The antecedents and innovation effects of domestic and
offshore R&D outsourcing
Olivier Bertrand
Graduate School of Management, St. Petersburg State University
Volkhovsky Per.3, 199 004 St. Petersburg, Russia
And Toulouse School of Economics
21 allée de Brienne, 31000 Toulouse, France
[email protected]
[email protected]
&
Michael J. Mol *
Warwick Business School
University of Warwick
Coventry, CV4 7AL, UK
United Kingdom
phone ++44 (0)24 7652 2148
[email protected]
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Abstract:
Firms increasingly tap external sources for innovation. This paper investigates the differences
between R&D outsourcing at home and abroad. We build a capabilities-based framework,
incorporating arguments on international management and governance. Home outsourcing
occurs when firms lack innovative capabilities. By contrast more innovative firms use foreign
suppliers to add specific complementary capabilities. We argue that having a specialized R&D
process and existing foreign involvement increase the preference for offshore outsourcing over
domestic outsourcing. We predict that offshore outsourcing, while increasing governance costs,
improves product and process innovation performance, while domestic outsourcing reduces it.
The empirical analysis, on a large number of businesses in France, broadly supports this
framework. We discuss what makes firms better at R&D outsourcing and through what process it
affects innovation.
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INTRODUCTION
In their quest for new inputs for innovation purposes firms increasingly tap external sources,
both at home and abroad. The decision where to outsource research and development (R&D)
activities has important implications for firm innovativeness and strategy. Scholarly views are
shifting away from the traditional rejection of R&D outsourcing (Porter, 1980; Williamson,
1985) toward a more open approach, suggesting that outsourcing can be beneficial (Chesbrough,
2003). But so far they have largely ignored differences between outsourcing R&D at home and
outsourcing it abroad, even though understanding these differences and their implications for
innovation performance is important. In this paper we demonstrate that firms outsource R&D at
home to overcome a lack of internal capabilities; whereas they outsource abroad when their
specialized R&D processes and overseas involvement produce a need for complementary
capabilities. We theorize and empirically confirm that R&D outsourcing abroad improves
innovation performance, while domestic R&D outsourcing damages it.
Firms, governments, and academics have long acknowledged the benefits of innovation
for the firm, its customers and other stakeholders, and society at large. Firms have wellestablished innovation and R&D functions to help them innovate. But a recent and critical
empirical trend has been the disaggregation of innovation value chains through domestic and
offshore outsourcing, even in high-tech industries, leading to displacement of internal R&D
(Contractor, Kumar, Kundu, and Pedersen, 2010; Grimpe and Kaiser, 2010; Howells, Gagliardi,
and Malik, 2008; Lewin, Massini, and Peeters, 2009; Mol, 2005; Mudambi, 2008). Domestic and
offshore outsourcing can potentially affect R&D capabilities and costs. From a managerial
perspective, it is important to understand how outsourcing R&D contributes to innovation
outcomes, and when offshore outsourcing is a viable strategy. In this paper, following Lei and
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Hitt (1995), we interpret R&D outsourcing as the procurement of R&D activities from
independent suppliers, in contrast to internal R&D sourcing (within the business) and affiliate
R&D sourcing (from elsewhere in the corporation). Offshore R&D outsourcing refers to
activities procured from independent suppliers located outside the focal country (for the purposes
of this paper, France). We argue that R&D capabilities are one example of a dynamic capability
(Helfat et al., 2007) and are used to create innovation, specifically new products and processes.
Various strands of literature have addressed aspects of this issue. There are literatures
around knowledge-seeking internationalization and multinational subsidiaries (Almeida, 1996;
Berry, 2006; Criscuolo, Narula, and Verspagen, 2005; Dunning and Narula, 1995); global and
offshore outsourcing (Murray and Kotabe, 1999; Lewin et al., 2009; Mol, van Tulder, and Beije,
2005); and the externalization of R&D activities (Afuah, 2001; Chesbrough, 2003; Leiponen and
Helfat, 2010; Veugelers and Cassiman, 1999). For instance, it has been argued that overall R&D
outsourcing may have a negative curvilinear effect on innovation outcomes (Grimpe and Kaiser,
2010). Yet, in spite of our increased knowledge about R&D outsourcing, some important
research questions remain unanswered. In particular, while researchers have studied how the
outsourcing of some activities may differ at home and abroad, they have not done this for R&D,
even though firms have a clear choice about where to outsource their R&D (Narula, 2001). In
addition, given the strategic nature of R&D, there is a persistent debate about whether R&D
outsourcing is good or bad for innovation outcomes (e.g., Adams and Marcu, 2004), and a lack
of clarity over the effect of the outsourcing location on innovation.
In this paper we contribute to these debates conceptually, arguing that domestic and
offshore R&D outsourcing play different roles in firms’ innovation capabilities. We also make an
empirical contribution by proving the importance of specific factors related to the firm’s R&D
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process and its international involvement, in determining the choice between domestic and
offshore outsourcing; and by showing that offshore outsourcing contributes positively to
innovation, while domestic outsourcing has a negative effect on it.
The paper proceeds as follows. First, we build a conceptual framework, drawing on
capabilities-based arguments coupled with theoretical insights from the international
management governance literatures. Then we present longitudinal data on internal and external
R&D activities of a large number of business units in France. Our analyses broadly support the
proposed framework. We conclude that while domestic R&D outsourcing is often undertaken
when firms lack their own innovative capabilities, firms that are willing and able to outsource
abroad to access complementary capabilities are rewarded with better innovation outcomes.
RESEARCH QUESTIONS
Obtaining and using new knowledge has become a crucial aspect of firms’ competitive
strategies, as it allows them to successfully bring new or improved products to the market, using
novel or better processes. The internationalization, outsourcing, and innovation literatures have
identified two intertwined trends in the organization of innovation activities. One is the growing
amount of (domestic) R&D contracted to outside firms. The other is that R&D activities
increasingly occur across geographical borders. Our hypotheses (below) capture both trends.
There is a substantial literature around the externalization of R&D activities (e.g.,
Chesbrough, 2003; Linder, Javrvenpaa, and Davenport, 2003; Veugelers and Cassiman, 1999),
which argues for the need to involve external knowledge suppliers in the innovation production
system and suggests best ways to set up contracts with outside R&D suppliers (Fey and
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Birkinshaw, 2005; Lai, Riezman, and Wang, 2009; Leiponen and Helfat, 2010). There is also a
literature around knowledge-seeking internationalization (e.g., Berry, 2006; Dunning and Narula,
1995), demonstrating how multinational firms use internationalization to acquire or accumulate
new knowledge and how diversity in different national innovation systems can encourage firms
to internationalize. Finally, there is a literature around outsourcing, global sourcing, global
outsourcing and more recently offshoring (e.g., Bertrand, forthcoming; Di Gregorio, Musteen,
and Thomas, 2009; Gilley and Rasheed, 2000; Lewin et al., 2009; Martinez Noya, Garcia Canal,
and Guillen, 2010; Mol et al., 2005; Murray and Kotabe, 1999), which is concerned with the
antecedents of this phenomenon, and sometimes with its impact on firm performance. But there
is a lack of firm-level evidence on offshore outsourcing, especially of R&D, and to the best of
our knowledge no previous work has addressed the set of hypotheses we tackle here.
