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# Technological Forecasting & Social Change

[journal homepage: www.elsevier.com/locate/techfore](http://www.elsevier.com/locate/techfore)

## Industrial design rights and the market value of firms[✩]

David E. Andersson [a][,][∗], Anton Ekman [b], Anton Huila [c], Fredrik Tell [d]

a Department of Business Studies, Box 513, S-751 20 Uppsala University, Sweden
b Deloitte, Sweden
c EY, Sweden
d Department of Business Studies, Uppsala University, Sweden


A R T I C L E I N F O

_JEL classification:_
O34
L25
O32

_Keywords:_
Industrial design rights
Patents
Trademarks
R&D
Intellectual property
Market value
Tobin’s q

**1. Introduction**


A B S T R A C T

This paper studies how investments in design affect the market value of firms, using European Registered
Community Designs and national Swedish design rights data combined with R&D, patent and trademark data,
for the period 2003–2013. This paper is the first large-scale quantitative study using industrial designs rights
to measure design. Nonlinear least-squares regressions are used to investigate the association between these
variables and the market value of Swedish firms. The results show that industrial designs rights have a positive
and significant relationship to the market value of firms. It provides both new evidence on the effect of
industrial design rights on the market value of firms and internationally comparable results for other intangible
assets such as patents, trademarks and R&D. Theoretically, the paper contributes to the understanding of design
knowledge and the valuation of design rights.


and Vezzani, 2020; Sandner and Block, 2011) and important theoretical implications for innovation research in particular with respect to
market innovations (Castaldi and Dosso, 2018; Castaldi, 2020; Castaldi
and Mendonça, 2022), there is still a dearth of studies that assess the
relative importance of IDRs for the market value of firms. Admittedly
less common than patents and trademarks, Alcacer et al. (2017) still
estimate that close to 1 million IDR applications (937.000) were submitted worldwide in 2013. IDR applications had then doubled in ten
years and constituted about a fifth of global trademark applications
(4.87 million) and less than half of patent applications (2.57 million).
The increased use of IDRs is indeed remarkable as ‘‘...growth in the use of
_IP tools has outpaced growth in both GDP and trade. Interestingly, industrial_
_design applications which were lower in absolute terms than applications for_
_the more-favored IP tools of patents and trademarks have grown even faster_
_than FDI for substantial parts of the decade’’ (Alcacer et al., 2017, p. 166)._

Fig. 1 exhibits a similar growth pattern in the EU for IPR applications for the period 2003–2016, albeit with patents dominating
and a larger proportion of IDR applications relative to trademarks.


As other intellectual property rights (IPR), Industrial Design Rights
(IDRs) are knowledge assets that have been suggested to serve as important drivers in the contemporary global economy (Alcacer et al., 2017;
Montresor and Vezzani, 2020). In general, there is substantial value
accumulations associated with IPR and the U.S. Chamber of Commerce
Global Innovation Policy Center 2022 suggests that ‘‘America’s IP is
_worth $6.6 trillion, more than the nominal GDP of any other country in_
_the world’’. At the same time, while there is variegation of intellec-_
tual property rights into patents, trademarks and IDRs (WIPO, 2003;
Galindo-Rueda and Millot, 2015; Pinate et al., 2022), until recently
research has been relatively one-sided in its focus on using patents
to assess the value of firms’ knowledge assets (Czarnitzki et al., 2006;
Hall, 2007; Hall and MacGarvie, 2010; Hall and Oriani, 2006; Toivanen
et al., 2002; Chen and Chang, 2010; Lee and Lee, 2017).
While a recent stream of literature has provided analyses of trademarks in relation to patents that show both their economic value (Dosso


✩ Acknowledgments: We thank Shinjinee Chattopadhyay, Per Ekman, Philip Kappen, Jung H. Kwon, Yunchen Sun and Ivo Zander for helpful comments as
well as participants of session 12 at DRUID19 (Copenhagen Business School, Denmark). We are grateful to the Swedish Patent and Registration Office (PRV) for
giving us access to their trademark and design databases. Maximilian Gustafsson provided excellent research assistance.
Funding: This work was supported by Vinnova (grant number 2017-04473), Torsten Söderbergs Stiftelse (grant number E58/17) and Jan Wallanders och Tom
Hedelius Stiftelse samt Tore Browaldhs Stiftelse (grant number P20-0286).
∗ Corresponding author.
_[E-mail address: david.andersson@fek.uu.se (D.E. Andersson).](mailto:david.andersson@fek.uu.se)_

[https://doi.org/10.1016/j.techfore.2023.122827](https://doi.org/10.1016/j.techfore.2023.122827)
Received 18 February 2022; Received in revised form 11 August 2023; Accepted 3 September 2023

Available online 16 September 2023
[0040-1625/© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).](http://creativecommons.org/licenses/by/4.0/)


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and D’Ippolito, 2017; Montresor and Vezzani, 2020); the importance
of design for innovation performance in service and product markets (Candi and Saemundsson, 2011; Fjællegaard et al., 2019; Ghisetti
and Montresor, 2019); and indicated challenges for firms to use and
defend their holdings of IDRs to appropriate rents when rights are
contested (Filitz et al., 2015; Filippetti and D’Ippolito, 2017; Heikkilä
and Peltoniemi, 2019).
These and other studies suggest that design constitutes an important
innovation capability for firms and that IDRs analogous with patents
and trademarks should have the potential to serve as an indicator for
specific knowledge assets (Filippetti et al., 2019; Ghisetti et al., 2021)
that are valued by investors and financial markets. Therefore, the aim
of the study presented in this paper is to investigate: How does ownership
_of IDRs relate to firms’ market value?_
Using the market value approach of knowledge assets using Tobin’s
q suggested by Zvi Griliches and Bronwyn Hall with colleagues, later
amended by Sandner and Block (2011) to include IPR portfolios, we
seek answers to this question by analyzing a novel dataset covering
Swedish firms’ ownership of IPRs (patents, trademarks, IDRs), accounting data, and stock prices between 2003–2013. More specifically, we
evaluate IDRs both in comparison to and combined with R&D, patents
and trademarks. We collected and analyzed data on IDRs, patents and
trademarks, publicly available from the Swedish Patent and Registration Office (PRV), the European Patent Office (EPO) and the EUIPO.
The results show that, in general, financial markets tend to reward
companies that invest in IDRs. Our study also reveals that, in line with
previous research, patents, R&D and trademarks also indicate a positive
relationship to the firm’s market value.
This study zooms in on a specific set of knowledge assets (IDRs)
in a specific context (Swedish firms). In light of this focus (with
its associated benefits and limitations), we suggest that our findings
make important empirical and theoretical contributions. Empirically,
to our knowledge, the study is the first of its kind to demonstrate
the firm market value of an (increasingly) important IPR, namely
IDRs. In line with previous research on the market value of patents
and trademarks, the study shows that financial markets value also
IDRs. Moreover, not only is the absolute value of IDRs indicated by
the study (by an increment of 0.126), but this effect is also put in
relation to the valuation of patents and trademarks for the same dataset.
Finally, while Sweden has been singled out as one of the most designintensive countries in the world (Filitz et al., 2015; Galindo-Rueda and
Millot, 2015), valuation of Swedish firms’ design activities emanating in
IDRs has not yet been examined in previous research, which contrasts
with studies in other prominent European design countries such as
the UK (e.g. Bascavusoglu-Moreau and Tether, 2011); Germany (e.g.
Filitz et al., 2015); Italy (e.g. Filippetti and D’Ippolito, 2017); Denmark (e.g. Galindo-Rueda and Millot, 2015; Fjællegaard et al., 2019)
and Finland Heikkilä and Peltoniemi (2019).
Theoretically, we contribute to the understanding of design knowledge and valuation of design rights by financial markets. Even though
IDR in theory appear a relatively weak form of IPR, this study show
that despite the uncertainty surrounding the quality of IDRs financial markets evaluate them positively. We suggest three explanations
for this observation. First, a particular characteristic of IDRs as an
IPR is their explicit product connection (Walsh, 1996). Second, assuming that design capability is an unobservable antecedent of IDRs,
such innovative capabilities are attributable to firms competitive advantage (as expected by shareholders). Drawing upon the knowledge
based view of the firm (KBV), our findings lend support to prior
theoretical conjectures that design is a distinguishable innovative capability that firms can use to reap competitive advantage (d’Ippolito,
2014; Galindo-Rueda and Millot, 2015; Ghisetti, Montresor, and Vezzani, 2021). Third, design is more coupled with embodied aesthetic
knowledge (Ewenstein and Whyte, 2007).
In the following, the paper is organized accordingly. Section 2

summarizes the legal background of IDRs in Europe and positions


**Fig. 1. Industrial design right, trademark and patent applications, 2003–2016.**
_Notes: This figure depicts applications filed at the EPO and EUIPO._
_Source: WIPO Statistics Database and EUIPO Open data._

