Top R&D investors and international knowledge seeking : the role of emerging technologies and technological proximity.
Date: 2015-11-03
Institutions: Institute for Prospective Technological Studies
Subjects: EU research policy, industrial research, innovation, investment, knowledge economy, patent, research and development, research report, technological change, technology

IPTS Working Papers on Corporate R&D and Innovation – No 09/2015 

Top R&D Investors and international 
knowledge seeking: the role of emerging 
technologies and technological proximity 

Mafini Dosso and Antonio Vezzani 

2 0 1 5  

EUR 27483 EN 

European Commission 
Joint Research Centre 
Institute for Prospective Technological Studies 

The main authors of this paper are: Mafini Dosso and Antonio Vezzani - JRC-IPTS, European Commission, Seville, Spain). 

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Abstract 

This paper sheds new lights on the internationalization of technological activities of the top corporate R&D investors 
worldwide. In particular, we provide evidence on the technological factors determining their international R&D location 
strategies. The empirical analysis is based on the  patenting activities of the top R&D investors, as reported by the EU 
Industrial  R&D  Investment  Scoreboard,  at  the  USPTO  over  the  period  2010–2012.  The  technological  proximity  to  the 
host  country in  which  these  companies  seek  for  new  knowledge  is a  key  determinant  for  their R&D  location  decision. 
However, technological proximity has a non-linear effect on the companies' location strategies as they search for new 
technologies  not  too  close  to  their  knowledge  base.  Furthermore,  top  R&D  investors  worldwide  target  countries  with 
comparative advantages in emerging technologies. Countries willing to attract high-value investments should create an 
environment conducive to the creation and development of brand new ideas with a high potential impact on the long 
term growth. 

IPTS WORKING PAPER ON CORPORATE R&D AND INNOVATION – NO. 09/2015 
TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

Abstract1,2 

This  paper  sheds  new  lights  on  the  internationalization  of technological  activities  of  the 
top  corporate  R&D  investors  worldwide.  In  particular,  we  provide  evidence  on  the 
technological  factors  determining  their  international  R&D  location  strategies.  The 
empirical analysis is based on the patenting activities of the top R&D investors, as reported 
by  the  EU  Industrial  R&D  Investment  Scoreboard,  at  the  USPTO  over  the  period  2010–
2012. The technological proximity to the host country in which these companies seek for 
new  knowledge  is  a  key  determinant  for  their  R&D  location  decision.  However, 
technological  proximity  has  a  non-linear  effect  on  the  companies'  location  strategies  as 
they search for new technologies not too close to their knowledge base. Furthermore, top 
R&D  investors  worldwide  target  countries  with  comparative  advantages  in  emerging 
technologies.  Countries  willing  to  attract  high-value  investments  should  create  an 
environment conducive to the creation and development of  brand new ideas with a high 
potential impact on the long term growth. 

Keywords: International Knowledge seeking, Multinational Corporations (MNCs), 
Patents, Emerging technologies, Technological proximity 

JEL Classification: O30, F23, L20 

1 We  would  like  to  thank  the  participants  to  the  EMAEE  2015  Conference  in  Maastricht  and  to  the 
Workshop  "What  do  we  know  and  what  should  we  know  about  international  knowledge  sourcing?”  in 
Catania  for  their  helpful  comments.  We  are  also  grateful  to  Koen  Jonkers  (European  Commission,  JRC) 
and  Enrico  Santarelli  (University  of  Bologna,  Italy)  for  their  comments  on  an  earlier  version  of  the 
manuscript. We are also grateful to Jeanne Thévenot for the revision of previous drafts. We are of course 
responsible for all the remaining errors. 
2 This Working Paper is issued in the context of the  Industrial Research and Innovation Monitoring and 
Analysis  (IRIMA)  activities  that  are  jointly  carried  out  by  the  European  Commission's  Joint  Research 
Centre  (JRC)  –  Institute  for  Prospective  Technological  Studies  (IPTS)  and  the  Directorate  General 
Research and Innovation - Directorate A, Policy Development and Coordination. 

1 

IPTS WORKING PAPER ON CORPORATE R&D AND INNOVATION – NO. 09/2015 
TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

1. Introduction 

The internationalization of research and development (R&D) and innovation-related 
activities  has  raised  long  lasting  interests  within  the  economic  and  innovation 
literature.  This  dimension  of  the  globalisation  process  represents  an  increasingly 
important  aspect  of  corporate  strategies.  In  order  to  gain  or  maintain  a  competitive 
edge, Multinational Corporations (MNCs) increasingly rely on international knowledge 
networks,  notably  through  cross-borders  ownership,  mergers  and  acquisitions, 
greenfield  investments,  collaborations  and  contractual  research,  and  intellectual 
property  transactions.  At  the  same  time,  countries  are  competing  to  strengthen  their 
attractiveness  for  large  scale  technology  and  knowledge  intensive  activities,  as  a  key 
source to boost high-quality jobs and competitiveness. 

Empirical  studies  examining  the  patterns,  drivers  and  effects  of  the  international 
generation  of  knowledge  could  be  broadly  classified  along  three  complementary 
perspectives.  A  first  approach  has  investigated  the  organization  and  importance  of 
foreign  R&D  activities  in  the  host  countries,  notably  via  the  assessment  of  the 
contribution  of  foreign  R&D  affiliates  to  research,  human  resources  or  employment 
(Belderbos  et  al.  2008,  OECD  2010).  Complementary  evidence  has  been  provided 
through the analysis of inward and outward foreign direct investments in R&D activities 
(Florida  1997,  Kuemmerle  1999,  Castelli  and  Castellani  2013).  A  third  stream  of  the 
literature  has  focused  on  the  international  locations  of  large  firms’  R&D  activities, 
exploiting the information contained in MNCs’ patent documents (Patel and Vega 1999, 
Cantwell and Piscitello 2005).  

These contributions have pointed out the central role of MNCs in the international 
innovation activities, motivated by the need of adapting or exploiting the technologies 
developed at home. Further evidence has shown that MNCs increasingly locate research 
facilities to foreign locations in order to tap into the knowledge and techniques created 
abroad as a complement to their in-house technological activities, or in order to develop 
new  knowledge  and  competences  (Cantwell  et  al.  2004,  Criscuolo  et  al.  2005).  With 
respect  to  the  location  determinants,  besides  firm-specific  characteristics,  important 
drivers have been  identified in relation  to the type of activities and  the host  country’s 
attributes  such  as:  i)  the  market  features,  ii)  the  presence  of  high  quality  scientific 
infrastructure  and  human  resources,  iii)  the  agglomeration  forces,  iv)  tax  breaks  and 
government  support,  legal  and  intellectual  property  protection  systems.  Nevertheless, 
the  relative  importance  of  these  drivers  also  depends  on  the  industries  in  which  such 
corporations operate and on the different propensities of resorting to the international 
markets  for  their  knowledge  creation  activities.  Regarding  the  locations  choices,  the 
role  of  the  Triad  'United  States-Japan-Europe',  as  the  main  destination  of  the 
international investment in R&D, has been highlighted.  