Capabilities
Broadly speaking, our arguments in support of those hypotheses revolve around the need for
R&D capabilities1. In recent years, scholars in strategic management have been concerned with
the concept of dynamic capability (Eisenhardt and Martin, 2000; Teece, Pisano, and Shuen,
1997), defined as ―the capacity of an organization to purposefully create, extend, and modify its
resource base‖ (Helfat et al., 2007: 4). ―Resource base‖ refers to the ―tangible, intangible, and
human assets (or resources) as well as capabilities which the organization owns, controls, or has
1
We acknowledge there are other perspectives. But as recently argued (Contractor et al, 2010: 1418) “traditional
theory lenses – such as transaction costs, or resource based theory, or Dunning’s (1993) OLI (ownership, location,
and internalization) paradigm for FDI – are inadequate to fully explain, or capture the nuances of recent strategic
thinking with regards to offshoring and outsourcing decisions”. We believe the capabilities view provides a viable
alternative, although we include various arguments from these other lenses below.
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access to on a preferential basis‖ (Helfat et al., 2007: 4)—in other words, this includes resources
and capabilities of outside suppliers accessed through outsourcing arrangements.
R&D capabilities are one example of this and their presence supports technological
innovation in the form of new products and processes. Some R&D capabilities help produce
fundamentally new research insights—the ―R‖ in R&D—while others are more applied—the
―D.‖ Research may be harder to outsource than development because the associated transaction
costs can be prohibitive (Williamson, 1985). The capabilities view posits that firms differ in the
extent to which they possess the capabilities required to innovate, and that this heterogeneity
produces different governance decisions about how much R&D to outsource (Barney, 1999).
Firms wanting to innovate but having fewer required R&D capabilities than potential outside
suppliers, will be more inclined to outsource R&D (Jacobides and Winter, 2005).
Although there are other motives for outsourcing, including cost and speed, the prime
motive is probably to seek expertise that is not available internally (Howells et al., 2008), that is,
to access R&D capabilities. There are two types of R&D capability that firms may look for
externally. When a firm’s own capabilities are deficient, or when it looks for a lower cost
replacement, it will need substitute capabilities. By contrast, complementary capabilities
augment the firm’s internal capability base (Lorenzoni and Lipparini, 1999). Firms are known to
be willing to invest more in relationships with outside suppliers, and deal with higher governance
costs, to obtain complementary capabilities(Lorenzoni and Lipparini, 1999). We contend that
they will also be willing to encounter the higher governance costs that arise when outsourcing
abroad. Broadly, we argue that domestic R&D outsourcing is primarily used to access relatively
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generic innovation inputs while offshore R&D outsourcing is likely to be used to help firms
access more specialized complementary innovation inputs.2
In line with earlier literature on capabilities and innovation (Eisenhardt and Martin, 2000;
Helfat and Peteraf, 2009; Massini, Lewin, and Greve, 2005; Mol and Birkinshaw, 2009; Teece,
2007), we further posit that firms’ prior processes and positions are the factors that help to create
and attain innovation capabilities, since capabilities are shaped by past learning (Helfat et al.,
2007; Nelson and Winter, 1982). More specifically, we argue that the need for firms to access
complementary R&D capabilities, by outsourcing abroad, is driven by the degree of
specialization and complexity of its underlying R&D process. The attainment of capabilities is
also facilitated by the firm’s context, especially its existing foreign involvement. We now argue
for these two factors in more detail, presenting specific associated variables.
R&D Process
A firm with a more specialized and complex R&D process will require not only more but also a
wider range of R&D inputs. We define a specialized R&D process as one that requires many and
varied R&D inputs. These inputs will typically not all be found under one roof, hence the need to
outsource some R&D to external suppliers. Moreover, once a firm looks for specialized R&D
inputs it is less likely to find them at home, because few companies supply them, reducing the
likelihood that a leading domestic supplier will be found (Quinn and Hilmer, 1994). Specialized
2
In this paper we do not explicitly consider the costs of innovation, preferring to focus on innovation effectiveness.
This is not to deny that recently, after the time frame of measurement in the data presented here, there has been more
of a tendency to look abroad for cheap innovation inputs—but that is not our focus. We will comment on this again
later.
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R&D suppliers tend to be based in other, adjacent industries that may well be located abroad,
given that countries are specialized in different fields of technology and innovation (Alcácer and
Chung, 2007), and that industries are often clustered (Porter, 1990).
In other words, when firms look for capabilities which are relatively mundane, they often
find them in a wide variety of locations around the world, including the home country. If these
capabilities can be outsourced at home, it generally makes little sense to source them from
abroad given the costs involved (we will discuss in more detail later). By contrast, R&D tapped
from international markets provides firms with more opportunities and choices, and hence a
greater potential for complementarities with the internal R&D function. We suggest three
specific indicators for specialized processes.
First, a firm’s internal R&D intensity represents the relative importance given to R&D by
top management. Firms that spend heavily on R&D will by-and-large create a larger number of
R&D outputs and consequently, to avoid duplication, a wider range of outputs, implying that
such firms have a more complex and more specialized R&D process. Firms may choose to invest
more in R&D to provide them with opportunities for differentiation (Porter, 1985).
Differentiation can be enhanced by drawing on diverse supplies, not just in the home country but
around the world. Offshore R&D outsourcing could be a complementary mechanism to the
finding in the literature that certain types of firm and industry actively seek to locate parts of
their internal innovation value chain abroad (Cantwell and Mudambi, 2005; Frost, 2001).
Alternatively, R&D intensity can be viewed as an indicator of absorptive capacity (Cohen
and Levinthal, 1990). We argue that absorptive capacity is needed to use the complementary
capabilities accessed through offshore R&D outsourcing; if firms undertake much internal R&D
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they can better absorb complementary capabilities accessed externally. We see R&D intensity as
the first indicator of specialization of the firm’s internal R&D process, and argue that it is more
strongly associated with offshore than domestic outsourcing of R&D.
Hypothesis 1: The internal R&D intensity of a firm positively influences its choice to use
offshore, rather than domestic, R&D outsourcing.
A second indicator can be found in the use of affiliate R&D sourcing. Businesses that are part of
a larger corporation may use other businesses within the corporation for some of their R&D
needs, as an alternative to internal or outsourced R&D. In the international business literature,
affiliate sourcing has typically been conceived as a transfer pricing issue (Buckley and Pearce,
1979); but we argue here that affiliates may also be employed because they engage in other lines
of business in the same geography, or in the same line of business in another geography. On that
basis, an affiliate can deliver different inputs to the firm’s innovation process. Research in
innovation (Cassiman and Veugelers, 2006), has suggested the presence of complementarities
between internal and external R&D activities; similarly, we suggest that R&D activities sourced
from affiliates may display complementarities with R&D that is outsourced offshore. The use of
affiliate sourcing thus becomes another indicator of a complex and specialized R&D process and
we expect it to be predictive of the use of offshore, rather than domestic, outsourcing of R&D.
Hypothesis 2: The affiliate R&D sourcing intensity of a firm positively influences its
choice to use offshore, rather than domestic, R&D outsourcing.
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As a third indicator, basic R&D is fundamentally different from applied, market-facing R&D. In
the simplest terms, basic R&D contains more research while applied R&D contains more
development. Like internal R&D intensity, basic R&D has been seen as an indicator of
absorptive capacity, more fundamental to scientific progress, and less important to commercial
success. UNCTAD (2005) has described basic research as advancing scientific knowledge
without an immediate commercial objective. So basic research contributes to a firm’s research
capabilities and absorptive capacity. By contrast, applied research aims at gaining new
knowledge to meet a specific and recognized need, while development uses knowledge from
research in the production of new materials, devices, or methods.
