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TYPES OF SPECIFICITY, CONTRACTS AND TRANSACTION COSTS: AN EMPIRICAL INVESTIGATION OF OUTSOURCING
AGREEMENTS
Jerome Barthelemy
ESSEC Business School 95021 Cergy Pontoise Cedex – France
E-mail: [email protected]
Bertrand V. Quelin (Corresponding author) *
HEC Paris – School of Management 78351 Jouy-en-Josas Cedex – France
Tel.: +33.1.39.67.72.36 Fax: +33.1.39.67.94.54 E-mail: [email protected]
November 2002
Key words: Transaction cost Economics, Resource-based View, Contract, Monitoring * Correspondence: Bertrand Quelin – HEC School of Management – 78351 Jouy-en-Josas Cedex – France This paper benefited greatly from the comments provided by the anonymous referees of the Academy of Management Conference at Denver and Strategic Management Society Conference at Paris. Bertrand Quelin acknowledges the financial support of the HEC Foundation.
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Types of Specificity, Contracts and Transaction Costs: An Empirical Investigation of Outsourcing Agreements Abstract In this paper, we use both Transaction Cost Economics (TCE) and the Resource Based View
of the firm (RBV) to study outsourcing agreements. We use insight from both theories to
develop an original approach of specificity by decomposing it between transactional, core and
relational specificity. While TCE proponents generally focus on the link between contractual
hazards and governance forms, this study tests the link between contractual hazards (i.e.,
specificity and environmental uncertainty), the contractual aspects of outsourcing and the
level of ex post transaction costs. Our empirical research analyses 82 outsourcing contracts.
The results suggest that all three types of specificity and environmental uncertainty have a
positive impact on ex post transaction cost via an increase of contractual density. Moreover,
flexible contracts are useful to mitigate hazards when specific assets are outsourced. Putting
in the contract both incentives and penalties, pricing and monitoring clauses is a requirement
to reduce supplier opportunism.
Key words: Transaction cost Economics, Resource-based View, Contract, Monitoring
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INTRODUCTION
With the blurring of the firm’s traditional boundaries, new forms of contracting have
progressively emerged. Outsourcing is one of the most prominent ones and is currently
booming in service activities (Quinn, 1992; Outsourcing Institute, 2001). Service activities
outsourcing has moved beyond basic activities from the value chain (e.g., gardening, catering
and cleaning) to encompass more elaborate ones (e.g., information technology,
telecommunications, research and development, and logistics). Basically, two types of
outsourcing can be distinguished: (1) outsourcing as an alternative to vertical integration and
(2) outsourcing as a means to vertically disintegrate (i.e., allowing vendors to assume
activities that were once undertaken in-house).
Outsourcing as an alternative to vertical integration refers to the classical “make or buy”
issue. This topic has been extensively studied both theoretically and empirically. Over the past
25 years, Transaction Cost Economics (TCE) has emerged as the most widely used theoretical
explanation for firm boundary choices (Williamson, 1975, 1985, 1996). While early papers
tested the main TCE hypotheses (Monteverde and Teece, 1982; Anderson and Schmittlein,
1984; Walker and Weber, 1984, 1987; Walker and Poppo, 1991), researchers have started
exploring the link between governance and performance (Masten, Meehan and Snyder, 1991;
D’Aveni and Ravenscraft, 1994; Poppo and Zenger, 1998; Leiblein, Reuer and Dalsace,
2002).
Outsourcing as a means to vertically disintegrate refers to the decision to contract out an
activity in which the firm has invested in the past. The goal of companies that outsource such
service activities is to achieve higher profitability with less in-house resources (Gilley and
Rasheed, 2000). While outsourcing as a means to vertically disintegrate has been extensively
covered in the managerial literature (Lacity and Hirschheim, 1993; Lacity, Willcocks and
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Feeny, 1995; Saunders, Gebelt and Hu, 1997; Useem and Harder, 2000), it has been neglected
in the academic literature (Boone and Verbeke, 1991; Lei and Hitt, 1995).
In this paper, we propose an in-depth study of outsourcing agreements to assess the impact
of contractual hazards on ex post transaction cost. So far, most of the TCE-based empirical
research has focused on the link between contractual hazards and organizational forms (i.e.,
firm, hybrid forms and hierarchy) (Shelanski and Klein, 1995). Analysis of contractual
agreements has been minimal and empirical studies have rarely directly measured transaction
costs [see Masten, Meehan and Snyder (1991) for an exception]. Moreover, we contend that
the TCE concept of asset specificity must be extended in the context of vertical disintegration.
Hence, we distinguish between three types of specificity: core specificity, transactional
specificity, and relational specificity. Firms that vertically disintegrate have invested in
activities that contribute to their competitive advantage to some extent (i.e., core specificity).
These activities rest on dedicated employees and equipment that are transferred to the supplier
(i.e., transactional specificity). Finally, dealing with a supplier instead of carrying out an
activity in-house entails the development of relation-specific assets (i.e., relational
specificity).
We develop a three-tier model linking the main contractual hazards (i.e. the three types of
specificity and environmental uncertainty), contractual density and ex post transaction costs.
While specificity is generally considered the most important contractual hazard,
environmental uncertainty is a multidimensional concept that reflects the lack of knowledge
about events that may take place in the environment (Joskow, 1988a and b; Klein, 1988;
Sutcliffe and Zaheer, 1998). In the next section, the theoretical background of the study is
introduced and hypotheses are proposed. Thereafter, we explain the methodology. In the
following section, we present and discuss the empirical results of the research. Finally, we
conclude with implications, limitations and suggestions for further research.