However,  more  recent  evidence  show  that  internationalization  of  R&D  is  taking 
place  at  a  higher  pace  and,  increasingly  towards  (and  from)  the  so-called  emerging 
countries  (Thursby  and  Thursby  2006,  von  Zedtwitz  2006),  thus  challenging  the 
traditional  R&D  location  theories,  whereby  MNCs  would  generally  locate  knowledge 
creation  activities  next  to  their  decisions  centres  (headquarters).  Therefore,  the 

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TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

international distribution of innovation activities is changing over time, notably as more 
countries build up higher quality or new scientific and technological capabilities. At the 
same  time,  the  increasing  complexity  of  products  leads  MNCs  to  rely  on  a  greater 
variety  of  technological  competences,  which  is  likely  to  require  the  location  of  R&D 
facilities  in  the  neighbouring  of  excellence  research  and  scientific  centres  around  the 
world  (Moncada-Paternò-Castello  et  al.  2011).  Moreover,  in  this  search  of  new 
knowledge  firms  are  bounded  by  the  path-dependent  and  cumulative  nature  of  the 
innovation process (Dosi 1988, Cantwell 1989, Dosi et al. 1990).  

In the international knowledge seeking strategies this should translate into a certain 

degree of technological proximity between MNCs and the targeted (host) countries.  

In  a  complementary  manner,  among  the  drivers  leading  a  company  to  invest  in 
foreign  locations,  is  the  attempt  to  tap  into  specific  technological  knowledge  (Guellec 
and  Pottelsberghe  de  la  Potterie  2001,  Cantwell  2009).  In  particular,  firms  may  be 
attracted  by  certain  locations  with  a  superior  capacity  in  developing  new  emerging 
technologies.  Indeed,  these  technologies  are  likely  to  lead  to  the  discovery  of  path-
breaking, brand new products and processes (Schoenmakers and Duyster 2010). 

Emerging  technologies  are  receiving  an  increasing  attention  both  from  the  policy 
and  the  academic  communities.  Indeed,  they  are  perceived  as  technologies  which  can 
provide  solutions  to  global  challenges  and  a  ground  for  sustainable  business 
opportunities  (WEF  2014)  with  the  potential  to  change  the  economy  and  society. 
However,  consensus  is  still  lacking  on  how  to  define  them  and  to  operationalize  their 
detection (Rotolo et al. 2015). Moreover, although they are expected to yield a positive 
impact  on  economic  growth,  exercises  trying  to  estimate  their  impact  remain  scarce. 
Similarly, empirical evidence on how these emerging technologies actually influence the 
locations choices of MNCs is still lacking, to the best of our knowledge. 

 Departing  from  these  latter  observations,  this  paper  sheds  new  lights  on  the 
internationalization  of  technological  activities  of  the  top  corporate  R&D  investors 
worldwide  (European  Commission  2013).  More  precisely,  we  assess:  i)  the  impact  of 
the  specialization  of  the  (possible)  destination  country  in  emerging  technologies  in 
attracting foreign MNCs, and ii) the extent to which MNCs perform  a local technological 
search in their international knowledge seeking strategies. 

The  remainder  of  the  paper  is  organized  as  follows.  Section  2  sets  down  the  main 
theoretical  foundations  for  the  analysis  of  the  internationalization  of  R&D  and 
innovative  activity.  Section  3  presents  the  data,  and  illustrates  the  empirical  strategy 
and the variables. Section 4 discusses the main findings. Finally, Section 5 concludes. 

2. Theoretical background 

Inspired by the observations of US MNCs’ international activities, the seminal works 
of Vernon (1966, 1979) constitute an early theoretical discussion  on the  international 
location  of  technological  activities.  In  his  attempt  to  rethink  the  product  cycle  (PC) 

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TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

hypothesis3, Vernon  has somehow anticipated some  of the  current  trends observed in 
the  development  of  international  knowledge  and  innovation  networks.  He  has 
underlined the prominence of the parent company’s home market for the development 
of innovations. This prominence, although decreasing, is still supported by the current 
evidence  on  the  higher  opportunities  for  scale  economies  in  R&D,  the  economies  of 
integration and agglomeration, the importance of demand-led innovation, and the more 
effective  communication  between  potential  customers  and  suppliers  (Vernon  1966, 
1979,  Cantwell  1995).  However,  as  for  the  increasing  reliance  on  foreign  locations, 
Vernon did not anticipated that these factors may also extend to other innovative places 
or  world  regions  characterized  by  high  market  potentials,  high-skilled  workforce 
and/or specific techno-industrial specializations. This shifting has been favoured by the 
development  of  more  effective  information  and  communication  channels  between 
geographically  distant  markets  and  the  reduction  of  income  and  education  disparities 
among  a  larger  set  of  countries.  Furthermore,  in  Vernon’s  theoretical  typology,  few 
MNCs  would  be  able  to  develop  global  scanning  capabilities.  These  global  scanning 
capabilities,  if  they  ever  exist,  would  refer  to  the  ability  of  internationally  integrated 
MNCs to collect and interpret information from multiple global locations, with virtually 
null  international  communication  costs  (Vernon  1979).  Therefore  innovation  in  these 
hypothetical  MNCs  could  thus  be  stimulated  from  markets  located  anywhere  in  the 
globe. However, to our knowledge the existence of such fully internationally integrated 
networks  still  remains  scarcely  documented  in  the  empirical  analyses.  Nevertheless, 
evidence show that foreign R&D affiliates have gained in autonomy and importance in 
the  knowledge  creation  activities  (Zanfei  2000,  Dunning  and  Lundan  2009),  and  that 
MNCs  increasingly  develop  simultaneously  intra-  and  inter-firm  networks4 for  the 
generation  of  innovations  (Zanfei  2000,  Archibugi  and  Iammarino  2002,  Cantwell  and 
Zhang 2011).  

 During  the  last  three  decades,  many  studies  have  contributed  to  further  improve 
our  understanding  of  the  patterns  and  drivers  of  the  internationalization  of  research 
and development (R&D) and innovation-related activities. There is clear evidence that 
companies  are  increasingly  relying  on  international  R&D  and  innovative  activities, 
through  cross-border  greenfield  investments,  mergers  and  acquisitions,  strategic 
alliances,  collaborations  and  contractual  research,  standardisation  activities  and 
intellectual property transactions. The importance of foreign R&D in the host countries’ 

3 In the earlier version of the PC model, Vernon (1966) offers an alternative explanation to the patterns of 
international trade in which the locations of production would not depend exclusively on relative costs, 
but on the life cycle of the product. In the early stages, the production of the new product is localised at 
home due to the more effective communication between the supplier and the targeted market. As far as 
production  and  demand  expand,  the  producers  are  more  likely  to  invest  in  production  facilities  abroad 
and  re-export  the  related  products  from  these  new  locations  towards  the  home  market.  According  to 
Vernon,  this  phenomenon  is  further  accentuated,  and  may  extend  to  less  developed  economies  with 
cheaper  labour  costs  in  the  standardized  product  phase,  which  entails  high  output  volumes,  less 
uncertainty and higher costs considerations.    
4 Zanfei  refers  to  this  phenomenon  as  a  ‘double  network’  (internal  and  external  to  the  MNCs)  where 
foreign R&D units have developed increasing capabilities to access and contribute to knowledge available 
for economic uses (Zanfei 2000). Akin to this notion is the concept of two-way knowledge flows discussed 
by  Cantwell  and  Zhang  (2011),  which  reflects  the  growing  importance  of  knowledge  spillovers  from 
foreign-owned subsidiaries to indigenous firms. 