Yearly Registered Community Designs (RCD)-applications filed with
the EUIPO grew by 160% between 2003 and 2016. The number of
IDRs filings is approaching the numbers of other IPRs. Following the
establishment of the RCD in 2003, in 2018, approximately 1.1 million
applications had been filed and it has become one of the largest IDR
registers in the world, for users both outside and within the EU and
is seen as a quick and relatively cheap way to obtain protection in
the EU (Heneghan, 2016). As design rights are under a registration
system in Europe while patent applications undergo pre-examination,
the relative holdings of granted design rights relative to patents are
even higher than for applications.
Illustrating the value firms put on their IDRs and that they are
prepared to enforce them aggressively, in May 2018, a judge in California ordered Samsung to pay Apple US$533.3 million in damages
for infringement of Apple’s EU Registered Community Design (RCD)
for the iPad and several of Apple’s original iPhone and iPad design
patents.[1] The ruling had its origins in a 2011 court case in which Apple
accused Samsung of infringements of several design patents and utility
patents in several countries. Following the 2018 ruling, Apple’s issued
an official statement saying that it ‘‘believe[d] deeply in the value of
_design’’.[2]_ Another lawsuit, in February 2018, had a different outcome;
the European General Court upheld the decision by the European Union
Intellectual Property Office (EUIPO) to revoke Crocs Inc.’s RCD No.
257001-0001. The RCD protected the well-known footwear producer’s
design, which had generated more than US$1 billion in yearly sales
since its launch in 2002.[3] Crocs Inc. also lost in a major infringement
litigation case heard in the Delhi High Court against seven Indian
footwear manufacturers over its Indian industrial design rights (Ghosh
and Khan, 2018).
Accordingly, there have been calls for more research into the aesthetic dimension of innovation and the role of IDRs (Filitz et al., 2015;
Galindo-Rueda and Millot, 2015; Filippetti et al., 2019; Holgersson
and van Santen, 2018). Recent research has demonstrated that firms
– in-house or in collaboration with specialized design suppliers – integrate design when innovating (Candi and Gemser, 2010; Filippetti

1 In total, Samsung was obliged to pay $538.6 million, of which
$5.3 million was for infringing Apple’s utility patents. See USA Today,
[at https://eu.usatoday.com/story/tech/2018/05/24/samsung-must-payapple-](https://eu.usatoday.com/story/tech/2018/05/24/samsung-must-payapple-539-million-copying-iphone-patents/623908002/)
[539-million-copying-iphone-patents/623908002/ (last accessed: 19 February](https://eu.usatoday.com/story/tech/2018/05/24/samsung-must-payapple-539-million-copying-iphone-patents/623908002/)
2020).
2 See Footnote 1.
[3 Novagraaf, at https://www.novagraaf.com/en/insights/what-croc-crocs-](https://www.novagraaf.com/en/insights/what-croc-crocs-eu-design-revoked)
[eu-design-revoked (last accessed: 19 February 2020).](https://www.novagraaf.com/en/insights/what-croc-crocs-eu-design-revoked)


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the study as a knowledge-based approach to analyzing IDRs and firm
value. Section 3 introduces the data and elaborate the methodological
approach. Section 4 presents the results from the empirical analysis,
while Section 5 provides a concluding discussion entailing limitations,
further research, contributions and implications.

**2. Industrial design rights: What are they and do they matter for**
**firm value?**

_2.1. Legal definition and development of industrial design rights in Europe_
_and Sweden_

The World Intellectual Property Office (WIPO) refers to different

types of IPR: trademarks, patents and IDRs. A trademark is a registered
distinctive sign that identifies a certain good or service, produced or
provided by an individual or a company; a patent is an exclusive right
granted for a technical invention; an IDR protects a design in the form
of ornamental or aesthetic aspects (Galindo-Rueda and Millot, 2015;
Pinate et al., 2022). Design can include three-dimensional features such
as shape and texture, or two-dimensional features such as patterns,
lines and color (WIPO, 2003). Previous research suggests that designs
contribute to firm value through their connection and complementarity
to other types of innovation (Walsh, 1996). Unlike patents, designs are
not required to include an inventive step to be granted. At the same
time, designs are less general than trademarks, in the sense that the
granting of an IDR requires the design to be novel and individual in
character, as well as associated with a product or service.

In Europe, the legal foundations of IDRs developed in two stages

(Filitz et al., 2015). The European Council passed an EU directive in
1998, requiring all EU members to have a formal IDR registration
process to harmonize national protection. This directive established
a definition of IDRs as ‘the appearance of the whole or a part of a
product resulting from the features of, in particular, the lines, contours,
colors, shape, texture and/or materials of the product itself and/or
its ornamentation’ (Directive 98/71/EC). That is, a design needs to
be new and distinguishable from other existing designs. The second
step involved the passing of Community Design Regulation in 2002
(Regulation EC 6/2002), resulting in two types of IDRs across the EU:
the registered community design (RCD), and the unregistered community design (UCD) which provides automatic protection throughout
Europe three years after disclosure. In line with The Hague System
(initiated in 1925), owners of IDRs can also register them with the
World Intellectual Property Office (WIPO). Registering through WIPO
means that the owner of the IDR needs only to apply to WIPO to
receive protection in several European countries. However, for the
period covered in this study (2003–2013) a vast majority (ca. 80%–
90%) of European IDRs were filed using domestic patent offices, and
almost all US and Chinese IDRs were filed domestically (Alcacer et al.,
2017, pp. 183–184; 189). In contrast to patents, there is no examination
before granting an RCD (i.e. a registration system). However, since
third parties can file oppositions to challenge the validity of European
design rights, applicants may still be careful in registering designs
that do not meet the individuality and novelty criteria (Fjællegaard
et al., 2019). The maximum protection time is 25 years, and requires a
renewal fee to be paid every five years (Alcacer et al., 2017, p. 191).

At the national level, Swedish industrial design law originated in

the 10 July 1899 law on ‘protection of specific patterns and models’
(Swedish code of Statutes 1899/59). However, this law applied only
to the metal working industries and granted protection for only five
years from the filing date of the application. Current Swedish IDRs are
regulated by the industrial design law passed in 1970 (Law 1970:485)
and are granted in increments of one to five years to a maximum of
25 years. The applicant can choose to apply for several increments
at the same time or renew every five years. National Swedish IDRs
is administered by the Swedish PRV. Table 1 presents an overview of
different IPRs.


_2.2. Industrial design rights as knowledge assets_

Broadly defined, knowledge assets include knowledge about orga
nizational processes, organizational routines and structural arrangements, as well as formal and legally binding documents confirming the
firm’s rights to the intellectual output produced by the organization and
its members. Teece (2000, p. 35) notes that: ‘‘[Knowledge] assets include
_tacit and codified know-how, both technical and organizational, whether or_
_not protected by the instruments of intellectual property such as trade secrets,_
_copyrights and patents’’. Following Teece’s 2000 distinction, and drawing_
upon Ewenstein and Whyte (2007, pp. 690–692) demarcation between
aesthetic knowledge as embodied competency and symbolic style, we
conceptually separate two knowledge asset properties attributable to
IDRs. First, IDRs are a result of firms’ design capabilities, that is,
often tacit and embodied know-how that differs from other R&D-based
knowledge (see Section 2.2.1). Second, an IDR is a codified intellectual
property right (IPR) expressing a certain style represented in symbolic
and non-verbal expressions associated with specific and distinguishable
jurisdictions and legal procedures (see Section 2.2.2).

_2.2.1. Industrial design as capability_

While IDRs are conferred to holders as legal rights, they emanate

from design activities undertaken by firms seeking to innovate and gain
competitive advantage in the marketplace by appealing to aesthetic
emotions of customers through form and functionality of products
and services. WIPO defines industrial design as ‘‘the creative activity of
_achieving a formal or ornamental appearance for mass-produced items that,_
_within the available cost constraints, satisfies both the need for the item to_
_appeal visually to potential consumers, and the need for the item to perform_
_its intended function efficiently’’ (WIPO, 2004, p. 112). Thus conceived,_
design activities are exemplars of organizational routines that encapsulate firm-specific organizational knowledge (Nelson, 1991). In line
with arguments put forward in knowledge based theories of firms and
competitive advantage (Grant, 1996; Kogut and Zander, 1992; Teece,
1982), if such design knowledge is idiosyncratic to the firm and difficult
to imitate for competitors while at the same time being conducive to
deliver value to customers, investments in design activities serve as a
source for competitive advantage.

Design capability specifically designates aesthetic knowledge (Filitz

et al., 2015; Walsh, 1996). Several conditions can be fulfilled by design
capabilities to contribute to firm performance and sustainable competitive advantage (Barney, 1991; Barney and Hesterly, 2010). By being
uniquely tied to products and services design appeals to tactile and
symbolic experience and evoke emotions among its users, thereby delivering value to them (Sisodia, 1992). Design capabilities are rare when
they are embodied in designers in specific contexts that are unevenly
distributed among firms and not readily transferable to competitors.
The embodied and tacit nature of aesthetic knowledge (Ewenstein and
Whyte, 2007) also makes it difficult for competitors to identify and
imitate required capabilities. Moreover, as much aesthetic knowledge
takes long time to master and may require apprenticeship practices,
there are time compression diseconomies (Dierickx and Cool, 1989)
associated with them that further hinder the copy of design capabilities.
Finally, it is difficult to organize and integrate design capabilities as it
requires both (a) ‘‘knowledge integration by design’’; that is, creative
acts of knowledge generation and conception afforded by the design
process in itself; (b) ‘‘knowledge integration of design’’, that is, design
knowledge to be articulated, systematized and integrated in relation
to other knowledge assets (Åman et al., 2017), (see also Gemser and
Leenders, 2001; d’Ippolito, 2014; Montresor and Vezzani, 2020).

