Paper to be presented at the
35th DRUID Celebration Conference 2013, Barcelona, Spain, June 17-19
Resource co-specialization and supplier concentration in concurrent
sourcing
Mari Sako
University of Oxford
Said Business School
mari.sako@sbs.ox.ac.uk
George Chondrakis
University of Oxford
Said Business School
george.chondrakis@sbs.ox.ac.uk
Paul M. Vaaler
University of Minnesota
Carlson School of Management
vaal0001@umn.edu
Abstract
Although the preconditions for the simultaneous use of multiple sourcing modes have been explored, the question of
what determines how much to make and how much to buy in plural sourcing has been understudied. This study fills this
gap. Using longitudinal data of in-house lawyers at, and law firms used by, Fortune 500 firms, we find empirical evidence
that plural sourcing strategies are tilted in favor of ?make? whenever firms have opportunities for resource
co-specialization (notably between legal resources and R&D, marketing, and top management teams) and a broad
portfolio of suppliers that raises the cost of contracting. Our study suggests that plural sourcing research benefits from
examining a group of transactions within a corporate function, to complement the predominant focus on transaction-level
outcomes.
Jelcodes:M10,-
Resource Co-Specialization and Supplier Concentration in Plural Sourcing: Evidence
from Legal Services Sourcing at Fortune 500 Companies
INTRODUCTION
How do firms organize economic transactions? Since the seminal work on firm
boundaries by Coase (1937, 1988), scholars have addressed this question by identifying
multiple modes (i.e. make, buy, ally, etc.). Prior work in transaction cost economics (TCE)
analyzed the transactional characteristics that lead to choosing one of these modes (Poppo et
al., 1998; Walker et al., 1984; Williamson, 1985) while the resource-based view of the firm
(RBV) suggests that firm boundaries reflect differences in capabilities and knowledge
(Argyres, 1996; Jacobides et al., 2005; Kogut et al., 1996).
Both TCE and RBV employ a comparative analysis of sourcing modes, leading to the
choice of the most efficient institutional arrangement (i.e. market, hierarchy or hybrid) for
each transaction. However, prior research has documented the simultaneous use of multiple
sourcing modes by firms, calling this concurrent sourcing (Parmigiani, 2007; Parmigiani et
al., 2009), plural sourcing (Bradach, 1997; Gulati et al., 2006; Heide, 2003; Jacobides et al.,
2006), or taper integration (Harrigan, 1986; Rothaermel et al., 2006). In contrast to a TCE or
RBV logic, firms are often found to both make and buy the same input.
There is robust theory and evidence on the conditions under which plural sourcing is
likely to occur. For example, Parmigiani (2007) demonstrates that greater overlap between
the firm’s and the supplier’s expertise increases the likelihood of plural sourcing while
Parmigiani et al. (2009) explain that firms may make and buy sets of complementary
components. Performance uncertainty and information asymmetry between buyers and
suppliers (Dutta et al., 1995; Heide, 2003), technological volatility (Krzeminska et al.,
1
forthcoming), and complementarities in incentives or knowledge (Puranam et al.,
forthcoming) can also lead to plural sourcing.
While important in identifying the prevalence of plural sourcing, this research has
provided limited guidance on a logical follow-on question, that is, how to explain the mix of
internal and external sourcing (Parmigiani, 2007:306; Puranam et al., forthcoming).
Assuming that a firm does indeed both make and buy, why would it choose 80% make vs.
20% buy as opposed to 40% make vs. 60% buy? Thus, given the presence of preconditions
for plural sourcing, how do firms decide how much to make and how much to buy?
In addition, the literature does not explore the selection of suppliers and their impact
on the design of plural sourcing strategies. For example, if a firm decides to buy 40% for a
given product or service, this 40% could be outsourced to a single firm or multiple firms.
Existing theory assumes the decisions on the make-buy balance and supplier selection to be
independent of each other. This is despite the fact that behind the ‘façade of the market’ lies
another firm, with its own capabilities and contractual relationship with the focal firm
(Jacobides et al., 2005). To the extent that supplier selection influences the cost of
contracting, it would have an impact on the make-and-buy decision.
In this paper we build on recent progress in the area of plural sourcing and address
these two limitations. In doing so we identify two mechanisms that help better understand the
design and variability in plural sourcing strategies. First, resource co-specialization enhances
the benefits of internalization. By resource co-specialization we refer to the synergistic gains
that arise from the interaction of different resources within firm boundaries (Lippman et al.,
2003; Teece, 1986). When firms outsource part of production they essentially position certain
resources, e.g. personnel, equipment etc. outside of their boundaries. By doing so, they
forego opportunities to harvest synergies resulting from resource combinations that increase
their marginal productivity through on-going interaction, shared expertise, and knowledge
2
spillovers (Dierickx et al., 1989; Kogut et al., 1992; Milgrom et al., 1995). Consequently, in
cases of plural sourcing the extent of integration, or make, will increase when there are
opportunities for resource co-specialization with other firm resources.
Second, we highlight the impact of supplier concentration (Moeen et al., 2013) on the
relative importance of internal versus external suppliers in plural sourcing. Here we suggest
that the number of suppliers chosen to outsource to is not independent of the proportion that
is bought. A large number of suppliers leads, ceteris paribus, to high mundane transaction
costs and reduces the benefits from relational contracting (Baker et al., 2002; Langlois,
2006), resulting in the firm relying more heavily on make in plural sourcing. By contrast,
when firms use a small number of suppliers, they will benefit from relational contracting and
lower transaction costs and consequently buy more from their suppliers (Dyer, 1997; Moeen
et al., 2013).
We develop our arguments in the context of corporate legal services, a setting where
the use of both internal and external suppliers for the same input, known as multi-sourcing, is
common (Sako, 2011; Susskind, 2008). We demonstrate that resource co-specialization
drives the design of plural sourcing strategies as the balance tilts in favor of make when firms
rely more on R&D resources, advertising resources, international presence, and legal
expertise in their top management team. We also find that the extent of insourcing increases
when the firm sources from a large number of law firms. Although this result might sound
counterintuitive, it is explained by the endogenous impact of supplier concentration on the
costs of contracting.