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TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

economies  is  generally  assessed  through  the  contribution  of  foreign  R&D  affiliates  to 
the R&D expenditures (funding and performance), the R&D-related employment and to 
the  patenting  activities  (Patel  and  Pavitt  1991,  Cantwell  1989,  1995,  Guellec  and  van 
Pottelsberghe  de  la  Potterie  2001,  Picci  2010).  Another  significant  way  of  exploiting 
innovations  in  foreign  markets  is  through  foreign  direct  investment  (FDI)  in  R&D 
activities  (UNCTAD  2005,  Castelli  and  Castellani  2013).  These  studies  confirm  that 
MNCs have increasingly moved away from a myopic model of knowledge creation and 
innovation almost exclusively oriented towards the home country. These international 
R&D activities have been mainly implemented following the North-North pattern (from 
and  to  developed  markets),  particularly  within  the  Triad  countries,  i.e.  the  United 
States, Europe and Japan. However, studies also point out the increasing importance of 
emerging countries in the hierarchy  of foreign R&D locations  (e.g. UNCTAD  2005,  von 
Zedtwitz 2006, OECD 2011). 

The interest in the causes of such phenomenon has given birth to a major stream of 
the  literature,  which  focuses  on  the  motives  and  determinants  of  the  international 
knowledge activities of companies. These studies have mainly exploited data relating to 
FDIs  in  research  (Kuemmerle  1999,  Alcácer  and  Chung  2007)  and  to  the  foreign 
patenting  activities  of  large  companies  (among  others,  Cantwell  1989,  Patel  and  Vega 
1999, Cantwell and Iammarino 2000, Le Bas and Sierra 2002, Criscuolo et al. 2005, Picci 
2010).  As  suggested  by  these  contributions,  it  is  still  more  often  the  case  that  MNCs 
implement  international  R&D  activities  to  adapt  the  knowledge  and  technologies 
developed  at  home  to  local  market  conditions  or  to  adopt  a  home-base  exploiting 
strategy. Although this locational strategy is still prevailing, evidence also point out the 
increasing importance of locating R&D activities abroad in fields where both the home 
and  host  countries  have  developed  relatively  stronger  advantages.  Such  strategy  has 
been referred to as home-based augmenting or asset-augmenting activity (Kuemmerle 
1999,  Patel  and  Vega  1999,  Cantwell  and  Iammarino  2000,  Le  Bas  and  Sierra  2002, 
Cantwell  et  al.  2004).  In  other  words  MNCs  increasingly  tap  into  the  knowledge 
developed elsewhere in order to complement their own domestic strengths. Le Bas and 
Sierra  (2002),  and  Criscuolo  et  al.  (2005)  at  the  regional  level,  suggest  that  firms 
actually  pursue  simultaneously  adaptive  and  innovative  international  knowledge 
seeking strategies.  

A  complementary  line  of  analysis  has  been  dedicated  to  the  main  determinants 
influencing the  locational choices  of MNCs mainly relying on the  inventor(s)’s address 
(Guellec  and  van  Pottelsberghe  de  la  Potterie,  2001,  Picci  2010)  and  the  citations 
contained in the patents documents (Cantwell and Piscitello 2005). Additional evidence 
on  the  main  location  factors  has  been  also  been  gathered  through  surveys5 (Florida 
1997,  UNCTAD  2005,  European  Commission  2013).  These  studies  show  that  the 
internationalization of R&D and innovative activities is mainly driven by a combination 
of  interrelated  supply-  and  demand-side  factors,  and  by  the  technological  and 
institutional attributes of the home and host economies. Important supply-side factors 

5 Comprehensive reviews on the determinants of international R&D activities can be found in OECD 2008, 
2011. 

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TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

include  the  motives  and  type  of  R&D  activities  (UNCTAD  2005,  Criscuolo  et  al.  2005), 
firm size and corporate performances, the co-location of production activities, as well as 
the specific managerial and organisational practices of the firms (i.e. R&D management 
and  flexibility,  communication  and  problem-solving,  see  Moncada-Paternò-Castello  et 
al. 2011). Besides firm-specific characteristics, the decisive factors for MNCs have been 
identified in relation the host country’s attributes such as: 

i)  the  market  features  (size,  growth  potential,  purchasing  power).  Following  the 
traditional market and demand-driven orientation, most studies argue that the size and 
the  characteristics  of  the  local  markets  have  a  positive  influence  on  the  locational 
choices  of  firms.  That  is  firms  would  set  up  foreign  R&D  laboratories  in  order  to 
respond to demand needs/customers preferences.  

ii) the presence of high quality scientific infrastructure and human resources. Firms 
would favour countries well-endowed with for instance universities and, research and 
technological centers of excellence and with a higher proportion of scientists, engineers 
or higher education graduates. 

iii)  the  agglomeration  forces  (clusters,  scientific  parks,  outstanding  innovative  or 
creative cities, etc). Firms may favour a particular location in order to beneficiate from 
the  knowledge  activities  developed  by  companies  from  the  same  industry  (intra-
industry  and  specialization  spillovers  or  proximity  to  other  companies)  or  firms 
operating  in  different  industries  (inter-industry  and  diversity  externalities)  (e.g. 
Cantwell  and  Piscitello  2005,  Alcácer  and  Chung  2007).  Furthermore,  agglomeration 
may  exhibit  some  asymmetries  along  different  dimensions  (Boschma  et  al.  2015) 
suggesting that the related determinants may affect differently the location decisions of 
firms across industries (or technologies). Although these forces are expected to play a 
significant  role  on  the  location  decision,  the  application  of  such  a  proximity-based 
approach  on  country  level  data  would  entail  several  restricting,  and  even  fallacious 
assumptions.  Symmetrically,  geographical  distance,  contrary  to  proximity,  is  expected 
to  exert  a  negative  effect  on  the  probability  of  firms  to  locate  in  a  country  given  the 
increased costs it entails. 

iv)  tax  breaks  and  government  support,  legal  and  intellectual  property  protection 
systems.  An  important  structural  location  determinant  is  the  government  direct  and 
indirect  support  to  R&D  activities.  The  traditional  rationale  for  government 
intervention is that, in its absence private R&D spending may be sub-optimal in certain 
fields. This sub-optimality may emerge due to the specific time (i.e. beyond the lifetime 
horizon  of  companies)  and 
for  developing  certain 
technologies with expected society-wide impacts. It may also result from the extent to 
which  firm  are  able  to  appropriate  the  returns  of  their  R&D  investments.  Therefore 
firms would tend to locate in countries characterized by a strong or reliable protection 
of intellectual property (ies), thus limiting the risk of leakage or imitation. However, as 
underlined in the  OECD review (2008),  evidence  on the  relationship between  IPR and 
the  location  decision  is  rather  equivocal.  Beyond  the  expected  economic  growth  and 
jobs  prospects,  the  commitment  of  national  or  regional  authorities  constitutes  a 
relevant  signal  and  a  clear  incentive  for  companies  willing  to  further  develop  their 

investment  requirements 

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AND TECHNOLOGICAL PROXIMITY 

research  and  innovation  activities.  This  may  lead  to  a  double  gain  for  the  related 
economies  which  may  attract  high-value  R&D  activities  as  well  as  allow  local  firms  to 
beneficiate from and build upon them.  

Nevertheless,  the  relative  importance  of  these  drivers  also  depends  on  the 
technologies,  the  industries  in  which  such  corporations  operate  and,  on  the  different 
propensities  of  resorting  to  the  international  markets  for  their  knowledge  creation 
activities.  