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THEORETICAL BACKGROUND
Analyzing Outsourcing Agreements
The primary aim of TCE is to explain when an internal organizational mode (i.e.,
hierarchy) may be preferable to an external one (i.e., market). Basically, TCE suggests that
three conditions are necessary for a transaction to be carried out internally: (1) the assets
involved must be highly specific to the transaction, (2) the level of uncertainty surrounding
the transaction must be high, and (3) the transaction must occur frequently (Williamson,
1985). Williamson (1991) has then moved beyond the ‘market vs. hierarchy’ dichotomy,
arguing that a wide range of hybrid organizational modes exists between these two extremes.
According to TCE, the total cost of carrying out an activity includes production and
transaction costs. The best mode for organizing transactions is the one that minimizes the sum
of production costs and transaction costs. In the case of outsourcing, transaction costs can be
decomposed into four categories (Williamson, 1985; Dyer, 1997): (1) search costs (i.e., the
costs of gathering information to identify and evaluate an outsourcing vendor), (2) contracting
costs (i.e., the costs of negotiating and writing the outsourcing contract), (3) monitoring costs
(i.e., the costs of monitoring the agreement to ensure that the outsourcing vendor fulfills its
contractual obligations), (4) enforcement costs (i.e., the costs associated with ex post
bargaining and sanctioning of the outsourcing vendor when it does not perform according to
the contract). While search and contracting costs are generally termed ex ante transaction
costs, monitoring and enforcement costs are usually termed ex post transaction costs.
TCE has two main limitations when it comes to studying outsourcing agreements as a
means to vertically disintegrate. First, the TCE framework was essentially developed to study
“make or buy” issues and remains vague about the content of contracts. Second, it is static
and does not take into account the fact that outsourced activities used to be performed
internally. Distinguishing between different types of specificity can help take this feature into
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account.
Density of Contractual Agreements
An in-depth study of outsourcing agreements requires insights from the long-term contract
literature (Joskow, 1985, 1987, 1988a and b, 1990; Masten et Crocker, 1985; Goldberg and
Erickson, 1987; Crocker and Masten, 1988, 1991). The long-term contract literature
investigates the link between transaction attributes and contractual clauses such as contract
duration, prices and quantities. It essentially focuses on raw materials and transportation
activities.
There have been changes since Joskow’s (1985: 33) remark: “Most of the empirical work
(using TCE) has focused on examining the choice between vertical integration and the market
(...) Analysis of contracts has been minimal.” A major advance in economics is the
recognition that contracts are incomplete (Berheim and Whinston, 1998) and that self-
enforcement mechanisms must be developed to ensure performance (Klein and Leffler, 1981;
Cusumano and Takeishi, 1991; Sako and Helper, 1998). The long-term contract literature can
be seen as an extension of the standard TCE literature. The basic rationale is that contracts get
increasingly complex when asset specificity increases for three reasons. First, they must help
mitigate potential opportunistic behaviors from the vendor (Klein, 1996 and 2000). Second,
they must enable the client to avoid over-dependence on the vendor. Third, as economic
conditions may evolve, they must be sufficiently flexible to respond to changes in the
environment.
In this paper, we introduce a new concept that we term contractual density. Contractual
density can be defined as the extent to which outsourcing contracts are comprised of elaborate
clauses. For example, dense contracts may detail roles and responsibilities, specific
procedures for monitoring, penalties for non-compliance and processes for dispute resolution.
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The law and economic literature suggests that six main types of clauses are paramount in
outsourcing contracts: (1) duration (Jokow, 1985 and 1987); (2) control clauses (Halvey and
Melby, 1996); (3) incentive clauses (Klein and Leffler, 1981; Cusumano and Takeishi, 1991);
(4) price clauses (Crocker and Masten, 1991; Joskow, 1988b); (5) flexibility clauses (Joskow,
1988a) and (6) end of contract clauses (Masten, 1988; Wiggins, 1991). Each of these six types
of clauses can be more or less elaborate.
Transactional and Core Specificity
Asset specificity is of crucial importance for TCE (Williamson, 1985). In this paper, we
will refer to the TCE concept of asset specificity as transactional specificity. Most scholars
currently distinguish between six dimensions of asset specificity: site, equipment, human
resources, dedicated assets, brand, and temporal (Williamson, 1996). The paradigmatic TCE
case is that of a supplier using transaction-specific assets to deliver a good or service tailored
to the needs of a single customer. In the case of outsourcing as a means to vertically
disintegrate, clients transfer assets to their outsourcing vendor. The transfer of custom-tailored
assets to a vendor is likely to make it quite costly to switch vendors or reintegrate an
outsourced activity. This dependence will yield high transaction costs if there is risk of
opportunism and if rationality is bounded (Williamson, 1985).
Beside transactional specificity, we introduce a new type of specificity. Core specificity
refers to the extent to which the resources that underlie an outsourced activity contribute to
the competitive advantage of the firm. This concept is theoretically rooted in the Resource
Based View of the firm (RBV) (Amit et Schoemaker, 1993; Barney, 1991; Dierickx et Cool,
1989; Grant, 1991; Penrose, 1957; Teece, Pisano et Shuen, 1997; Wernerfelt, 1984).
According to the RBV, firms are repositories of resources and capabilities. While firms are a
bundle of resources, the interactions between resources are far more important than the
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resources themselves. According to Prahalad and Hamel (1988), a firm’s “core competencies”
are the “collective learning in the organization, especially how to coordinate diverse
production skills and integrate multiple streams of technology”.
