Information Technology Outsourcing: Asset Transfer and the Role of Contract Young Bong Chang Business School Sungkyunkwan University 25-2, Sungkyunkwan-ro, Jongno-Gu, Seoul,Korea,110-745 Seoul, Republic of Korea [email protected]Vijay Gurbaxani Center for Digital Transformation The Paul Merage School of Business University of California Irvine, CA 92697-3125 [email protected]Kiron Ravindran IE Business School Calle María de Molina, 11-13-15 28006 Madrid, Spain [email protected]June 2015
Transcript
Information Technology Outsourcing: Asset Transfer and the Role of Contract
Young Bong Chang
Business School Sungkyunkwan University
25-2, Sungkyunkwan-ro, Jongno-Gu, Seoul,Korea,110-745 Seoul, Republic of Korea
Information Technology Outsourcing: Asset Transfer and the Role of Contract
1. Introduction
External provision has become the predominant mode of acquiring information technology
services. The worldwide market for IT outsourcing (ITO) was estimated at $288 billion in 2013 and
predicted to grow at over 5.4% annually through 2015 (Overby 2013). Over 60% of the respondents in a
large global survey indicated that outsourcing was a standard practice within their company and reported
high levels of satisfaction (Deloitte 2012). While these data indicate the dominance of ITO as the
preferred delivery option, examples of contractual disputes and unraveled outsourcing relationships are
also not uncommon (DiamondCluster 2006; Deloitte 2012). These observations suggest that companies
see economic benefit in sourcing IT services from external providers, but that these relationships are also
fraught with risk.
The academic literature has recognized this tradeoff. Prior research has noted the advantages that
specialized providers possess, generated by economies of scale and specialization. It has also recognized
the significant transaction costs inherent in ITO arrangements, stemming from the deployment of
relationship-specific assets and the considerable technological and business uncertainty in multi-year
deals. While some analysts have argued against external service provision (Wholey et al. 2001) because
of the difficulty in writing efficient contracts in these settings, the widespread adoption of IT outsourcing
indicates that its economic advantages seem to outweigh the contractual concerns. Economic theory
suggests that outsourcing contracts will seek to maximize the gains from the arrangement and economize
on transaction costs. This paper studies how contracts can be used to manage the tradeoffs between the
risks inherent in outsourcing arrangements with the available gains.
Before proceeding further, we describe the scope of IT outsourcing arrangements that we are
interested in given the many different interpretations in the literature. We study ITO arrangements that
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are multi-year, annuity-based arrangements in which a firm provides services on a continuous basis for
the duration of the contract.1 In this paper, we define ITO as, “A long-term contractual arrangement in
which one or more service providers are assigned the responsibility of managing all or part of a client’s
information systems infrastructure and operations.” This definition is consistent with academic usage (see
Dibbern et al. 2004) and with that of industry analysts (International Data Corp. 2006; Gartner 2008).
More importantly, our definition sets a specific context for the relationship, which helps identify the
nature of the risk and the potential gains in the ITO relationship.
Consider a typical situation where a client firm has historically sourced IT services internally and
“owns” the assets underlying service delivery – data center and networking equipment, personal
computers and mobile devices, proprietary software, facilities, human capital and so on. The firm then
decides to source some or all of these IT services from an external provider with the goal of improving
performance on dimensions such as cost and quality. In many, but not all cases, the vendor firm, as part of
the outsourcing arrangement, acquires assets that were used in service delivery - hardware, software,
people and facilities - from the client and uses them to deliver the contracted services. While there can be
other motivations for asset transfer, one particularly important reason is that achievement of service
improvements requires upfront and ongoing investments in the production assets.
This requirement for investment in the underlying production assets sets up the essential tension
in this paper. The argument in favor of asset ownership by the vendor derives from property rights theory,
which recognizes that firms will likely not make investments in assets they do not own. In this view,
conferring the associated property rights to the vendor provides it with the incentive to continue to invest
in the relationship-specific assets (RSA) enabling the provision of lower cost or higher quality services
over the life of the contract (Grossman and Hart 1986). The argument against transferring asset ownership
to the vendor, derived from transaction cost economics, is that the transfer of RSA intensifies ‘bilateral
1 We exclude arrangements that are project or task based and defined in terms of specific deliverables such as bespoke software development. Also note that our dataset predates the emergence of cloud-based delivery.