Furthermore,  the  economic  literature  dealing  with  technological  change  has 
underlined  the  path-dependent  and  cumulative  nature  of  this  process  (Dosi  1988, 
Cantwell  1989,  Dosi  et  al.  1990).  In  our  framework,  this  should  be  reflected  in  the 
relationship between companies and host-countries technological profiles. This idea is 
consistent  with  Cohen  and  Levinthal’s  notion  of  absorptive  capabilities  (Cohen  and 
Levinthal 1990), defined as the capacity of scanning, accessing and combining external 
knowledge. Accordingly, firms are expected to seek for new knowledge in technological 
areas  in  which  they  have  developed  prior  knowledge.  More  recent  studies  have  also 
referred  to  this  as  the  willingness  of  firms  to  connect  related  knowledge  assets  or  to 
establish  corporate  technological  coherence  (Cantwell  2009).  Akin  to  the  studies  on 
recombination  and  innovation  (Cecere  and  Ozman  2014),  an  important  dimension  of 
recombinative  capabilities6 is  the  extent  to  which  firms  locate  their  foreign  R&D 
activities  where  complementary knowledge  is  available. As pointed out by Cecere  and 
Ozman  (2014),  "The  indirect  effect  of  proximity  on  innovation  works  through  the 
recombination  capabilities.  High  recombinative  capabilities  are  best  complemented  by 
local search processes" (p. 651). However the search for too close knowledge increases 
the probability of redundancy which may lead to lower expected benefits deriving from 
international knowledge seeking. As a corollary, the selection of technologically distant 
locations  may  open  more  opportunities  for  explorative  R&D  and  innovation-oriented 
search, thus limiting the access to redundant knowledge. This creates a tension between 
distant  and  local  knowledge  seeking  for  firms  willing  to  maintain  a  certain  level  of 
technological  variety.  The  related  trade-offs  in  firms’  strategy  may  entail  a  non-linear 
relationship  between  the  technological  proximity  and  the  probability  to  undertake 
international R&D activities. Therefore:  

H1a: firms tend to search new technological knowledge in areas close to their current 

strengths (local search) when they undertake international R&D activities  

H1b: technological proximity has a non-linear effect on the location decision of firms 

when they undertake international R&D activities  

Among  the  reasons  leading  a  company  to  invest  in  foreign  locations,  there  is  the 
attempt  to  enter  into  specific  technologies  in  which  the  host  country  has  relatively 
higher  comparative  advantages  (Guellec  and  Pottelsberghe  de  la  Potterie  2001, 
Cantwell  2009).  In  particular,  when  taking  their  location  decisions  firms  may  favour 
host countries with superior capacities in developing new emerging technologies, which 
could  lead  to  the  discovery  of  path-breaking,  brand  new  products  and  processes 

6 Recombinative capabilities refer to the internal capabilities of firms to combine previously unconnected 
elements or to find new ways of combining previously connected elements. 

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TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

(Schoenmakers and Duyster 2010). Indeed, emerging technologies are perceived as new 
technologies with the potential to change the economy and society and to contribute to 
a further technology-driven economic growth (Hung and Chu 2006, OECD 2012, Rotolo 
et al. 2015). Such technologies can bring an important contribution to the value-added 
streams  through  the  transformation  of  existing  industries  or  the  creation  of  new 
industry  (-ies).  By  tapping  into  these  technologies,  firms  may  gain  considerable 
advantages in maintaining themselves at the edge of the global technological race. 

Hence,  the  high  degree  of  novelty  (or  newness)  characterizing  these  technologies 
(Small et al. 2014), is particularly relevant in our framework. It should be noted that the 
novelty attached to the emerging technologies may be related both to the method or the 
function fulfilled by the technology. In other words, emerging technologies may build on 
different basic principles with respect to those used before (Arthur 2007) or may put an 
existing  technology 
into  a  new  use  (Adner  and  Levinthal  2002)  and  thus 
(re)invigorating already existing knowledge.  

In  our  framework,  the  search  for  new  technologies  implies  that  companies  will 

prefer locations with a higher specialization in emerging technologies.  

However,  the  two  dimensions  (radicalness  and  cumulativeness)  of  emerging 
technologies imply a tension in the search for new knowledge. From the one hand, the 
cumulative  nature  of  new  technology  creation  would  suggest  that  companies  may 
obtain additional returns from the adoption of emerging technologies that are close to 
their  technological  knowledge;  thus  somehow  relaxing  the  constraints  posed  by  the 
companies'  absorptive  capabilities 
in  their  (international)  knowledge  sourcing 
strategies.  On  the  other  hand,  the  radical  and  disruptive  character  of  emerging 
technologies  suggests  that  companies  may  look  for  them  in  technological  domains 
relatively  farther  from  their  knowledge  base.  Hence  companies  may  either  go  for 
location specialized in emerging technologies with a close knowledge base or opt for a 
'less  close'  knowledge  base.    A  priori,  we  are  not  able  to  determine  which  of  the  two 
dimensions prevail in the location decision. 

Therefore, on the basis of the above arguments we expect that:  

H2a: firms are more likely to locate their international R&D activities in countries with 

relatively higher technological advantages in emerging technologies  

H2b: firms are more likely to  locate in countries with  relatively higher technological 

advantages in emerging technologies depending on the level of technological proximity 

These  mechanisms  have  not  yet  found  empirical  confirmation.  The  validation  of 
these  hypotheses,  especially  when  jointly  hold  with  H1,  would  contribute  to  fill  a  gap 
that has been long standing in the empirics of international knowledge seeking.  

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AND TECHNOLOGICAL PROXIMITY 

3. Empirical application 

3.1 Data 

Our analysis makes use of the 2013 EU Industrial and R&D Investment Scoreboard, 
which provides annual data on the top 2000 R&D investors worldwide, accounting for 
about 80% of the world’s business investment in R&D (European Commission 2013). 7 
The  patents  filed  by  these  companies  at  the  US  Patent  Office  (USPTO)  have  been 
retrieved  from  the  PATSTAT8 database  in  the  framework  of  a  JRC-OECD  joint  project. 
The  matching  has  been  carried  out  on  a  by-country  basis  using  a  series  of  string 
matching algorithms contained in the Imalinker system (Idener Multi Algorithm Linker) 
developed for the OECD by IDENER, Seville, 2013. 9 

The  matching  exercise  employs  information  on  the  Scoreboard  companies' 
subsidiary  structure  (about  500,000  subsidiaries)  as  reported  in  the  ORBIS  database. 
Subsidiaries  located  in  a  different  country  with  respect  to  a  company's  headquarter 
have  been  included  when  performing  the  matching  of  patents  to  company-level  data. 
Their  patent  applications  have  been  associated  to  their  ultimate  owner.  A  more 
extensive description of the approach used to perform the matching between Orbis and 
PATSTAT can be found in Squicciarini and Dernis (2013), while a thorough illustration 
of  the  innovation  activities  of  the  world  corporate  top  R&D  investors  can  be  found  in 
Dernis et al. (2015).   

The final dataset includes information on patents filed at the USPTO over the period 
2010-2012  for  the  1594  MNCs  with  at  least  one  application  at  that  office.  These 
companies,  with  headquarters  located  in  38  different  countries,  have  filed  about 
470,000 patent applications, representing about 29% of the total patent applications at 
USPTO  over  the  same  period.  Table  A1  (in  appendix)  shows  the  distribution  of 
international  patent  applications  across  destinations.  The  dataset  is  completed  by  a 
series of country-specific information discussed in the next section. 