Indeed, there is growing evidence that design pay dividends in terms

of innovation and firm performance. For instance, empirical research
has utilized country-specific (e.g. Marsili and Salter, 2006, for the UK),
industry and country specific (e.g. Alegre et al., 2012, for ceramic
tile industry in Italy and Spain), regional and sector specific (e.g.
Candi and Saemundsson, 2011, for new technology based firms in the


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**Table 1**
Overview of intellectual property rights.
_Source: PRV, EUIPO, EPO, WIPO._

Intellectual property right Type Jurisdiction Time Administration

National Design Industrial Design Right National 25 years[b] National
Registered Community Design (RCD) Industrial Design Right EU 25 years EUIPO
Unregistered Community Design (UCD) Industrial Design Right EU 3 years EUIPO
International Design (Hague system)[a] Industrial Design Right National 25 years WIPO
National Patent Patent National 20 years National
European Patent[a] Patent EU 20 years EPO
Patent (PCT)[a] Patent National 20 years WIPO
National Trademark Trademark National No limit National
Community Trademark (CTM) Trademark EU No limit EUIPO
International Trademark (Madrid system)[a] Trademark National No limit WIPO

_Notes: This table presents an overview of different types of industrial design rights, trademarks and patents and the corresponding jurisdictions_
and administration levels.
a Denotes national IPR applied for through a common application process administered by EPO or WIPO.

b US design patents are only valid for 14 years.


Nordic countries), or cross-industry and cross-country (e.g. Montresor
and Vezzani, 2020, for European firms) survey data. These and other
studies demonstrate that design knowledge resulting in successful new
features of products and services give rise to competitive advantage in
the marketplace. At the same time, this and much other empirical work
focus on firm investments in design knowledge and design activities,
but not specifically any outcomes that may be granted in terms of IDRs
and their potential value as knowledge assets.

_2.2.2. IDRs as IPR_

In addition to capability-based sources associated with competitive

advantages, IPRs serve as important means for appropriating rents
from knowledge assets (Grant, 1991; Teece, 2000; Filitz et al., 2015;
Filippetti and D’Ippolito, 2017). IPRs are formal devices for appropriating value and protecting against imitation (e.g. Teece, 1986; Arundel,
2001). By providing monopoly right to specific knowledge, IPRs protect
its owner against the extraction of transaction value from the innovation by others, thereby allowing for value capture. As illustrated in
Table 1, there are different IPRs that also are granted and enforced
under varying jurisdictions.

In the case of IDRs as IPRs, a key feature is the conversion of

design knowledge into ornamental or aesthetic features of functional
products or services that can be illustrated in two-dimensional (2D) or
three-dimensional (3D) representations. Theoretically, there are rival
arguments when it comes to the relative strength of IDRs as an IPR
device for appropriating returns. Due to the product-specificity of IDRs,
they can be conceived as strong IPRs, as arguably it is on product
markets competition between different value propositions to consumers
take place (Roberts, 1999). In comparison to other IPRs emanating from
R&D, IDRs differ. Patents cover the right to an invention, that is, a
solution to a specific problem in a field of technology and the most
important criteria for patentability is usefulness and novelty — not its
encapsulation in a product (WIPO, 2004, p. 17). Trademarks, on the
other hand, refers to ‘‘any sign that individualizes the goods of a given
_enterprise and distinguishes them from the goods of its competitors’’ (WIPO,_
2004, p. 68). Accordingly, trademarks more so than design rights apply
more generally to firms.

On the other hand, formally IDRs appear as a rather weak form of

IPR. Opportunities for specification of both individual distinctiveness
and novelty is limited by its format (also allowing for filing multiple
designs in one application). The European IDR system is a registration
system where examination of distinctiveness is not scrutinized in relation to prior art. This means that de facto verification is taking place
ex post, relying on appeals and infringement litigation as mechanisms.
Moreover, in addition to being a relatively expensive, localized and
time-consuming process, empirical evidence suggests that it is difficult
to uphold IDRs in court (Alcacer et al., 2017; Filitz et al., 2015;
Filippetti and D’Ippolito, 2017; Heikkilä and Peltoniemi, 2019). This
suggests that while IDRs are being increasingly used their benefits for
appropriating rents are highly uncertain. So what is the value of IDRs?


_2.2.3. Market value of IDRs_

IDRs are observable knowledge assets that firms that when owned

by firms whose shares are publicly traded on stock markets are valued
– together with its other assets – by shareholders, where expectations
about future profits are reflected in stock prices (Griliches, 1981; Hall,
1999; Nesta and Saviotti, 2006). Holdings by a firm of IDRs signal
themselves as IPRs (being assessed as stronger or weaker in its potential
to appropriate rents). IDRs also signal unobservable design innovation
capabilities whose potential both for current value capture as well as for
value creation for the future is evaluated and reflected in shareholder
expectations about future profits of firms.

In research, IDRs have been used as a proxy for design innovations

as an outcome measure (Fjællegaard et al., 2019) or as a measure of
specifically ‘‘green designs’’ and their impact on innovation (measured
by ‘‘green’’ patents) (Ghisetti et al., 2021). Still, especially in comparison with patents and, more recently, trademarks, empirical evidence
collected and analyzed regarding the market value of firms owning
IDRs is scarce. There are some exceptions which include studies of
UK and Australian IDRs. For instance, Bosworth and Rogers (2001)
include IDRs in their study of IPR and the market value of Australian
firms in the mid-1990s. Griffiths et al. (2011) investigate profits in
relation to IDRs for Australian firms, but find scant evidence of a
linkage. Bascavusoglu-Moreau and Tether (2011), in the case of the UK,
examine IDRs and firm sales and find a positive relationship especially
for national IDRs. Given the recent attention that design has attracted
in innovation studies, and the rapidly increasing use of IDRs by firms,
the aim of this paper is therefore to examine further how ownership of
IDRs relate to firms’ market value.

_2.3. Estimating market value of firms_


To estimate the economic value of IPRs and the returns from

innovation-generating activities we use Tobin’s q (Montgomery and
Wernerfelt, 1988). The first method using values based on Tobin’s 1969
formulation of the variable q – the ratio of the market value to the
replacement cost – was developed by Lindenberg and Ross (1981).
Using this method, the firm’s market value includes both its physical
and intangible assets. Investors in financial markets evaluate the future
returns for various companies and these evaluations form the basis for
the valuations reflected eventually in stock prices. On the assumption
of an efficient market, the stock price is equal to all future cash
flows generated by the company (Fama, 1970). Therefore, the market
value can be seen as a leading indicator of the firm’s future performance (Hall, 1999). Hall et al. (2007) suggest that the market value
approach assumes that firms are composed of assets; this approach,
assumes, also, that the company’s value is a function of its component
assets, determined by the financial markets. These component assets
include both physical and intangible assets. According to Griliches


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(1981) and Hall (1999) assets can be estimated in a typical linear
market value equation (Eq. (1)).

_𝑉𝑖𝑡(𝐴𝑖𝑡, 𝐾𝑖𝑡) = 𝑞𝑖𝑡(𝐴𝑖𝑡_ + 𝛾𝐾𝑖𝑡)[𝜎] (1)

with

_𝑞𝑖𝑡_ = exp(𝑦𝑡 + 𝑚𝑙 + 𝑢𝑖𝑡) (2)

where 𝑉𝑖𝑡 is the value of company 𝑖 at time 𝑡. 𝐴 is tangible assets
and 𝐾 is knowledge assets. Knowledge assets include R&D, patents,
trademarks and IDRs. The value of the company is the sum of the value
of its tangible and knowledge assets.[4] _𝜎_ captures returns to scale and
_𝜎_ = 1 indicates returns proportionate to scale (Pemberton and Rau,
2011). 𝛾 is the marginal contribution value of one additional unit spent
on knowledge assets and, if 𝜎 = 1, represents the shadow value of the
firm’s knowledge assets relative to its tangible assets (Hall and Oriani,
2006). Consequently, the product of 𝑞𝑖𝑡 and 𝛾 reflects the absolute
shadow value of investors’ expectations about knowledge assets. In line
with previous studies, despite the loss of accuracy, we keep 𝛾 fixed
to prevent variation across time (Hall and Oriani, 2006; Sandner and
Block, 2011). The shadow value is understood as the implicit market
outcome of the interaction between the company and its investment
activity and between investors and their evaluation of the company in
the financial market. The shadow value should not be understood as a
structural parameter (Hall, 1999; Hall and Oriani, 2006). The valuation
coefficient, 𝑞𝑖𝑡, comprises factors that represent the valuation effects of
time 𝑡, industry 𝑙 and individual disturbances 𝑢𝑖𝑡, and captures factors
affecting the valuation in a multiplicative way (see Eq. (2)) (Hirsch and
Seaks, 1993). These factors may include individual risk as well as the
market conditions (Griliches, 1981). The general effects of these factors
on the valuation are represented by 𝑦𝑡 and 𝑚𝑙.

As already noted, R&D investments and patents can represent

knowledge assets 𝐾 (Hall et al., 1993; Hall and Oriani, 2006) and
several studies include both (Cockburn and Griliches, 1988; Griliches
et al., 1991; Toivanen et al., 2002; Hall et al., 2005; Hall and MacGarvie, 2010). Hall et al. (2005) found that simple patent counts have
less explanatory power than citation-weighted patent stocks, which
accounts for much of the unequally distributed values of patents. In the
present study we include IDRs, patents and trademarks in the market
value equation.