This paper contributes to our understanding of plural sourcing by moving beyond the
recognition of the phenomenon to the identification of specific strategies that firms employ
and their antecedents. Moreover, this study is important in extending the inquiry on firm
boundaries to the domain of corporate functions. The vast majority of an admittedly
3
voluminous literature on vertical integration (or disintegration) has focused on primary
activities (Gibbons, 2005; Williamson, 1985), to the neglect of corporate functions providing
important support activities in the value chain (Porter, 1985). This paper highlights the
importance of investigating firm boundary-setting and the mix of make and buy activities
with a focus on value-adding professional and business services in corporate functions (Sako,
2013).
In the next section we review the relevant literature and explain why corporate legal
services provide an ideal setting to test our predictions. Then, we present in sequence our
hypotheses, data and methodology, and results. The final part offers a concluding discussion.
PLURAL SOURCING: THEORY & EVIDENCE
TCE and RBV are the two dominant theories employed to understand firm boundary
decisions. On the one hand, TCE explains the make-or-buy decision as a response to close
comparison of costs associated with each alternative (Williamson, 1985). Market-based buy
strategies tend to have lower costs and thus dominate comparable make strategies
emphasizing firm ownership of and hierarchical control over suppliers. But cost advantages
of buy over make strategies reverse themselves in exceptional circumstances where hazards
with market-based contracting are substantial. In contrast, RBV contends that the reason an
activity is conducted within the firm is not market failure but rather firm success: the firm as
an institution enjoys an ‘organizational advantage’ in organizing economic activity (Madhok,
2002:536). Thus, RBV explains firm boundary-setting based on competitive interest in
exploiting value from difficult to imitate resource bundles (Barney, 1986).
TCE and RBV differ on many dimensions but share assumptions about the choice of
one ‘optimal’ exclusive governance mode that runs counter to long-term use of multiple
sourcing modes. Nevertheless, the simultaneous use of multiple sourcing channels is
something we observe empirically, and numerous studies testify to its systematic use, at
4
different points in production of goods and services in different industry contexts (Bradach,
1997; Heide, 2003; Jacobides et al., 2006; Parmigiani, 2007; Porter, 1980). Plural sourcing,
along with other terms such as tapered integration or concurrent sourcing, has been used to
describe such phenomena.
The benefits and rationale for undertaking plural sourcing are well understood. Some
of the earlier arguments focused on the role of demand uncertainty, whereby firms can avoid
maintaining idle capacity through the use of external suppliers (Adelman, 1949), and the
threat of backwards integration to external suppliers (Harrigan, 1986). Besides these, firms
also have a better understanding of the production process when making and buying and are
thus better at monitoring suppliers (Dutta et al., 1995; Heide, 2003). Finally, ‘knowledge
complementarities’ between the two sourcing modes have been noted (Puranam et al.,
forthcoming). For example, internal and external suppliers can benefit from mutual learning
and from transferring best practices across different organizational arrangements (Bradach,
1997; Cassiman et al., 2006; Parmigiani, 2007).
Of course, these findings have not gone unchallenged by TCE orthodoxy. Williamson
(1985) suggests that plural sourcing is actually an artifact of ill-identified transactional
heterogeneity. Consistent with this argument, He et al. (2006) find that although trucking
firms appear to engage in plural sourcing (through the use of both internal and external
drivers), they are in fact choosing to outsource hauls that are qualitatively different from the
ones undertaken internally. Similarly, Azoulay (2004) demonstrates that variation in project
characteristics guides pharmaceutical companies when choosing to outsource or assign their
own employees on different projects. More generally, the difficulty in identifying when firms
both make and buy ‘exactly the same input’ presents a substantial challenge to plural
sourcing research (Krzeminska et al., forthcoming).
5
Two further limitations of prior theorizing are notable. First, there is little guidance on
the relative balance of make and buy in cases of plural sourcing (Parmigiani, 2007; Puranam
et al., forthcoming). When the preconditions for plural sourcing exist, we still know little
about how firms choose the mix of internal and external procurement.
Second, existing theories do not analyze supplier selection and its impact on the
design of plural sourcing strategy. Although the role of suppliers’ capability and expertise has
been explored (Parmigiani, 2007; Parmigiani et al., 2009), the overall cost of contracting is
assumed to be independent of concentration in the portfolio of suppliers. However, this
premise is unlikely to hold given that the costs of contracting are affected by the nature of the
contractual relationship between any two parties. In particular, one-off arms-length
transactions between parties are characterized by increased costs of contracting because there
are higher ‘mundane’ transaction costs and lower opportunities to benefit from relational
contracting (Dyer, 1997; Langlois, 2006; Moeen et al., 2013). Hence, the degree of supplier
concentration, and its subsequent impact on the cost of contracting, should influence the
make-buy balance in the plural sourcing of products or services.
In order to address these limitations and contribute to our understanding of plural
sourcing we study corporate legal services. This setting is ideal as it is an unambiguous
example of plural sourcing (see below). We are thus able to dispense with the discussion
about whether inputs are actually both internally and externally procured and focus instead on
observed variability in the design of plural sourcing strategies.
In addition, by moving from the level of the individual transaction to that of a
portfolio of transactions (i.e. legal services) we are able to account for patterns of
interdependence between different transactions and firm resources (Moeen et al., 2013;
Puranam et al., forthcoming). Without such focus, it is impossible to observe ‘spillovers’
from different transactions (Mayer, 2006) and the effect of complementarity between inputs
6
(Parmigiani et al., 2009). Firms regularly employ suppliers for a variety of inputs – with
varying degrees of similarity (Krzeminska et al., forthcoming) – and supplier selection is
naturally affected by existing contractual relationships. For example, a corporation using a
law firm for patent filing could choose the same law firm in case some of its patents are
targeted in a patent suit, given the law firm’s expertise and experience in this area. A
portfolio-level analysis ensures that this information is not lost.
The plural sourcing of legal services
The procurement of legal services by corporations presents an ideal context for the
study of plural sourcing (Sako, 2011; Susskind, 2008). Firms typically have an in-house legal
department headed by a general counsel (GC) leading a staff of in-house lawyers, while at the
same time regularly engaging external law firms. Make-and-buy strategies are driven to some
extent by transactional characteristics: routine legal tasks, such as regulatory form filing, may
be undertaken by in-house lawyers while external lawyers may take the lead on more
specialized tasks such as complex acquisitions, litigation, and criminal matters. However, inhouse and external lawyers often work simultaneously, as a team or in parallel, on the same
type of legal matter. For example, combined teams of in-house and external lawyers support
and consult senior managers during acquisitions. Similarly, in-house legal departments
usually undertake patent filing and prosecution with the help of specialist law firms.