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dependence’ in the relationship and leads to increased transaction risk (Williamson 1975; Klein et al.
1978). Williamson (1985) observed that the existence of a durable, transaction-specific asset is often the
source of large market transaction costs since special arrangements, typically long-term contracts, are
necessary to prevent both parties from acting opportunistically after one firm makes an investment in a
specific asset.
The client’s switching costs increase when the vendor owns the assets by making it more difficult
to terminate the vendor and bring services back in-house or transfer their delivery to another vendor. This
increases the likelihood for a vendor to engage in post-contractual opportunistic behavior.
Simultaneously, the vendor’s risk also increases as a result of its significant upfront and largely sunk
investment in the acquisition of these RSA. Given their transaction-specific nature, which we discuss
more fully later, the market value of these depreciating assets is lower than their value in their current use.
This leads to an improvement in the client firm’s bargaining position. It is important to note that in
annuity-based outsourcing arrangements at the time, the delivery assets purchased by the vendor were
used to provide service to the client from which they were purchased. That is, vendors did not typically
commingle technology assets between their various clients.
In situations where market exchange occurs in spite of high transaction costs, contracts are the
primary mechanism by which these risks can be mitigated (Joskow 1985; Kern and Willcocks 2001).
While all ITO arrangements are characterized by some level of transaction-specific investments and
switching costs, the transfer of assets underlying service delivery has the potential to substantially
increase the risk of these arrangements to both parties. Therefore, contracts with asset transfer should
include additional protections in the form of clauses that safeguard the interests of both parties. This
implies that there should be observable differences in contracts with and without asset transfer.
Of course, the goal of an ITO arrangement is to achieve the client firm’s objectives, which most
often are related to decreasing cost, improving quality, and increasing the business impact of technology.
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It is well recognized that asset ownership, performance incentives and job design2 are complementary
dimensions of a management system (Holmstrom and Milgrom 1991; 1994). Therefore, a well-designed
management system that takes these complementarities into account should lead to better performance
outcomes. In our case, if assets are transferred to the vendor, the set of outsourced tasks and performance
incentives incorporated in the agreement should complement asset ownership and lead to better outcomes.
The simultaneous goals of achieving the client’s strategic objectives for outsourcing and
mitigating the risks of asset transfer creates the central challenge that motivates our research question:
How are contracts used to improve IT outsourcing outcomes both in terms of the achieving the goals for
outsourcing and mitigating the risk of ex-post opportunism associated with the presence of asset transfer?
We develop a conceptual framework based in property rights theory and transaction cost
economics to study the use of various contractual elements to improve outcomes and to manage risk.
Using this framework, we develop hypotheses about the use of specific contractual clauses to protect the
interests of the client and the vendor in case of asset transfer, and whether contractual features lead to
better outcomes. Utilizing our focused definition of IT Outsourcing, we implemented a survey to build a
reasonably homogenous dataset of ITO engagements in which the source and nature of hold up risk is
relatively similar across deals. We conduct a preliminary analysis on this data to verify that there are, in
fact, observable differences between contracts with and without asset transfer. Next, we formally test the
hypotheses by comparing contracts where assets are transferred (CA) to contracts where assets are not
transferred (CNA).
We establish that when assets are transferred, contract structure does in fact differ considerably
relative to the case where the client continues to own the assets. Specifically, we find that these contracts
are more extensive with several clauses dedicated to specifying cooperation from both client and vendor.
These contracts are also of longer duration. Moreover, we show that asset transfer to the vendor is
2 Job design refers to the delegation of specific tasks and associated decisions as to how they will be conducted to the agent or vendor.
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complemented by a specific set of contract features - flexible pricing mechanisms and incentives for
achieving improved performance outcomes - that jointly lead to improved ITO performance.
