and, thus, participate in the

development of the technology system with a broader

knowledge scope. But starting from multiple specialized

components in a converging technology system does not

seem to offer an ideal approach. Baldwin et al.'s (2014)

study on software releases supports this notion by sug-

gesting that an understanding of the design of the tech-

nology system enables coupling at the component level.

In summary, our fourth proposition suggests that the

sequence of knowledge accumulation in a complex tech-

nology system should start with design knowledge,

followed by specialized knowledge bases in subsequent

development stages:

Proposition 4. Firms that engage in the

development of an emerging complex technol-

ogy system with multiple components rich in

design knowledge can, in later stages, expand

further by building additional knowledge stocks

in components rich in specialized knowledge.

4.4 |Focused evolving technology

strategy

The focused evolving strategy refers to firms that initially

start with a focused approach, by entering the development

of the converging technology system with a single technol-

ogy component and over time, reaching a more compre-

hensive knowledge scope. This dynamic technology

strategy enables the opportunity to align and, thus, co-

evolve the firm's knowledge scope with ongoing develop-

ments in the technology system. This technology strategy is

adopted by the majority of firms in our sample. The benefit

of this technology strategy may be that through the co-

evolution with the converging technology system, partici-

pation and influence are increased and aligned with matur-

ing interfaces and emerging dominant designs, which in

turn, might enable orchestration (Grodal et al., 2015).

From their initial focused approach, we can distin-

guish between three different complexities that the firms

develop to: narrow systemic, broad systemic, and com-

plete systemic. Looking at the different levels of knowl-

edge complexity that firms build over time, the largest

share of firms develop to a broad systemic approach, cov-

ering both knowledge bases but not covering all four

technology components (see Figure 6).

An interesting finding here is regarding the knowl-

edge base: while a share of firms only expands within

design knowledge, no firm can be observed to start and

remain in only specialized components, that is, ink or

substrate (see Figure 7). Instead, all firms that start in

components embedding specialized knowledge, over

time, build knowledge bases in design knowledge, too. It

appears that investing in components rich in design

knowledge enables firms to position themselves in the

converging technology system, taking architectural

design challenges into account (Jaspers et al., 2012). For

the investigated printed electronic case, this means,

for example, that material suppliers cannot only produce

conductive ink for the manufacturing process of printed

electronics without an understanding of the complex

design requirements of the converged printed electronics

application and/or process itself. This highlights the need

720 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

for firms that invest in components rich in specialized

knowledge, to also build design knowledge in order to

meet the demands of a dynamically evolving technology

system and allow for compatibility.

In line with prior research, we argue that in highly

dynamic environments, as characterized by converging

technology system, specialized knowledge alone is not

sufficient—contrarily, building additional knowledge

across design knowledge bases seems critical (Fleming,

2001; Fleming & Sorenson, 2001; Galunic & Rodan, 1998;

Henderson & Clark, 1990; Wang & Von Tunzelmann,

2000). Rotolo et al. (2015) find that emerging technology

systems inherit uncertainty and dynamics, which, accord-

ing to our findings, can be overcome by firms if they co-

evolute their technology strategy with the development

of the technology system.

The observations made in the focused evolving tech-

nology strategy underline again the importance of design

knowledge, which embeds an understanding of system

structure, intersection, and possible interdependencies

(Baldwin & Clark, 2000; Grodal et al., 2015; Jaspers et al.,

2012). The importance of design knowledge for every

firm, no matter the initial knowledge base, is reflected in

the following proposition:

Proposition 5. Firms that start engaging in

the development of an emerging complex tech-

nology system with a focused approach and

then expand, tend to additionally develop

design knowledge to allow co-evolution with the

converging technology system.

Building a sustained position in the evolving technol-

ogy system, potentially acting as a system integrator, is in

contrast to theory, not necessarily bound to the firm's

timing of engagement (Bayus & Agarwal, 2007; Lee et al.,

2000). However, while the focused evolving strategy is

prominent in our sample regardless of timing of entry,

followers have a slightly higher tendency to follow

alternative technology strategies to the focused evolving

approach. Those firms that we observe to enter late

appear to have a higher tendency to start systemic com-

pared to pioneers. This can potentially be extended with

a finding observed by García-Cabrera et al. (2019), who

conclude that followers tend to have a higher technologi-

cal competence. This also aligns with the early findings

of Lieberman and Montgomery (1988), who argue in

their seminal work on first-mover advantages that pio-

neers need more capacity to protect their position against

aggressive followers—this shows in our case through a

strong majority of pioneers expanding their investments

in depth and breadth over time. Figure 8summarizes the

five propositions on technology strategy, integrating sys-

tem coverage, relevant knowledge stocks, and strategy

evolvement.

5|CONCLUSION

This study explores technology strategies in converging

technology systems based on the conceptualization of

TSC. To the best of our knowledge, this is the first

attempt to account for the complexities inherent in con-

verging technology systems and offering an operational

approach to strategically master associated challenges.

More precisely, TSC draws on the scope, distinguishing

between a focused and a systemic approach; and the

underlying knowledge base, distinguishing between com-

ponents rich in design or specialized knowledge. The

conceptualization of TSC adds a novel dimension to tech-

nology strategy in the realm of complex, uncertain, and

dynamic characteristics of emerging technology systems.

Based hereon, the study identifies four central technology

strategies that differ regarding their technology systems

coverage and their dynamics. The results indicate that all

firms build design knowledge over time, whereas it is

FIGURE 8 Empirically informed technology strategies and propositions.

WAMBSGANSS ET AL.721

remarkable that not all firms build specialized knowledge,

no matter what technology strategy is pursued.

This study provides a valuable contribution to the

previous understanding of technology strategies, which

are yet lacking a systems perspective: In their founda-

tional article on technology strategy, Zahra (1996) con-

ceptualized a company's technology strategy based on

six dimensions: timing of entry, number of products,

internal/external R&D source, R&D spending, portfolio

of applied/basic R&D projects, and use of patenting. We

expand their notion by offering TSC as an additional

dimension of technology strategy. While Zahra (1996)

focuses on the competitive environment, TSC as a strat-

egy dimension allows additional insights into a firm's co-

evolution with the emerging technology system.

Moreover, this study advances Schilling and Hill's

(1998) process view of the new product development pro-

cess by shedding light on the connection and co-

evolution between a firm's technology strategy to the

development of complex emerging technology systems.