Barney (1991: 106) suggested that resources must meet four criteria to lead to a
competitive advantage: value, rareness, imperfect imitability, and lack of substitutes.
Commenting on Barney (1991), Monteverde (1997: 100) noticed that: “the concept of a
firm’s set of exceptional strategic resources as defined by the four considerations above has a
parallel in the transaction cost literature as the economic construct asset specificity”. While
core specificity and transactional specificity may be related concepts, they are also different.
Despite some theoretical support (Klein, Crawford and Alchian 1978; Williamson, 1985),
the link between transactional specificity and performance is not straightforward (Nooteboom,
1993; Lohtia, Brooks and Krapfel, 1994). While high core specificity leads to high
performance, high transactional specificity does not necessarily lead to high performance
(Leiblein, Reuer and Dalsace, 2002).
Relational Specificity
Beside transactional specificity and core specificity, we introduce an additional concept of
relational specificity. For an outsourcing client, relational specificity refers to the extent to
which specific resources must be developed to deal with a particular vendor instead of
carrying out an activity in-house (Dyer, 1997; Dyer and Singh, 1998). In the context of
service outsourcing, relational specificity has both a human and procedural dimension (Zaheer
and Venkatraman, 1995). Human specific assets are the skills and knowledge that employees
from the outsourcing client must develop to deal with the supplier (Anderson, 1985; Masten,
Meehan and Snyder, 1991). Procedural specific assets are the business processes of the
outsourcing client that must be customized to meet the requirements of the vendor (Malone,
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Yates and Benjamin, 1987).
When outsourcing clients make specific investments to adjust to their vendor, the resulting
routines have two characteristics. First, they are hard to alter once they have been established.
Second, they are not easy to transfer to another vendor. Hence, relational specificity increases
switching costs and the extent of damage in case of a “hold-up” from the vendor. On the other
hand, it also increases the value of the relationship for the partner, which reduces the
likelihood of a “hold-up” (Asanuma, 1989).
RESEARCH HYPOTHESES
Transactional Specificity and Contract Density
Outsourcing creates an inter-organizational relationship between the client and an outside
vendor. When specific assets are transferred to the vendor, there is a high risk of “hold up”
(Klein, Crawford and Alchian, 1978). Vendors may also seek to standardize the transferred
assets to benefit from greater economies of scale (Ang and Cummings, 1997: 250). This may
result in poor performance or low quality goods rendered to the client. In order to avoid such
standardization, outsourcing clients need to develop complex contracts that can shelter them
from the potential opportunism of the vendor.
The relationship between asset specificity and the complexity of governance structures is a
key assumption of TCE. As Dyer (1997: 535) very clearly stated: “The standard (transaction
cost) reasoning is that as asset specificity increases, more complex governance structures
(i.e., more complex contracts) are required to eliminate or attenuate costly bargaining over
profits from specialized assets”. In the case of outsourcing, complex governance structures
means elaborate contracts with detailed clauses. While most empirical studies using TCE have
tested the link between asset specificity and one of the three governance structures (i.e.,
market, hybrid form and firm), no study has empirically explored the impact of asset
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specificity on a large panel of contractual clauses. By extending Joskow’s (1985 and 1987)
approach to other clauses than duration, we suggest that the benefits of dense contracts
increase with the value of relationship-specific investments.
Hypothesis 1: The higher the transactional specificity, the higher the contractual
density.
Core Specificity and Contract Density
The resources that constitute the core business of a firm must be accumulated during a
long-term process (Dierickx and Cool, 1989; Foss, 1994; Quelin, 1996). When such resources
are transferred to outside vendors, elaborate contracts are necessary to avoid disruption.
Contracts that are not sufficiently dense may not be resilient enough and force the client to
switch vendors or reintegrate an outsourced activity. Because resource accumulation is a
complex and long process, frequent vendor switches or reintegration of an outsourced activity
can be very detrimental to the client.
Contrary to the link between transaction specificity and contract density, the link between
core specificity and contract density is not related to the opportunism hypothesis (Conner and
Prahalad, 1996). Elaborate contracts are necessary to make sure the competitive advantage of
the client will not be threatened (by switching vendors or reintegrating the outsourced
activity) rather than shelter it from the opportunism of its vendor. Hence, we hypothesize a
positive impact of core specificity on the density of outsourcing contract.
Hypothesis 2: The higher the core specificity, the higher the contractual density.
Relational Specificity and Outsourcing Contract Complexity
Relational specificity must be clearly distinguished from transactional specificity. While
transactional specificity refers to the specificity of the outsourced activity, relational
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specificity characterizes the specificity of the relationship with a particular vendor. When a
firm entrusts a vendor with an activity, business process assets dedicated to this particular
outsourcing relationship are developed. These business process assets incorporate both a
human and procedural component (Zaheer and Venkatraman, 1995).
When relational specificity is high, trading partners are able to generate a “relational quasi-
rent” (Aoki, 1988). However, a higher degree of dependence due to investments in relation-
specific assets requires contractual safeguards so that the vendor may no opportunistically
appropriate the “relational quasi-rent”. At the same time, switching vendors must be avoided
as it may also result in the loss of the “relational quasi-rent” (Asanuma, 1989).
Hypothesis 3: The higher the relational specificity, the higher the contractual density.
Core Specificity and Transactional Specificity
Several authors have suggested that capabilities rely on highly idiosyncratic assets (Amit
and Schoemaker, 1993; Barney, 1997; Monteverde, 1997; Reve, 1990). For instance, Barney
(1997: 33) suggested that “resources and capabilities that build up over long periods of time
(history) are likely to be characterized by high levels of transaction-specific investments”.