To bring products to market, all technology-intensive firms need to engage in some level
of applied R&D—but only a minority are involved in basic R&D. Basic R&D uses scientists
more than engineers and the scientific community is global. It is therefore concentrated in a few
global centers of excellence, where it is supported by the appropriate research infrastructure, like
universities and government subsidies. By contrast, the applied R&D function is often charged
with inducing more local product content and can be found in most localities. As a consequence,
basic R&D tends to be more specialized and complex, and so should be positively associated
with firms’ choices to use offshore, rather than domestic, R&D outsourcing.
Hypothesis 3: The share of basic R&D in a firm’s total R&D positively influences its
choice to use offshore, rather than domestic, R&D outsourcing.
Foreign involvement
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Context is another key factor determining the extent to which firms source complementary
capabilities through offshore R&D. In particular, a firm’s existing international involvement
allows it better access to and assessment of a range of foreign suppliers. As we saw earlier,
international business typically involves higher transaction costs. More specifically, in the case
of R&D outsourcing the costs of partner search and evaluation abroad are typically higher
(Rangan, 2000). However, when a firm has existing international experience and networks,
which have perhaps evolved through links with other parts of the corporation, it can lower these
costs thanks to two distinct mechanisms. First, existing foreign involvement enables a firm to get
to know possible suppliers. This might be because they are its customers, are recommended (or
enforced) by its customers, or are located near them. Second, existing foreign involvement
reduces the negative impact of cross-country barriers and the liability of foreignness, created by
cultural or institutional differences. The dual use of contacts and experience explains why inward
and outward internationalization are positively correlated (Welch and Luostarinen, 1993),
suggesting more outward internationalization is associated with higher levels of offshore R&D
outsourcing.
Firms are typically short-sighted in their search for network partners (Rangan, 2000),
preferring domestic partners over foreign ones; and the same appears to be true for outsourcing
partners (see Cusmano, Mancusi, and Morrison, 2010; Mol et al., 2005). This is symptomatic of
how such searches take place, as firms demonstrate a strong preference for socially embedded
relationships (Uzzi, 1997). Embeddedness is often lost when crossing borders, as firms encounter
different cultural and institutional settings. But firms with prior network ties abroad, or with prior
experience of operating abroad, may have established some level of local embeddedness in other
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countries, which they can exploit to reduce the costs of searching and evaluating R&D
outsourcing partners.
A simple, initial indicator of existing foreign involvement is whether the focal firm is
itself a subsidiary of a foreign multinational. This is a relatively clear-cut illustration of our
argument, because the focal firm will already rely at least to some extent, and perhaps quite
heavily, on outsourcing partners—it may be importing a set of relationships through its parent
firm. Since the parent firm likely operates subsidiaries in other countries, the focal firm may also
be able to draw on these subsidiaries’ networks in its search for suppliers.
By contrast, subsidiaries of foreign multinationals could be much more restricted in their
knowledge of local suppliers in the host country than local competitors. This means they will
make less use of domestic outsourcing; innovative overseas subsidiaries are known to draw a
substantial amount of their knowledge from elsewhere, including the parent company’s home
country (Criscuolo, Narula, and Verspagen, 2005; Frost, 2001). It is also likely that there will be
a limited amount of knowledge in certain industries in the host country; how limited clearly
depends on the country’s size and its level of technological sophistication. Foreign subsidiaries
can act as brokers between their host country and overseas systems of innovation by importing
relevant knowledge into the country from elsewhere. Therefore we argue that subsidiaries of
foreign multinationals are more likely to use offshore, rather than domestic, R&D outsourcing.
Hypothesis 4: Being a subsidiary of a foreign multinational positively influences a firm’s
choice to use offshore, rather than domestic, R&D outsourcing.
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A second indicator is involvement in international trade, which scholars have shown is
conducive to the bilateral exchange of technological and market information between countries.
Salomon and Jin (2008) find that firms learn by exporting, which enhances their efficiency.
Export intensity can therefore be expected to have a positive effect on the probability that a firm
will engage in innovation activities. But exporting firms will also encounter potential overseas
R&D suppliers through their export activities or, more indirectly, will encounter customers,
agents, competitors, and others who will lead them to potential R&D outsourcing suppliers
abroad. Therefore we argue that export intensity is another positive predictor of the choice to use
offshore, rather than domestic, R&D outsourcing.
Hypothesis 5: The export intensity of a firm positively influences its choice to use
offshore, rather than domestic, R&D outsourcing.
Innovation performance
Older literature in economics and strategy stressed the disadvantages of outsourcing R&D
(Stigler, 1951; Porter, 1980). These authors appeared primarily to consider domestic outsourcing.
Internal R&D can help a firm create scale advantages, because it increases firm size; scope
advantages, since the firm may combine its R&D function with other functions, such as
production and marketing; and barriers to entry—the need to do R&D increases cost levels for
new entrants into the industry (Stigler, 1951; Porter, 1980). Internal R&D could also enable a
firm to create distinct product offerings as part of differentiation strategies, or process
innovations, which help firms that operate a cost-based strategy (Porter, 1985). By contrast, an
external supplier of R&D may provide competing firms with the same or very similar inputs. In
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Porter’s (1985) view, outsourced R&D activities may also be difficult to integrate with other
activities in the value chain because of the need to cross inter-organizational boundaries; this can
result in customers forming inconsistent perceptions of the firm’s product differentiation.
Consistency, it is argued, is paramount to the success of a differentiation strategy (Porter, 1985).
Various mechanisms may be at work here. The transaction cost literature (Williamson,
1985) argues that externalizing activities will entail very high transaction costs if they are highly
asset-specific, face much uncertainty, and are difficult to measure—even more so if these
conditions occur simultaneously. All three effects are present in R&D. The assets required for
R&D, such as scientists, laboratories, and scientific equipment, are not only costly but also tend
to have limited value if employed in alternative settings. R&D is typically uncertain, because if
outcomes are predictable there is no need to innovate. And work of scientists is hard to measure.
This suggests R&D is not a natural candidate for externalization. Where R&D is outsourced,
opportunism is a real possibility and the costs of monitoring outside suppliers may be high.
The use of external R&D may also create so-called disruption costs (Puranam and
Srikanth, 2007), because external inputs are harder to integrate. Puranam and Srikanth (2007)
demonstrated such disruption costs in the case of mergers and acquisitions. We would expect a
firm to have difficulty integrating the outputs provided by external suppliers into its innovation
processes, given the difficulties of coordinating efforts across organizational borders (Kogut and
Zander, 1992). In addition, because external suppliers are more easily substitutable, there is a
greater likelihood that firms will switch outsourcing suppliers over time, further increasing
disruption costs. According to this older literature, externalizing R&D is a second-best option
that firms take up only if they fail to engage successfully in internal R&D. So if a firm
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outsources R&D activities domestically, it does so because it lacks the internal capabilities to
undertake R&D activities, not because it prefers outsourcing to internalization.
But recently an alternative view has arisen, which suggests that using a significant
amount of external R&D may actually be a good thing (Chesbrough, 2003). The key argument of
this open innovation literature is that external partners may have knowledge that is unavailable
internally, and that it is cheaper to obtain that knowledge through cooperative relationships rather
than by acquiring the knowledge source. Procter and Gamble’s well-known Connect+Develop
initiative is a key example. There is anecdotal evidence that firms use open and external
innovation more frequently, for instance in software development, and Mol (2005) showed that
R&D-intensive industries are increasingly reverting to outsourcing, which might suggest that
outsourcing could help with innovation outcomes, even in those industries.