In particular, our findings highlight the importance for

firms to adjust their knowledge base and the importance

of design knowledge as an enabler to understanding

interdependencies between components and potentially

allowing orchestration of the development.

We also expand the approach of Cho et al. (2015),

who assign each firm to a single technology component

based on their industry classification, while we offer a

more fine-grained perspective by assigning each patent to

a single technology component. While Cho et al. (2015)

rely on collaborative network activities to emphasize the

increase in technological intensity, our study offers a

more intricate view on the co-evolution of firms partici-

pating in emerging technology systems. This enables a

better understanding of how firms expand their internal

knowledge base and scope when participating in an

emerging complex technology system. Our findings based

on the two knowledge bases, design and specialized, and

the relevance of their sequencing, further advance the

findings of Persoon et al. (2021), who emphasize

the importance of technological cumulativeness.

The results of this study lead to several practical impli-

cations. The findings enable managers to become aware of

the complexity inherent in converging technology systems.

In particular, we suggest a structuring as follows: First, to

structure a complex technology system into components

and their emerging development; second, to build an

understanding of to what extent components and involved

knowledge bases might originate from another hitherto

distant technology system; and third, to monitor interde-

pendencies between components and the technology sys-

tem's underlying architectural design. Moreover, by

disentangling underlying interdependencies, firms can

identify bottlenecks and competence gaps in a timely

manner. Overall, TSC and its dynamics as a relevant

technology strategy dimension may support firms in

developing their technology strategies in the increasingly

complex and uncertain environment surrounding

emerging technology systems.

5.1 |Limitations and future research

Despite the significance of our findings, it is important to

consider them in light of several limitations. This study

refers to patents as indicator of firms' development and

knowledge-building activities in a converging technology

system. While the search string has been carefully put

together based on previous studies and validated by indus-

try experts, interviews with these industry experts addi-

tionally suggested that a patent search string needs to

balance capturing all relevant patents and keeping noise at

a manageable level. Thus, said interviews indicated that

aiming for completeness is not realistic in a technology

landscaping approach, similar to our underlying study,

due to the nature of patents, which are often written with

the intention not to be found. Therefore, a risk remains

that not every patent relevant to the field could be repre-

sented in this study. To mitigate this risk, we truncated

search terms and selected patent families instead of indi-

vidual patents as a basis, whereby we increase the proba-

bility of inclusion and securing a comprehensive sample.

Another limitation regarding patents relates to com-

pleteness. Even though patenting is widespread in the elec-

tronics industry, it might not cover all technology

development activities, as not every invention is patented

in the first place. Patents thus provide a robust albeit not

entirely complete reflection on technology strategies. More-

over, patents do not capture the entirety of companies'

knowledge-building approaches. To this end, firms' technol-

ogy portfolios beyond patents in printed electronics might

add further insights. Future research could triangulate pat-

ent data by capturing in-licensing (Motohashi, 2008),

mergers and acquisition data (Rennings et al., 2022), or

technology collaborations, as well as additional publications

on firms' technology strategies, such as annual reports.

Moreover, the findings regarding key players in the

systemic evolving technology strategy may be somewhat

limited by the consequence of small number statistics. As

our database contains only firms that present a long-term

interest in the field through continuous participation, this

causes a relatively small sample size of 74 key players in

the field. Consequently, the systemic evolving technology

strategy has only been observed in three key players.

Even though these three players show the same pattern

of evolution, we suggest interpreting this specific

722 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

technology strategy with caution. Further studies in other

complex technology systems, possibly with a larger sam-

ple, could be undertaken to further explore the technol-

ogy strategies and propositions uncovered here.

Another point that should be noted is that the

underlying sample focuses on firms actively participat-

ing in the converging technology system and does not

include companies that resist participation and those

that withdraw from sustained participation. Future

research efforts could address this point and extend the

sample beyond active participants, for example, to

explore ineffective technology strategies and potential

reasons for their ineffectiveness. We would also like to

draw the readers' attention to the fact that the underly-

ing assumption of knowledge accumulation does not

necessarily imply that firms are continuously active in

these knowledge areas and, on a similar note, the sam-

ple is not able to account for strategic reorientation. We

suggest integrating this in future studies, for example,

by using additional patent-based measures such as pat-

ent newness or citations.

Scope and knowledge base as foundations of TSC, in

combination with dynamics, seem especially relevant

for developing deliberate technology strategies in the

context of complex technology systems. However, future

research could reflect the identified technology strate-

gies against Mintzberg and Waters' (1985)viewonthe

nature of strategy in general: not all strategies are ex-

ante consciously intended, some also simply emerge as a

pattern.

For scholars rooted in convergence research, the four

technology strategies in this paper may serve as a starting

point to investigate how company dynamics impact

industry dynamics. Future research might therefore

explore which industry background and competence pro-

files, in connection to specialized versus design knowl-

edge, allow the orchestration of converging technology

systems and how this affects the overall industry

structure.

Lastly, it would be highly desirable if further research

included the novel dimension of TSC amongst other

dimensions of technology strategy. This would not only

validate the novel construct but also help to understand

how it relates to other dimensions. To further increase

generalizability, a replication of our analyses in other

high-technology sectors involving complex technology

systems seems insightful.

ACKNOWLEDGMENTS

We would like to thank Philip Emmerich, Mile Katic,

and Lora Tsvetanova for their valuable contributions to

our initial exploration and structuring of data informing

about firms' activities in the printed electronics field. An

earlier version of this paper won the 28th IPDMC

Thomas P. Hustad best student paper award, which moti-

vated us to further explore this exciting topic. Further-

more, we thank the JPIM Editors-in-Chief, Prof. Jelena

Spanjol and Prof. Charles Noble, as well as the three

anonymous reviewers for their valuable comments and

guidance throughout the review process of this paper.

Open Access funding enabled and organized by

Project DEAL.

CONFLICT OF INTEREST STATEMENT

The authors have no conflict of interest to declare.

ETHICS STATEMENT

The authors have read and agreed to the Committee on

Publication Ethics (COPE) international standards for

authors.