Similarly, Amit and Schoemaker (1993: 35) contended that “capabilities … refer to a firm’s
capacity to deploy resources, usually combination using organizational processes, to effect a
desired end. They are information-based, tangible and intangible processes that are firm-
specific and are developed over time through complex interactions among the firm’s
resources”.
The underlying rationale of Barney (1997) and Amit and Schoemaker (1993) is the
following. In order to contribute to the competitive advantage of the firm and be core specific,
resources must meet four criteria: value, rareness, imperfect imitability and lack of substitutes
(Barney, 1991). In other words, to be core specific, resources must also be rare (i.e.,
idiosyncratic). However, this link between TCE-based and RBV-based concepts has yet to be
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empirically tested and improved.
Hypothesis 4: The higher the core specificity, the higher the transactional specificity
Environmental Uncertainty and Contractual Density
Most TCE-based empirical studies found that vertical integration is necessary when
relevant contingencies are either numerous or unpredictable. Williamson (1991) suggests that
organizational forms such as outsourcing are very sensitive to environmental uncertainty. As
adaptations cannot be made unilaterally (as with the market) or by fiat (as with hierarchy),
changes in outsourcing relationships require mutual consent.
When environmental uncertainty is high, outsourcing contracts should be very detailed to
make monitoring less difficult and facilitate adjustments (Klein, 1988; MacLeod and
Malcomson, 1993). Elaborate contractual clauses should be built in the contract to permit
adjustments as events unfold (Masten, 1984) and avoid constant renegotiations aimed at
reaching mutual consent (Walker and Weber, 1984). More recently, options theory has
suggested that higher levels of uncertainty require flexible provisions and lead to complex
contracts (Trigeorgis, 1998). Hence, we propose that environmental uncertainty also has a
positive impact on contractual density.
Hypothesis 5: The higher the environmental uncertainty, the higher the contractual
density
Contractual Density and ex post Transaction Costs
The link between the content of outsourcing contracts and transaction costs is quite
straightforward. According to Balakrishnan and Wernerfelt (1986: 348): “As the number of
contingencies in the contract goes up, it becomes more expensive to write, monitor and
enforce”. When a contract contains elaborate clauses, the ex post transaction costs are high
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because of the expenses involved in: (1) ensuring that the vendor fulfills the contractual
requirements (i.e., monitoring costs) and (2) enforcing the contractual clauses (i.e.,
enforcement costs) (Barthelemy, 2001; Williamson, 1991). Thus, the more complex the
contracts, the more expensive it becomes to manage the relationship with the outsourcing
vendor. However, this link has seldom been tested and there has not been a lot of change since
Williamson (1985: 105) observed: “A common characteristic of (TCE-based empirical)
studies is that direct measures of transaction costs are rarely attempted”.
Hypothesis 6: The higher the contractual density, the higher the ex post
transaction costs.
The hypotheses are summarized in Figure 1 below.
<-------------- Insert Figure 1 about here -------------->
RESEARCH METHOD
Sample and Data Collection
We collected detailed primary data on outsourcing operations through a survey of
European and American firms. As there was no systematic database on “vertical
disintegration” operations, we conducted an exhaustive electronic search of two major
databases: ABI/INFORM-GLOBAL and REUTERS. We were able to compile an initial
sample of 816 “vertical disintegration” outsourcing contracts signed between 1992 and 1997.
We chose this time frame because we wanted to exclude older outsourcing contracts, as the
managerial turnover for these contracts would have led to the gathering of inaccurate
information on the conditions under which the contracts were signed.
The survey was carried out in four phases. First, measurement scales were developed based
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on relevant literature and interviews with twenty European and non-European managers
responsible for outsourcing contracts. Thereafter, the questionnaire was tested with three
French managers. Based on their responses, the pre-test was revised and re-tested with three
Anglo-Saxon managers (i.e., one American, one British and one Australian). Finally, we
mailed the questionnaires to senior executives in charge of managing outsourced activities for
the 816 companies in our initial sample. According to the single respondent approach, these
executives are those most apt to provide the necessary information (John and Reves, 1982).
Two follow-up letters were sent after the initial mailing.
A total of 91 completed questionnaires were received, representing a response rate of
approximately 11%. Of these 91 questionnaires, 9 could not be used because of missing data,
leaving 82 useful questionnaires. As the dependent variables were measured with the same
questionnaire as the independent variables, common methods may skew the results (i.e.,
respondents may give self-justifying answers). In order to overcome the methodological
limitations of self-report measures, we sought to develop “objective” measures for all the
dependent variables (i.e., contractual clauses and ex post transaction costs).
We were also concerned about the validity of our measurements because we relied on
questionnaires completed solely by outsourcing clients. However, Heide and John (1990)
found that buyers and suppliers share consistent perceptions of exchange relationship
attributes. A potential response bias was tested for by comparing the respondents and non-
respondents on two key criteria: total sales and number of employees. The data were obtained
from Compact Disclosure and Kompass Europe (i.e., its European equivalent). This common
technique was used in previous outsourcing studies such as Teng, Cheon and Grover’s (1995)
and Ang and Cummings’s (1997). Like Teng, Cheon and Grover (1995), we randomly
selected a sub-sample of 30 non-respondents and compared their total sales and number of
employees with those of the 82 respondents. The results of the t-tests (respectively t = 0.346
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for total sales and t = 0.625 for number of employees) showed no difference at the
significance level of 0.05. Hence, it is possible to generalize the results of the study to the
entire sample.