Of  course,  patents  data  entail  several  well-known  shortcomings10.  The  recourse  to 
patents  differs  greatly  across  firms  and  sectors.  Systematic  classifications  of  patents 
based on their relative  value remain very rare so that all inventions are considered of 
equal importance. Besides some inventions are not patented, although they may lead to 
successful innovations. Nevertheless patents constitute a relevant and unique proxy to 
study the inventive activities of companies (Acs and Audretsch 1989, de Rassenfosse et 
al. 2013) as they are made available on long time periods and increasingly for a larger 
set  of  countries11.  Moreover  patent  documents  provide  a  wealth  of  information 

7 For  more  information  on  the  sample  of  companies  included  in  the  EU  Industrial  and  R&D  Investment 
Scoreboard, see http://iri.jrc.ec.europa.eu/scoreboard.html.  
8 PATSTAT  is  the  European  Patent  Office’s  Worldwide  Patent  Statistical  Database  which  contains  data 
about 70 million applications of more than 80 countries. See more details at http://www.epo.org.  
9 For a description of Imalinker, see http://www.idener.es/?portfolio=imalinker. 
10 See for instance Griliches (1990), Archibugi (1992). 
11 Beyond the overall increase in patent applications, this refers notably to the international efforts and 
collaboration made to link or to harmonize the patents procedures and data across several national and 
regional IP Offices, as the IP5 and its Ten foundation projects (see 

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TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

concerning inventors, the applicants and the technical characteristics of the invention, 
all relevant for our analysis. The different areas of technology to which patents pertain 
are classified according to the International Patent Classes (IPC). For comparability and 
interpretation  purposes,  these  technologies  have  been  reassigned  to  the  35 
technological fields originally developed by Schmoch (WIPO 2013). The R&D locations 
are determined by using the residence of the inventor(s), which proxy the country (-ies) 
in which the research leading to the invention has been carried out. Such approach has 
been used by, among others, Guellec and Pottelsberghe de la Potterie (2001), Archibugi 
and  Iammarino  (2002),  Le  Bas  and  Sierra  (2002),  Picci  (2010),  and  Schettino  et  al. 
(2013).  

3.2 Variables description 

To investigate the decision of companies to locate R&D activities abroad, patents are 
assigned to the country of residence of the inventor(s)12 at the origin of the technology 
to be patented. International patenting activities are detected when the location of the 
inventors  differs  from  that  of  the  Scoreboard  company  legally  owning  the  intellectual 
property right. In the multi-inventors and multi-countries cases, fractional counts of the 
same  patent  between  the  different  countries  are  applied.13 One  fifth  of  the  patent 
portfolio  of  our  sample  has  involved  inventor(s)  from  countries  different  from  the 
headquarter location.  

Upon  this  setting,  the  determinants  of  the  location  decision  of  top  corporate  R&D 
investors  are  investigated  relying  on  the  main  factors  identified  by  the  previous 
literature.  

The  revealed  technological  advantage  (RTA)  is  a  common  indicator  to  assess  the 
degree  of  technological  specialization.  It  is  constructed  as  the  revealed  comparative 
advantage  defined  by  Balassa  (1965)  which  characterizes  the  relative  weight  of  an 
economic  sector  on  dimensions  such  as  trade,  production,  R&D  or  patents  (Patel  and 
Pavitt 1991, Cantwell et al. 2004, Liegsalza and Wagner 2013). In this paper we use the 
revealed technological advantage (RTA) to compute the host countries' specialization in 
emerging  technologies.  As  put  forward  by  Rotolo  et  al.  (2015),  there  are  multiple 
definitions  and  methodologies  in  the  literature  to  identify  emerging  technologies.14 
Among  them,  the  OECD’s  definition  (2013),  based  on  the  Kleinberg  (2003) 

http://www.wipo.int/edocs/mdocs/aspac/en/wipo_inn_tyo_10/wipo_inn_tyo_10_ref_theme03_1.pdf ) or 
Cooperative Patent Classification (CPC) initiative. 

12 The choice of the inventor’s country of residence is the most relevant for measuring the technological 
innovativeness  of  researchers  and  laboratories  located  in  a  given  country.  While  patent  counts  by 
applicant  countries  reflect  more  the  degree  of  control  on  patents  by  country's  residents,  wherever  the 
invention is made (OECD.Stat). 
13 See Dernis et al. (2001) for a more in depth description of the methodology used.   
14 Recently, Rotolo et al. have suggested a reconciling definition of an emerging technology as “a radically 
novel and relatively fast growing technology characterised by a certain degree of coherence persisting over 
time  and  with  the  potential  to  exert  a  considerable  impact  on  the  socio-economic  domain(s)  […].Its  most 
prominent impact, however, lies in the future and so in the emergence phase is still somewhat uncertain and 
ambiguous.”  (Rotolo  et  al.  2015,  page  1828).  Following  this  definition,  our  conception  of  emerging 
technologies is a priori narrower due to the intrinsic nature of our data. 

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AND TECHNOLOGICAL PROXIMITY 

methodology, constitutes a relevant choice given the nature and the construction of our 
data.15 Accordingly  emerging  technologies  are  identified  at  the  4-digit  level  of  the  IPC 
classification on the basis of the sudden and persistent increase in patent applications 
pertaining to these technological fields. The RTA of a country in emerging technologies 
is computed as the ratio between its patent share in these technologies and the share of 
world patents in the same technologies:  

𝑅𝑇𝐴 𝑖𝑛 𝑒𝑚𝑒𝑟𝑔𝑖𝑛𝑔 𝑡𝑒𝑐ℎ𝑛𝑜𝑙𝑜𝑔𝑖𝑒𝑠𝑗05_09 =

𝑠ℎ𝑎𝑟𝑒_𝑒𝑚𝑗05_09
𝑠ℎ𝑎𝑟𝑒_𝑒𝑚05_09

where,  𝑠ℎ𝑎𝑟𝑒_𝑒𝑚𝑗05_09  denotes  the  share  of  country 

in  emerging 
technologies  over  the  five  years  preceding  the  period  in  which  companies  patenting 
activities  are  observed  -  that  is,  2005-2009  -  and 𝑠ℎ𝑎𝑟𝑒_𝑒𝑚05_09 is  the  same  share 
calculated on the overall world patents.  

j  patents 

To quantify technological proximity we use the angular separation measure (and its 
square) originally introduced by Jaffe (1989) in his analysis of knowledge spillovers16. 
In  our  application  this  is  computed  between  the  host  country’s  and  the  company’s 
vectors  of  patent  shares  across  technological  fields.  In  particular,  technological 
proximity  between  company 𝑖 and  country 𝑗   is  computed  across  vectors  in  a  35-
dimensional technological space (the technological fields identified by Schmoch) and is 
calculated as: 

𝑇𝑒𝑐ℎ𝑛𝑜𝑙𝑜𝑔𝑖𝑐𝑎𝑙 𝑝𝑟𝑜𝑥𝑖𝑚𝑖𝑡𝑦𝑖𝑗  =  

𝑓𝑖𝑓𝑗′

√(𝑓𝑖𝑓𝑖′) ∗ (𝑓𝑗𝑓𝑗′)

where  𝑓𝑖  is  the  distribution  of  patents  filed  by  a  company  𝑖  across  the  35 
technological classes defined by Schmoch over the period considered, and 𝑓𝑗 represents 
the  distribution  of  patents  of  a  country 𝑗 across  the  same  technological  classes.  As  for 
the RTA measures, the technologies shares within countries are calculated on the five-
year  period  preceding  the  actual  patenting  period  of  companies  (2005-2009).  On  the 
same  period  we  calculate  the  (Log of) number of patents  of  the  hosting  country,  which 
proxies its knowledge base.  