ORCID

Annika Wambsganss https://orcid.org/0000-0001-6421-

2764

Stefanie Bröring https://orcid.org/0000-0003-2014-2586

Søren Salomo https://orcid.org/0000-0002-2578-3262

Nathalie Sick https://orcid.org/0000-0002-0713-6918

REFERENCES

Andries, Petra, and Dries Faems. 2013. “Patenting Activities and

Firm Performance: Does Firm Size Matter?”Journal of Product

Innovation Management 30(6): 1089–98. https://doi.org/10.

1111/jpim.12047.

Baldwin, Carliss, Alan MacCormack, and John Rusnak. 2014. “Hid-

den Structure: Using Network Methods to Map System Archi-

tecture.”Research Policy 43(8): 1381–97. https://doi.org/10.

1016/j.respol.2014.05.004.

Baldwin, Carliss Y., and Kim B. Clark. 2000. Design Rules: The

Power of Modularity. Cambridge, MA: The MIT Press. https://

doi.org/10.7551/mitpress/2366.001.0001.

Barbieri, Nicolò, Alberto Marzucchi, and Ugo Rizzo. 2020.

“Knowledge Sources and Impacts on Subsequent Inventions:

Do Green Technologies Differ from Non-Green Ones?”

Research Policy 49(2): 103901. https://doi.org/10.1016/j.

respol.2019.103901.

Bayus, Barry L., and Rajshree Agarwal. 2007. “The Role of Pre-

Entry Experience, Entry Timing, and Product Technology Strat-

egies in Explaining Firm Survival.”Management Science

53(12): 1887–902. https://doi.org/10.1287/mnsc.1070.0737.

Belderbos, Rene, Dries Faems, Bart Leten, and Bart Van Looy.

2010. “Technological Activities and Their Impact on the Finan-

cial Performance of the Firm: Exploitation and Exploration

within and between Firms.”The Journal of Product Innovation

Management 27(6): 869–82. https://doi.org/10.1111/j.1540-5885.

2010.00757.x.

Blind, Knut, Bastian Krieger, and Maikel Pellens. 2022. “The Inter-

play between Product Innovation, Publishing, Patenting and

WAMBSGANSS ET AL.723

Developing Standards.”Research Policy 51(7): 104556. https://

doi.org/10.1016/j.respol.2022.104556.

Bonnet, Didier, and George Yip. 2009. “Strategy Convergence.”

Business Strategy Review 20(2): 50–5. https://doi.org/10.1111/j.

1467-8616.2009.00599.x.

Bröring, Stefanie. 2008. “How Systemic Innovations Require

Alterations along the Entire Supply Chain: The Case of Animal-

Derived Functional Foods.”Journal on Chain and Network Sci-

ence 8(2): 107–19. https://doi.org/10.3920/JCNS2008.x093.

Bröring, Stefanie. 2010. “Developing Innovation Strategies for

Convergence –Is ‘Open Innovation’Imperative?”International

Journal of Technology Management 49(1–3): 272–94. https://

doi.org/10.1504/ijtm.2010.029421.

Bröring, Stefanie, and Jens Leker. 2007. “Industry Convergence

and Its Implications for the Front End of Innovation: A Prob-

lem of Absorptive Capacity.”Creativity and Innovation Manage-

ment 16(2): 165–75. https://doi.org/10.1111/j.1467-8691.2007.

00425.x.

Brusoni, Stefano, Andrea Prencipe, and Keith Pavitt. 2001. “Knowl-

edge Specialization, Organizational Coupling, and the Bound-

aries of the Firm: Why Do Firms Know More than They

Make?”Administrative Science Quarterly 46(4): 597–621.

https://doi.org/10.2307/3094825.

Chesbrough, Henry W., and David J. Teece. 2002. “Organizing for

Innovation: When Is Virtual Virtuous?”Harvard Business

Review 80(8): 127.

Cho, Yongrae, Euiseok Kim, and Wonjoon Kim. 2015. “Strategy

Transformation under Technological Convergence: Evidence

from the Printed Electronics Industry.”International Journal of

Technology Management 67(2–4): 106–31. https://doi.org/10.

1504/IJTM.2015.068222.

Choi, David, and Liisa Valikangas. 2001. “Patterns of Strategy Inno-

vation.”European Management Journal 19(4): 424–9. https://

doi.org/10.1016/S0263-2373(01)00045-7.

Clarivate. 2018. “Derwent Innovation: DWPI and INPADOC Fam-

ily Criteria.”https://support.clarivate.com/Patents/s/article/

Derwent-Innovation-DWPI-and-INPADOC-Family-Criteria?

language=en_US.

Clarivate. 2022. “Derwent World Patents Index: Derwent Value

Added Information.”https://support.clarivate.com/Patents/s/

article/Derwent-World-Patents-Index-Derwent-value-added-

information?language=en_US.

Clark, Kim B. 1985. “The Interaction of Design Hierarchies and

Market Concepts in Technological Evolution.”Research Policy

14(5): 235–51. https://doi.org/10.1016/0048-7333(85)90007-1.

Clarke, Ken, David Ford, and Mike Saren. 1989. “Company Tech-

nology Strategy.”R&D Management 19(3): 215–29. https://doi.

org/10.1111/j.1467-9310.1989.tb00643.x.

Cui, Zheng, Chunshan Zhou, Song Qiu, Zheng Chen, Jian Lin,

Jianwen Zhao, Changqi Ma, and Wenming Su. 2016. Printed

Electronics: Materials, Technologies and Applications.

Singapore: John Wiley & Sons Singapore Pte. Ltd.

Curran, Clive Steven, Stefanie Bröring, and Jens Leker. 2010.

“Anticipating Converging Industries Using Publicly Available

Data.”Technological Forecasting and Social Change 77(3): 385–

95. https://doi.org/10.1016/j.techfore.2009.10.002.

Curran, Clive Steven, and Jens Leker. 2011. “Patent Indicators for

Monitoring Convergence –Examples from NFF and ICT.”

Technological Forecasting and Social Change 78(2): 256–73.

https://doi.org/10.1016/j.techfore.2010.06.021.

Das, Raghu, and Peter Harrop. 2013. Printed, Organic & Flexible

Electronics Forecasts, Players & Opportunities 2012–2022. New

York: PR Newswire Association LLC.

D'Aveni, Richard A. 1994. Hypercompetition: Managing the Dynam-

ics of Strategic Maneuvering. New York: Free Press.

Drechsler, Wenzel, and Martin Natter. 2012. “Understanding a

Firm's Openness Decisions in Innovation.”Journal of Business

Research 65(3): 438–45. https://doi.org/10.1016/j.jbusres.2011.