Weighing these two alternatives, we argue in favor of the first, that externalizing R&D
may undermine innovation. At present, most firms have only limited experience with open
innovation and as a consequence may not be very good at integrating external R&D successfully.
In the initial stages of outsourcing, decisions are driven more by costs than by benefits such as
new capabilities (Bettis, Bradley and Hamel, 1992). Unlike other forms of outsourcing, R&D
outsourcing is still in the early stages of development. And we are primarily interested in the
likelihood of innovating. By contrast, open innovation is often used not to increase the chances
innovating but to lower its costs, that is, to create a more efficient innovation process.
Hypothesis 6a: Domestic R&D outsourcing reduces a firm’s product innovation
performance.
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Hypothesis 6b: Domestic R&D outsourcing reduces a firm’s process innovation
performance.
We also argue, however, that the use of offshore R&D suppliers may differ from the use of
domestic suppliers in important ways. The international management literature identifies various
motives for internationalization, including resource, market, efficiency, and strategic asset or
capability seeking (Dunning, 1993). The quest for knowledge through internationalization is a
subcategory of the latter. The literature produces two fundamental insights about how offshore
R&D outsourcing could be more beneficial than domestic outsourcing. One, as suggested earlier,
is that, all other things being equal firms prefer a domestic supplier to a foreign one, because of
the difficulties and costs involved in finding, evaluating and dealing with foreign trading partners
(Rangan, 2000). Another is that by including foreign sources in their search for knowledge, firms
increase their potential knowledge pool significantly.
The global sourcing literature has provided evidence of a trade-off between lower
production costs (or, as per Zajac and Olsen, 1993, a higher transaction value) and higher
transaction costs (Mol, van Tulder and Beije, 2005). Many firms lack the will and/or the
managerial capabilities to outsource abroad. To make the argument in another way: the use of
independent suppliers abroad is a choice that firms understand they are making at some cost. The
costliness of offshore outsourcing is demonstrated, for instance, by the finding that retailers use
offshore outsourcing for private brands but not for manufacturer brands, because offshore
outsourcing undermines brand specificity (Chen, 2009). A firm must believe that the choice to
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outsource abroad provides a positive pay-off, through the ability to access foreign R&D suppliers
that have something specific or even unique to contribute to the firm’s innovation process.
According to Quinn and Hilmer (1994), part of the attraction of outsourcing is the ability
to access world-leading suppliers, regardless of their location. Firms that restrict themselves to
home-based suppliers miss out on the large knowledge pool abroad. National innovation systems
help to shape firm capabilities and resources. As a consequence, resources are more
homogeneous within a country and more heterogeneous across countries; the global supply base
therefore provides more opportunities for innovation. Breadth of knowledge sources is known to
have positive effects on innovation outcomes (Katila and Ahuja, 2002). Rosenkopf and
colleagues (Rosenkopf and Nerkar, 2001; Rosenkopf and Almeida, 2003) suggest that by
building up experience in accessing foreign sources, firms may overcome some of the problems
associated with transferring knowledge across geographical borders. Finally, offshore
outsourcing provides firms with flexibility, allowing easy switching between suppliers and
countries and lower commitment to specific technologies. This adds to the firm’s ability to
develop further its core competences, specifically its internal R&D strengths.
Overall, therefore, while we argue that domestic outsourcing of R&D is more likely to be
undertaken by firms lacking capabilities, we also argue that the use of foreign suppliers of
outsourced R&D is a positive choice driven by the desire to access specialized and highly
productive capabilities that only exist elsewhere. As a consequence, this choice ought to have a
positive effect on innovation outcomes.
Hypothesis 7a: Offshore R&D outsourcing increases a firm’s product innovation
performance.
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Hypothesis 7b: Offshore R&D outsourcing increases a firm’s process innovation
performance.
DATA AND METHODS
Sample
In our paper we use two large databases on firms operating in France. First, we apply the R&D
enquiry (Enquête Recherche et Développement) carried out by the Ministry of Higher Education
and Research (Ministère de l’Enseignement supérieur et de la Recherche, MESR). This
confidential business-level survey includes a sample of representative R&D-intensive firms
resident in France. All reported firms have some internal R&D activity, which means that R&D
outsourcing is an option for them. The MESR enquiry provides rich details on firms’ internal and
external innovation activities. Dependent variables are measured for the period 1999–2004. The
number of firms included in the survey varies between approximately 3000 and 3500 firms a
year, representing a 40–50% response rate, although there are big differences between the sets of
firms sampled in different years, that is, the data panel is unbalanced. This R&D dataset has
previously been exploited in some economics papers (e.g., Blanchard, Huiban, and Sevestre,
2006; François, Favre, and Negassi, 2002). We supplement the innovation dataset by matching it
with the EAE (Enquête Annuelle d’Entreprises) database. The EAE is collected by the Ministry
of Industry (Service des Etudes et des Statistiques Industrielles, SESSI) and contains annual data
on the balance sheet and income statement of manufacturing, retailing, and services firms with
more than 20 employees located in France. France is a large country with technological strengths
in some industries, but relative weakness in others.
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By combining these sources, we obtain a database that provides different options from
most existing academic research on outsourcing and innovation. In particular, longitudinal data
allow us to lag the independent variables, alleviate concerns over reverse causality, and do
greater justice to the non-immediate impact of outsourcing decisions. Scholars who have raised
concerns about the possible negative impact of outsourcing on firm innovativeness (e.g. Kotabe,
1998; Nooteboom, 1999) suggest that such effects are typically long-term in nature. Thus it
makes sense to study decisions over a longer period of time and lag effects. Few sources contain
reliable measures for both innovation and R&D outsourcing, particularly across borders. The
Europe-wide Community Innovation Survey, for instance, contains measures of innovativeness
and R&D outsourcing but does not distinguish between domestic and offshore outsourcing.
Given the timing of the data, a number of important observations must be made. First, the
geographic location of foreign R&D suppliers is not identified. However, it is unlikely that many
firms in this sample had engaged in the relatively recent phenomenon of outsourcing R&D to
low-cost countries like India and China. The subsidiaries of foreign firms in the sample are
overwhelmingly from OECD countries. Foreign subsidiaries tend to rely quite heavily on
knowledge sources in their home country or region (Criscuolo et al., 2005). By contrast, most
foreign R&D supply sources are found in established locations in Western Europe, North
America, and Japan, which strengthens the suspicion that offshore R&D outsourcing was
undertaken to improve innovation outcomes rather than to lower the costs of innovating.
Second, monetary variables are expressed in thousands of French francs and are deflated
using 1995 prices as a benchmark, to rule out effects due to price inflation. Third, R&D
outsourcing increased in this sample during 1999–2004, when compared to 1993–1998. This
confirms the trend that R&D outsourcing is becoming more prevalent. Moreover, the foreign
20
component increased more rapidly than the domestic component and accounts for most of the
growth in non-internal R&D. Fourth, as demonstrated below, outsourced R&D was still a minor
phenomenon compared to internal R&D. This suggests that true open innovation, in the sense of
external sources being critical to innovation, was the exception rather than the rule.