_2.4. Adding intellectual property into the market value equation_


By treating the different asset types symmetrically, we assume that

the firm can choose to invest in any of these assets. 𝛾𝐼 is the relative
shadow value of one additional unit of investment in the IPR portfolio
to physical assets. By including logarithms to account for returns to
scale, the estimation equation becomes:

_𝑙𝑛_ ( 𝑉𝐴𝑖𝑡𝑖𝑡 ) = 𝑙𝑛𝑞𝑖𝑡 + (𝜎 −1)𝑙𝑛𝐴𝑖𝑡 + 𝜎𝑙𝑛 (1 + 𝛾𝐾 _𝐾𝐴𝑖𝑡𝑖𝑡_ + 𝛾𝐼 _𝐴𝐼𝑖𝑡𝑖𝑡_ ) (5)

**3. Methods and data**

_3.1. Data_


We analyze IDRs and other IPRs owned by Swedish firms. Few, if

any, previous studies estimating IPR, and more specifically IDRs, and
market value of firms use Swedish data. In general, Sweden repeatedly
ranks as one of the world’s most innovative countries, with high levels
of R&D input, output and efficiency (Cornell et al., 2017). With respect
to design, Galindo-Rueda and Millot (2015, p. 11) estimate that the
Swedish design industry was the fifth largest in Europe in 2011 (after
the UK, Italy, Germany and France, all countries with at least five
times the population of Sweden and except for Italy at least five times
the size of GDP). Examining RCD registrations and relating them to
GDP, Filitz et al. (2015, p. 1196) single out Sweden with Austria,
Denmark and Switzerland as particularly strong countries. Moreover,
ownership of shares in companies quoted on Swedish stock exchanges
is fairly international, the proportion of non-Swedish ownership rose
from 34% in 2003 to 41% in 2013 (Statistics Sweden, 2022). To
further highlight the relative spread of opportunities for investment
in Swedish companies, several of the major Swedish engineering-based
multinationals are also listed on overseas stock exchanges. We therefore
submit that the Swedish financial context and Swedish firms is suitable
for a study of the value of design rights, despite the relative small
number of observations that can be obtained.

We collected international patent data from EPO’s PATSTAT Online

Autumn 2017 edition and use EUIPO’s Open Dataset to gather EUwide IDR and trademark data. For data on Swedish IDRs, patents
and trademarks, we obtained information from the Swedish Design
Database, the Swedish Patent Database, and the Swedish Trademark
Database via the PRV. Firm level and financial accounting data were
collected from Thomson Reuters Eikon database, and time-series data
on inflation rates were obtained from Statistics Sweden. To further
validate our calculated IPR stock, obtain qualitative insight into IPR
management and explain the results of the regressions, we conducted
five interviews with representatives of some of the companies in our
sample.

The market value equation needs input in the form of market

value, we therefore consider only publicly traded companies. Eikon
is used to identify firms listed as large cap, mid cap, and small cap
on the NASDAQ Stockholm Exchange during the years 2003–2013.
Since the aim is to represent all companies listed on the NASDAQ
Stockholm Exchange, we impose no restrictions on specific industries.
More specifically, we extract total revenue, enterprise value, cash and
cash equivalents, total assets, total debt, R&D expenditure and the
standard industry classification. We conducted a random sample check
of company annual reports to validate the Eikon financial data. We
deflated SEK (Swedish krona)-values to year 2003 prices imputed from
Statistics Sweden’s yearly consumer price index.

The data extracted from the PATSTAT and EUIPO databases extend

to applications originating in 2017 not all of which had been processed
or granted. Since the number of applications in process increases for
more recent years, granted registered rights decrease. As we are interested only in granted applications, we truncate the data to include
only those applications granted no later than end 2013. We set the end
of our observation period to 2013 to minimize the effect of potential
truncation bias due to the lag between application submission and
grant. PRV and EUIPO data suggest that 97% of submitted applications


We include IDRs, patents and trademarks in the market value equa
tion in two ways. First, we assume that IPRs are a type of knowledge
assets. In the market value equation, we include a separate term for IPR
portfolio, which is in line with previous studies using this method (see
Bosworth and Rogers, 2001; Greenhalgh and Rogers, 2007; Hall and
Oriani, 2006; Sandner and Block, 2011). In our analysis, IPR portfolios
consist of design, patent and trademark assets. Functionally, we assume
that all three asset classes can be treated similarly to R&D. In Eq. (3),
we include IPR portfolio as an additional additive term, 𝐼. Beside
IPRs, knowledge assets are not listed on balance sheets. We therefore
operationalize knowledge assets as R&D separately from IPRs and let
R&D represent 𝐾. In Eq. (4), 𝐼 includes design assets (𝐷), patent assets
(𝑃 ) and trademark assets (𝑇𝑀). Consequently, we reformulate the
market value equation by including IPR portfolios.

_𝑉𝑖𝑡(𝐴𝑖𝑡, 𝐾𝑖𝑡, 𝐼𝑖𝑡) = 𝑞𝑖𝑡(𝐴𝑖𝑡_ + 𝛾𝐾 _𝐾𝑖𝑡_ + 𝛾𝐼 _𝐼𝑖𝑡)[𝜎]_ (3)

where

_𝐼𝑖𝑡_ = 𝐷𝑖𝑡 + 𝑃𝑖𝑡 + 𝑇𝑀𝑖𝑡 (4)

4 If there are important complementarities or synergies between tangible
and intangible assets the value can be larger than the sum of the separate
assets.


-----

are decided after four years, which results in a negligible effect on the
2013 cohort.[5] This approach has the advantage that it uses actual IPR
stocks rather than assumptions for the later years in the observation
period, which avoids truncation bias.

The extracted Swedish data reflect all available historically granted

IPRs for the firms in our sample, registered at the PRV. Our Swedish
IDR data with legal entities as applicants, are from 1993, the first year
when these statistics are available. We track patents from 1984, the
earliest year when a patent would still be valid in 2003, the start of our
observation period. Our Swedish trademark data are from 1884, which
is the earliest year in the dataset. Following the rationale applied to
Swedish data, we collected European IDR data from the Open Dataset
provided by EUIPO starting in 2003. As noted above, the RCD came
into force in 2002 and introduced EU-wide IDRs. Thus, there are no IDR
data for Europe before 2003. European Community trademarks (CTM)
were collected from 1996 onwards; EUIPO began operations in 1996,
hence, there are no CTMs prior to that year. Global data on patents from
PATSTAT Online is collected from 1984 to 2016 based on the filing
date. This allows us to build accurate asset stocks for the companies in
our sample.

_3.2. Variables_


_3.2.2. Knowledge assets_

Knowledge assets are not listed on balance sheets. We operationalize

the knowledge assets of interest as both R&D and IPR, but distinct
from each other. R&D expenses tend not to be entered on balance
sheets due to the uncertain value of many R&D investments (Ross,
1983). However, we estimate knowledge assets based on R&D expenses.
We use historical R&D expenditure and a declining-balance formula to
calculate knowledge stock (Eq. (7)) (Hall et al., 2005; Hall, 2007). We
use a fixed depreciation rate, set to 15%, to account for obsolescence,
in line with e.g., Hall (2007).

_𝑅𝐷𝑡[𝑠𝑡𝑜𝑐𝑘]_ = 𝑅𝐷𝑡[𝑓𝑙𝑜𝑤] + (1 − _𝛿)𝑅𝐷𝑡[𝑠𝑡𝑜𝑐𝑘]−1_ (7)

Because our financial data go only to 2002, we assume that R&D

stocks grew at a constant annual growth rate, 𝑔, of 8% which allows us
to compute initial R&D stock for the first observed year (Eq. (8)).

1
_𝑅𝐷0[𝑠𝑡𝑜𝑐𝑘]_ = _𝛿_ + 𝑔 _[𝑅𝐷]0[𝑓𝑙𝑜𝑤]_ (8)

Disclosure of R&D expenses is loosely regulated (Hall et al., 2007)

and the decision to disclose it is arbitrary. Some companies consider
that this information should be reserved to internal use and choose
not to disclose it (Toivanen et al., 2002), which could cause sample
selection bias (Belcher et al., 2002) because the calculation of R&D
stocks requires uninterrupted historical data of R&D expenditures. We
assign an R&D dummy variable to companies lacking R&D expenditures
or with partial R&D histories. Missing values are coded 0 in line with
earlier research (Hall, 2007; Sandner and Block, 2011).

_3.2.3. Industrial design rights_

We use the declining-balance formula to calculate IDR stock, 𝐷,

(Eq. (9)), and use the IDR application date to define yearly flows. We
let IDR stocks depreciate because IDRs have a life span of maximum
25 years. In addition, as mentioned above, an IDR can be related to
technical inventions that have become obsolete. No other studies consider depreciating IDR stocks; therefore, there is no agreed appropriate
depreciation rate. However, since the underlying innovative activity
of IDRs can be said to share similar traits as with R&D and other
industrial activities (Walsh, 1996; Filitz et al., 2015), we use the same
depreciation rate, 𝛿.

_𝐷𝑡[𝑠𝑡𝑜𝑐𝑘]_ = 𝐷𝑡[𝑓𝑙𝑜𝑤] + (1 − _𝛿)𝐷𝑡[𝑠𝑡𝑜𝑐𝑘]−1_ (9)

We do not calculate initial stocks since Swedish national IDR data

goes back to 1979, but RCDs were introduced only in 2003.

_3.2.4. Patents_

We use the methodology applied to IDR stocks to calculate patent

family stocks (Eq. (10)).