Measures and Variables
The constructs were operationalized with a mix of original and adapted scales derived from
the conceptual definition of each construct, the relevant literature and field interviews.
Transactional Specificity
Though transactional specificity is probably the most important TCE concept, there is no
commonly accepted method for operationalizing it (Lohtia, Brooks and Krapfel, 1994; Klein
and Shelanski, 1995). Generally, assets are considered to be specific when they cannot be
redeployed for alternative uses (Klein and Leffler, 1981; Williamson, 1985: 53). In the case of
outsourcing, employees and equipment are transferred to the vendor. Hence, the
“redeployability” criterion does not make much sense. Consistent with previous research
(Anderson and Weitz, 1986; Poppo and Zenger, 1998), we operationalized asset specificity as:
(1) the cost of switching vendors; (2) the time needed to switch vendors; (3) the cost of
reintegrating the outsourced activity; (4) the time needed to reintegrate the outsourced
activity. All four variables were measured on a five-point Likert scale ranging from “very
low” to “very high”.
Core Specificity
There is no accepted tool to evaluate the degree of core specificity of an activity. While
criteria such as value, rareness, non-imitability and non-substitutability (Barney, 1991) have
been developed to spot the “crown’s jewels” of the firm (Montgomery, 1995), they are not
very useful to compare outsourced activities. Hence, we operationalized core specificity with
a mix of criteria from the managerial literature. The four items were the: (1) degree to which
15
the activity contributed to the overall profitability of the firm (Barney, 1997; Quinn and
Hilmer, 1994); (2) degree to which the activity was integrated within the firm (Quinn and
Hilmer, 1994; Willcocks, Fitzgerald and Feeny, 1995); (3) degree to which the activity
enabled the firm to differentiate itself from its competitors in the eyes of the customers
(Leonard-Barton, 1992; Stalk, Evans and Schulman, 1992); (4) degree to which the activity
was viewed as strategic (Teng, Cheon and Grover, 1995). All four variables were measured
on a five-point Likert scale from “very little” to “very highly”.
Relational Specificity
Consistent with Zaheer and Venkatraman (1995), we operationalized relational specificity
as the extent to which: (1) dealing with the outsourcing vendor implied changes for the
employees in the client firm; (2) dealing with the outsourcing vendor implied changes for the
overall functioning of the client firm. Both variables were measured on a five-point Likert
scale from “very little” to “very highly”.
Environmental Uncertainty
We operationalized environmental uncertainty as the difficulty to assess the future needs of
the outsourcing clients in terms of required: (1) technology (Balakrishnan and Wernerfelt,
1986; Walker and Weber, 1984, 1987); (2) activity level (Anderson and Schmittlein, 1984;
Walker and Weber, 1984; John and Weitz, 1988); (3) performance level; and (4) vendor
skills. The last two variables were included in our research upon the suggestion of managers
from the field interviews. All four variables were evaluated on a five-point Likert scale
ranging from “very easy ” to “very hard to assess”.
Contractual Density
Regarding contractual density, we had to develop our own measures based on the long-
term contract literature. Six different clauses were operationalized: (1) duration (Jokow, 1985
and 1987); (2) control clauses (Halvey and Melby, 1996); (3) incentive clauses (Klein and
16
Leffler, 1981; Cusumano and Takeishi, 1991); (4) price clauses (Crocker and Masten, 1991;
Joskow, 1988b); (5) flexibility clauses (Joskow, 1988a) and (6) end of contract clauses
(Masten, 1988; Wiggins, 1991). For each clause, we summed three to five dummies derived
from literature (see the Appendix 1).
Ex post Transaction Costs
Our measure for transaction costs is based on Williamson (1985) and Wallis and North
(1986). These authors suggested that the costs associated with employees working in
transaction functions (i.e., functions not directly associated with production) could be used as
a direct estimate of transaction costs. Consequently, we operationalized ex post transaction
costs as: (1) the number of employees responsible for monitoring the contract and managing
the relationship with the outsourcing vendor, (2) the annual cost of monitoring the contract
and managing the relationship with the outsourcing vendor. In order to avoid
heteroscedasticity problems (i.e., disproportionate effect from a skewed distribution), the log
transform of both variables was used in the analyses. Finally, it should be noted that our
measures do not capture the remaining residual loss from choosing outsourcing over vertical
integration (Hill, 1995). We focus exclusively on the cost borne to reduce “shirking” in
outsourcing relationships.
Control for Response Bias and Data Heterogeneity
Industry
Our data were collected in randomly selected industries. Existing evidence indicates that
industry type has no impact on outsourcing strategies (Loh and Venkatraman, 1992; Teng,
Cheon and Grover, 1995). However, we opted to include a binary dummy variable for service
and industrial sectors.
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Type of Outsourced Activity
Most empirical studies on service outsourcing focus on Information Technology (IT) (e.g.,
Ang and Straub, 1998; Saunders, Gebelt and Hu, 1997; Lacity and Willcocks, 1998) and
Research and Development activities (e.g., Pisano, 1990; Ulset, 1996). As we believe the TCE
framework to be sufficiently powerful to simultaneously handle different activities, we used a
sample composed of different service activities. As IT and telecommunications are the most
“pervasive” activities, we included a dummy variable for IT and non-IT activities (Applegate,
McFarlan and McKenney, 1999).
Geographical Origin
Since we collected data both in Europe and North America, a binary dummy variable (i.e.,
European and American outsourcing contracts) was included to control for the impact of the
geographical origin.