Measures
Dependent variables
This study investigates both the antecedents and innovation effects of R&D outsourcing. To
measure Offshore R&D outsourcing propensity, the dependent variable for hypotheses 1–5, we
divide spending on all of a firm’s international R&D transactions with independent suppliers
(i.e., offshore R&D outsourcing deals) by all spending (i.e., domestic and offshore outsourcing
of R&D). This variable takes on values between zero, when all outsourcing occurs in France, and
1, when all outsourcing takes place abroad. Note that the analysis on this measure is restricted to
firms that undertake R&D outsourcing, as hypotheses 1–5 focus on a firm’s choices in terms of
domestic or offshore outsourcing. Note also that many firms do not outsource any R&D offshore.
We use more than one measure for innovation performance. This not only ensures
broader applicability of the findings, but also improves their reliability. We look at both product
and process innovation, in the belief that both could potentially be affected by decisions to
outsource R&D (at home or abroad), and since both matter to the long-term competitive
advantage of firms. Over the long run, firms that create innovative products and processes can
compete more effectively in the marketplace. Innovative products, such as those brought out by
Apple in recent years, are required to grab and maintain customers’ attention. Innovative
21
processes, on the other hand, help firms minimize their use of scarce resources, as Toyota has
shown over many years. In the earlier stages of an industry’s life cycle, product innovation may
be more important, while process innovation comes to the fore as an industry matures.
Product innovation is constructed as a dummy variable taking a value of 1 if a firm
successfully created at least one product innovation in a given year and zero otherwise. The
survey asks ―Has the firm innovated in terms of its products thanks to its R&D during this year?‖
Product innovation could consist of improving existing products or introducing new products to
the market. The process innovation variable is constructed in the same way. In the survey
process is defined as the way in which the firm produces its goods. The MESR R&D enquiry
does not report either variable before 1999. Therefore, our effective analysis covers the 1999–
2004 time period (and 1997–2002 for the independent variables, given the time lag).
Independent variables
Internal R&D is calculated as in-house R&D spending divided by total sales (to avoid
multicollinearity with firm size). As stated in hypothesis 1, this should positively influence the
choice to use offshore, rather than domestic, outsourcing. Presumably, the more R&D intensive
the firm is, the more likely it is to generate innovations, since it undertakes more attempts at
innovating. The database also provides information on the sourcing of R&D from other affiliates
in the corporation, in France and abroad. We calculate Affiliate R&D Sourcing by dividing all
R&D procurement from other units of the corporation by total sales. Hypothesis 2 states the
proposed effect of affiliate outsourcing on the propensity to outsource R&D offshore, but it is
less clear that this measure should have a positive effect on the likelihood of innovation. On the
one hand, firms may benefit from technological knowledge that exists elsewhere in the
22
corporation. On the other, they may be instructed by corporate headquarters to use captive
suppliers, for political or other internal reasons, and these captive suppliers may be less effective.
Basic Research is a ratio variable calculated as internal spending on basic research divided by all
internal research spending (basic and applied). The variable Export Intensity was measured by
the ratio of exported to total sales. The variable Foreign Affiliate is a dummy variable with value
1 for firms that have a foreign parent company and zero otherwise.
The variable of interest in hypothesis 6 is Domestic R&D Outsourcing and represents all
spending on a firm’s international R&D transactions with independent suppliers divided by total
sales. Likewise, Offshore R&D Outsourcing (hypothesis 7) represents all spending on a firm’s
R&D transactions with independent suppliers within France divided by total sales.
Control variables
In addition we add control variables relating to the firm, its industry, and time. We first account
for non-technological determinants of R&D performance. Firm Size is measured by the
logarithm of the number of employees. It takes into account potential economies of scale and
scope in the production of goods and R&D output. It may also proxy resources owned by the
firm. Thus we expect larger firms to be more innovative. Return on Sales is calculated by
dividing net profits by sales and is included to control for whether more profitable firms are more
innovative. The variable Labor Productivity, calculated as the sales level per employee, is
introduced to assess whether more productive firms have a higher likelihood of innovating.
In addition to non-technological determinants, we control for the mode of financing the
R&D budget (External Financing), that is, the share of the R&D budget that is financed by
external partners. R&D expenditure can be financed by internal funds or external partners. The
23
latter could be parent companies or independent private firms and public institutes. External
financing could then consist of public subsidies or financial transfers without compensation from
the parent company. It could also take the form of contracts and delegation of research projects.
By including this variable we want to ensure that subsidies provided by the European Union, for
example, are not a main cause of positive or negative innovation outcomes. R&D Salary,
calculated as total R&D wages divided by the number of employees, may indicate a greater
dedication to innovation and be a proxy for R&D employees’ skill. The final firm-level control
variable, Capital Intensity R&D, is calculated by dividing a firm’s internal R&D capital
expenditure by its sales. It may affect a firm’s innovation outcomes positively in the long term.
At the industry level we use the Herfindahl-Hirschman industry concentration index. The
time-varying variable Industry Concentration is equal to the sum of the squares of firms’ market
shares in a given sector at the four-digit level. When competition is strong, firms have more
incentives to pursue innovation, aiming to enhance their efficiency and upgrade capabilities. On
the other hand, the Schumpeterian perspective argues that monopoly rents favor innovation.
Finally, we introduce two-digit level sector and year dummies in all estimations to control for
unobserved heterogeneity. Industry fixed effects consider permanent unobserved differences
across industries and reflect industry characteristics influencing innovation, like technological
opportunities or spillovers. Such differences and characteristics will have a clear impact, for
example, on R&D intensity levels and the amount of basic R&D taking place in the industry.
Time dummies account for external shocks affecting innovation levels across the economy.3
3
We also considered the number of patents registered at the European patent office as a proxy of past innovation
success and R&D inputs. This variable is available from 1998 only. Since including it does not change our findings,
yet substantially reduces the number of observations, we do not show those results.
24
All independent and control variables are lagged one year for the analyses predicting the
propensity to outsource R&D offshore and two years for the analyses predicting product and
process innovation. As argued above, the impact of R&D inputs—sourced internally, from
affiliates, or externally—on innovation outcomes takes time. Likewise, outsourcing decisions
may be informed by historical rather than current conditions, although here we might expect a
shorter time lag, since managers may respond to changes more quickly (firms cannot ―decide to
innovate‖; they can only attempt to do so). Our main findings turn out not to be very sensitive to
the time window. For instance, lagging variables three years does not affect our conclusions.
Table 1 shows the distribution of firms across industries using the French NAF codes
(similar to SIC / NACE). There is a reasonable spread across industries (with no single industry
dominating) but as we might expect, given the focus on firms undertaking at least some R&D
internally, the distribution is skewed toward certain parts of the manufacturing sector.
-------------------------------Insert table 1 around here
--------------------------------
FINDINGS
Table 2 includes the means and standard deviations of the variables, as well as bivariate
correlations. It is worth noting that firms that outsource domestically are also more likely to
outsource abroad, although the correlation is not so strong as to produce multicollinearity
concerns. Firms that invest more in internal R&D spend more on R&D outsourcing, especially
domestic outsourcing. This clearly indicates that some firms are simply more R&D intensive
25
than others because of what they produce, or because they attempt to innovate more than their
competitors, and this R&D intensity cuts across organizational boundaries.