The plural sourcing of legal services is not surprising given complementarity between
the in-house lawyer’s firm-specific and the outside counsel’s practice-specific knowledge and
experience (Puranam et al., forthcoming). Important synergies and learning opportunities
arise from such interactions. There are also bargaining and oversight dimensions to consider
in the plural sourcing of legal services (Dutta et al., 1995; Harrigan, 1986). If firms have the
capacity to re-direct legal matters from outside counsel to qualified in-house lawyers, then
these firms also have more power to bargain over the costs of retaining outside counsel. They
7
can also exercise oversight of outside counsel actions to assure high-quality and costeffective representation in some legal matter. Conversely, the use of external law firms helps
create competitive pressure to the in-house legal department, thus ensuring a minimum level
of efficiency in its operations (Jacobides et al., 2006).
HYPOTHESES
Co-specialization of legal resources
A central tenet of RBV is that firms create and capture value by deploying different or
unique combinations of resources. This suggests that the value of a resource is not
exogenously determined but rather depends on other surrounding resources. Lippman et al.
(2003) go as far as to state that no resource is firm-specific, and suggest that firm value can
be traced to the presence of co-specialized resources that exist within the legal shell of the
firm. Resource co-specialization then is associated with excess value, or synergy, that results
from the interaction of different resources within firm boundaries.
A number of explanations have been put forward in the literature to explain the
emergence of gains from resource co-specialization.1 Nelson et al. (1982) describe how
organizational resources are engaged in functioning routines that enable firms to economize
on coordination costs. Kogut et al. (1992) explain that the emergence of high-order principles
through organizational membership enhances knowledge creation and sharing.
The generation of synergies resulting from resource co-specialization will affect the
design of plural sourcing strategies, as firms will be less reluctant to outsource production.
Market contracting entails the externalization of resources, which reduces the opportunities
of resources to become co-specialized. Hence, in the case of plural sourcing, there will be
more emphasis on make when resource co-specialization is likely to generate synergies. It is
1
We prefer to use the concept of resource co-specialization as opposed to resource complementarity (Milgrom
et al. 1995) because resource co-specialization emphasizes the dynamic nature of the process of generating
synergy. This synergy is not a characteristic of the resource but develops through ongoing interactions within
firm boundaries. Complementarity results in a more instant generation of surplus value due to the attributes of
assets or resources that may lie within or across the firm boundary.
8
important to clarify here that our notion of resource co-specialization is distinct from
complementarity between procurement modes as described by Puranam et al. (forthcoming).
Whereas they focus on the excess value resulting from the simultaneous use of both market
contracting and hierarchical governance, we emphasize the excess value resulting from the
interaction of internalized resources with other firm resources.
Legal resources can be combined with other firm resources, giving rise to
opportunities for exploiting resource co-specialization. Thus, instead of regarding lawyering
as necessary fixed overhead costs for the corporation, in-house legal resources may be seen
as a source of competitive advantage (Bagley, 2008; Orozco, 2010). But exactly what firm
resources give rise to co-specialization opportunities, which in turn increase reliance on the
internal legal department?
International firms
Internationalization as a process compounds the complexity of all managerial tasks
(Carpenter, 2002; Prahalad, 1990; Sanders et al., 1998). As multinationals enter foreign
markets which are more distant in geographic, cultural, and administrative dimensions
(Ghemawat, 2001), they suffer from greater ‘liability of foreignness’ (Zaheer, 1995). In
relation to legal tasks, complexity multiplies with the number of foreign jurisdictions in
which the company has presence, as it has to deal with diverse institutional environments.
This additional complexity creates opportunities for generating value through
regulatory arbitrage. This term is used to describe cases when parties take advantage of a gap
between the economics of a deal and its regulatory treatment, restructuring the deal to reduce
or avoid regulatory costs (Fleischer, 2010:227). Examples include transfer pricing, effective
cross-jurisdictional tax planning, investment decisions based on tax, or other regulatory
incentives. Yet, a strong legal expertise within the firm is required in order to identify such
opportunities and fully capture their benefits (Bagley, 2008). As Marchant et al. (1999)
9
explain, legal expertise largely relies on tacit knowledge of the context and past experience
with the specifics of the situation. Hence, frequent interaction between the corporate legal
department and, say, the corporate accounting department (for international tax planning) or
the strategic planning department (for foreign direct investment or M&A) is likely to create
important benefits for international firms through the identification and realization of
unexplored opportunities. The potential to exploit opportunities from the co-specialization of
legal with other resources, arising from multi-jurisdictional international presence, is likely to
favor more ‘make’ in the plural sourcing of legal services. Thus:
H1: The more internationalized a firm is, the greater its reliance on the internal
sourcing of legal services.
R&D intensive firms
Besides international firms, we also expect R&D intensive firms to rely more on their
internal legal departments. Firms investing in new technology must choose an appropriate
strategy to appropriate gains by protecting their intellectual property, for example by
choosing between secrecy and patenting. Exactly what to patent and how to patent is a knowhow that arises from the co-specialization of legal and technical knowledge. Internal patent
lawyers tend to be highly knowledgeable about the company’s unique technologies (Somaya
et al., 2007). They can interact with the firm’s R&D department to discuss patentable ideas
from an early stage and thus help to increase the share of the value appropriated from
innovation. For example, Reitzig et al. (2009) have found that intermediate levels of crossfunctional involvement between the legal and R&D department increase the speed of patent
grants.
In case studies of innovating firms there is also increased evidence on the role and
importance of internal legal experts in the management of intellectual property – for example
through various committee memberships (Fox, 1998; Grindley et al., 1997). Hence, the value
10
of in-house lawyers will be higher for R&D intensive firms due to the co-specialization of
legal and technical resources. We therefore hypothesize that:
H2: The higher the R&D intensity of a firm is, the greater its reliance on the internal
sourcing of legal services.
Advertising intensive firms
Similarly to R&D intensive firms, firms that rely on advertising to compete will
benefit from the co-specialization of legal resources. Advertising relies on the use of
intangible assets, such as brand names and trademarks, which require protection from
competition. Increased interaction between the legal and marketing departments will
therefore help firms devise a trademark strategy that is informed by and exploits the legal
opportunities and limitations in the use of trademarks (Cohen, 1986, 1991). This will enable
firms to reduce brand dilution and create stronger brand names. Increased communication
between lawyers and marketers is important in this process as lawyers can identify threats to
the intellectual capital of the firm that are not immediately obvious to marketing stuff
(Peterson et al., 1999). In view of these gains, firms with high advertising intensity will rely
more on their internal legal department. Thus:
H3: The higher the advertising intensity of a firm is, the greater its reliance on the
internal sourcing of legal services.