11.003.

Ernst, Holger. 1997. “The Use of Patent Data for Technological

Forecasting: The Diffusion of CNC-Technology in the Machine

Tool Industry.”Small Business Economics 9(4): 361–81. https://

doi.org/10.1023/A:1007921808138.

Ernst, Holger. 2003. “Patent Information for Strategic Technology

Management.”World Patent Information 25(3): 233–42. https://

doi.org/10.1016/S0172-2190(03)00077-2.

Fleming, Lee. 2001. “Recombinant Uncertainty in Technological

Search.”Management Science 47(1): 117–32. https://doi.org/10.

1287/mnsc.47.1.117.10671.

Fleming, Lee, and Olav Sorenson. 2001. “Technology as a Complex

Adaptive System: Evidence from Patent Data.”Research Policy

30(7): 1019–39. https://doi.org/10.1016/S0048-7333(00)00135-9.

Ford, David. 1988. “Develop Your Technology Strategy.”Long

Range Planning 21(5): 85–95. https://doi.org/10.1016/0024-6301

(88)90109-4.

Friar, John, and Mel Horwitch. 1985. “The Emergence of Technol-

ogy Strategy. A New Dimension of Strategic Management.”

Technology in Society 7(2): 143–78. https://doi.org/10.1016/

0160-791x(85)90023-5.

Galunic, D. Charles, and Simon Rodan. 1998. “Resource Recombi-

nations in the Firm: Knowledge Structures and the Potential

for Schumpeterian Innovation.”Strategic Management Journal

19(12): 1193–201. https://doi.org/10.1002/(SICI)1097-0266

(1998120)19:12<1193::AID-SMJ5>3.0.CO;2-F.

García-Cabrera, Antonia Mercedes, María Gracia García-Soto, and

Arístides Olivares-Mesa. 2019. “Entrepreneurs' Resources,

Technology Strategy, and New Technology-Based Firms' Perfor-

mance.”Journal of Small Business Management 57(4): 1506–30.

https://doi.org/10.1111/jsbm.12411.

Giachetti, Claudio, and Giovanni Battista Dagnino. 2017. “The

Impact of Technological Convergence on Firms' Product Portfo-

lio Strategy: An Information-Based Imitation Approach.”R and

D Management 47(1): 17–35. https://doi.org/10.1111/radm.

12116.

Golder, Peter N., and Gerard J. Tellis. 1993. “Pioneer Advantage:

Marketing Logic Marketing Legend?”Journal of Marketing

Research 30(2): 158–70.

Grodal, Stine, Aleksios Gotsopoulos, and Fernando F. Su

arez. 2015.

“The Coevolution of Technologies and Categories during

Industry Emergence.”The Academy of Management Review

40(3): 423–45.

Hacklin, Frederik. 2008. Management of Convergence in Innovation:

Strategies and Capabilities for Value Creation beyond Blurring

Industry Boundaries, 1st ed. Heidelberg: Physica-Verlag

Heidelberg.

Hacklin, Fredrik, Boris Battistini, and Georg Von Krogh. 2013.

“Strategic Choices in Converging Industries.”MIT Sloan Man-

agement Review 55(1): 64–74.

Hagedoorn, John, and Geert Duysters. 2002. “External Sources of

Innovative Capabilities: The Preference for Strategic Alliances

724 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

or Mergers and Acquisitions.”Journal of Management Studies

39(2): 167–88. https://doi.org/10.1111/1467-6486.00287.

Henderson, Rebecca M., and Kim B. Clark. 1990. “Architectural

Innovation: The Reconfiguration of Existing Product Technolo-

gies and the Failure of Established Firms.”Administrative Sci-

ence Quarterly 35(1): 9–30. https://doi.org/10.2307/2393549.

Hu, Guohua, Joohoon Kang, Leonard W. T. Ng, Xiaoxi Zhu,

Richard C. T. Howe, Christopher G. Jones, Mark C. Hersam,

and Tawfique Hasan. 2018. “Functional Inks and Printing of

Two-Dimensional Materials.”Chemical Society Reviews 47(9):

3265–300. https://doi.org/10.1039/c8cs00084k.

Huang, Qijin, and Yong Zhu. 2019. “Printing Conductive Nano-

materials for Flexible and Stretchable Electronics: A Review

of Materials, Processes, and Applications.”Advanced Mate-

rials Technologies 4(5): 1–41. https://doi.org/10.1002/admt.

201800546.

Jaspers, Ferdinand, Andrea Prencipe, and Jan van den Ende. 2012.

“Organizing Interindustry Architectural Innovations: Evidence

from Mobile Communication Applications.”The Journal of

Product Innovation Management 29(3): 419–31. https://doi.org/

10.1111/j.1540-5885.2012.00915.x.

Kapoor, Rahul, and Nathan R. Furr. 2015. “Complementarities and

Competition: Unpacking the Drivers of Entrants' Technology

Choices in the Solar Photovoltaic Industry.”Strategic Manage-

ment Journal 36(3): 416–36. https://doi.org/10.1002/smj.2223.

Karvonen, Matti, Tuomo Kässi, and Rahul Kapoor. 2010. “Techno-

logical Innovation Strategies in Converging Industries.”Inter-

national Journal of Business Innovation and Research 4(5): 391–

410. https://doi.org/10.1504/IJBIR.2010.034378.

Karvonen, Matti, Matti Lehtovaara, and Tuomo Kässi. 2012. “Build-

Up of Understanding of Technological Convergence: Evidence

from Printed Intelligence Industry.”International Journal of

Innovation and Technology Management 9(3): 1250020. https://

doi.org/10.1142/S0219877012500204.

Kim, Juram, Seungho Kim, and Changyong Lee. 2019. “Anticipat-

ing Technological Convergence: Link Prediction Using Wikipe-

dia Hyperlinks.”Technovation 79(2019): 25–34. https://doi.org/

10.1016/j.technovation.2018.06.008.

Kim, Keungoui, Sungdo Jung, and Junseok Hwang. 2019. “Technol-

ogy Convergence Capability and Firm Innovation in the

Manufacturing Sector: An Approach Based on Patent Network

Analysis.”R and D Management 49(4): 595–606. https://doi.

org/10.1111/radm.12350.