-------------------------------Insert table 2 around here
-------------------------------The analyses in Table 3 investigate the antecedents of offshore and domestic outsourcing
of R&D. The table contains three Tobit models predicting the ratio between offshore and total
R&D outsourcing. A Tobit model is most appropriate because the dependent variable is not only
double bounded (between zero and one), but also contains many observations at the lower limit
(firms that outsource at home but not abroad) and some at the upper limit (firms that outsource
abroad but not at home). Model 3, the most complete model, suggests that a range of factors
helps predict the dependent variable. In line with our predictions, firms are likely to outsource
abroad more if they invest more in internal R&D (hypothesis 1) and if they source more from
affiliates (hypothesis 2); and are marginally more likely to do so if basic R&D plays a larger part
in their efforts (hypothesis 3). This attests to the importance of the nature of the firm’s R&D
process when a firm makes choices about where to outsource. We also find that a firm’s existing
international involvement increases the likelihood of locating outsourcing abroad, either through
foreign affiliates (hypothesis 4) or being export intensive (hypothesis 5).
-------------------------------Insert table 3 around here
-------------------------------Next, we turn our attention to the innovation effects of R&D outsourcing. Hypotheses 6
and 7 relate offshore and domestic outsourcing of R&D to innovation outcomes. Given the
dichotomous nature of the dependent variables, a Probit or Logit analysis is appropriate here.
26
Based on our pooled cross-section data, which capture innovation, we employ a Probit model
with robust standard errors to analyze the determinants of product innovation and the specific
role of R&D externalization.4,
5
Recent research has stressed the importance of investigating
marginal effects when undertaking analyses on limited dependent variables (Wiersema and
Bowen, 2009). So we present both the normal effects, in the odd columns, and the marginal
effects, in the even columns. As can be observed from this table, there are no substantive
differences for any variable in either direction or level of significance between these analyses.
Thus we simply refer to the results.
Turning first to Table 4, we present analyses for product innovation as the dependent
variable. Models 4 and 6 exclude the independent variables accounting for domestic and offshore
R&D outsourcing. Where we do include them, other variables seem to have a broadly similar
effect. Model 7 is the most complete model and shows support for both hypotheses 6a—
domestic outsourcing of R&D has a negative effect on product innovation—and 7a—offshore
outsourcing has a positive one. As expected, internal R&D intensity, firm size, prior profitability,
and export intensity all have a positive effect on the likelihood of product innovation, while
industry concentration has a negative effect. More intriguing is the negative effect for R&D
sourcing from affiliates.
-------------------------------Insert table 4 around here
-------------------------------4
The choice is effectively one of convenience but if we use a Logit analysis instead of Probit, there is no substantive
change in the findings.
5
We also tested whether the pooling of multiple observations of the same firm has an effect, through the cluster
subcommand, but our findings remain the same.
27
Table 5 repeats these procedures but with process innovation as the dependent variable.
Domestic outsourcing is shown to have a negative effect on the likelihood of successfully
innovating processes, confirming hypothesis 6b, but not hypothesis 7b, which predicts a positive
effect associated with offshore outsourcing. Although the sign of this variable is positive, it is
non-significant. We address this in more detail below. Among the control variables, the pattern is
largely the same as for product innovation: internal R&D intensity, firm size, export intensity,
and prior profitability all act as positive predictors, while sourcing from affiliates is a negative
predictor. No significant effect was obtained for industry concentration, however.
-------------------------------Insert table 5 around here
-------------------------------The results are very robust to a range of different model specifications and econometric
techniques. For instance, if we include additional variables or exclude variables from the model,
we still find that domestic outsourcing has a negative impact on innovation outcomes while
offshore outsourcing has a positive impact, although the number of observations decreases with
the introduction of further variables. If we use panel data analysis, we still obtain the same
findings. We do not present these analyses here because for an overwhelming majority of firms
we do not have data for all relevant years, which produces a very unbalanced panel.
One possible concern with this type of analysis is endogeneity (Bascle, 2008). More
particularly, it may be that firms simultaneously choose their offshore outsourcing levels and
desired innovation outcomes. To try and tackle this, we searched for an instrumental variable that
influences domestic or offshore outsourcing but not innovation. We looked at firm nationality.
But unfortunately, given that around 75% of the firms in the sample are French, there was not
28
enough variance. We then looked at variables related to the institutional environment,
particularly the weighted exchange rate of the French franc. But since this variable is only time,
not firm, variant, it was not useful. We do believe, however, that the lagging of variables by two
years, as applied in the empirical analysis, helps to alleviate endogeneity concerns.
DISCUSSION
The findings confirmed hypotheses about the antecedents of the choice between offshore and
domestic R&D outsourcing. This supports our framework, which suggested that firms are more
likely to choose offshore outsourcing when they have a) a more specialized R&D process, and b)
previous international involvement, which can be used to search and evaluate external sources
located abroad. We argued that while international outsourcing incurs higher firm governance
costs, it also produces complementary capabilities (Lorenzoni and Lipparini, 1999) that likely
enhance the firm’s internal R&D function.
The results also confirmed hypothesis 6 and partially confirmed hypothesis 7. This is
interesting, because of their contradictory nature. It appears that firms revert to outsourcing at
home for defensive purposes, either to save costs or because their own internal R&D is somehow
deficient. By contrast, when firms decide to source from independent suppliers located abroad,
they may do so to tap specialist sources of knowledge that complement and strengthen their own
internal R&D. So the choice to use independent foreign suppliers is a positive one, consistent
with arguments in international management (Doz, Santos and Williamson, 2001; Dunning,
1993) that international knowledge-seeking strategies can deliver innovation advantages. The
29
findings are consistent with the idea that some outsourcing decisions have positive innovation
performance effects but others lead to negative outcomes (Grimpe and Kaiser, 2010).
But the analyses did not confirm hypothesis 7b, linking offshore outsourcing to process
innovation, which is puzzling. As a post-hoc analysis we therefore tested whether the effect of
offshore outsourcing differed significantly between the product and process innovation
equations, which turned out to be the case (and for domestic outsourcing as well). This indicates
that offshore outsourcing has a lesser effect on product innovation than it has on process
innovation. What, conceptually, could help us explain this difference? Process innovation is
typically more specific to the firm than product innovation and requires more organizational and
local adaptation; that is, process innovation is more embedded than product innovation. So it
typically requires more changes in organizational routines, which are by definition specific to the
context of the organization (Nelson and Winter, 1982). This makes it harder to integrate external
R&D into process innovation efforts and the disruption costs associated with outsourcing could
have a more negative impact. This could be especially true for offshore outsourcing, where firms
effectively face a double translation exercise, having both to translate foreign inputs into inputs
that can be used in France, and inputs from an external supplier into inputs that can be adapted
for use inside the firm. The complexities associated with such a double translation exercise might
be such that the advantages of offshore outsourcing we initially hypothesized do not hold true for
a more firm- and location-specific form of innovation, like process innovation.
IMPLICATIONS
30
This paper has implications for academic research, which has not yet investigated the
phenomenon of R&D outsourcing much (Martinez Noya et al., 2010), let alone predict its
innovation consequences. It contributes to a growing body of knowledge around outsourcing and
contains important additions. First, we look not only at sourcing from independent suppliers, but
also include affiliate R&D sourcing. Sourcing from affiliates may substitute for external sourcing
and controlling for it makes our findings more credible. Second, unlike most work in the area,
we explore the international dimension of R&D outsourcing, comparing it to domestic R&D
outsourcing, and conclude it has different drivers. In addition, most empirical work on
outsourcing focuses on its determinants rather than its effects. This study goes beyond this and
shows that offshore and domestic R&D outsourcing may produce different innovation outcomes.