We add to the empirical literature on the role of contract by conducting an empirical examination
of contract structure in ITO arrangements that represent a comprehensive, and often strategic, sourcing
relationship. Our study makes several contributions to the understanding of contracts as a means of
governing ITO relationships both by mitigating transaction risk and by helping assure better ITO
performance outcomes. First, our results complement earlier research by providing a new understanding
of how the transaction risks associated with asset transfer can be mitigated using contract. Prior studies
have relied on indirectly inferring asset specificity from the nature of the outsourced tasks usually due to
data limitations. We take a fundamentally different approach to specific assets. That is, we examine how
contracts can be used to mitigate the transaction risks associated with the transfer of assets essential to
service delivery from the client to the vendor. Second, our context is very different from, but
complementary to prior research, in that we focus on mitigating the risks of opportunism associated with
vendors’ ownership of durable transaction-specific assets in large multi-year IT outsourcing
arrangements, which in the traditional Williamsonian (1985) sense is the contracting challenge.
Importantly, asset transfer is both observable and contractible. A property of our unique dataset is
that the level of risk is very high given the scale and scope of the transaction. Our primary dataset allows
us to incorporate and account for factors that are generally unobservable in secondary data, yet can
critically influence contract design, such as the strategic objectives for the arrangement. In contrast, most
prior studies have used secondary datasets, requiring the grouping of different kinds of IT outsourcing
arrangements with substantial differences in the set of outsourced activities and hence in their individual
risk profiles. These prior studies, in the main, are focused on smaller deals with lower potential economic
consequences. Finally, our study examines the role of contract in the achievement of the client’s goals for
ITO, which of course, is the primary purpose of external service provision. Specifically, we draw on
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Grossman and Hart (1996) and Holmstrom and Milgrom (1991,1994) to examine the complementarity
between vendor ownership of assets, performance incentives and job design.
This paper is structured as follows. The next section presents our theoretical approach and a review
of the relevant literature. Section 3 derives relevant hypotheses on the role of contract. In section 4, we
present the data and the results of a preliminary analysis, which we conduct to verify that there are, in
fact, observable differences between contracts with and without asset transfer. This is followed by the
formal analysis and presentation of our results in section 5. In section 6, we discuss the results and
conclude with the implications of our findings and the limitations of our study.
2. Theory and Related Literature
Our research adopts the perspective of incomplete contracting. The central premise of Incomplete
Contract Theory is that contracting for all future states of the world is either impossible due to bounded
rationality (Williamson 1975) or inefficient due to the ex-ante cost of contract design (Segal 1999).
Within this framework we examine two closely related streams of literature: Property Rights Theory
(PRT) which deals with ex-ante incentive alignment (Grossman and Hart 1986; Hart and Moore 1990)
and Transaction Cost Economics (TCE) (Williamson 1985) which deals with contracting and ex-post
economizing of transaction costs. PRT proposes the transfer of residual rights3 to the relation-specific
assets to the vendor as an incentive for vendor investment. However, TCE cautions against the risks
associated with the potential opportunism that may arise from transferring these residual rights to a third
party. The two theories adopt complementary perspectives in that one view focuses on the benefits of
asset transfer ex-ante while the other highlights its costs ex-post.
Property Rights Theory
PRT applies in situations where an agent requires an asset to deliver a service to the principal. It
is assumed that the effort invested by agents is not verifiable even if it is observable. It can then be shown 3 Residual rights, in contrast to specific rights, are those that have not been explicitly specified in the contract.
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that both ownership of the RSA either by the principal or jointly by both parties can lead to
underinvestment in these assets by the agent. Agents might choose to under-invest in the asset
anticipating that the principal might force the agent to renegotiate terms after the investment has been
made. On the other hand, owning the residual rights gives the agent an incentive to invest. Thus,
Grossman and Hart (1996) argue that allocation of ownership rights is not a function of coordination cost
or contracting “ink cost” but rather an incentive mechanism to enhance efficient investments, ex-ante. The
underlying assumption here is that aligning incentives ex-ante will prevent opportunistic behavior ex-
post.
Optimal arrangements for production must keep asset ownership, job design, and explicit
incentives in balance. In situations where effort is not verifiable as is the case in our context, and if the
principal owns the assets required for service delivery, optimal contracts tend to have restricted incentives
for production, especially in multi-task settings. However, when asset ownership shifts to the vendor, and
the vendor must allocate effort to multiple tasks, the optimal incentive contract will provide stronger
incentives to engage in production to prevent the vendor from being too cautious (Holmstrom and
Milgrom 1991). Hence, no discussion of services outsourcing is complete without simultaneous
discussion of the appropriate asset ownership structure and the incentive mechanisms.