<-------------- Insert Table 1 about here -------------->
Statistical Method
Two statistical techniques were used to test the model: Partial Least Square (PLS) and PLS
regression. PLS (Lohmöller, 1989; Hulland, 1999) was preferred over LISREL (Jöreskog and
Sörbom, 1989) because it requires less stringent assumptions about the randomness of the
sample and the distribution of variables. It is also better suited to deal with small data samples
(Fornell, 1982; Wold, 1982, 1985). We also resorted to PLS regression (Umetri, 1996). PLS
regression is a statistical method that can deal with multicollinearity issues. Multicollinearity
becomes a concern when there are high correlation among the independent variables. Our
model has built-in multicollinearity. For instance, we simultaneously expect: (1) core
specificity to impact transactional specificity; (2) core specificity and transactional specificity
to impact contractual density. The PLS regression algorithm was initially developed by Wold,
18
Martens and Wold (1983) and Wold, Albano, Dunn, Esbensen, Hellberg, Johansson and
Sjöström (1983). It has been very frequently used in chemistry but it can be very useful for
management studies as well. Its mathematical properties have been described in Helland
(1988) and Höskuldsson (1987).
ANALYSIS AND RESULTS
The model was estimated in two stages. First, we used PLS to evaluate the reliability and
validity of the measurement model (i.e., links between manifest and latent variables). Second,
we used PLS regression to study the causal relationships within the structural model (i.e.,
links between the latent variables).
Measurement Model Results
Three criteria must be used to assess the adequacy of the measurement model (Hulland,
1999), the results of which were obtained through PLS (Lohmöller, 1989). Individual item
reliability was assessed by examining the correlation (i.e., loadings) of the manifest variables
with their respective latent variable. Individual item reliability is usually deemed acceptable
when it is higher than 0.7 (Nunally, 1978). The item “cost to reintegrate the outsourced
activity” was dropped as its loading was below 0.5. While most other items had loadings
higher than 0.7, the loadings of the contractual density items were generally comprised
between 0.6 and 0.7. As this paper is the first to operationalize contractual density, we
considered these measures to be exploratory and decided to keep all six items. (see Table 2).
Convergent validity was assessed through the “internal consistency” measure1 (Fornell and
Larcker, 1981). Internal consistency is deemed acceptable when higher than 0.7. As shown in
Table 3, the constructs all have acceptable internal consistency. Discriminate validity was
1 Internal consistency = (Σ λyi)2 / ((Σ λyi2) + Σ var (εi))
19
assessed through Average Variance Extracted (AVE)2 (Fornell and Larcker, 1981). For
discriminant validity to be acceptable, the correlation between latent variables must be
inferior to the square root of the AVE of every latent variable. As shown in Table 4, this
criterion is met for all pairs of constructs.
<-------------- Insert Tables 2, 3 and 4 about here -------------->
Structural Model Results
The structural model results were obtained through PLS regression (Umetri, 1996). The
PLS regression coefficients and R2 can be interpreted as multiple regression coefficients and
standard R2 (see Table 5).
<-------------- Insert Table 5 about here -------------->
Hypothesis 1 was supported (β = 0.25; p < 0.01). High transactional specificity results in
dense contracts. The higher the level of transactional specificity, the higher the risk of “hold
up” (Klein, Crawford and Alchian, 1978) and asset standardization (Ang and Cummings,
1997). In order to deal with a potentially opportunistic vendor, elaborate contractual
safeguards must be developed.
Hypothesis 2 was supported (β = 0.15; p < 0.05). Core specificity has a positive impact on
the density of outsourcing contracts. Firms that outsource activities close to their “core
business” need to have a total control over the vendor to avoid disruption. Hence, they tend to
develop tight and precise contracts.
Hypothesis 3 was supported (β = 0.11; p < 0.10). Relational specificity has a positive
2 Average Variance Extracted = Σ λyi2 / (Σ λyi2 + Σ var (εi))
20
impact on the density of outsourcing contracts. When outsourcing clients adapt to their
vendors, they tend to develop elaborate contracts to protect the “relational quasi-rent”.
Hypothesis 4 was supported (β = 0.22; p < 0.05). Core specificity has an impact on
transactional specificity. This result suggests that activities that are close to the “core
business” of a firm also rest on transaction specific assets.
Hypothesis 5 was supported (β = 0.21; p < 0.01). The higher the uncertainty about the
future needs of the outsourcing client, the more elaborate clauses must be included in the
contract in order to deal with unexpected contingencies.
Finally, hypothesis 6 was also empirically supported (β = 0.34; p < 0.01). Dense
outsourcing contracts lead to high monitoring and enforcement costs. In other word, every
contractual clause has a cost.
Control Variables
As the data used in this paper were heterogeneous, we also tested whether the findings
were robust over different countries, industries and activities. Of the three variables, only
“activity” turned out to have a positive and significant impact on the dependent variables. IT
outsourcing operations are generally characterized by higher contractual hazards, which result
in denser contracts and higher ex post transaction costs. In order to further explore the impact
of this variable, we re-ran the model on two sub-samples (i.e. IT activities vs. non-IT
activities). Our findings turned out to be robust even when splitting the sample into IT
outsourcing vs. non-IT outsourcing operations. Hence, the logic of our model was respected
regardless of industry, country or activity characteristics.
DISCUSSION
TCE is the main framework to discriminate between activities that should be internalized
and activities that should not. Our study used constructs from standard TCE such as
21
transactional specificity and environmental uncertainty. However, the unique characteristics
of outsourcing (e.g., transfer of an in-house activity to the vendor, further need to access to
service…) may limit the explanatory power of TCE. In order to take the unique characteristics
of outsourcing into account, we introduced the concepts of core specificity and relational
specificity. We focused on outsourcing as a way to vertically disintegrate that means the firm
has largely invested in specific assets before contracting out. As several managerial studies
(Huber, 1993; Cross, 1995; Quinn, 2000), we stressed the critical nature of the relationships
between outsourcing clients and their vendors, especially for services that have direct
connections with manufacturing and the “core businesses”.