Third, our analysis includes a time lag, which is appropriate given the non-immediate impact of
outsourcing decisions on innovation. Fourth, we look at both product and process innovation
outcomes since firms will differ in their pursuit of and preferences for innovation. It also shows
that the findings presented here, especially the differential impacts of domestic and offshore
R&D outsourcing, are robust and applicable to innovation broadly.
In terms of the study of capabilities (Helfat et al., 2007), the paper contributes by
pointing at the role of geography in producing different types of capability when it comes to an
advanced activity such as R&D. We found broad evidence for the presupposition that domestic
outsourcing of R&D helps firms to access more generic substitute capabilities, while offshore
outsourcing provides access to specific complementary capabilities. It is interesting to note the
negative effect of affiliate sourcing on product and process innovation outcomes, which suggests
the corporate system may not be a very rich source of inputs for the innovation process.
31
For practitioners we can highlight the pitfalls of sourcing R&D externally, but also
suggest that there are some potential payoffs for those firms willing to go through the trouble of
finding highly qualified foreign suppliers. What questions can be asked beyond those we have
tried to answer here? One specific area of further inquiry is to develop an understanding of what
factors might help firms to use outsourcing more effectively. For instance, are there differences
in absorptive capacity that lead to some firms having more capabilities than others in terms of
integrating external R&D into the internal production of innovations? And even if there are such
differences, do they apply equally to domestic and offshore outsourcing? The outsourcing
literature has addressed how firms that outsource can benefit from having some internal
involvement (Brusoni, Prencipe, and Pavitt, 2001). Absorptive capacity has received much
attention but has not been specifically applied to outsourcing. More broadly still, do firms have a
capability to outsource R&D and can that capability be developed and nurtured over time?
Related to our finding that offshore outsourcing of R&D produces positive results, it
would be useful to gain a more in-depth understanding of what drives this finding. Is it the case
that firms that outsource abroad use previously established internal facilities or outsourcing
networks in those foreign countries? And what is the role of foreign subsidiaries in this process?
The literature on foreign subsidiaries suggests some firms follow proactive strategies in dealing
with other parts of the internal network and benefit from such strategies.
Various limitations apply. First, as is always the case, the sample is temporally and
geographically specific. Firms in France during the time frame analyzed here were generally in
the early stages of using external sources, especially abroad, for procuring R&D. In the
meantime, firms in France and beyond have increased their use of (offshore) external R&D
sources. This implies not only that the likelihood of finding a firm that uses (offshore) external
32
sources would be higher today than it is in our sample but also that the use of external sources in
the sample, at home and even more so abroad, may have been somewhat immature. This could
imply that firms in our study period were less good at managing external R&D suppliers than
they are now. This suggests our findings may somewhat understate the true (positive) effect of
sourcing from external suppliers. As we noted above, no specific data were available on supplier
locations. Clearly it matters whether they are located in the United States—where they are
probably used for specific innovation inputs—or India—where they are most likely used for cost
reasons. As argued above, in all likelihood there was relatively little R&D outsourcing from nonOECD countries in our sample. At the same time, this suggests the positive effect could
disappear. Finally, we would have liked to include additional variables but were limited by the
data available. On the positive side, this database includes many firms and is longitudinal in
nature, which helps to reduce problems of reverse causality. And it contains hard outsourcing
and innovation measures, which helps to prevent the problem of common method bias.
Future research could take a number of directions. One may be the use of qualitative
methods to uncover why firms do not engage in offshore R&D outsourcing if it is as beneficial
as suggested here. Do firms face any particular obstacles when attempting to outsource abroad?
Are these obstacles related to cultural, language, or other institutional differences, which are
difficult to clear? Or are these firms unaware of the innovation benefits of offshore outsourcing?
Foreign firms in the sample are more likely to outsource abroad, which suggests the network
effects discussed earlier are quite strong.
Another direction is to investigate how domestic and offshore R&D outsourcing affects
other performance measures, such as the costs or return on investment of innovation. While our
focus has been on the likelihood of innovating, firms face choices about how much to invest in
33
order to achieve those outcomes. As argued above, the notion of open innovation is at least partly
built around lowering the costs of innovating. Domestic outsourcing, and increasingly offshore
outsourcing, could be used to lower these costs.
CONCLUSION
In this paper we studied the differences between decisions to source R&D from independent
suppliers within or outside the focal country. We focused particularly on what helps explain such
differences and on how domestic and offshore R&D outsourcing may impact product and
process innovation outcomes differentially. The findings, based on a large sample of businesses
in France during the period 1999–2004, indicate that offshore R&D outsourcing is more likely in
firms that have a highly specialized R&D process existing international involvement. They also
suggest that the use of domestic suppliers can have a substantial negative effect on product and
process innovation outcomes; but using foreign suppliers can have a positive effect on product
innovation outcomes. We then questioned what makes some firms better than others at
outsourcing R&D, and what through what process outsourcing affects innovation. Since R&D
outsourcing, especially offshore, is a relatively small yet rapidly growing phenomenon, it is of
great interest to academics and practitioners alike to understand how it is developing.
34
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41
Table 1 Industry classification
NAF
Code
Industry
Share in
sample
1-14
Agriculture, extraction, mining
0.6
15-22
Tobacco, food, clothing, wood, paper production
4.1
23
Coking, refinery, and nuclear industries
1
24
Chemicals, including pharmaceuticals
20.5
25-26
Rubber, plastic and other mineral (non-metallic)
10.5
27-28
Metallurgy and metal works
7.7
29
Production of machinery and equipment
17.5
30-31
Production of computer, office, electric equipment
10
32-33
12.7
34-37
Production of radio, tv, communication equipment; medical, optical and clock (watch)
instruments
Transportation equipment and others
40-45
Utilities and construction
0.6
46-99
Services
5.2
9.6
42
Table 2 Summary Statistics and Correlation Matrix
Mean
S.D.