Various streams of literature, ranging from sociology to law, have adopted the PRT approach to
examine the allocation of ownership and decision rights. From our perspective, PRT offers an appropriate
approach to examine asset transfer in IT outsourcing and suggests that, “The relevant comparison is not
between the non-integrated outcome and the complete contract outcome but instead between a contract
that allocates residual rights to one party and a contract that allocates them to another” (Grossman and
Hart 1986).
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Transaction Cost Economics
TCE, developed largely by Williamson (1975; 1985), has focused on understanding the
relationship between governance structure and the characteristics of exchange. It holds that firms would
choose to adopt a market-based governance mechanism over a hierarchical governance mechanism if
production cost advantages outweigh transaction costs. This viewpoint of economic governance that
balances the cost of producing in-house versus that of acquiring the product or service from outside the
firm is mainly driven by the extent to which market sourcing invites transaction costs. These transaction
costs are, among other things, a result of the asset specificity of the underlying production assets. When
durable transaction specific assets are involved in the production of the goods or service, it gives rise to
the possibility of ex-post bargaining to appropriate the surpluses accrued from the investment in these
assets. Such ex-post bargaining is a central source of the transaction costs.
TCE devotes significant attention to the role of durable transaction-specific assets because they
elevate ex-post transaction risk and thus pose an additional challenge in securing the production cost
advantage that markets can offer. Specifically, investment in relationship-specific assets by either party
creates mutual dependence. Combined with uncertainty in supply or demand, it becomes costly to account
for future contingencies leading to a heightened risk of ex-post opportunism. It is to minimize this cost of
ex-post opportunism that Williamson says, “support institutions of contract do matter” (Williamson 1985
p. 29). TCE therefore provides us with another lens with which to examine the role of ex-post
mechanisms of governance in the contract.
3. Literature Review
Given the difficulty of obtaining contractual data, there are only a few studies in the IS literature
that have conducted an empirical analysis of contract structure in managing ITO relationships. These
papers have generally focused on mitigating specific transaction risks. None of these papers examine the
role of contract in helping achieve the performance objectives of the ITO arrangement. In this section, we
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review the few complementary papers that examine how an outsourcing contract is designed to address
transaction risks.
While empirical analysis of the effect of asset specificity on contract features is generally scarce,
there are a few influential papers have done so in focused industry settings. Before we review the IS
literature, we briefly highlight the research on managing supplier relationships by Klein et al. (1978) and
Joskow (1985, 1987). Klein et al. (1978) examine the potential for appropriating the quasi-rents
associated with RSA in various industries. They argue that of the two possible solutions of vertical
integration and contracting, the former is likely to be the dominant solution when the cost of contracting
is high. In a series of seminal papers, Joskow (1985; 1987) presents the results of an exhaustive case
study on the role of contract in minimizing transaction costs in the context of coal procurement by electric
power plants. In particular, he notes that even though transaction costs are seemingly high, market
exchange is often the observed solution. In light of this observation, he posits that contracts are used to
minimize transaction costs and conducts a comprehensive analysis of contracts to understand how
contractual features are related to transaction risks. He examines four kinds of sourcing arrangements:
from the spot market, from preferred suppliers, from strategic partners, and joint ventures. He shows how
differences in asset specificity lead to differences in contractual features. For example, he finds that when
the electric utility company and a coal mine jointly invest in sizeable RSA like railroads to carry the coal,
the contracts are of longer duration, includes specific contractual guarantees including delivery
commitments and dispute resolution, specifies expectations from the vendor such as product quality, and
provides flexibility in pricing even though the pricing structure is specified at the outset of the
relationship. He concludes that these measures protect both parties from behaving opportunistically and
that contract is a crucial mechanism to mitigate risk and reduce transaction costs.
Gurbaxani (2007) is among the first studies to demonstrate the important role of contract clauses
in mitigating transaction risk for both clients and vendors in ITO arrangements. This qualitative study
examines contractual terms used in ten large arrangements in which assets were transferred to the vendor.
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It examines the frequency with which clauses that protect the interests of the client and the vendor are
present in the contracts. These clauses include specified purchase and supply obligations, service level
agreements, scheduled renegotiation, termination, arbitration, force majeure and competitive restrictions.