Klarin, Anton, Yuliani Suseno, and Jennifer Ann L. Lajom. 2023.

“Systematic Literature Review of Convergence: A Systems Per-

spective and Re-evaluation of the Convergence Process.”IEEE

Transactions on Engineering Management 70(4): 1531–43.

https://doi.org/10.1109/TEM.2021.3126055.

Kodama, Fumio. 1992. “Technology Fusion and the New R & D.”

Long Range Planning 26(1): 154. https://doi.org/10.1016/0024-

6301(93)90314-6.

Langerak, Fred, and Erik Jan Hultink. 2006. “The Impact of Prod-

uct Innovativeness on the Link between Development Speed

and New Product Profitability.”Journal of Product Innovation

Management 23(3): 203–14.

Lee, Hun, Ken G. Smith, Curtis M. Grimm, and August

Schomburg. 2000. “Timing, Order and Durability of New Prod-

uct Advantages with Imitation.”Strategic Management Journal

21(1): 23–30. https://doi.org/10.1002/(SICI)1097-0266(200001)

21:1<23::AID-SMJ64>3.0.CO;2-0.

Leten, Bart, Rene Belderbos, and Bart Van Looy. 2016. “Entry and

Technological Performance in New Technology Domains:

Technological Opportunities, Technology Competition and

Technological Relatedness.”Journal of Management Studies

53(8): 1257–91. https://doi.org/10.1111/joms.12215.

Lieberman, Marvin B., and David B. Montgomery. 1988. “First-

Mover Advantages.”Strategic Management Journal 9(1): 41–58.

https://doi.org/10.1002/smj.4250090706.

Maine, Elicia, V. J. Thomas, and James Utterback. 2014. “Radical

Innovation from the Confluence of Technologies: Innovation

Management Strategies for the Emerging Nanobiotechnology

Industry.”Journal of Engineering and Technology Management

32: 1–25. https://doi.org/10.1016/j.jengtecman.2013.10.007.

Malerba, Franco, and Luigi Orsenigo. 1996. “Technological

Regimes and Firm Behaviour.”In Organization and Strategy in

the Evolution of the Enterprise 42–71. London: Palgrave Macmil-

lan. https://doi.org/10.1007/978-1-349-13389-5_3.

Marketsandmarkets. 2021. “Printed Electronics Market by Printing

Technology (Screen Printing, Inkjet Print-Ing), Application

(Displays, PV Cells), Resolution, Material (Inks, Substrates),

End-Use Industry, and Geography (2021–2026).”https://www.

marketsandmarkets.com/Market-Reports/printed-electronics-

market-197.html.

Marples, David L. 1961. “The Decisions of Engineering Design.”

IRE Transactions on Engineering Management EM-8(2): 55–71.

https://doi.org/10.1109/IRET-EM.1961.5007593.

Martinez, Catalina. 2010. “Insight into Different Types of Patent

Families.”OECD Science, Technology and Industry Working

Papers. 2010(2). https://doi.org/10.1787/5kml97dr6ptl-en.

Metcalfe, J. S. 1995. “Technology Systems and Technology Policy in

an Evolutionary Framework.”Cambridge Journal of Economics

19(1): 25–46. https://doi.org/10.1093/oxfordjournals.cje.a035307.

Mintzberg, Henry, and James A. Waters. 1985. “Of Strategies, Delib-

erate and Emergent.”Strategic Management Journal 6(3):

252–72.

Motohashi, Kazuyuki. 2008. “Licensing or Not Licensing? An

Empirical Analysis of the Strategic Use of Patents by Japanese

Firms.”Research Policy 37(9): 1548–55. https://doi.org/10.1016/

j.respol.2007.12.014.

Persoon, Peter, Rudi Bekkers, and Floor Alkemade. 2021. “How

Cumulative Is Technological Knowledge?”Quantitative Science

Studies 2(3): 1092–118. https://doi.org/10.1162/qss_a_00140.

Porter, A. L., and D. E. Chubin. 1985. “An Indicator of Cross-

Disciplinary Research.”Scientometrics 8(3–4): 161–76. https://

doi.org/10.1007/BF02016934.

Porter, Michael E. 1991. “Towards a Dynamic Theory of Strategy.”

Strategic Management Journal 12(2): 95–117.

Rennings, Michael, Anna Pina Farina Burgsmüller, and Stefanie

Bröring. 2022. “Convergence towards a Digitalized

Bioeconomy—Exploring Cross-Industry Merger and Acquisi-

tion Activities between the Bioeconomy and the Digital Econ-

omy.”Business Strategy and Development 6(1): 53–74. https://

doi.org/10.1002/bsd2.223.

Rotolo, Daniele, Diana Hicks, and Ben R. Martin. 2015. “What Is

an Emerging Technology?”Research Policy 44(10): 1827–43.

https://doi.org/10.48550/arxiv.1503.00673.

Sanchez, Ron, and Joseph T. Mahoney. 1996. “Modularity, Flexibil-

ity, and Knowledge Management in Product and Organization

Design.”Strategic Management Journal 17(2): 63–76. https://

doi.org/10.1002/smj.4250171107.

WAMBSGANSS ET AL.725

Schilling, Melissa A., and Charles W. L. Hill. 1998. “Managing the

New Product Development Process: Strategic Imperatives.”

Academy of Management Executive 12(3): 67–81. https://doi.

org/10.5465/ame.1998.1109051.

Shmulewitz, Ascher, Robert Langer, and John Patton. 2006. “Con-

vergence in Biomedical Technology.”Nature Biotechnology

24(3): 277. https://doi.org/10.1038/nbt0306-277a.

Sick, Nathalie, and Stefanie Bröring. 2022. “Exploring the Research

Landscape of Convergence from a TIM Perspective: A Review

and Research Agenda.”Technological Forecasting and Social

Change 175: 121321. https://doi.org/10.1016/j.techfore.2021.

121321.

Staudenmayer, Nancy, Mary Tripsas, and Christopher L. Tucci.

2005. “Interfirm Modularity and Its Implications for Product

Development.”The Journal of Product Innovation Management

22(4): 303–21. https://doi.org/10.1111/j.0737-6782.2005.00128.x.

Stembridge, Bob. n.d. “Optimized Assignee and Ultimate Parent: Lift-

ing the Fog around Patent Ownership.”Derwent Innovation.

https://clarivate.com/derwent/wp-content/uploads/sites/3/2020/

08/Clarivate-Analytics_IPS_Optimized-Assignee_FIN.pdf.