_𝐹𝑡[𝑠𝑡𝑜𝑐𝑘]_ = 𝐹𝑡[𝑓𝑙𝑜𝑤] + (1 − _𝛿)𝐹𝑡[𝑠𝑡𝑜𝑐𝑘]−1_ (10)

We calculate patent family stocks because they represent the un
derlying inventions protected by the patents, and apply a 15% yearly
depreciation rate to write down this stock (Hall, 2007; Sandner and
Block, 2011). The firm-specific yearly flow of patents is determined
based on the priority application and filing year in each simple patent
family. We do not compute initial stocks since the time starts in 2003
and data were collected from PATSTAT starting in 1984. The pure
patent stock has limited explanatory power because patent value is
not normally distributed (Harhoff et al., 1999, 2003). To ensure that
we capture patent quality, we can consider measures such as citations,
family size and oppositions. We calculate citations in line with prior
research (Bloom and Van Reenen, 2002; Hall et al., 2005; Hall, 2007;
Sandner and Block, 2011).

We calculate family-to-family citations in simple families, which

comes closest to one invention citing another invention. In this study,
we consider citations within three years after publication to capture the
bulk of the patent citations during each patent’s lifetime (Marco, 2007;


We chose to calculate all assets as stock variables rather than flow

variables because stock variables capture all annual inflows into the
stock up to a specific point in time 𝑡, whereas flow variables capture
annual inflows in year 𝑡. For instance, if a company’s IDR stock in
_𝑡_ −1 is 50 IDRs, and it files for five more IDRs in year 𝑡, the stock
in year 𝑡 will be 55 IDRs. Obsolescence is accounted for by letting
the stock of 𝑡 −1 depreciate (Hall, 2007). A company is valued by
the discounted future cash flows generated by its assets (Fama, 1970).
The knowledge used for current product development is assumed to be
based on experience of past investment in, for instance, R&D. Although
this experience-based knowledge depreciates over time, it influences
investors’ estimations of future company performance and valuation.
Our approach is in line with Sandner and Block (2011), who use stock
variables to account for R&D, patents and trademarks. Observations
with no IDRs, patents, trademarks or R&D are coded 0 and accounted
for by a corresponding dummy variable.

_3.2.1. Tobin’s q_

Our dependent variable is the natural logarithm of Tobin’s q — see

Eq. (6), defined as the ratio of the company’s market value, 𝑉, to the
book value of its total assets, 𝐴 (Greenhalgh and Rogers, 2006; Hall
and Oriani, 2006; Sandner and Block, 2011).

_𝑙𝑛𝑞𝑡_ = 𝑙𝑛 _𝐴[𝑉][𝑡]𝑡_ (6)

The firm’s market value is the aggregate equity and debt market

value. We proxy the equity value by the firm’s market capitalization
plus preferential stock and minority interests. Market capitalization is
defined as the number of shares times the share price. We proxy the
market value of debt by the book value of total debt, which is equal
to the short-term plus the long-term debt (Blundell et al., 1992, 1999;
Hall and Oriani, 2006). The total assets book value is the total assets
recorded in the balance sheet.[6]

5 In general however, trademarks and IDRs are granted much quicker than
patents.
6 Researchers in corporate finance have developed advanced estimates of
Tobin’s q (e.g. Perfect and Wiles, 1994), but it is always a trade-off between
precision and sample size (DaDalt et al., 2003).


-----

Mehta et al., 2010; Sandner and Block, 2011). Also, a constant time
limit of three years reduces the risk of truncation issues regarding year
of application. To measure the quality of firm-specific patent stock, we
weight each patent by the number of citations. The stock of citations
can be written as:

_𝐶𝑡[𝑠𝑡𝑜𝑐𝑘]_ = 𝐶𝑡[𝑓𝑙𝑜𝑤] + (1 − _𝛿)𝐶𝑡[𝑠𝑡𝑜𝑐𝑘]−1_ (11)

_3.2.5. Trademarks_

To compute stock of trademarks, we apply the same methodology

as used to estimate IDR and patent stocks. We calculate the flow of
trademarks in any specific year, based, in most cases, on trademark
registration date apart from EUIPO data which do not have registration dates. In this case, we use the date the trademark was filed for
registration. Since around 90% of trademarks are published within 11
weeks of filing (EUIPO, 2011), this has little effect on our calculated
trademark stock. In contrast to our computation of R&D asset stock,
we do not depreciate trademark stock. R&D assets are likely to lose
their value over time, due to obsolescence and new technological
developments and patents have a restricted lifetime. We therefore apply
a depreciation rate when determining the value of knowledge assets
and patent stocks (Hall, 2007). However, arguably, trademarks become
more valuable as time passes. They have no time limit, that is, the grant
period (of trademarks) is infinite if renewal fees are paid continuously,
generally every 10 years, and the trademark is used on the market.
Therefore, over time, firms can continue to use their trademarks portfolio to generate value which is why we apply no depreciation rate to
trademarks.

In this study, we consider a trademark to be ‘dead’ if the renewal

fee is not paid or if the registration office cancels the trademark as the
result of a successful termination request from a competing firm. We
handle the first type of case by including an estimated renewal rate, 𝑟.
The average renewal rate of CTMs originating between 1996 and 2007
is about 45% (EUIPO, 2018), so we set 𝑟 to 45%. The second case has
no substantial impact in practice: EUIPO statistics for 2003 to 2013
show only 8,305 trademark applications recorded as cancelled among
the 896,169 trademark applications filed during this period (EUIPO,
2018). Eq. (12) provides the estimation of the trademark stock:

_𝑇𝑀𝑡[𝑠𝑡𝑜𝑐𝑘]_ = 𝑇𝑀𝑡[𝑓𝑙𝑜𝑤] −(1 − _𝑟)𝑇𝑀𝑡[𝑓𝑙𝑜𝑤]−10_ [+][ 𝑇𝑀]𝑡[𝑠𝑡𝑜𝑐𝑘]−1 (12)

As noted earlier, although we do not compute initial trademarks

stock, for simplicity we bundle trademark applications filed before
1983. This affects 5% of the trademark applications. We then assume
that trademarks are held in infinity after the first renewal. This assumption affects 8.6% of the trademark applications. These two actions
have a negligible effect on trademark stocks, so our data provide a full
history of Swedish trademarks. Also, as noted earlier, EUIPO trademark
data are available only from 1996. However, a substantial number of
applications in 1996 refer to international trademarks as firms applied
for protection in Europe for pre-existing trademarks (Sandner and
Block, 2011).

_3.2.6. Control variables_

Following prior studies, we include year and industry dummies to

control for time and industry effects in the market valuation (Griliches,
1981; Blundell et al., 1999; Hall et al., 2007; Sandner and Block, 2011).
We use Standard Industry Classification (SIC) codes as the basis of our
industry classifications, and sort all of the sample firms into categories,
resulting in : Manufacturing, Paper, Public Utilities, Electronics, Trade,
Finance, Transport Equipment and Services. However, 73% of firms are
in the Manufacturing group, so to allow for more granularity among
manufacturing industries, we subdivide Manufacturing, based on the
first two numbers in the SIC code, and obtain: Other manufacturing,
Other Metals, Mining & Construction, Machinery and Instruments (see
Table 3). Thus, we have a total of 12 industry classes, with the largest
class representing 14.6% of firms. Section 5.1 provides more detail on
industry characteristics.


_3.3. Econometric model_

Next, we add the variables, relative to their appropriate bases to

measure their respective intensities. IDR stock (D) relative total assets
(A), R&D stock (RD) relative total assets (A); patent family stock (F)
relative R&D stock (RD); citation stock (C) relative patent family stock
(F); and trademark stock (M) relative total assets (A) (Eq. (13)).

_𝑙𝑛_ _𝐴[𝑉][𝑖𝑡]𝑖𝑡_ = 𝑙𝑛𝑞𝑖𝑡 + (𝜎 −1)𝑙𝑛𝐴𝑖𝑡 (13)

+ 𝜎𝑙𝑛 1 + 𝛾1 _𝑅𝐷𝑖𝑡_ + 𝛾2 _𝐷𝑖𝑡_ + 𝛾3 _𝑇𝑀𝑖𝑡_ + 𝛾4 _𝐹𝑖𝑡_ + 𝛾5 _𝐶𝑖𝑡_
( _𝐴𝑖𝑡_ _𝐴𝑖𝑡_ _𝐴𝑖𝑡_ _𝑅𝐷𝑖𝑡_ _𝐹𝑖𝑡_ )

We do not hold unidentified firm-level components constant. By

employing a pooled regression model, we examine the market value
of the firms IPRs portfolio for a broad range of firms and industries,
which, for our purposes, limits the impact of unidentified firm-level
components (Sandner and Block, 2011). Tangible assets, knowledge
assets and IPR portfolio change only slightly year on year; thus, were
we to apply fixed firm-level effects, we would observe a relatively
low degree of variance in the data. Significant deltas in the asset base
within specific firms would need a rigid time interval, which we do not
consider in this paper.

To estimate Tobin’s q, we apply a Non-Linear Least Squares (NLLS)

regression (Hall et al., 2007; Sandner and Block, 2011; Rahko, 2014).
Prior studies using Ordinary Least Squares (OLS) use 𝑋 as an approximation for ln(1 + 𝑋). However, as Hall et al. (2007) suggest,
this method of approximating X leads to imprecision when knowledge
assets increase relative to physical assets. Instead, the NLLS technique
allows accurate estimation of nonlinear functions where the market
value equation is such a function. Due to nonlinearity, interpretation of
the coefficients is not straightforward and the regressors use different
units (e.g., SEK, IDRs, trademarks, patents etc.). To take account of
non-linearity and allow easier comparison and interpretation of the coefficients, we apply elasticities to each of the main regressors associated
with Tobin’s q.