Legal expertise in TMTs
Legal resources may be used directly by top management teams (TMT) to hone their
capability for making strategic choice. Defined as ‘the ability of a TMT to communicate
effectively with the counsel and to work together to solve complex problems’, ‘legal
astuteness’ is a valuable dynamic capability (Bagley, 2008:378). By incorporating legal
know-how in business decisions, ‘legally astute’ TMTs use legal tools to create options (e.g.
11
in litigation), and convert regulatory constraints into opportunities (e.g. by proactively going
beyond the letter of the law in environmental compliance to improve financial performance).
Legal astuteness impacts on the orientation of both TMTs and company lawyers. As
for TMTs, the upper echelons perspective points out that organizational outcomes reflect the
values and cognitive bases of powerful actors in the organization (Hambrick et al., 1984).
Consequently, examining prior experiences and background of TMT members help us
identify the ways they shape and direct the resources at their disposal. In the legal context,
TMTs with legal expertise may create more structures and processes to improve the
effectiveness of the in-house legal function. Thus, the presence of a functional TMT member
influences organization design, and equally, the TMT composition is affected by changes in
organization structure (Menz, 2012).
Legal astuteness also affects the orientation of in-house corporate lawyers. They
would be expected to be proactive in identifying complementarities between business
opportunities and legal know-how. They are, in effect, counsels (combining legal and
business advice) or entrepreneurs (giving priority to business objectives rather than legal
analysis), rather than cops (limiting their advice to legal mandates) (Nelson et al., 2000). In
short, these ‘decision consultants’ (Rosen, 1984) give legal advice in the context of the
business. Thus, legally astute TMTs rely much on the GC’s capacity to create value from the
co-specialization of legal resources and business-context knowledge within the firm. Thus,
the more legally astute the TMT, the more likely the GC is a member of the TMT and the
more likely in-house lawyers rely on co-specialization of legal and firm-specific business
knowledge.
H4: The general counsel’s membership in the top management team will result in
greater reliance on the internal sourcing of legal services.
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Supplier concentration
Besides resource co-specialization, the degree of concentration of suppliers affects the
design of plural sourcing strategy. As explained before, heterogeneity in supplier selection
has not been explored in the context of plural sourcing. In essence, the analytical calculus that
prompts a firm to choose plural sourcing is assumed to be independent of the composition of
supplier portfolio. Here, however, we suggest that different degrees of supplier concentration
impose different costs of contracting to the outsourcing firm. These costs depend on the
nature of the contractual relationship. Low scale, arms-length transactions are characterized
by high costs of contracting as the parties do not have much incentive to invest in firmspecific transacting platforms and systems (Baldwin et al., 2003; Langlois, 1992, 2006). In
addition, infrequent interactions with suppliers do not generate inter-organizational trust and
the associated benefits of relational contracting and increased commitment (Baker et al.,
2002; Dyer, 1997; Sako et al., 1998). Hence, in the presence of high costs of contracting, we
expect lower reliance on external providers.
In-house legal departments may choose to procure legal services from a large number
of law firms in pursuit of increased expertise in some area (e.g. regulatory compliance in a
specific industry) or lower cost. This model is closer to arms-length-style market governance,
as firms scan the environment for the best possible provider for their specific legal needs.
Alternatively, legal departments could outsource to a concentrated panel of law firms
involved in relational governance. This mode involves less flexibility in terms of supplier
selection but the firm benefits from reduced costs of contracting. For example, having an ongoing and committed relationship with a law firm facilitates communication (as there is no
need to identify points of contact or firm background), and ensures that the client firm will
get the top partners for their case.
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We therefore expect a company’s willingness to invest in relational governance with a
selected few law firms to result in a high degree of outsourcing and a smaller in-house legal
department (Moeen et al., 2013). By contrast, companies collaborating with a large number
of law firms will increase their reliance on internal legal resources. Thus, we predict the
following:
H5: The larger the number of external law firms employed by a firm, the greater its
reliance on the internal sourcing of legal services.
EMPIRICAL METHODS
Data and sampling
To evaluate our theoretical framework and test our hypotheses, we first collect
information on the size and composition of internal legal departments and their relationships
with external law firms. This information is not publicly available, so we use proprietary
survey and secondary data collected by ALM Legal Intelligence, a research unit within the
American Lawyer Media Group. In particular, we used ALM’s annual survey of in-house
legal departments as well as ALM’s reports on corporate activity, including litigation, M&A
transactions, and corporate bankruptcies. These data are available from 2004 until 2011 for
Fortune 500 companies2.
To be included in our sample, we require firms to have ALM annual survey data as
well as data on firm operations in Compustat corporate and industry segment files. Our final
dataset is an unbalanced panel consisting of 1230 observations from 285 firms (i) observed
over up to eight years (t). Our reported number of observations drops to 945 as several
statistical analyses below require the inclusion of one-year lagged variables.
2
For 2004 and 2005 the data are only available for Fortune 250 companies.
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Dependent variable
Consistent with other empirical work on plural sourcing (Parmigiani, 2007;
Parmigiani et al., 2009), we seek comparable information on internal and external suppliers
of legal services. Ideally we would have information on hours worked on specific matters by
in-house lawyers at corporations as well as hours worked on the same matters by lawyers at
outside law firms on behalf of these client corporations. Such data are not publicly available
as lawyers at both types of organizations treat such information as sensitive and strictly
confidential.
We do, however, have ALM survey data on the number of in-house lawyers and the
number of external law firms providing outside legal work for these firms. Thus, we
construct our dependent variable based on the count of in-house lawyers (as reported in the
ALM annual survey of general counsel (GC)) and include the count of external law firms as a
right-hand side term. Our dependent variable is the natural log of the annual count of inhouse lawyers per $100 billion in firm sales. Changes in the dependent variable then reflect
changes in the in-house lawyer count attributed to factors unrelated to organic growth.