Strauss, Anselm L. 1987. Qualitative Analysis for Social Scientists.

Cambridge: Cambridge University Press.

Su

arez, Fernando F., Stine Grodal, and Aleksios Gotsopoulos. 2015.

“Perfect Timing? Dominant Category, Dominant Design, and

the Window of Opportunity for Firm Entry.”Strategic Manage-

ment Journal 36(3): 437–48.

Su

arez, Fernando F., and Gianvito Lanzolla. 2005. “The Half-Truth

of First-Mover Advantage.”Harvard Business Review 83(4):

121–34.

Su

arez, Fernando F., and James M. Utterback. 1995. “Dominant

Designs and the Survival of Firms.”Strategic Management Jour-

nal 16(6): 415–30. https://doi.org/10.1002/smj.4250160602.

Sukri, Suriani, and Rushami Zien Yusoff. 2019. “Technology Strat-

egy: Literature Review and Issues.”International Journal of

Innovation, Creativity and Change 8(6): 67–84.

Talmar, Madis, Bob Walrave, Ksenia S. Podoynitsyna, Jan

Holmström, A. Georges, and L. Romme. 2020. “Mapping, Ana-

lyzing and Designing Innovation Ecosystems: The Ecosystem

Pie Model.”Long Range Planning 53(4): 101850. https://doi.

org/10.1016/j.lrp.2018.09.002.

Taylor, John Eric, and Raymond E. Levitt. 2004. “Understanding

and Managing Systemic Innovation in Project-Based Indus-

tries.”Innovations: Project Management Research. Stanford

University.

Thomke, Stefan, Eric Von Hippel, and Roland Franke. 1998.

“Models of Experimentation.”Research Policy 27(3): 315–32.

Tushman, Michael L., and Charles A. O'Reilly. 1996. “Ambidex-

trous Organizations: Managing Evolutionary and Revolutionary

Change.”California Review Management 38(4): 8–29.

Veugelers, Reinhilde. 1997. “Internal R&D Expenditures and Exter-

nal Technology Sourcing.”Research Policy 26(3): 303–15.

https://doi.org/10.1016/s0048-7333(97)00019-x.

Vicente-Gomila, Jose M., Anna Palli, Begoña de la Calle, Miguel A.

Artacho, and Sara Jimenez. 2017. “Discovering Shifts in Com-

petitive Strategies in Probiotics, Accelerated with TechMining.”

Scientometrics 111(3): 1907–23. https://doi.org/10.1007/s11192-

017-2339-5.

Wang, Q., and N. Von Tunzelmann. 2000. “Complexity and the

Functions of the Firm: Breadth and Depth.”Research Policy

29(7): 805–18. https://doi.org/10.1016/S0048-7333(00)00106-2.

World Intellectual Property Organization. 2015. “Guidelines for

Preparing Patent Landscape Reports.”

Yayavaram, Sai, Manish K. Srivastava, and M. B. Sarkar. 2018.

“Role of Search for Domain Knowledge and Architectural

Knowledge in Alliance Partner Selection.”Strategic Manage-

ment Journal 39(8): 2277–302.

Yoo, Youngjin, Richard J. Boland, Kalle Lyytinen, and Ann

Majchrzak. 2012. “Organizing for Innovation in the Digitized

World.”Organization Science 23(5): 1398–408. https://doi.org/

10.1287/orsc.1120.0771.

Zahra, Shaker A. 1996. “Technology Strategy and New Venture Per-

formance: A Study of Corporate-Sponsored and Independent

Biotechnology Ventures.”Journal of Business Venturing 11(4):

289–321. https://doi.org/10.1016/0883-9026(95)00128-X.

Zahra, Shaker A., and William C. Bogner. 2000. “Technology Strat-

egy and Software New Ventures' Performance: Exploring the

Moderating Effect of the Competitive Environment.”Journal of

Business Venturing 15(2): 135–73. https://doi.org/10.1016/

S0883-9026(98)00009-3.

Zahra, Shaker A., and Gerard George. 2002. “Absorptive Capacity:

A Review, Reconceptualization, and Extension.”The Academy

of Management Review 27(2): 185–203.

AUTHOR BIOGRAPHIES

Annika Wambsganss is a collaborative research

fellow at the Faculty of Engineering and IT at the

University of Technology, Sydney, Australia and at the

Chair of Technology and Innovation Management at

Technical University Berlin, Germany. With a graduate

degree in innovation management and entrepreneur-

ship and a background in industrial engineering, her

research interest focuses on the intersection of strategic

management and knowledge developments in innova-

tive settings. Annika has presented her results at vari-

ous international conferences.

Stefanie Bröring holds the Chair for Entrepreneurship

and Innovative Business Models and is a professor at the

Ruhr-University Bochum (RUB), Germany. She also

serves as the Academic Director of the RUB Worldfac-

tory Start-up Centre. Her research interests span the

emergence of novel (clean) technology systems, technol-

ogy transfer, business model transformation as well as

the rise of cross-industry ecosystems triggered by science

and technology convergence. Her work is published in

various journals including IEEE Transactions on Engi-

neering Management,R&D Management,Technovation,

Journal of Technology Transfer,Technological Forecasting

and Social Change,andmore.

Søren Salomo holds the Chair for Technology and

Innovation Management at the Technical University of

Berlin, Germany and is a professor for innovation man-

agement at the Center for Entrepreneurship at Danish

726 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

Technical University (DTU). He is a member of the

Danish Academy of Technical Sciences and of the Aca-

demic Senate of TU Berlin. His research interests entail

corporate innovation management with a special focus

on process and organizational system mechanisms for

supporting innovation. Recently, his interest expands

toward individual innovative behavior. Søren's work

has been published in the Journal of Product Innovation

Management,Research Policy,Creativity and Innovation

Management, and more.

Nathalie Sick is a Senior Lecturer in Contemporary

Technology Management and a core member of the

Centre for Advanced Manufacturing in the Faculty

of Engineering and IT at the University of Technol-

ogy, Sydney, Australia. Her research interests are

heterogeneous collaborations, industry convergence,

and technology forecasting in technology-driven

environments. Nathalie is particularly interested in

spanning the boundaries between different disci-

plines, industries, and actors in the collaboration

arena, such as industry, university, and government.