From  the  Main  Science  and  Technology  Indicators  database  (MSTI-OECD)  we  take 
the  percentage  of  Business  enterprise  expenditure  on  R&D  (BERD)  financed  by  the 
government of the hosting country (% Gov BERD expenditure) and the variables used to 
calculate the difference in the GDP per capita between the hosting country and the  top 
R&D  investors’  location,  the  former  minus  the  latter  (∆  log  gdp  per  capita).  The  two 
variables are calculated on the period 2005-2009. 

15 Emerging  technologies  are  identified  as  the  4-digit  IPC  classes  that  experienced  a  patent  "burst",  a  
sudden and persistent increase in the number of patents filed in the 2000s (OECD, 2013). Patent bursts 
reflect the increase of patent applications in comparison to those patterns observed in the previous years 
and in other technological fields. Only IPC combinations with positive bursts are considered. 

16 Jaffe  (1986)’s  angular  separation  is  still  one  of  the  most  widely  employed  measures  in  the  applied 
research  on  technological  distance  between  companies  or  between  companies  or  other  entities  (see 
recent uses among other by Aldieri 2013, Bloom et al. 2013) 

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AND TECHNOLOGICAL PROXIMITY 

From the Barro-Lee dataset (Barro and Lee 2010) the difference between the share 
of  tertiary  education  in  the  host  and  origin  countries  is  calculated  (∆ of % of tertiary 
education). Unfortunately, these figures derive from census data and are available only 
with intervals of five years. Our application employs those relative to 2005.17 

Finally, as a common practice in the R&D internationalization literature we control 
for a series of geographical measures drawn  from the GeoDist database. This database 
provides  a  series  of  gravity  variables  developed  and  described  by  Mayer  and  Zignago 
(2005,  2011).  In  particular,  we  use  the  (log  of)  the  kilometric  distance  between  the 
capital of the hosting and original country location of the Scoreboard company and two 
binary  variables  as  follows:  Common  borders  that  takes  value  1  if  the  two  countries 
share  a  border,  and  Common language  is  they  share  the  same  language.  Table  A2  (in 
appendix) shows that the correlations between the explanatory variables are generally 
quite low.   

3.3 Econometric strategy 

In  the  empirical  application,  we  model  a  company's  decision  to  locate  its 
international  technological  activities  upon  firms’ 
location-specific 
technological conditions, traditional R&D location factors, and other controls commonly 
used  in  the  economic  geography  literature.  The  drivers  of  the  location  decision  are 
estimated  with  a  multilevel  mixed-effects  logistic  regression  which  allows  controlling 
for  both  fixed  and  random  effects.  The  probability  of  a  firm 𝑖 operating  in  sector 𝑗 to 
locate in a given country 𝑐 could be written as:  

location  and 

𝑃 (𝑦𝑐𝑖𝑗 = 1|𝑥𝑐𝑖𝑗, 𝜇𝑖, 𝛾𝑗) = 𝐹(𝛽𝑥𝑐𝑖𝑗 + 𝜇𝑖 + 𝛾𝑗) 

where  𝑥𝑖𝑗 identifies the drivers of the company decision to locate in a given foreign 
country presented in the previous section, 𝜇𝑖 and 𝛾𝑗 are company- and industry- specific 
random  intercepts,  and 𝐹(∙) is  the  cumulative  logistic  distribution  mapping  the  linear 
predictor to the probability of success (𝑦𝑐𝑖𝑗 = 1) with 𝐹(𝜗) = exp(𝜗) /{1 + exp(𝜗)}. The 
random  parameters  define  the  stochastic  portion  (unobserved)  of  the  choice  function 
which can be correlated over alternatives. This property relaxes the assumption of lack 
of correlation among alternatives characterizing conditional logit models that gives rise 
to  the  independence  of  irrelevant  alternatives  (IIA)  property  and  its  restrictive 
substitution patterns (Train 2003). 

This  setting  allows  a  more  appropriate  modelling  of  a  firm  decision  to  locate  in  a 
given  country by  directly dealing with the  clustered structure  of the  data, where  each 
cluster  has  its  own  choice  behaviour.  Indeed,  in  the  present  setting  instead  of 
considering  all  observations  at  once,  these  are  organized  as  a  series  of N independent 
clusters (our companies) nested into I different clusters (industries).  

The mixed logit model has a great flexibility, however the computational burden of 
the  simulation  techniques  involved  has  limited  its  application  until  the  computational 
capacity  of  computers  has  reached  levels  to  ensure  results  in  an  admissible  time.  A 

17 We also tried to use figures relative to 2000 and 2010. The use of different time periods does not affect 
the results.  

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AND TECHNOLOGICAL PROXIMITY 

similar  setting  has  been  used  by,  among  others,  Basile  et  al.  (2008)  to  analyse  the 
subsidiary  location  of  multinational  firms  in  50  European  regions,  and  Griffith  et  al. 
(2014)  to  ascertain  the  importance  of  corporate  income  taxes  in  determining  where 
firms choose to legally own their intellectual property rights. 

4. Results 

The  estimation  results,  summarized  in  Table  1,  provide  support  for  the  research 
hypotheses put forward in the  theoretical background.  The first two  columns  (Spec. 1 
and  Spec.  2)  report  the  estimation  results  including  the  differences  in  language,  the 
geographical distances, the (possible) host country’s knowledge base and our main focal 
variables  (the  RTA  of  the  host  country  in  developing  emerging  technologies,  the 
measure  of  its  technological  proximity  with  a  given  company  and  its  square).  The 
remaining variables discussed above are included in Spec. 3 and 4. Finally, in Spec. 5 we 
introduce  the  interaction  between  a  country  relative  specialization  in  emerging 
technologies and its technological proximity with a company.  

The  distance  from  the  headquarters’  location  affects  negatively  the  probability  of 
locating  innovation  activities  in  a  given  foreign  country,  the  relative  estimated 
coefficients  are  negative  and  strongly  significant  for  all  the  specifications.  However, 
sharing a common border turns out to not have a significant effect. This finding suggests 
that  despite  the  strong  decrease  in  communication  costs  and  the  increase  of 
communication  facilities  experienced  with  the  advent  of  ICT  technologies,  the 
organizational  and  managerial  costs  of  international  R&D  teams  still  represent  an 
important  barrier  to  locate  R&D  activities  abroad.  On  the  other  hand,  when  locating 
abroad companies do not simply “pass the border”, but carefully choose their location 
on  complementary  criteria  as  sharing  a  common  language.  The  dummy  indicating  the 
commonality of spoken language positively affects the firms’ location decisions. Indeed 
sharing  a  common  language  increases  the  efficiency  in  transferring  and  aggregating 
knowledge (Grant 1996).  

Our  proxy  for  a  country  knowledge  base,  or  innovation  capacity,  is  positive  and 
significant  in  all  the  specifications.  Companies  tend  to  locate  where  knowledge 
opportunities  are  higher.  This  finding  is  in  line  with  many  studies  stressing  the 
importance of scientific resources as a motive for R&D investments.  

The results support our hypotheses H1a and H1b on the preference of companies to 
search  in  the  neighbourhood  of  their  current  knowledge  when  they  undertake 
international  knowledge  seeking  activities.  The  technological  proximity  between  a 
company and a given country increases the probability of locating R&D investments in 
this country. 