An increase (decrease) in the dependent variable can be attributed to two possibilities:
a) increased (decreased) reliance on internally made legal services by in-house lawyers rather
than externally bought legal services by outside law firms; or b) an increase (decrease) in the
overall amount of legal work that needs to be undertaken on behalf of the firm by both
internal and external providers. In order to account for the second possibility and isolate
changes in the make-and-buy mix, we include controls for the overall amount of legal work
undertaken and employ multiple regression analyses that incorporate dynamic processes and
account for possible reverse causality.
15
Independent variables
Internationalization. We measure the degree of internationalization as a count of the
number of countries where each firm operates via subsidiaries in a given year. Although
different measures of internationalization have been suggested, we use the number of
countries as it more accurately captures the complexity associated with operating in multiple
jurisdictions. Even modest sales or presence in a country requires basic knowledge of and
compliance with substantive laws and legal processes.
R&D intensity. We calculate R&D intensity as R&D expenses divided by sales.
Advertising intensity. We calculate advertising intensity as advertising expenses
divided by sales.
General counsel in TMT. In order to examine the GC’s participation in the firm’s
TMT, we construct a dummy variable taking the value of one when the GC has the title
‘Senior Vice President’ or ‘Executive Vice President’ and otherwise taking the value of zero.
Data on the GC’s role were obtained from S&P’s Capital IQ database which includes
biographical and other information on key professionals, executives and directors.
Law firms. In order to measure the degree of concentration in the provision of external
legal services we use a count of external law firms working for a given client corporation
surveyed. This variable is included in ALM’s annual survey and asks GCs to identify the law
firms that undertook legal work on their behalf in a given year. All other equal, the higher the
number of law firms, the lower the degree of concentration in the provision of external legal
services across the group.
Control variables
We include a number of time-varying firm controls including firm debt exposure,
calculated as total debt divided by total assets, firm profitability, calculated as EBITDA
divided by sales, and the natural log of the count of firm employees. We also control for the
16
effect of product diversification using the entropy measure of diversification, where industry
segments are defined by 4-digit SIC codes. In addition, we include a count of new
acquisitions started in a given firm as well as a count of new litigation cases started in a given
year where the firm was involved either as defendant or plaintiff.3 Both acquisitions and
lawsuits are important controls as they may prompt a significant increase in the amount of
legal work to be done in-house or externally. To account for the possibility that the additional
work may come with some delay, we also include one-year lagged value of these two counts.
To better control for the overall amount of legal work undertaken by the firm in each
year, we also use annual selling, general and administrative expenses (SG&A) as a proxy for
legal expenses. This variable is reported by Compustat and includes all commercial expenses
of operation not directly related to production, including GC office expenses and legal fees
paid to law firms. We are thus able to observe changes in the legal service make and buy
propensity as opposed to changes in the overall amount of legal work undertaken. Finally, we
include a dummy variable which is equal to one when the firm is in bankruptcy proceedings
in a given year. Table 1 reports summary statistics and correlations for the variables.
- Insert Table 1 about here Econometric specifications
Standard fixed- or random-effects specifications allow us to control for unobserved
firm characteristics that influence the legal services make-and-buy decision. However, our
data have two additional characteristics that need to be accounted for. First, the in-house
lawyer count is likely to be influenced by past observations. Including a lagged value of the
dependent variable as a regressor allows us to account for autocorrelation but the presence of
both a lagged dependent variable and fixed-effects can render estimates inconsistent (Nickell,
3
ALM only collects data for ‘important’ acquisitions and lawsuits as reported in trade publications. Although
this probably results in loosing some information, this is unlikely to bias our results as reporting criteria are
similar for all firms in our sample. In addition, the biggest acquisitions and lawsuits are likely to have the most
important effect on legal service sourcing dynamics.
17
1981). Second, several of our regressors may be endogenously determined or predetermined,
that is, correlated with current or past disturbances. To address these concerns we employ a
dynamic panel data estimator with GMM-type instruments (Arellano et al., 1991). This
estimator is ideal for ‘small T, large N’ panels like ours. In addition, GMM estimators are
robust to heteroskedasticity in the cross-section and unknown patterns of serial correlation
(Arellano, 1987).
More specifically, we estimate a statistical model of the form:
!!" ! !! !!
!!!
! ! ! !!" ! !! ! !! ! !!"
where !!" is the natural log of the count of lawyers divided by sales in firm i of year t, !!" is a
vector of explanatory variables, !! is a year effect, !! is a time-invariant firm-specific effect
and !!" is the error term.
The GMM estimator originally proposed by Arellano et al. (1991) uses first
differencing to remove unobservable firm-specific effects and then instruments the
endogenous variables using lagged levels of the series. However, this approach is
problematic in our setting as the first-differenced GMM estimator is found to have large
finite sample bias and poor precision when time series are short and persistent (Blundell et
al., 1998). Instead, we employ the system GMM estimator suggested by Arellano et al.
(1995) and Blundell et al. (1998). This approach uses lagged differences as instruments for
equations in levels, in addition to lagged levels as instruments for equations in first
differences. The system estimator introduces an additional assumption that changes in
instrumenting variables are uncorrelated with the fixed effects. All models were calculated
using the xtabond2 Stata module (Roodman, 2006).
To address concerns about simultaneity bias we treat the number of law firms and
general counsel in TMT variables as endogenous while the remaining explanatory variables
as predetermined. From the control variables, selling, general and administrative expenses are
18
endogenous as they proxy overall legal expenses. Litigation cases are also treated as
endogenous given that larger legal departments are more likely to take cases to court. The
remaining control variables are treated as exogenous. We use the forward orthogonal
deviation transformation instead of first differencing given that our panel is unbalanced. This
minimizes data loss while preserving the orthogonality among the errors (Arellano et al.,
1995; Roodman, 2006). Finally, we use standard errors that are robust to heteroskedasticity
and arbitrary patterns of autocorrelation within firms.
RESULTS
Descriptive statistics and preliminary analysis
Descriptive statistics and pair-wise correlations are reported in Table 1. The sample
mean for In-house lawyers is 5.37, suggesting that firms employ on average 3.62 lawyers per
billion dollar of sales. The raw number of in-house lawyers at Fortune 500 firms sampled
exhibited substantial variation ranging from a handful to more than 1200 in certain firms such
as General Electric. The sample mean of Outside law firms is 1.83, meaning that firms
reported on average nine outside law firms as undertaking legal work on their behalf in a
given year. Those numbers ranged from one to more than 50 outside law firms. Pair-wise
correlations are largely intuitive. Variables corresponding to the five hypotheses for testing
all exhibit the predicted positive sign when correlated with the dependent variable.