In this paper, we decomposed the concept of specificity into three different dimensions.
While the concept of transactional specificity is classic, core specificity underlines the fact the
firm has previously invested in resources that were valuable and rare enough to serve its
strategic objectives. Obtaining an efficient relationship with the vendor also requires some
specific procedures and interfaces between the client and the vendor (i.e., relational
specificity).
The three dimensions of specificity we decomposed were found to be positively associated
with contractual density. The contractual density was also significantly related to the ex post
transaction costs. One other variable of interest –the environmental uncertainty– had positive
effect on contractual density. From this analysis, we can begin to construct a sketch of the
outsourcing decision which (1) is related to specific assets, (2) requires a contract that is dense
enough, (3) induces ex post transaction costs. These findings mean that if Williamson’s view
(1975, 1985) that asset specificity increases transaction costs can be valuable, it must be
carefully qualified. Certain characteristics of contract (e.g., penalties, incentives, and
monitoring) can compensate the opportunism risk and mitigate hazards. The analysis of
contract content must consider how contract clauses create incentives but also how they favor
22
self-enforcement (Klein, 1996). As contracts are always incomplete, it is often useful to make
the relationship self-enforcing over a large range of post-contractual conditions. This is why
our “contractual density” construct includes both control, incentive and flexibility clauses. We
also integrated features that are specific to outsourcing contracts such as end-of-contract
clauses.
Outsourcing is quite paradoxical as it consists in entering a contractual agreement with a
vendor after investing in-house. The TCE empirical literature has repeatedly stressed that
asset specificity and uncertainty diminish the attractiveness of outsourcing as compared to
vertical integration (Anderson and Schmittlein, 1984; Masten, 1984). Provided the contract is
dense enough, our results suggest that it may be appropriate to outsource activities even when:
(1) the level of specificity is high; (2) environmental uncertainty makes performance
specification, verification and monitoring difficult. Therefore, even if they help reinforce the
core business, support service activities may not necessarily be internalized.
Hill (1990) questioned Williamson’s (1979) assumption that if asset specificity is high,
outsourcing should be replaced by vertical integration because of the risk of opportunism.
Some scholars have also argued that asset specificity is not a sufficient condition for vertical
integration (Walker and Poppo, 1991). Our study suggests that firms may outsource specific
assets even when the level of environmental uncertainty is high.
In this paper, we have shown that the various types of specificity and environmental
uncertainty both have a positive impact on ex post transaction costs via an increase in
contractual density. Quite noticeably, our results contradict conclusions from the managerial
literature. For example, Lacity and Willcocks (1998) argued that short-term contracts are
always better than long-term ones. Harris, Giunipero and Hult (1998) found that flexible
contracts should always be used. On the contrary, our results suggest that there is no “one best
way” and that the clauses should be contingent on the contractual hazards.
23
The findings with respect to specificity and uncertainty are consistent with the findings of
Leiblein et al. findings. The TCE perspective is bolstered by the significance of variables
related to transactional specificity and environmental uncertainty. Our results are somewhat
different from those of previous examinations of make or buy decision (Lacity and Willcocks,
1998). The data here support Joskow’s findings (1985, 1988) of significant relationship
between specificity and long term contracting. Moreover, the results of this study contribute
to a better understanding of what is possible to contract in case of high level specificity. In
sum, the link between contractual hazards, contractual density and ex post transaction costs
improve the TCE predictions.
Limitations
While this study provides important implications for firms, it also has several limitations.
First, we focused on outsourcing agreements and did not study the rationale for outsourcing.
Second, our “contractual density” variable did not capture the increasing role of trust and
partnerships between outsourcing clients and vendors. The study basically suggested that
managers craft elaborate contracts when they face high contractual hazards. However,
relational norms such as trust could be used as substitutes for dense contracts or even vertical
integration (Uzzi, 1997; Dyer and Singh, 1998). Third, since we wanted to avoid crude and
imprecise proxies, some of the constructs were based on the personal evaluation of managers
involved in outsourcing decisions. Although managers in charge of outsourced activities
responded to the survey, meaning that the quality of their responses is assured, the reliability
of our variables was not tested on a very large sample. Despite these limitations, this study is
one of the first to empirically investigate outsourcing as a means to vertically disintegrate, and
hopefully, will open doors for further research.
Future Research
Several future research directions seem promising. First, the interplay between the formal
24
and informal sides of outsourcing relationship management could be further explored. In this
paper, we have focused on the formal side (i.e., the contract) rather than on the informal side
(i.e., relational norms and trust). From the literature, it is still not clear whether relational
norms and contracts should be viewed as substitutes or complements. Some authors contend
contracts are costly substitutes for relational norms (Uzzi, 1997). Contracts may even prevent
relational norms from developing as they signal distrust (Ghoshal and Moran, 1996;
Macaulay, 1963). On the other hand, formal contracts and relational norms may be seen as
complements.