**4. Industrial design rights and the market value of Swedish firms,**
**2003–2013**

_4.1. Descriptive statistics_

For the years 1984 to 2013, we combine IDRs, patents and trade
marks at firm level to construct the IP portfolio. National IDR data
extracted from the Swedish Design Database yielded 5592 records. We
extracted 1,105,811 recorded RCD applications from EUIPO’s Open
Dataset. We match these records to the financial dataset, which yielded
a total of 1,890 records, representing 6609 IDRs from 94 firms. We
match patent data to financial data by querying the 16 synonyms in
the financial data by the four synonyms available in PATSTAT. This
yields 94,207 matched records. These belong to 20,592 patent families
and 148 firms. We extracted citation data separately from PATSTAT
by matching patent family and citation IDs. We filtered the records
by individual family-to-family citations. This results in 29,005 unique
family-to-family citations attributable to 122 of the firms in our sample.
We extracted 126,743 records of national trademark applications with
company owners, from the Swedish Trademark Database. The EUIPO
Open Dataset yields 1,478,599 CTM applications from 1996 to 2013.
We checked for duplicates and matched 5,909 trademark applications
to 270 of the firms in our sample.[7]

We gathered financial data on all publicly listed firms on the

NASDAQ Stockholm large, mid and small cap lists, between 2003 and
2013. We account for firms on a month-to-month basis so as not to


7 The earliest matched trademarks originate in 1885 and belong to Holmen
AB and Swedish Match AB.


-----

**Table 2**
Descriptive statistics.
_Source: PATSTAT Online Autumn 2017 edition, EUIPO Open Dataset, Thomson Reuters Eikon database, Swedish Design Database, Swedish_
Patent Database, and Swedish Trademark Database (PRV).

mean sd min median max

Tobin’s q 1.736 1.536 .304 1.275 10.05
Market value (billion SEK)[a] 61.76 143.3 .089 13.76 1042.3
Total assets (billion SEK)[a] 77.89 298.6 .062 10.40 2319.9
Total debt (billion SEK)[a] 26.33 116.7 0 1.854 933.8
Revenue (billion SEK) 32.99 50.30 .009 10.60 280.9
R&D stock (billion SEK)[b] 5.450 17.00 .013 1.161 151.3
R&D/Total assets[b] .207 .309 .003 .094 2.678
Patent stock[b] 83.51 125.3 .039 9.109 542.6
Patent stock/Total assets[b] 5.922 15.11 .018 1.834 142.0
Patent stock/R&D stock[b] 35.81 75.79 .781 19.28 841.5
Citation stock[b] 132.3 355.9 0 9.281 2698.2
Citation stock/Patent stock[b] 1.138 1.537 0 7221 9.101
Trademark stock[b] 37.29 54.50 .45 11.6 242.5
Trademark stock/Total assets[b] 6.303 13.21 .009 1.805 89.22
IDR stock 10.07 19.31 .063 1.991 109.1
IDR stock/Total assets 1.493 2.858 .001 .473 18.09
No R&D dummy .266 .442 0 0 1
No Patent dummy .147 .355 0 0 1
No Trademark dummy .088 .284 0 0 1

_Notes: This table provides descriptive statistics for the main variables and the controls used in our analysis. n = 487 observations and n = 73_
firms.
a Prices deflated to real 2003 year prices using CPI data from Statistics Sweden.

b Excludes observations with no reported R&D, patents or trademarks. R&D data are available for 357 observations. Patent data are available
for 415 observations. Trademark data are available for 444 observations.

**Table 3**
Industry characteristics.
_Source: PATSTAT Online Autumn 2017 edition, EUIPO Open Dataset, Thomson Reuters Eikon database, Swedish Design Database, Swedish_
Patent Database, and Swedish Trademark Database (PRV).

Observations Observations (%) Total assets[a] Tobin’s q Patent stock IDR stock Trademark stock

Mining & Construction 22 4.52 48.12 0.66 3.23 0.73 16.75
Other manufacturing 63 12.9 11.92 1.74 57.30 6.13 68.62
Paper 39 8.0 81.32 0.79 83.96 17.17 15.16
Other metals 56 11.5 8.26 1.41 23.57 2.58 14.31
Machinery 71 14.6 31.92 1.70 126.73 14.25 30.02
Electronics 36 7.4 22.39 2.31 58.33 17.98 70.62
Instruments 57 11.7 10.09 2.93 10.30 1.61 7.38
Public utilities 9 1.8 229.66 1.13 225.81 47.86 109.07
Trade 27 5.5 17.36 3.57 0 1.01 26.67
Finance 11 2.3 1982.06 0.44 245.80 35.66 36.65
Transport equipment 41 8.4 94.40 0.97 207.92 12.64 33.91
Services 55 11.3 11.52 1.62 26.13 10.40 34.25


_Notes: This table Presents the industry distribution in our data. n = 487 observations from n = 73 firms._

a SEK billions in 2003 real prices.


lose firms not observed by the end of each financial year. This initial
step yielded 3070 observations attributable to 400 firms. A total of
33,110 IDRs, trademarks and patent families were matched. We adjust
for missing values in the components of our dependent variable, Tobin’s
q, and observations with no knowledge assets or IP, that is, no R&D,
patents, trademarks or IDRs. This results in 2059 observations and
269 firms. We adjust the dataset for extreme outliers, which affects
104 observations.[8] This reduces the dataset to 1945 observations and
268 firms. Finally, since this study’s main focus is the value of IDRs,
we exclude firms with no IDRs. The final dataset consists of 487
observations for 73 firms. Table 2 presents the descriptive statistics. The
firms in our sample come from a range of industries. Table 3 shows the
industry distribution and shows that Machinery, Other manufacturing
and Instruments are the largest industries in the sample.

Certain variables fluctuate across industries. For example, Tobin’s

q varies considerably across industries, ranging from 0.44 to 3.57, although 8 of the 12 industries (66.7%) have an average Tobin’s q above

8 Observations in the 1st and 99th percentile of Tobin’s q, R&D
Stock/Total Assets, Patent Stock/Total Assets, Trademark Stock/Total Assets;
IDR Stock/Total Assets were excluded.


1. Average patent stock and IDR stock generally show a larger variation
across industries compared to average trademark stock. None of the
firms in the Trade category owns patents. Average trademark stock
shows the lowest variance across industries. IDR stocks are generally
small in all industries, with the lowest value in Mining & Construction.

Table 4 presents the sample based on firm size, proxied by total

assets. We split the sample into deciles based on total assets. We observe
a Pareto distribution in which large firms have disproportionately large
total assets compared to the mean. Smaller firms tend to have a higher
Tobin’s q: the smallest firms in the sample have an average Tobin’s
q of 2.50 while the largest firms have an average Tobin’s q of 0.80.
Among our observations, the largest firms contribute to the majority of
the patent stocks (deciles 8, 9 and 10).

Unlike patent stocks, IDR stocks and trademarks stocks do not

follow a linear relation to firm size. For average trademark stock, the
minimum of 2.02 is in the 1st decile while and the maximum average
of 75.31 is in the 9th decile; also, mid-sized firms and the largest firms
have average trademark stocks. For average IDR stock, the minimum
value of 1.53 is assigned to firms in the 2nd decile while the maximum
of 39.46 applies to firms in the 10th decile. However, again, mid-sized
firms have similar IDR stocks to firms in the 8th and 9th deciles.


-----

**Table 4**
Characteristics by total assets.
_Source: PATSTAT Online Autumn 2017 edition, EUIPO Open Dataset, Thomson Reuters Eikon database, Swedish Design Database, Swedish_
Patent Database, and Swedish Trademark Database (PRV).

Decile Observations Observations (%) Total assets[a] Tobin’s q Patent stock TM stock Des stock

1 49 10.06 .26 2.50 2.57 4.21 1.76
2 49 10.06 .58 2.29 6.70 8.68 1.53
3 49 10.06 1.24 2.36 8.00 11.11 2.82
4 48 9.86 2.48 1.40 4.95 12.41 1.68
5 49 10.06 5.67 1.39 12.00 13.80 2.20
6 49 10.06 19.44 1.86 76.38 49.99 12.16
7 48 9.86 29.95 1.12 79.45 58.13 7.21
8 49 10.06 43.03 2.37 100.27 51.28 12.57
9 49 10.06 76.27 1.18 182.94 75.31 19.69
10 48 9.86 608.26 .80 240.61 55.52 39.46

Total 487 100 77.89 1.73 71.16 33.99 10.07

_Notes: This table displays the distribution of our data by firm size measured as total assets. n = 487 observations from n = 73 firms._

a Billion SEK real 2003 prices.


**Table 5**
Correlation matrix.
_Source: PATSTAT Online Autumn 2017 edition, EUIPO Open Dataset, Thomson Reuters Eikon database, Swedish Design Database, Swedish_
Patent Database, and Swedish Trademark Database (PRV).

1 2 3 4 5 6 VIFs

Tobin’s q
log Total assets −0.349*** 3.20
R&D/assets 0.271*** −0.286*** 1.83
Patents/R&D 0.218*** −0.062 0.030 1.30
Citations/Patents 0.109* 0.114* 0.372*** 0.121** 1.68
Trademarks/assets 0.252*** −0.424*** 0.223*** 0.197*** 0.095* 1.68
IDRs/assets 0.321*** −0.567*** 0.370*** 0.068 0.077 0.343*** 1.87

_Notes: This table presents the Pearson correlation between our dependent and independent variables. VIFs = variance inflation factors. n = 487_
observations from n = 73 firms.

-  p<0.05.
** p<0.01.
*** p<0.001.