Figures 1A-E present results from Lowess analyses4 of In-house lawyers and make
and buy determinants related to Hypotheses 1-3 and 5 (Internationalization, R&D intensity,
Advertising intensity, and Outside law firms), and from comparative bar-chart analyses of Inhouse lawyers related to Hypothesis 4 (General counsel on TMT). The pattern of results in
all figures indicates preliminary support for Hypotheses 1-5.
4
Lowess analyses compute linear regressions around each observation of given determinant (e.g.,
Internationalization) with neighborhood observations chosen within some sampling bandwidth and weighted by
a tri-cubic function. Based on the estimated regression parameters, In-house lawyers values are computed.
Combinations of determinants and In-house lawyers are then connected, yielding a Lowess curve.
19
- Insert Figures 1A-E about here Regression analysis
Table 2 presents the results of our regression analysis. Models 1-2 present fixedeffects specifications while Models 3-5 present results from the system GMM estimator.
Simpler fixed-effects models suggest that the lagged dependent variable, In-house lawyersit-1,
explains roughly 30% of variation in the dependent variable. We noted previously, however,
that the lagged dependent variable coefficient estimates in fixed-effects regressions are
typically biased downwards (Nickell, 1981). When the number of time-periods, t, are few as
here, the downward bias can be substantial as corrected system GMM regression results
demonstrate. Coefficients on In-house lawyersit-1 jump from 0.310 and 0.305 in Models 1-2
to 0.973, 0.882 and 0.883 in Models 3-5. All estimates are significant at the 1% level.
Model 3 reports one-step system GMM results with the lagged dependent variable
and controls only. Models 4-5 are fully-specified and report one- and two-step system GMM
results (the two-step estimator is corrected for downward bias in the computed standard
errors (Windmeijer, 2005)). Diagnostics at the bottom of each column suggest that key
estimation assumptions hold. The Arellano-Bond z test for second- and higher-order autocorrelation is not statistically significant. This is not weakened by the number of instruments
as instrument count is lower than the number of firms (Roodman, 2006). Hansen’s J test fails
to reject the null hypothesis that the instruments generated are exogenous.
- Insert Table 2 about here We look primarily to results in Models 4-5 for evidence to evaluate support for our
hypotheses. Results support our predictions and the importance of resource co-specialization
in designing plural sourcing strategies. Consistent with Hypothesis 1, we observe positive
coefficients for Internationalization significant at the 1% level. Firms operating in more
countries increase their dependence on in-house lawyers. Consistent with Hypotheses 2 and
20
3, we see positive coefficients on R&D intensity significant at the 10% level and positive
coefficients on Advertising intensity significant at the 5% level. Consistent with Hypothesis
4, we observe positive coefficients on General counsel on TMT significant at the 10% level,
suggesting that elevating senior legal personnel to top management ranks also increases inhouse lawyer counts.
Recall that Hypothesis 5 explains that the design of the portfolio of external legal
service providers is not independent of the proportion of legal work that is externally
procured. Our analysis confirms the hypothesized positive relation between the number of
law firms supplying to a company and the propensity to internalize legal work. The
coefficient for the number of external law firms is positive and significant at the 10% level,
suggesting that the proportion of legal work undertaken within the firm boundaries increases
with the number of external service providers. Although this result might sound counterintuitive, it is consistent with a relational contracting logic. Firms employing a large number
of suppliers do not develop the mechanisms that reduce contractual uncertainty and, as a
result, face higher contracting costs.
From the control variables we find that firm profitability is negatively correlated with
the extent of internal procurement of legal services. The coefficient for SG&A expenses, a
proxy for the overall amount of legal work undertaken by the firm, is also negative and
significant. This might reflect the ‘natural’ tendency to outsource legal work due to low asset
specificity and increased expertise in the marketplace. Finally, the coefficient for the number
of acquisitions undertaken is negative and significant. Given that corporate acquisitions
require specialist legal knowledge during negotiations, due diligence, contract design etc, it is
reasonable to expect that more outsourcing of legal work will take place.
21
Robustness checks
These results prove robust to several changes in model specification and sampling.
For example, we excluded firms from our sample that were involved either in antitrust suits
or in bankruptcy proceedings – see Model 6. We also obtain consistent results when remeasuring the dependent variable, In-house lawyers, as a simple count and then analyzed in
Poisson panel count models – see Models 7-8. Results remain essentially unchanged when
employing different variable definitions (e.g. we varied Internationalization to account for
the number of foreign jurisdictions with differing (from US) legal system and rule-of-law
traditions) and when excluding possible outliers (e.g. R&D intensity values above 30%).
Another issue we explored further is the measurement of supplier portfolio
concentration. On average, we expect that a high number of law firms undertaking work for
the focal firm is associated with low concentration in the supply of legal services. However,
this relationship is less clear when there are changes in the type of representation. For
example, assume firm A employs 4 different law firms in four different practice areas
(M&As, patent litigation etc) while firm B similarly employs 4 law firms but in one practice
area. As it stands, our measure suggests that both corporations have the same level of supplier
concentration. However, firm B clearly has a less concentrated portfolio of suppliers given
that it has 4 different suppliers for the same practice area. To account for this, we counted the
number of law firms undertaking work for the focal firm in each practice area (this
information is available from ALM) and then averaged these. A high number of this measure
suggests that the focal firm has multiple suppliers in the same practice area, which is
indicative of low concentration in the provision of legal services. Consistent with our results,
the coefficient for this variable remains positive and significant at the 6% level.
22
DISCUSSION AND CONCLUSION
A substantial body of research has examined the conditions under which plural
sourcing is likely to occur. Moving beyond the question of when it occurs, the issue of how
firms choose the balance between making and buying in plural sourcing has remained underexplored. This study fills that gap. In doing so we identify two mechanisms that dictate the
make-buy balance in plural sourcing, namely resource co-specialization and supplier
concentration. Our framework enables us to predict the make-and-buy mix in the context of
legal services provision.
The empirical findings support the view that when making and buying, firms exploit
resource co-specialization and supplier selection to tip the balance in favor of in-house
production and delivery. We noted statistically significant increases in the reliance on inhouse lawyers with increases in the number of countries where the firm had operations, with
increasing R&D and advertising expenses as a percentage of sales, when the CG is part of the
firm’s TMT, and as the number of law firms providing work for the firm increases. Overall,
these findings provide broad-based support for our make-and-buy framework that explains
how firms decide to balance internal and external activities.