1
2
3
4
5
6
7
8
9
10
11
12
13
1
Internal R&D
.05
.06
1
2
Affiliate R&D
Sourcing
Foreign
Affiliate
Firm Size
.00
.01
.06
1
.28
.45
-.15
-.05
1
5.92
1.31
-.21
.10
.12
1
Export
Intensity
Return on
Sales
Industry
Concentration
Capital
Intensity R&D
External
Financing
Domestic R&D
Outsourcing
Offshore R&D
Outsourcing
Labor
Productivity
Basic
Research
R&D Salary
.40
.27
-.04
.01
.16
.09
1
.03
.12
-.05
.01
.02
-.03
.04
1
1012.6
1307.7
-.06
.02
-.09
.29
-.01
-.05
1
.11
.31
.06
-.01
.09
.03
.03
-.01
.00
1
.07
.17
.17
.04
-.01
.07
-.02
-.02
-.01
-.01
1
.00
.01
.31
.08
-.06
.03
-.05
-.02
.02
.03
.15
1
.00
.00
.10
.08
-.02
.03
.02
.04
-.02
.01
.03
.33
1
471.9
545.0
-.06
.06
.01
.10
-.02
.12
.11
.02
.01
.01
.02
1
.03
.10
.08
-.02
-.02
-.02
.03
-.02
.08
.01
-.02
.00
-.02
-.01
1
355.44
124.3
.07
.07
.04
.16
.10
.03
.08
-.02
.07
.07
.04
.10
.00
3
4
5
6
7
8
9
10
11
12
13
14
Monetary variables are expressed in French currency (000s of French francs). Source: Enquête Recherche et Développement,
French Ministry of Higher Education and Research (Ministère de l’Enseignement supérieur et de la Recherche, MESR);
Enquête Annuelle d'Entreprises (French Ministry of Industry (Service des Etudes et des Statistiques Industrielles, SESSI)
43
Table 3 Tobit analysis of ratio offshore R&D outsourcing / total R&D outsourcing
Model 1
0.85***
(0.22)
0.10***
(0.03)
0.22*
(0.12)
3.48***
(1.06)
0.29***
(0.05)
0.07***
(0.01)
0.00**
(0.00)
0.00
(0.00)
Model 2
0.85***
(0.22)
0.10***
(0.03)
0.22*
(0.12)
3.46***
(1.06)
0.29***
(0.05)
0.07***
(0.01)
0.00**
(0.00)
0.00
(0.00)
0.00
(0.00)
Constant
-0.97***
(0.09)
-0.97***
(0.09)
Model 3
0.88***
(0.22)
0.10***
(0.03)
0.22*
(0.12)
3.42***
(1.06)
0.29***
(0.05)
0.07***
(0.01)
0.00**
(0.00)
0.00
(0.00)
0.00
(0.00)
-0.12**
(0.06)
-0.96***
(0.09)
Log likelihood
-2373
-2373
-2370
Observations
4190
4190
4190
Internal R&D
Foreign Affiliate
Basic Research
Affiliate R&D Sourcing
Export Intensity
Firm Size
Labor Productivity
Industry Concentration
R&D Salary
Capital Intensity R&D
Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
All time-varying variables are lagged one year. All estimations include both year and industry dummies.
44
Table 4 Probit analysis of effects of offshore and domestic R&D outsourcing on product innovation (with marginal
effects)
Internal R&D
Affiliate
R&D Sourcing
Foreign Affiliate
Firm Size
Export Intensity
Return on Sales
Industry
Concentration
Model 4
ME
Model 5
ME
Model 6
ME
Model 7
ME
1.76***
0.56***
2.47***
0.78***
1.75***
0.51***
2.38***
0.70***
(0.57)
(0.18)
(0.61)
(0.19)
(0.64)
(0.19)
(0.69)
(0.20)
-9.60***
-3.04***
-9.14***
-2.88***
-9.09**
-2.67**
-8.80**
-2.58**
(2.61)
(0.83)
(2.56)
(0.81)
(3.59)
(1.05)
(3.56)
(1.04)
-0.08
-0.03
-0.09
-0.03
-0.09
-0.03
-0.10
-0.03
(0.06)
(0.02)
(0.06)
(0.02)
(0.07)
(0.02)
(0.07)
(0.02)
0.12***
0.04***
0.13***
0.04***
0.15***
0.04***
0.15***
0.04***
(0.02)
(0.01)
(0.02)
(0.01)
(0.02)
(0.01)
(0.02)
(0.01)
0.44***
0.14***
0.41***
0.13***
0.45***
0.13***
0.42***
0.12***
(0.10)
(0.03)
(0.10)
(0.03)
(0.11)
(0.03)
(0.11)
(0.03)
0.49**
0.16**
0.44**
0.14**
0.50**
0.15**
0.47**
0.14**
(0.20)
(0.06)
(0.20)
(0.06)
(0.22)
(0.06)
(0.22)
(0.06)
-7.03e05***
(2.08e-05)
-2.22e05***
(6.58e-06)
-7.02e05***
(2.08e-05)
-2.21e05***
(6.57e-06)
-8.51e05***
(2.34e-05)
-2.50e05***
(6.87e-06)
-8.44e05***
(2.34e-05)
-2.47e05***
(6.84e-06)
-9.08***
-2.87***
-8.89***
-2.61***
(2.04)
(0.64)
(2.35)
(0.69)
18.40***
5.80***
18.32**
5.37**
(6.50)
(2.05)
Domestic R&D
Outsourcing
Offshore R&D
Outsourcing
Capital
Intensity R&D
External
Financing
Constant
(7.56)
(2.22)
-0.10
-0.03
-0.10
-0.03
(0.10)
(0.03)
(0.10)
(0.03)
-0.26
-0.08
-0.21
-0.06
(0.17)
(0.05)
(0.17)
(0.05)
-0.368*
-0.481**
-0.44*
-0.54**
(0.196)
(0.199)
(0.23)
(0.23)
Log likelihood
-1681
-1671
-1293
-1287
Observations
3095
3095
3095
3095
2513
2513
2513
2513
Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
All time-varying variables are lagged two years. All estimations include both year and industry
dummies.
45
Table 5 Probit analysis of effects of offshore and domestic R&D outsourcing on process innovation (with marginal
effects)
Internal R&D
Affiliate R&D Sourcing
Foreign Affiliate
Firm Size
Export Intensity
Return on Sales
Industry Concentration
Model 8
ME
Model 9
ME
Model 10
ME
Model 11
ME
2.57***
0.97***
3.35***
1.26***
2.51***
0.92***
3.40***
1.25***
(0.53)
(0.20)
(0.57)
(0.22)
(0.60)
(0.22)
(0.66)
(0.24)
-9.62***
-3.63***
-8.77***
-3.30***
-9.07**
-3.33**
-8.09**
-2.97**
(2.84)
(1.07)
(2.72)
(1.03)
(3.64)
(1.34)
(3.56)
(1.31)
0.00
0.00
0.00
0.00
0.03
0.01
0.02
0.01
(0.05)
(0.02)
(0.05)
(0.02)
(0.06)
(0.02)
(0.06)
(0.02)
0.18***
0.07***
0.18***
0.07***
0.19***
0.07***
0.20***
0.07***
(0.02)
(0.01)
(0.02)
(0.01)
(0.02)
(0.01)
(0.02)
(0.01)
0.59***
0.22***
0.57***
0.22***
0.55***
0.20***
0.52***
0.19***
(0.09)
(0.04)
(0.09)
(0.04)
(0.10)
(0.04)
(0.10)
(0.04)
0.56***
0.21***
0.51**
0.19**
0.61***
0.22***
0.58***
0.21***
(0.20)
(0.07)
(0.20)
(0.08)
(0.21)
(0.08)
(0.22)
(0.08)
1.34e-05
5.05e-06
1.38e-05
5.18e-06
1.57e-05
5.77e-06
1.66e-05
6.09e-06
(2.06e-05)
(7.76e-06)
(2.06e-05)
(7.75e-06)
(2.32e-05)
(8.53e-06)
(2.33e-05)
(8.53e-06)
-9.56***
-3.60***
-11.35***
-4.16***
(2.29)
(0.87)
(2.89)
(1.06)
5.67
2.14
3.96
1.45
(4.71)
(1.77)
(6.83)
(2.51)
Domestic R&D Outsourcing
Offshore R&D Outsourcing
Capital Intensity R&D
External Financing
Constant
0.02
0.01
0.02
0.01
(0.10)
(0.04)
(0.10)
(0.04)
-0.22
-0.08
-0.15
-0.06
(0.16)
(0.06)
(0.16)
(0.06)
-0.985***
-1.103***
-0.98***
-1.12***
(0.185)
(0.188)
(0.21)
(0.22)
Log likelihood
-1936
-1925
-1547
-1536
Observations
3095
3095
3095
3095
2513
2513
2513
2513
Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
All time-varying variables are lagged two years. All estimations include both year and industry dummies.
46