We compute the correlations among our variables of interest (see

Table 5). Statistically significant correlations are denoted with asterisks. All correlations with Tobin’s q are statistically significant at the
5% level. With the exception of ln(Total Assets), all the regressors
show some degree of a positive correlation to Tobin’s q. IDR stock,
trademark stock and R&D intensity are correlated negatively to total
assets. Both IDR stock and trademark stock are correlated positively
to R&D intensity. Finally, IDR and trademark stocks are correlated
since they follow similar patterns in terms of firm size (see Table 4).
Since some of the correlation coefficients in Table 5 are above 0.3, we
calculate the Variance Inflation Factor (VIF) values for all the variables
to check for multicollinearity. Although total assets have a higher VIF
than the other variables, all are well below the critical value of 10,
which indicates no problems of multicollinearity.

_4.2. Econometric results_

Table 6 presents the results of the NLLS regressions. The natural

logarithm of total assets has coefficients that vary between negative
and positive in all the models and are significant in only two of the
six models. However, there are slight indications of weak economies of
scale among our firms and that larger firms are valued more highly.
R&D intensity is positively related to Tobin’s q in all the models. In
Models 3 and 4, the coefficient is above unity. If we include R&D
intensity in the regression in Model 2, R2 increases from 0.434 to 0.467
compared to Model 1. The elasticity of R&D intensity is similar to that
in Rahko (2014). Sandner and Block (2011) find a considerably lower
elasticity, of 2.75%, compared to the 7.50% we obtained. This elasticity
can be interpreted as a 100% increase in R&D intensity has a positive
impact of 7.50% on the firm’s market value. Among all our independent
variables, R&D intensity impacts Tobin’s q the most. Swedish firms’


R&D intensity is similar to that of German and French firms, but it
is higher than for Finnish, Danish, UK and Italian firms (Hall and
Oriani, 2006). US firms tend to outrival Swedish firms regarding R&D
intensity (Hall and Oriani, 2006; Bloch, 2008; Rahko, 2014).

Patent stock is positively related to R&D stock and shows a sig
nificant Tobin’s q in all the models. Our findings suggest additional
gains from of patent families to R&D spendings. It seems as financial
markets reward R&D efforts aimed at patentable inventions (Rahko,
2014). The positive relationship between patents based on R&D and
market value, supports the idea that patents are used to commercialize
products and to secure returns from R&D investments (Saracho, 2002).
The patent family yield for R&D is related positively to Tobin’s q, which
is consistent with the findings in Rahko (2014) and Hall et al. (2005).

Our analysis does not suggest an association of patent value indi
cators firms’ value; rather, the patent citation variable is insignificant
or weakly negative which is not in line with earlier research (Hall
et al., 2005; Sandner and Block, 2011; Rahko, 2014). The variable used
here measures family-to-family citations whereas other studies sometimes rely on aggregate measures of citations, including self-citations.
One explanation for the insignificance in our measure might be that
restricting the citation variable to forward family-to-family citations
limits the information incorporated to the extent that it does not signal
patent value. It might also be an indication that financial markets value
absolute patent stock and tend not to distinguish between ‘high’ or ‘low’
value patents.

Trademark stock to total assets is included only in Model 6, but

shows a positive and significant relation to firm value, controlling
for R&D, patents and IDRs. This is in line with Sandner and Block
(2011) and Greenhalgh and Rogers (2007). However, Bosworth and
Rogers (2001) find no such relationship. The result could be interpreted
as showing that trademarks serve a valuable function in hampering


-----

**Table 6**
The effect of industrial design rights on the market value of firms.
_Source: PATSTAT Online Autumn 2017 edition, EUIPO Open Dataset, Thomson Reuters Eikon database, Swedish Design Database, Swedish_
Patent Database, and Swedish Trademark Database (PRV).

Dependent variable: Tobin’s q

(1) (2) (3) (4) (5) (6)

Constant −0.402*** −0.557*** −0.764*** −0.765*** −0.730*** −1.016***

(0.0956) (0.116) (0.116) (0.117) (0.118) (0.117)
Log Total assets −0.0249* 0.00713 0.0208 0.0212 0.0481*** 0.0834***

(0.0139) (0.0149) (0.0143) (0.0144) (0.0177) (0.0173)
R&D/assets 0.872** 1.049*** 1.052*** 0.902**

(0.351) (0.387) (0.387) (0.387)
Patents/R&D 0.00537*** 0.00538*** 0.00515***

(0.000959) (0.000959) (0.00105)
Citations/patents −0.00423 −0.0364***

(0.0176) (0.0121)
IDR/assets 0.126*** 0.0777**

(0.0352) (0.0315)
Trademarks/assets 0.0198***
(0.00394)
No R&D 0.150* 0.245*** 0.243*** 0.129*

(0.0898) (0.0909) (0.0922) (0.0775)
No patents 0.133 0.132 0.00111
(0.105) (0.105) (0.102)
No trademarks 0.404***
(0.104)
Year dummies Yes Yes Yes Yes Yes Yes
Industry dummies Yes Yes Yes Yes Yes Yes

Observations 487 487 487 487 487 487
_𝑅[2]_ 0.434 0.467 0.510 0.510 0.479 0.560
Adjusted 𝑅[2] 0.408 0.440 0.482 0.481 0.453 0.531

Elasticities
R&D/assets 0.091*** 0.095*** 0.095*** 0.075***

(0.027) (0.025) (0.025) (0.026)
Patents/R&D 0.082*** 0.082*** 0.074***

(0.011) (0.011) (0.012)
Citations/Patents −0.003 −0.026***

(0.012) (0.010)
IDR/assets 0.114*** 0.060***

(0.022) (0.019)
Trademarks/assets 0.056***
(0.010)

_Notes: NLLS regressions. This table displays the effect of different knowledge assets and IPRs on the market value of firms measured as Tobin’s q._
A full set of year (10 categories) and industry (12 categories) dummies is included in all models. The reference group is Mining & Construction.
The reference year is 2003. Robust standard errors in parentheses.

-  𝑝< 0.10.
** 𝑝< 0.05.
*** 𝑝< 0.01.


counterfeiting, infringement and dilution of company brands (Kopp and
Suter, 2000). The elasticity of trademarks in Model 6 is similar to the
results of earlier studies (Greenhalgh and Rogers, 2007; Sandner and
Block, 2011). The effect of trademarks on the market value of firms in
Sweden seems to be in line with effects found on other European firms.

Finally, in Models 5 and 6, we include our main variable of interest,

ratio of IDRs to total assets. In Model 5, we include it without other IP
and R&D. The coefficient of 0.126 is strongly positive and, if interpreted
as the shadow value of IDRs, indicates that one additional IDR unit
is valued at SEK 126 million. This is comparable to the numbers
in Sandner and Block (2011) for trademarks. In Model 6, where we
control for patents, trademarks and R&D the coefficient decreases to
0.077 but remains significant at the 5% level.

To make our results comparable to previous research, we calculate

elasticities with respect to Tobin’s q for all the variables. We find
significant elasticities for all the variables except citations to patent
stock (Model 4). The elasticity of R&D goes from around 9% in Models
2, 3, and 4, to 7.5% in Model 6. This is higher than in Sandner and
Block (2011) and Rahko (2014), but lower than in Hall et al. (2007).
The elasticity of patent stock to R&D is of a similar magnitude in all the
models. To compare models (Table 6), we use R2 values. Compared to
the baseline Model 1, which includes only total assets, the R2 values


increase from 0.434 to 0.510 if we include both R&D intensity and
patent stock to R&D. The R2 in Model 5, which includes only IDR stock,
is slightly lower, but increases to 0.560 for the full model (Model 6)
which includes all the variables.

_4.3. Robustness checks_

To confirm the results of the NLLS regressions, we run the same

models, but using a regular OLS framework.[9] Table 7 presents the
results of the OLS regressions. The OLS regressions are qualitatively
similar to the results for the NLLS regressions. All the signs of the
coefficients are similar across both the NLLS and OLS regressions;
however, citations to patent stock are not significant in any of the
models, pointing, again, to a weak relationship between this variable
and the market value of the firms in our sample.

9 We also estimated the NLLS and OLS regressions on an extended dataset
which includes n = 541 observations. This dataset was not adjusted for extreme
outliers. The results for the NLLS using the extended dataset show no major
differences from the results for the primary dataset.


-----

**Table 7**
Robustness check — OLS regressions.
_Source: PATSTAT Online Autumn 2017 edition, EUIPO Open Dataset, Thomson Reuters Eikon database, Swedish Design Database, Swedish_
Patent Database, and Swedish Trademark Database (PRV).

Dependent variable: Tobin’s q

(1) (2) (3) (4) (5) (6)

log Total Assets −0.0249* −0.000696 0.0134 0.0130 0.0497*** 0.0706***

(0.0139) (0.0156) (0.0154) (0.0157) (0.0173) (0.0172)
R&D/Total Assets 0.468** 0.539** 0.534** 0.464** 0.448*

(0.230) (0.234) (0.240) (0.228) (0.235)
Patent Stock/R&D Stock 0.00213*** 0.00212*** 0.00212*** 0.00191***

(0.000333) (0.000338) (0.000293) (0.000303)
Citation Stock/Patent Stock 0.00318 −0.00702 −0.0234
(0.0159) (0.0148) (0.0145)
IDR Stock/Total Assets 0.0480*** 0.0419***

(0.0141) (0.0133)
Trademark Stock/Total Assets 0.00902***
(0.00172)
No R&D (dummy) 0.0810 0.139 0.140 0.153* 0.0698
(0.0905) (0.0907) (0.0912) (0.0856) (0.0809)
No Patent (dummy) 0.105 0.106 0.0472 0.0112
(0.106) (0.105) (0.104) (0.101)
No Trademark (dummy) 0.377***
(0.106)
Constant −0.402*** −0.501*** −0.666*** −0.664*** −0.851*** −0.907***

(0.0956) (0.116) (0.116) (0.117) (0.122) (0.114)

Observations 487 487 487 487 487 487
_𝑅[2]_ 0.434 0.460 0.498 0.498 0.521 0.549

_Notes: OLS regressions. This table displays the effect of different knowledge assets and IPRs on firms’ market value, measured as Tobin’s q. All_
the models include a full set of year (10 cats) and industry (12 cats) dummies. The reference group is Mining & Construction; the reference
year is 2003. Robust standard errors in parentheses.