Implications for theory and research
Our study has important implications for strategy theory. First, our study extends the
plural sourcing research by going beyond important but still basic questions of whether and
when firms engage in this practice to theorize about firm-level mechanisms, including
resource co-specialization and supplier selection, that determine the mix of sourcing modes.
Second, these co-specialization opportunities exist for resources lying in different
corporate functions. Thus, whilst our empirical context is the legal department as a focal
corporate function, other corporate functions also engage in plural sourcing by balancing
internal and external resources within the firm. In particular, in-house accountants work
23
alongside outside accounting and audit firms, in-house engineers with outside engineering
consultant firms, in-house marketing departments with marketing and PR agencies, and
internal strategy consultants with outside consulting firms. In these and other contexts, we
think our theoretical framework can provide researchers with relevant guides for making
inferences about make and buy strategies.
A third research implication relates to methods. We suspect that the dearth of research
on sourcing decisions in legal services is due to the absence of good data and the difficulty in
making causal inference. Despite their still relatively short time-series (i.e. seven years) and
limited cross-sectional coverage (i.e. Fortune 500 firms), our panel data provide us with
advantages relative to single firm case narratives (e.g. Smith, 2001) or one-time crosssectional surveys (e.g. Schwarcz, 2008).
Implications for practice
The findings of this study draw practitioners’ attention to a few, yet important, aspects
of the sourcing decisions in legal services. Some of them may appear paradoxical. First, in
legal circles, the last two decades have seen vigorous debate on the proper size and scope of
work for in-house lawyers. One view championed by the US giant, General Electric (Smith,
2001), argues for substantially increasing the number of in-house lawyers. In-house lawyers
are expected to increasingly play a dual role of being a lawyer and a business partner (Green,
2012). The chief legal officer (CLO) is said to be ‘one of the mightiest figures in the Csuite’5. This is because the 2002 Sarbanes-Oxley Act, the 2010 Dodd-Frank Act and the 2008
financial crisis have heightened the need for compliance and risk management, making
companies turn to lawyers to prevent corporate bosses from going to jail and to fend against
endless threats of lawsuits. Our study indicates that whilst the power and status of GC may be
5
‘A guardian and a guide’, Schumpeter column, The Economist April 7, 2012
24
on the rise, the resulting trend towards insourcing leads to business benefits only if resource
co-specialization benefits are exploited.
Limitations and further research
A number of limitations of this study are worth noting. The first limitation in the
analytical framework is self-imposed to simplify the analysis. Plural sourcing in legal
services in full manifestation involves multiple sourcing modes (make, buy, ally) from
multiple types of providers other than law firms, including LPO providers, legal technology
providers, and contract lawyers. By limiting our analysis to the co-existence of ‘make’ and
‘buy’ only from law firms, we did not take into account the impact of the growth of providers
other than law firms on the number of law firms and the consequent make-buy balance.
The second limitation lies in available data. Our study links the number of in-house
lawyers to the number of outside law firms, not the number of external counsel or hours spent
by these lawyers. In an ideal world, we would have better data on internal to external legal
personnel or hours worked. We deal with this limitation by including a number of control
variables and employing a dynamic panel data estimator.
A third limitation relates to sampling and generalizability. We think our framework
and evidence can be generalized to other large, established firms in the US. But this leaves
many other firm types where we are reluctant to generalize and advise additional study on
make and buy strategies. The discount consumer services purchasing giant, Groupon, was
founded in 2008, but did not have a full-time in-house counsel until 2011 when it already
operated in 48 countries generating $1.6 billion in annual revenue6 . Groupon’s history
suggests that explanation of plural sourcing strategies for legal services in entrepreneurial
firms may require quite different frameworks and assumptions.
6
ABA Journal. 2011. The new normal: Make or buy in the age of the free-agent lawyer. ABA Journal.com.
October 26. Available electronically at: http://www.abajournal.com/legalrebels/article/inhouse_lawyers_make_or_buy/!
25
Conclusion
We began this study by asking how firms develop plural sourcing strategies important
to their survival and success. We end it with a call for strategy researchers to continue
developing plural sourcing frameworks and evidence relevant to different organizational
forms and different product and service producing activities. We chose legal services and
demonstrated how such frameworks and evidence could help us understand the relative size
of in-house legal departments. Hitherto, strategy scholars have undervalued the analysis of
what Porter (1980) and others refer to as “support activities” to the firm. Our study suggests
that they can be essential to the firm’s strategy for gaining and maintaining competitive
advantage. In this context, we should count all the inside and outside professionals as part of
the search for an optimal make and buy mix in corporate functions. Research on firm
boundaries will be enriched by placing plural sourcing decisions in corporate functions on a
par with vertical (dis)integration decisions for the primary activities of the firm.