The coefficient capturing this effect is positive in all the specifications and does not 
vary  when  additional  controls  are  included.  These  results  support  the  local  search 
hypothesis. The square of the technological proximity enters with a negative sign in the 
estimation,  where  the  coefficient  of  the  linear  term  increases  in  magnitude;  this 

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suggests a curvilinear relationship between technological proximity and the company’s 
location  decision.  Firms  are  more  likely  to  locate  in  countries  whose  technological 
profiles  are  neither  too  similar  nor  too  different.  This  result  generalizes  previous 
findings  on  the  alliance  strategies  in  the  Information  Communication  Technologies 
sector (Cecere and Ozman 2014).  

Table 1: The firms’ decision to locate R&D in a foreign country 

Spec. 1 

Spec. 2 

Spec. 3 

Spec. 4 

Spec. 5 

Spec. 6 

Log number of patents (destination) 

RTA in emerging technologies (destination) 

Technological proximity 

Technological proximity (square) 

Tech. proximity * RTA in emerging technologies 

Kilometric distance (log) 

Common borders (0/1) 

Common language (0/1) 

% BERD expenditure (destination) 

∆ of log gdp per capita (origin/destination) 

∆ in % of tertiary education (origin/destination) 

Constant 

Random effects 
Industrial 

Company 

Observations 
Number of industries 
Chi-square 
Log-likelihood 
LR test vs logistic (p-values) 

0.675*** 
(0.015) 
0.509*** 
(0.049) 
1.809*** 
(0.084) 

0.676*** 
(0.015) 
0.583*** 
(0.050) 
4.214*** 
(0.328) 
-2.651*** 
(0.349) 

-0.189*** 
(0.020) 
0.018 
(0.079) 
1.022*** 
(0.046) 

-0.202*** 
(0.020) 
-0.029 
(0.079) 
1.060*** 
(0.046) 

0.677*** 
(0.015) 
0.759*** 
(0.100) 
4.773*** 
(0.430) 
-2.689*** 
(0.349) 
-0.431** 
(0.213) 
-0.201*** 
(0.020) 
-0.030 
(0.079) 
1.062*** 
(0.046) 

-7.919*** 
(0.239) 

-8.336*** 
(0.246) 

-8.564*** 
(0.271) 

1.380*** 
(0.458) 
2.122*** 
(0.183) 
39,282 
31 
3209 
-22949 
0.000 

1.260*** 
(0.424) 
2.050*** 
(0.178) 
39,282 
31 
3230 
-22919 
0.000 

1.258*** 
(0.423) 
2.052*** 
(0.179) 
39,282 
31 
3232 
-22917 
0.000 

0.777*** 
(0.017) 
0.501*** 
(0.062) 
1.750*** 
(0.090) 

-0.237*** 
(0.021) 
0.002 
(0.081) 
1.040*** 
(0.051) 
0.013*** 
(0.002) 
-0.187*** 
(0.036) 
-0.001 
(0.003) 
-8.684*** 
(0.265) 

1.422*** 
(0.477) 
2.198*** 
(0.196) 
35,068 
31 
3103 
-21444 
0.000 

0.779*** 
(0.017) 
0.592*** 
(0.063) 
4.720*** 
(0.360) 
-3.273*** 
(0.383) 

-0.252*** 
(0.021) 
-0.050 
(0.081) 
1.068*** 
(0.051) 
0.013*** 
(0.002) 
-0.177*** 
(0.036) 
0.001 
(0.003) 
-9.188*** 
(0.272) 

1.276*** 
(0.434) 
2.107*** 
(0.189) 
35,068 
31 
3134 
-21407 
0.000 

0.779*** 
(0.017) 
0.836*** 
(0.109) 
5.514*** 
(0.464) 
-3.342*** 
(0.384) 
-0.603*** 
(0.219) 
-0.251*** 
(0.021) 
-0.051 
(0.081) 
1.071*** 
(0.051) 
0.013*** 
(0.002) 
-0.178*** 
(0.036) 
0.001 
(0.003) 
-9.507*** 
(0.297) 

1.273*** 
(0.433) 
2.109*** 
(0.189) 
35,068 
31 
3138 
-21403 
0.000 

Standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Random effects are the estimated variances of the random 
intercepts at the industry and company level. The LR test strongly supports the model used with respect to the logistic 
regression.  

Also our hypothesis H2a translating the effect of superior host-country capabilities 
in emerging technologies on the location decision is confirmed. The related coefficient is 
positive  and  stable  across  the  different  specifications  used.  Ceteris  paribus,  and 

14 

 
 
  
  
  
  
  
  
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  
  
  
  
  
 
  
 
IPTS WORKING PAPER ON CORPORATE R&D AND INNOVATION – NO. 09/2015 
TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

especially considering that technological proximity is controlled for, companies show a 
higher  probability  to  locate  R&D  activities  in  countries  with  higher  revealed 
technological advantages in emerging technologies. 

This first set of results is particularly interesting from an innovation (and education) 
policy  perspective.  Countries  willing  to  attract  higher  values  investments,  as  those 
related to R&D activities, should create an environment conducive to the creation and 
development of brand new ideas with a high potential impact on the long term growth. 
Indeed, Schoenmakers and Duyster (2010) showed that, contrarily to the conventional 
wisdom, radical innovations are based on existing knowledge, to a greater extent than 
non-radical  ones  do,  and  mainly  derive  from  the  (re)combination  of  mature  and 
emerging  technologies  pertaining  to  different  technological  areas.  This  suggests  that 
supporting  a  multidisciplinary  environment,  which  facilitates  the  exchange  and 
integration of different knowledge, could be a valuable option to attract further private 
investments. 

Figure  1  presents  the  predicted  location  probabilities  for  different  values  of 
technological proximity (right axis) and countries revealed technological advantages in 
emerging technologies (left axis). The figure shows the inverted-U relationship between 
technological proximity and a company’s location decision discussed above. Most of the 
company-country  observations  have  technological  proximity  values  lying  in  the 
increasing  part  of  the  curve,  however  for  about  10%  of  the  company-country 
observations (involving almost 500 different companies) the value of the Jaffe measure 
implies  a  negative  marginal  effect  of  proximity  on  location  probabilities.  For  these 
observations, technological profiles are "too close".  

Figure 1: Predicted location probabilities for different values of technological proximity and country RTAs in 
emerging technologies  

Figure  1 somehow  illustrates  the  tension  underlying our hypothesis  H2b. For each 
level  of  technological  proximity,  the  location  probability  increases  with  a  country 

15 

 
 
 
 
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AND TECHNOLOGICAL PROXIMITY 

specialization in emerging technologies (lighter colours going from the right to the left 
of the figure). However, the negative sign of the coefficient for the interaction between 
technological  proximity  and  RTA  in  emerging  technologies  suggests  the  existence  of a 
trade-off  effect.  A  higher  technological  proximity  increases  the  location  probabilities 
especially  in  those  countries  with  a  relatively  low  specialization  in  emerging 
technologies,  whereas  a  low  technological  proximity  seems  to  be  more  important  for 
location decisions in countries with a higher specialization in emerging technologies.  

This  finding  echoes  the  exploiting-exploring  organizational  strategies  discussed  by 
March  (1991)  and  revisited,  among  others,  by  Kummerle  (1997),  and  Patel  and  Vega 
(1999), in the  context of  corporate  R&D internationalization.  Where, in the  latter case 
companies,  seeking  for  new  technological  opportunities,  are  willing  to  explore 
technological  domains  relatively  farer  from  their  knowledge  base;  in  the  first  case 
companies' location decision may be driven by the objective of reinforcing their actual 
knowledge base.    