The second promising research avenue is the impact of boundary decisions on the various
dimensions of firm performance. To date, little is known about the performance outcomes of
sourcing decisions. Expected outsourcing benefits include cost reduction, quicker response to
changes in the environment, and focus on the core business (Quinn and Hilmer, 1994). On the
other hand, outsourcing may result in a loss of capabilities vis-à-vis actual or potential
competitors (Bettis, Bradley and Hamel, 1992). An intermediate position is that the
performance of sourcing decisions is contingent on contractual hazards. While the strategy
literature has paid a great deal of attention to the factors that influence sourcing decisions,
little empirical work has focused on the performance implications of these decisions (D’Aveni
and Ravenscraft, 1994; Masten, 1993; Poppo and Zenger, 1998).
Further research could also give some thought to how current sourcing decisions are
influenced by past ones. Argyres and Liebeskind (1999) have recently introduced the notion
of governance inseparability to describe situations where there are interdependencies between
sourcing decisions. More generally, the RBV suggests that firms that have a great deal of
outsourcing expertise are more likely to outsource further activities than firms with less
refined outsourcing skills (Barney, 1999).
25
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APPENDIX: CONTRACTUAL DENSITY
Contract duration Control clauses
1. Service level reports with service level measures 2. Regular client and supplier meetings 3. Internal or external end-user surveys 4. Annual review 5. Cash penalties for nonperformance
Incentive clauses 1. Cash bonuses in case of performance superior to that specified in the contract 2. Risk and reward sharing 3. Extension of the outsourcing contract to other parts of the outsourced activity
provided the performance of the supplier is sufficient 4. Escalation procedures
Price clauses 1. Fixed price 2. Price indexing of price on a market average cost 3. Prices indexing on best vendors’ prices through « benchmarking »
Flexibility clauses
1. Adjustment of charges to changes in your business with a guaranteed minimum volume for the supplier
2. Adjustment of charges to changes in your business with non-guaranteed minimum volume for the supplier
3. Evolution of technology towards market standards End of contract clauses
1. Material reversibility with supplier assistance at the end of the contract (i.e., option to re-buy premises or equipment)
2. Human reversibility with supplier assistance at the end of the contract (i.e., option to hire employees of the supplier)
3. Material reversibility with supplier assistance in case of anticipated contract severance on your behalf
4. Human reversibility with supplier assistance in case of anticipated contract severance on your behalf
31
Figure 1. Theoretical model
Contractualdensity
Transactionalspecificity
Relationalspecificity
H3 (+)
H4 (+)
Corespecificity
H6 (+)Ex post
transaction costs
Environmentaluncertainty
H5 (+)
H1 (+)
H2 (+)
Table 1. Sample description Industry N % of sample Manufacturing 52 63% Services 30 27% Country Europe 62 76% North America 20 24% Activity Information Technology 44 54% Non-Information Technology 38 46%
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Table 2: Loading by construct Variables used in the model Loadings
(ξ1) Core specificity Degree to which the activity contributed to the overall profitability of the firm Degree to which the activity was integrated within the company Degree to which the activity enabled the company to differentiate itself from its competitors in the eyes of the customers Degree to which the activity was viewed as strategic
0.84 0.70
0.82 0.80
(ξ2) Relational specificity Extent to which dealing with the vendor implied changes for the employees of the client firm Extent to which dealing with the vendor implied changes for the overall functioning of the firm
0.95
0.81
(ξ3) Environmental uncertainty Difficulty of evaluating the future needs in terms of expected technology Difficulty of evaluating the future needs in terms of expected activity level Difficulty of evaluating the future needs in terms of expected performance level Difficulty of evaluating the future needs in terms of expected vendor skills
0.86 0.77 0.73 0.84
(η1) Transactional specificity Time to switch suppliers Time to reintegrate the outsourced activity Cost to switch suppliers
0.91 0.74 0.70
(η2) Contractual density Duration Control clauses Incentive clauses Price clauses Flexibility clauses End of contract clauses
0.85 0.60 0.59 0.68 0.62 0.62
(η3) Ex post transaction costs Number of employees in charge of monitoring the contract and the relationship with the supplier (log) Cost per year of managing the contract and the relationship with the outsourcing supplier (log)
0.91
0.96
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Table 3: Internal consistency and Average Variance Extracted by construct
Latent variables Number of items Internal
consistency Average Variance
Extracted (ξ1) Core specificity 4 0.87 0.61
(ξ2) Relational specificity 2 0.88 0.78
(ξ3) Environmental uncertainty
4 0.88 0.64
(η1) Transactional specificity 3 0.83 0.62
(η2) Contractual density 6 0.82 0.43
(η3) Ex post transaction costs 2 0.93 0.87
Table 4: Correlation between latent variables Latent variables (ξ1) (ξ2)
(ξ3) (η1) (η2) (η3)
(ξ1) Core specificity 0.78 0.25 0.14 0.23 0.28 0.17
(ξ2) Relational specificity 0.88 0.16 0.23 0.19 0.14
(ξ3) Environmental uncertainty
0.80 0.34 0.39 0.21
(η1) Transactional specificity 0.79 0.47 0.42
(η2) Contractual density 0.66 0.41
(η3) Ex post transaction costs 0.93
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Table 5: PLS regression parameters with control variables
Latent variables (η1) Transactional
specificity
(η2) Contractual
density
(η3) Ex post
transaction costs
(ξ1) Core specificity 0.22** 0.15**
(ξ2) Relational specificity 0.11*
(ξ3) Environmental uncertainty
0.21***
(η1) Transactional specificity
0.25***
(η2) Contractual density 0.34***
Industry 0.04 -0.02 -0.02
Country 0.04 -0.06 0.12
Type of outsourced
activity
0.26** 0.20*** 0.16*
R2 0.13 0.27 0.32
* p < 0.10 , ** p < 0.05 , *** p < 0.01
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