She has published her research in Technological

Forecasting and Social Change,Technovation,Jour-

nal of Cleaner Production, and others.

How to cite this article: Wambsganss, Annika,

Stefanie Bröring, Søren Salomo, and Nathalie Sick.

2023. “Technology Strategies in Converging

Technology Systems: Evidence from Printed

Electronics.”Journal of Product Innovation

Management 40(5): 705–732. https://doi.org/10.

1111/jpim.12693

WAMBSGANSS ET AL.727

TABLE A1 Overview of companies and their technology strategies.

Company name Timing

Initial

year

Initial

component

Initial

TSC

Initial

knowledge

base

Final

year

Final

components

(accum.)

Final

TSC

Final

knowledge

base

Technology

strategy

3M CO Pioneer 1990 Ink 1 Specialized 2010 Substrate/Ink/MD/

4 Both Focused

evolving

AMS AG Pioneer 2003 EA 1 Design 2018 Ink/MD/EA 3 Both Focused

evolving

APPLE INC. Pioneer 2012 MD/EA 2 Design 2019 MD/EA 2 Design Steady

systemic

ASE TECHNOLOGY HOLDING

CO. LTD.

Pioneer 2000 EA 1 Design 2018 MD/EA 2 Design Focused

evolving

AVERY DENNISON CORP. Pioneer 1997 EA 1 Design 2016 EA 1 Design Steady

focused

BASF SE Pioneer 1991 Ink 1 Specialized 2018 Ink/MD 3 Both Focused

evolving

BLUE SPARK TECHNOLOGIES

INC.

Follower 2005 EA 1 Design 2017 EA 1 Design Steady

focused

BOE TECHNOLOGY GROUP

LTD.

Pioneer 1993 EA 1 Design 2019 Substrate/MD/EA 3 Both Focused

evolving

BOEING CO. (THE) Follower 2004 MD/EA 2 Design 2019 MD/EA 2 Design Steady

systemic

BORGWARNER INC. Pioneer 1992 MD 1 Design 2005 MD/EA 2 Design Focused

evolving

BOSCH (ROBERT) GMBH Pioneer 2002 EA 1 Design 2014 MD/EA 2 Design Focused

evolving

BROTHER INDUSTRIES LTD. Pioneer 1998 EA 1 Design 2015 MD/EA 2 Design Focused

evolving

CANON INC. Pioneer 1999 Ink 1 Specialized 2018 Substrate/Ink/MD/

4 Both Focused

evolving

COMPAGNIE DE SAINT-

GOBAIN

Follower 2000 EA 1 Design 2019 Substrate/MD/EA 3 Both Focused

evolving

CORNING INC. Pioneer 2013 MD 1 Design 2017 Substrate/MD/EA 3 Both Focused

evolving

APPENDIX A.

728 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

TABLE A1 (Continued)

Company name Timing

Initial

year

Initial

component

Initial

TSC

Initial

knowledge

base

Final

year

Final

components

(accum.)

Final

TSC

Final

knowledge

base

Technology

strategy

DIC CORPORATION Pioneer 2006 Ink 1 Specialized 2019 Ink/MD/EA 3 Both Focused

evolving

DOW CHEMICAL CO. Pioneer 1993 MD 1 Design 2010 Substrate/MD 3 Both Focused

evolving

DUPONT DE NEMOURS INC. Pioneer 1998 Substrate 1 Specialized 2019 Substrate/Ink/MD/

4 Both Focused

evolving

EASTMAN KODAK COMPANY Pioneer 1991 MD 1 Design 2018 Substrate/Ink/MD/

4 Both Focused

evolving

FUJI FILM HOLDINGS CORP. Follower 1992 EA 1 Design 2015 Ink/MD/EA 3 Both Focused

evolving

GENERAL ELECTRIC

COMPANY

Pioneer 2002 MD 1 Design 2018 Ink/MD/EA 3 Both Focused

evolving

GLOBAL FOUNDRIES INC. Pioneer 1996 MD 1 Design 2013 MD/EA 2 Design Focused

evolving

GULA CONSULTING LLC Follower 2005 MD 1 Design 2010 Ink/MD/EA 3 Both Focused

evolving

HENKEL KGAA Pioneer 1993 Ink 1 Specialized 2015 Ink/MD 3 Both Focused

evolving

HITACHI LTD. Pioneer 1992 Ink 1 Specialized 2007 Ink/MD/EA 3 Both Focused

evolving

HON HAI PRECISION

INDUSTRY CO. LTD.

Pioneer 2000 EA 1 Design 2019 Ink/MD/EA 3 Both Focused

evolving

HONEYWELL INTERNATIONAL

INC.

Pioneer 1999 EA 1 Design 2018 MD/EA 2 Design Focused

evolving

HP INC. Pioneer 1990 EA 1 Design 2019 Ink/MD/EA 3 Both Focused

evolving

HSIO TECHNOLOGIES LLC Follower 2011 EA 1 Design 2018 EA 1 Design Steady

focused

ILLINOIS TOOL WORKS INC. Follower 2006 Substrate 1 Specialized 2018 Substrate/MD/EA 3 Both Focused

evolving

INFINEON TECHNOLOGIES AG Pioneer 2001 MD 1 Design 2019 MD/EA 2 Design Focused

evolving

(Continues)

WAMBSGANSS ET AL.729

TABLE A1 (Continued)

Company name Timing

Initial

year

Initial

component

Initial

TSC

Initial

knowledge

base

Final

year

Final

components

(accum.)

Final

TSC

Final

knowledge

base

Technology

strategy

INGREDION INC. Follower 2000 Ink 1 Specialized 2016 Ink/MD/EA 3 Both Focused

evolving

INTEL CORPORATION Follower 2001 MD 1 Design 2019 Ink/MD/EA 3 Both Focused

evolving

INTERNATIONAL BUSINESS

MACHINES CORP.

Pioneer 1990 MD 1 Design 2013 Substrate/Ink/MD/

4 Both Focused

evolving

JOHNSON ELECTRIC

HOLDINGS LTD.