26
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Table 1. Descriptive statistics and pairwise correlations
Descriptive statistics
Pair-wise correlations
Variable
Mean St.Dv. Min Max (1)
1) In-house lawyers
5.37
1.10
1.44 8.44 1.00
2) Internationalization
2.24
1.48
0.00 4.55 0.36* 1.00
3) R&D intensity
0.02
0.05
0.00 0.53 0.30* 0.41* 1.00
4) Advertising intensity
0.01
0.03
0.00 0.21 0.17* 0.14* 0.07* 1.00
5) General counsel on TMT
0.79
0.41
0.00 1.00 0.19* 0.02 0.05
6) Outside law firms
1.83
0.93
0.00 3.95 0.14* 0.21* 0.12* 0.02 0.09* 1.00
7) Diversification
0.90
0.36
0.00 2.05 0.01
0.17* -0.11* 0.09* 0.00
8) Debt
0.04
0.07
0.00 0.46 -0.02
0.04 0.00
9) Profitability
0.16
0.13 -0.31 0.77 0.40* 0.24* 0.20* 0.10* 0.11* 0.14* 0.00 0.10* 1.00
10) Employees
3.67
1.11
0.00 6.32 -0.08* 0.24* 0.06
11) SG&A
6.64
2.93
0.00 10.79 -0.20* 0.24* 0.28* 0.28* 0.07* 0.10* 0.08* -0.07* -0.12* 0.36* 1.00
12) Litigation
0.13
0.44
0.00 3.00 0.21* 0.18* 0.29* 0.12* 0.02
0.18* -0.04 0.04
13) Acquisitions
0.09
0.33
0.00 3.00 0.08* 0.09* 0.08* -0.01 -0.01
0.05 0.01 0.20* 0.22* 0.12* -0.04
14) Bankruptcy
0.00 0.06 0.00 1.00 0.04
N=945, * statistically significant at the 5% level
(2)
(3)
-0.01 -0.03
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11) (12) (13)
(14)
0.06 1.00
0.03 1.00
0.02 -0.10* 0.06 0.00 1.00
0.10* 0.08* 0.29* 0.15* 0.01
-0.02 -0.02
31
0.08* 0.01 0.03
-0.03
1.00
0.23* 0.12* 0.06
1.00
0.15* 1.00
-0.07* 0.04 -0.13* 0.07* 0.10* 1.00
Table 2. Panel data regression models of corporate legal services make and buy balance
Dep. Variable
In-house lawyers
Lagged dep. variable
No of lawyers
(count)
(7)
(8)
Fixed Random
effects
effects
Poisson Poisson
(1)
(2)
(3)
(4)
(5)
(6)
Fixed
effects
Fixed
effects
System
GMM
System
GMM
System
GMM
System
GMM
0.310**
(0.000)
0.305**
(0.000)
0.973**
(0.000)
0.882**
(0.000)
0.883**
(0.000)
0.882**
(0.000)
0.041**
(0.005)
0.770†
(0.072)
2.442*
(0.012)
0.090†
(0.094)
0.041†
(0.069)
0.040**
(0.008)
0.764†
(0.078)
2.389*
(0.012)
0.090†
(0.079)
0.041†
(0.072)
0.039**
(0.008)
0.912†
(0.051)
2.469*
(0.017)
0.0938†
(0.082)
0.0389†
(0.076)
0.043
(0.661)
0.518†
(0.068)
1.636*
(0.013)
0.180**
(0.000)
0.019**
(0.000)
0.006
0.021
0.022
0.000
(0.937)
(0.653) (0.641) (0.990)
-0.213
-0.179
-0.229
-0.218
-0.234
(0.562) (0.132) (0.165) (0.200) (0.144)
-1.026** -0.444* -0.346* -0.343* -0.290†
(0.000) (0.037) (0.029) (0.045) (0.075)
-0.344** 0.003
-0.009
-0.010
-0.012
(0.000) (0.825) (0.593) (0.553) (0.502)
-0.117** -0.018 -0.040** -0.040** -0.035*
(0.005) (0.204) (0.008) (0.007) (0.032)
-0.040*
0.065
0.046
0.047
0.053
(0.013) (0.169) (0.141) (0.132) (0.106)
-0.009
-0.014
-0.012
-0.012
-0.059†
(0.765) (0.746) (0.722) (0.730) (0.084)
-0.012
-0.030
-0.055† -0.055† -0.079*
(0.722) (0.369) (0.088) (0.089) (0.020)
-0.035
-0.014
-0.029
-0.028 -0.0301
(0.266) (0.683) (0.380) (0.391) (0.440)
-0.467* -0.480
-0.389
-0.382
(0.045) (0.411) (0.344) (0.356)
0.0301
(0.236)
-0.405*
(0.010)
-0.057
(0.486)
-0.000
(0.995)
0.093**
(0.000)
0.000
(0.923)
-0.010
(0.174)
-0.004
(0.682)
-0.018*
(0.036)
0.0210
(0.625)
0.141**
(0.000)
Explanatory variables
No of countries (log)
R&D intensity
Advertising intensity
General counsel in TMT
No of law firms (log)
0.055
(0.818)
2.878*
(0.028)
0.350
(0.778)
0.090*
(0.034)
0.023
(0.112)
0.270**
(0.000)
2.407**
(0.000)
1.240*
(0.049)
0.161**
(0.000)
0.014*
(0.017)
Control variables
Product diversification
Debt ratio
Profitability
No of employees (log)
Selling, general & admin
expenses (log)
No of litigation cases
No of litigation casest-1
No of acquisitions
No of acquisitions-1
Bankruptcy
Sales (log)
Constant
Year dummies
N (number of firms)
Wald x2 (R2)
Arellano-Bond test AR(1)
Arellano-Bond test AR(2)
No of instruments
Hansen test
0.103**
(0.000)
-0.139
-0.605**
(0.686)
(0.000)
-1.092**
-0.227**
(0.000)
(0.006)
-0.344**
-0.024
(0.000)
(0.356)
-0.118**
-0.049**
(0.005)
(0.000)
-0.028+
-0.010
(0.096)
(0.175)
-0.021
-0.000
(0.529)
(0.922)
-0.003
-0.019+
(0.911)
(0.057)
-0.034
-0.027**
(0.270)
(0.002)
-0.463*
-0.0228
(0.049)
(0.601)
0.331**
(0.000)
5.952** 5.658**
0.325
0.674*
0.676*
0.680*
0.264
(0.000)
(0.000) (0.257) (0.012) (0.013) (0.012)
(0.339)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
945(285) 945(285) 945(285) 945(285) 945(285) 921(280) 945(285) 945(285)
(0.344)
(0.361) 3119.9
4885.9
5060.1 5006.39 218.64
347.7
-3.80** -4.15** -3.97** -4.10**
0.31
0.23
0.23
-0.42
126
249
249
248
106.2
224.74
224.74
214.95
†
p-values in parentheses, p ! 10%, * p ! 5%, ** p !1%
32
Figures 1A-E. Locally-weighted scatter-plot smoothed and comparative bar-chart analyses of in-house
lawyer counts
Lowess smoother
2
2
In-house lawyers
loglawyers_per_sales
4
6
In-house lawyers
loglawyers_per_sales
4
6
8
8
Lowess smoother
1A
0
20
40
60
No_countries
80
100
1B
0
.1
.2
No of countries
bandwidth = .8
.4
.5
R&D intensity
bandwidth = .8
Lowess smoother
2
2
In-house lawyers
loglawyers_per_sales
4
6
In-house lawyers
loglawyers_per_sales
4
6
8
8
Lowess smoother
1C
.1
advert_intensity
.15
.2
1D
0
10
20
30
no_of_lawfirms
Advertising intensity
No of law firms
10
bandwidth = .8
In-house lawyers
loglawyers_per_sales
4
6
8
bandwidth = .8
.05
2
0
!
.3
rndintensity
1E
0
1
No
Yes
CG in TMT
33
40
50