-  𝑝< 0.10.
** 𝑝< 0.05.
*** 𝑝< 0.01.


**5. Concluding discussion**

_5.1. Limitations and further research_

This study serves as a first attempt to investigate the relation
ship between IDR ownership and firms’ market value and is associated with several limitations that can be addressed in future research.
Some of these limitations concerns the empirical data while others are
associated with the analytical approach.

Empirically, the IPR data used include only European and Swedish

coverage. Therefore, we cannot claim to have complete IPR portfolios
for the firms in the study as they might own IPRs in countries outside of
Sweden or the EU. However, there is little reason to expect bias in the
matching process. Thus, our conclusions about the difference between
and relative importance of separate IP stocks should hold. At the same
time, future research would benefit from a more global scope (Alcacer
et al., 2017) which would allow also for taking into account variegated
jurisdictional regulations and procedures with respect to IDRs. The
study is also limited to Swedish firms and Swedish stock markets. One
drawback of this sample in conjunction with strictly selecting firms
that owns three different types of IPR is that the number of observations drop. Using datasets with broader geographical coverage (Ghisetti
et al., 2021) could allow for more robust and more fine-grained analyses. Moreover, although arguably Sweden is an interesting context
due to its design-intensity, general innovativeness and the international presence of investors, attractiveness and expectations among
investors may be biased. Therefore, further studies in other countries
and institutional settings are necessary to validate and generalize the
findings presented here. Another potential limitation of the study is the
unobserved variables. We employ control variables for time, industry,
IPR and R&D, but do not consider other potentially important variables
such as firm size, firm age and IPR complementarity that might affect
firms’ market value. The set of variables we use is similar to those
used in other studies in the field (Hall et al., 2005, 2007; Sandner and
Block, 2011; Rahko, 2014), but using more variables in future studies
is desirable.


Analytically, the market value approach introduces some simplify
ing assumptions. For instance, it treats knowledge assets homogenously
and functionally equal, but as our findings indicate knowledge assets at
least to some degree are heterogeneous. In particular this should hold
with respect to R&D expenditures in relation to IPR, but potentially
also between patents, trademarks and IDRs. The advantage of the
market value approach is that it makes comparison of results to other
similar studies that have omitted IDRs possible (e.g. Sandner and Block,
2011; Rahko, 2014; Dosso and Vezzani, 2020) fairly straightforward.
However, to account for knowledge asset heterogeneity, future model
specification could use a sequential specification (e.g. Crépon et al.,
1998). Such an approach could also allow for analyzing an important
feature highlighted in the design literature, namely between design
value creation and design value capture (Åman et al., 2017; Montresor
and Vezzani, 2020). Further, our study uses IDR data combined with
data on patents and trademarks, but we do not analyze complementarities or compositional effects of IPR-bundles (Greenhalgh and Longland,
2005). Since IDRs may overlap with patents for some important features of technological innovations (Filitz et al., 2015), future studies
could investigate how IDRs and patents are used in combination. Also,
we use only IDR stocks. Future research could extend the scope of indicators to include, for instance IDR quality, such as renewals, Locarno
classes and appeals.

_5.2. Contributions and implications_


The study reveals potential market value of IDRs and contributes

to our empirical knowledge of this growing phenomenon. Our findings
from the analysis of the impact of R&D intensity patents, trademarks,
and IDRs of firms in a design-intensive country as Sweden with ownership of all three types of IPRs demonstrate that financial markets indeed
value firms’ ownership of IDRs. Our findings hold when we control for
R&D, patents and trademarks. Since IDRs capture aspects of innovation
not covered or protected by patents and trademarks, this supports the
suggestion that IDRs offer a rich and relatively unexplored area for


-----

further research (Filitz et al., 2015). By analyzing IDRs in relation to
patents, trademarks and R&D in the same dataset, we show that while
R&D adds the most to market value, IDRs are (almost) on par with
patents and trademarks.

The study also contributes to the theoretical understanding of design

knowledge and valuation of design rights by financial markets. When
compared to patents, IDRs in theory appear a relatively weak form of
IPR which give rise to uncertainty regarding uncontested IDRs as a measure of firm appropriability and value capture (Filippetti et al., 2019;
Filitz et al., 2015; Galindo-Rueda and Millot, 2015). This is mainly due
to multiple design filings in a single application, ex post determination
of novelty, and lacking enforceability when tried in court. Still, the
findings of this study show that despite the uncertainty surrounding
the quality of IDRs financial markets evaluate them positively.

Drawing upon our conceptual framework, we suggest three explana
tions to this observation. Explanations that we hope that can be further
developed and tested in future research. First, a particular characteristic
of IDRs as an IPR is their explicit product connection. The design of a
product or service refers to ornamental, often visual, and sometimes
tactile features. Such features are crucial to the appearance of the
product and the emotions evoked by its user. Accordingly, IDRs operate
directly in the market processes in which firms compete with their
products, for instance allowing for differentiation strategies (Walsh,
1996). Compared to other IPRs, the holding of IDRs signals potential value capture closely associated with discernible product markets
where firms are competing.

Second, assuming that design capability is an unobservable an
tecedent of IDRs, such innovative capabilities are attributable to firms
competitive advantage (as expected by shareholders). While the underlying activities undertaken to allow for IDR registration have not
been studied here, drawing upon the knowledge based view of the
firm (KBV), our findings lend support to prior theoretical conjectures
that design is a distinguishable innovative capability that firms can use
to reap competitive advantage (d’Ippolito, 2014; Galindo-Rueda and
Millot, 2015; Ghisetti et al., 2021).

Third, and related, underlying knowledge bases differ between IPRs.

Patents are associated with underlying scientific principles and technological paradigms that can be applied in a range of products (Pavitt,
1984). Trademarks draws upon market knowledge and are used more
broadly for corporate branding to appeal to customers (Castaldi, 2020).
In comparison, design is more coupled with embodied aesthetic knowledge (Ewenstein and Whyte, 2007). Arguably, not only do such design
capabilities important provide market value in their own right, but they
may also serve an important function for firms’ ability to innovate as
they operate between technological knowledge (as captured in patents)
and market knowledge (as measured by trademarks), allowing for
‘‘knowledge integration by design’’ (Åman et al., 2017).

Our findings have some implications for managers and policy mak
ers. In practice, and on a general level, our results indicate that the
firm’s IPR strategy (Reitzig, 2004; Candelin-Palmqvist et al., 2012)
affects shareholder value. However, research and literature on IPR
management has until recently by and large been informed by what
we know about patents as IPR. While recent research has added to the
understanding of trademarks as IPRs and IPR strategies (Castaldi, 2020;
Dosso and Vezzani, 2020), design rights to a large extent is unchartered
territory. More specifically, while IDRs and patents appear similar,
there are important differences both in terms of underlying knowledge
base (science vs arts) as well as formal claim procedures, jurisdictions
and enforceability. Accordingly, also expectations on what they can
provide in terms of competitive advantage and value may differ among
stakeholders. For managers, collaborators and investors, managing such
expectations in accordance with the ‘‘face value’’ of IDRs will become
increasingly important as the use of this specific type of IPR continues
to grow. Similar implications should be valid also for economic policy.
Additionally, while it has been argued that IDRs lends itself both as an
opportunity and indicator for ‘‘low-tech’’ innovation (Filitz et al., 2015;
Galindo-Rueda and Millot, 2015; Filippetti et al., 2019), our findings
suggest a prevalence of IDRs also in allegedly ‘‘high-tech’’ industries.


**CRediT authorship contribution statement**

**David E. Andersson: Writing – review & editing, Investigation,**

Formal analysis, Conceptualization, Methodology, Software, Writing –
original draft, Supervision. Anton Ekman: Writing – review & editing,
Conceptualization, Data curation, Writing – original draft, Investigation. Anton Huila: Writing – review & editing, Conceptualization,
Data curation, Writing – original draft, Investigation. Fredrik Tell:
Writing – review & editing, Conceptualization, Writing – original draft,
Supervision, Investigation.

**Declaration of competing interest**

The authors declare that they have no known competing finan
cial interests or personal relationships that could have appeared to
influence the work reported in this paper.

**Data availability**

Data will be made available on request.

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**David E. Andersson is post-doctoral researcher at the Department of Business Stud-**
ies, Uppsala University. His research focuses on markets for technology, economics
of innovation and the management of intellectual property rights, innovation and
technology.


**Anton Ekman is a manager at Deloitte. He is responsible for M&A transactions services**
and stationed in Stockholm, Sweden.

**Anton Huila is a senior consultant at EY working within the areas of risk management**
and financial services.

**Fredrik Tell is professor and chair at the Department of Business Studies, Uppsala**
University. His research is concerned with strategic temporal work and the relationship
between the future and the present, development of organizational knowledge and
capabilities, intellectual property rights and markets for technology and digitalization
and changing organizational routines.


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