Pioneer 1993 EA 1 Design 2018 EA 1 Design Steady

focused

KOCH INDUSTRIES INC. Pioneer 1995 MD 1 Design 2019 MD/EA 2 Design Focused

evolving

KONINKLIJKE PHILIPS N.V. Pioneer 1997 MD 1 Design 2012 Ink/MD/EA 3 Both Focused

evolving

KYOCERA CORP. Pioneer 1995 Ink 1 Specialized 2016 Ink/MD/EA 3 Both Focused

evolving

LG DISPLAY CO. LTD./LG

CHEM LTD.

Follower 2003 EA 1 Design 2019 Ink/MD/EA 3 Both Focused

evolving

MERCK KGAA Pioneer 2006 MD / EA 2 Design 2017 Ink/MD/EA 3 Both Systemic

evolving

MICRON TECHNOLOGY INC. Pioneer 1992 MD 1 Design 2010 Ink/MD/EA 3 Both Focused

evolving

MITSUBISHI ELECTRIC CORP. Pioneer 1990 MD / EA 2 Design 2016 MD/EA 2 Design Steady

systemic

MOTOROLA SOLUTIONS INC. Pioneer 1991 MD 1 Design 2008 Substrate/Ink/MD/

4 Both Focused

evolving

NEC CORP. Pioneer 1993 MD 1 Design 2014 Substrate/MD/EA 3 Both Focused

evolving

NOKIA CORPORATION Pioneer 1996 EA 1 Design 2019 MD/EA 2 Design Focused

evolving

OKI ELECTRIC INDUSTRY CO.

LTD.

Pioneer 1995 EA 1 Design 2001 MD/EA 2 Design Focused

evolving

PANASONIC CORPORATION Pioneer 1990 MD 1 Design 2016 Substrate/Ink/MD/

4 Both Focused

evolving

PARELEC INC. Pioneer 1999 MD 1 Design 2007 Ink/MD 3 Both Focused

evolving

730 JOURNAL OF PRODUCT INNOVATION MANAGEMENT

TABLE A1 (Continued)

Company name Timing

Initial

year

Initial

component

Initial

TSC

Initial

knowledge

base

Final

year

Final

components

(accum.)

Final

TSC

Final

knowledge

base

Technology

strategy

PARKER HANNIFIN CORP. Follower 1998 EA 1 Design 2018 Ink/MD/EA 3 Both Focused

evolving

POLARIS INDUSTRIES INC. Pioneer 2002 MD / EA 2 Design 2007 Substrate/MD/EA 3 Both Systemic

evolving

PRECURSOR ENERGETICS INC. Pioneer 2010 MD / EA 2 Design 2014 Ink/MD/EA 3 Both Systemic

evolving

QUALCOMM INC. Pioneer 2004 MD 1 Design 2014 MD/EA 2 Design Focused

evolving

RENESAS ELECTRONIC

CORPORATION

Pioneer 2001 EA 1 Design 2016 MD/EA 2 Design Focused

evolving

ROHM CO. LTD. Pioneer 1995 EA 1 Design 2015 MD/EA 2 Design Focused

evolving

SAMSUNG ELECTRO

MECHANICS CO. LTD./

SAMSUNG ELECTRONICS CO.

LTD.

Pioneer 1996 MD 1 Design 2019 Substrate/Ink/MD/

4 Both Focused

evolving

SAUDI ARABIAN OIL

COMPANY (SAUDI ARAMCO)

Follower 2003 Ink 1 Specialized 2018 Ink/MD/EA 3 Both Focused

evolving

SEIKO EPSON CORPORATION Pioneer 2002 MD / EA 2 Design 2008 MD/EA 2 Design Steady

systemic

SEMICONDUCTOR ENERGY

LABORATORY CO. LTD.

Follower 2004 EA 1 Design 2018 MD/EA 2 Design Focused

evolving

SHIN-ETSU CHEMICAL CO.

LTD.

Pioneer 1990 MD 1 Design 2018 Ink/MD/EA 3 Both Focused

evolving

SONY CORP. Follower 2006 EA 1 Design 2012 Substrate/Ink/MD/

4 Both Focused

evolving

STMICROELECTRONICS Follower 2012 EA 1 Design 2018 EA 1 Design Steady

focused

SUMITOMO CHEMICAL CO.

LTD.

Pioneer 2006 Ink 1 Specialized 2017 Ink/MD/EA 3 Both Focused

evolving

TACTOTEK OY Pioneer 2011 EA 1 Design 2019 Ink/MD/EA 3 Both Focused

evolving

(Continues)

WAMBSGANSS ET AL.731

TABLE A1 (Continued)

Company name Timing

Initial

year

Initial

component

Initial

TSC

Initial

knowledge

base

Final

year

Final

components

(accum.)

Final

TSC

Final

knowledge

base

Technology

strategy

TAIWAN SEMICONDUCTOR

MANUFACTURING CO.

Pioneer 2007 Ink 1 Specialized 2018 Ink/MD/EA 3 Both Focused

evolving

TCL CORP. Follower 2013 EA 1 Design 2019 Ink/MD/EA 3 Both Focused

evolving

TDK CORPORATION Pioneer 1999 MD / EA 2 Design 2018 MD/EA 2 Design Steady

systemic

TEXAS INSTRUMENTS INC. Pioneer 1996 MD 1 Design 2018 MD/EA 2 Design Focused

evolving

THIN FILM ELECTRONICS ASA Follower 2005 EA 1 Design 2019 Ink/MD/EA 3 Both Focused

evolving

TOSHIBA CORP. Pioneer 1991 MD 1 Design 2017 MD/EA 2 Design Focused

evolving

UNIMICRON TECHNOLOGY

CORP.

Follower 2006 Substrate/

MD/EA

3 Both 2013 Substrate/MD/EA 3 Both Steady

systemic

VORBECK MATERIALS CORP. Follower 2009 Ink 1 Specialized 2019 Substrate/Ink/MD/

4 Both Focused

evolving

X DISPLAY CO. TECHNOLOGY

LTD.

Follower 2007 EA 1 Design 2019 Substrate/MD/EA 3 Both Focused

evolving

XEROX CORP. Pioneer 1991 MD 1 Design 2019 Substrate/Ink/MD/

4 Both Focused

evolving

ZHUHAI SEINE TECHNOLOGY

CO. LTD.

Pioneer 2005 MD 1 Design 2007 Ink/MD 3 Both Focused

evolving

Abbreviations: EA, electronic application; MD, manufacturing device; TSC, technology system coverage.

732 JOURNAL OF PRODUCT INNOVATION MANAGEMENT