The positive impact of the percentage of BERD financed by the government confirms 
the importance of the R&D and innovation support policies, at least in attracting foreign 
R&D investments.  

Controlling  for  the  other  factors,  companies  tend  to  favour  countries  with  lower 
levels of GDP  per capita. This may  reflect the  search for skilled labour at a lower cost 
and is in line with the evidence showing an increasing participation of “less” developed 
countries in the global knowledge market. 

Our  proxy  for  the  differences  in  the  countries  education  levels  is  positive  but  the 
significance  does  not  hold  across  specifications.  In  other  words,  we  do  not  find  clear 
evidence  that  higher  education  levels  confer  advantages  in  attracting  foreign  R&D 
investments  of  Top  R&D  investors  worldwide.  However,  it  should  be  considered  that 
the  majority  of  developed  and  developing  countries  that  constitute  our  sample  have 
attained high levels of schooling. Therefore,  opting for measures related to the quality 
and  organization  of  the  education  systems  could  be  preferable  and  provide  clearer 
results.  

5. Conclusion 

This paper has shed new lights on the determinants of the international knowledge 
seeking strategies of the top R&D investors worldwide. Using patent applications at the 
USPTO we have been able to map their international R&D activities on the basis of the 
inventor(s)’s location contained in the patent documents. Two main mechanisms were 
scrutinized,  the  extent  to  which  companies  resort  to  the  international  knowledge 
markets  to  reinforce  their  technological  knowledge  base  and  to  tap  into  technologies 
with higher long-term potentials.  

Our  findings  show  that  top  R&D  investors  worldwide  actually  perform  R&D 
internationally  to  search  technological  knowledge  in  areas  close  to  their  current 
strengths, i.e. they favour a local technological search. However, technological proximity 

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TOP R&D INVESTORS AND INTERNATIONAL KNOWLEDGE SEEKING: THE ROLE OF EMERGING TECHNOLOGIES 
AND TECHNOLOGICAL PROXIMITY 

has a non-linear effect on the international location decision of firms. That is to say that, 
firms  will  favour  countries  which  perform  relatively  well  in  the  technological  areas 
where they have established prior advantages, but only up to a certain threshold. This 
finding echoes with the Cohen and Levinthal’s notion of absorptive capacity.  

In  a  complementary  manner,  firms  also  look  for  the  potential  advantages  deriving 
from  emerging  technologies  in  order  to  maintain  themselves  at  the  edge  of  the  global 
technological race. However, companies somehow face a trade-off between locating in a 
country specialized in emerging technologies and a country with a closer technological 
knowledge.  In  other  words,  the  attraction  effect  of  emerging  technologies  fades  away 
with higher levels of technological proximity.  

Emerging  technologies  are  receiving  an  increasing  attention  both  from  the  policy 
and  the  academic  communities.  Indeed,  they  are  perceived  as  technologies  which  can 
for  sustainable  business 
provide  solutions  to  global  challenges  and  ground 
opportunities  (WEF  2014)  with  the  potential  to  change  the  economy  and  society 
(Rotolo et al. 2015). Most of the attention has been posed on the definition of different 
approaches  to  detect  which  technologies  have  the  greatest  potential  impact  in  the 
medium and long-term. However, very little knowledge concerning the impact that the 
realization  and  widespread  use  of  these  emerging  technologies  has  been  so  far 
produced. More research is needed to understand the conditions for the emergence of 
certain technologies and their effects on country and regional development paths. 

Our  contribution  suggests  that  creating  an  environment  conducive  to  the 
development of emerging technologies not only could lead to a sustained growth, but is 
also  a  leverage  for  countries  to  attract  high  value  foreign  investments.  Particularly 
interesting  from  a  policy  perspective  is  the  fact  that  emerging  technologies  largely 
derive  from  the  use  of  existing  technologies  for  new  purposes  (Adner  and  Levinthal 
2002) and that radical innovations steam from existing knowledge as a (re)combination 
of  mature  and  emerging  technologies  from  different  domains  (Schoenmakers  and 
Duyster  2010).  Indeed,  creating  multidisciplinary  environments  that  facilitate  the 
exchange and integration of different knowledge areas (or supporting multi-technology 
projects)  can  trigger  new  technological  opportunities.  Moreover,  public  policies 
encouraging entrepreneurial initiatives in areas related to new technologies may lead to 
technological  advancements  typically  not  yet  foreseen  by  policy-makers  and/or 
the  commercialization  of  products 
potential  customers.  Finally,  supporting 
incorporating  these  emerging  technologies  can  foster  their  diffusion  and  the 
development of (new) industries. Analysing which kind of policies are likely to have the 
highest  impact  is  beyond  the  objective  of  this  contribution.  We  are  confident  that  the 
renewed  interest  on  innovation  and  industrial  policies  will  provide  new  evidence  to 
guide the policy action.  

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AND TECHNOLOGICAL PROXIMITY 

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Appendix 

Country 

Country 

Table A1: Distribution of patent applications across foreign destinations 
% of 
patents 
1.6 
1.4 
1.0 
1.0 
0.9 
0.8 
0.7 
0.4 
0.4 
0.4 
0.3 
0.3 

Belgium 
Austria 
Australia 
Korea, Republic Of 
Taiwan 
Finland 
Spain 
Ireland 
Denmark 
Norway 
Brazil 
Russian Federation 

United States 
Germany 
China 
United Kingdom 
France 
Japan 
Canada 
India 
Italy 
Israel 
Switzerland 
Netherlands 
Sweden 

% of 
patents 
31.6 
12.8 
12.3 
7.0 
5.7 
4.6 
4.1 
3.2 
2.6 
1.8 
1.8 
1.7 
1.7 

Table A2: Correlations between explanatory variables 

1 Log number of patents (destination) 

3 Technological proximity 

2 RTA in emerging technologies (destination) 

4 Log of Kilometric distance (origin/dest.) 

5 Common borders (0/1) 

6 Common language (0/1) 

7 % BERD expenditure (destination) 

8 ∆ log gdp per capita (origin/destination) 

9 ∆ in % of tertiary education (origin/dest) 

Avg. 

9.250 

0.354 

1.117 

8.430 

0.056 

0.143 

7.914 

-0.326 

-5.000 

1 

1 

0.061 

2 

1 

3 

4 

5 

6 

7 

8 

-0.271 

-0.057 

1 

-0.093 

-0.097 

0.066 

1 

0.024 

-0.105 

-0.327 

0.228 

0.036 

0.034 

0.064 

0.035 

-0.027 

-0.487 

1 

0.110 

-0.119 

0.408 

1 

-0.047 

0.022 

-0.038 

-0.115 

1 

-0.025 

-0.255 

-0.123 

0.002 

0.110 

-0.281 

0.042 

0.167 

-0.003 

-0.387 

1 

0.0621 

0.145 

0.412 

21 

 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
  
  
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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European Commission 
Joint Research Centre – Institute for Prospective Technological Studies 

Title: Top R&D Investors and international knowledge seeking: the role of emerging technologies and technological proximity 

Author(s): Mafini Dosso, Antonio Vezzani 

Luxembourg: Publications Office of the European Union 

2015 – 21 pp. – 21.0 x 29.7 cm 

EUR – Scientific and Technical Research series – ISSN 1831-9424 (online) 

ISBN 978-92-79-52085-3 (PDF)

doi:10.2791/853343 

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JRC Mission 

As the Commission’s  
in-house science service,  
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mission is to provide EU  
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doi:10.2791/853343 

         ISBN 978-92-79-52085-3