It finds that contractual clauses are indeed matched to transaction risks. It also observes that total
outsourcing contracts were longer than data center contracts resulting from the inclusion of application
services, which exhibit high human asset specificity.
Andersen and Dekker (2005) studied a large set of purchasing contracts for IT products and
associated services with an average contract value of $1,500. Although the context of their study is very
different from traditional definitions of ITO, we include it here because they provide a valuable
contribution in their measure of the extent to which a contract addresses contingencies. They refer to this
as contract extensiveness and operationalize it as a count of the number of contract clauses.
Barthélemy and Quélin (2006) study 82 outsourcing transactions including IT and Business Process
services and observe that contracts are more complex when outsourced activities have high switching
costs or are central to the firm. They define complexity as a weighted average of the ranks that they assign
to the mechanism specified in the clause for a set of clauses. They also incorporate measures for how
‘human assets’ within the client firm adapt to the vendor’s business requirements and a binary variable for
asset transfer but find no association between these measures and contract complexity. Note that this
measure of contract complexity is very different from the measure of contract extensiveness, since the
first imposes an ordering on a set of clauses while the latter is a count of the number of clauses.
Two more recent and particularly noteworthy studies, Susarla et al. (2010) and Chen and Bharadwaj
(2009), analyze datasets of ‘material contracts’ for IT services publicly disclosed to the U.S. Securities
and Exchange Commission. Their datasets include over 100 contracts with average contract values of $13
million and $10 million respectively and mean duration of 40 and 38 months respectively. IDC (2006),
using a definition of ITO consistent with ours, reports that the average size of the top 100 IT outsourcing
deals in 2005 was $700 million, which suggests that the data in these studies are drawn from a sample
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that reflects a very different class of outsourcing arrangements such as custom software development
projects and from smaller client firms.
Susarla et al. (2010) study three features of a contract – extensiveness, duration, and extension
clauses – and examine their association with task complexity and scope. Their central premise is that
complexity and scope can raise the need for relationship-specific investments, and in turn, the risk of
hold-up. They find that complex tasks tend to be governed by extensive contracts but not necessarily
long-term contracts. They argue that this is likely explained by the fact that a long-term contract for a
complex task may create the risk of inefficient bargaining with the vendor in the future. Provision for
contract extension is negatively associated with vendor ownership of residual assets, defined as assets
that are the outcome of service delivery. That is, when vendors own the results of service delivery, the
existence of a provision for contract extension is less likely. It is worth noting that these residual assets, as
contracted deliverables, are significantly different from the ones we study, which are the production assets
necessary for service delivery and were once owned by the client. In our context, in which vendors
operate IS functions previously run in-house, IT deliverables are rarely, if ever, owned by a vendor.
Chen and Bharadwaj (2009) link elements of risk in IT outsourcing to contract design. Based on
transaction cost economics, agency theory and relational exchange theory, they categorize contract
clauses into three classes: monitoring, property rights protection and contingency planning. They posit
that task characteristics -- asset specificity, process interdependence, complexity and uncertainty -- can
influence contract extensiveness, as defined by the inclusion of clauses in the three classes. Asset
specificity is coded as a binary variable depending on whether service delivery involves the “use of
customized technologies specific to the client firm.” They find that while asset specificity is associated
with property rights safeguards and dispute resolution mechanisms (in fixed price contracts), it has no
significant association with the overall measure of extensiveness.
Summarizing this literature, we conclude that theory suggests that vendors can be incentivized to
make ongoing investments in relation-specific assets (RSA) essential to service delivery if the residual
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rights to these assets are transferred to them. However, ex-ante incentives provided by transferring these
residual rights will not eliminate ex-post opportunism and likely increases it. Contracts do serve to
manage such ex-post opportunism through their use of specific clauses and features that mitigate
anticipated forms of transaction risk. While we have made considerable progress in understanding how
contracts are designed to mitigate the risks associated with asset specificity, there is much that is not well
understood. For instance, there appears to be no consensus on the relationship between contract
extensiveness and asset specificity in part due to the different interpretations of asset specificity. Given
the difficulty in measuring asset specificity, the studies above have inferred the degree of asset specificity
by examining some of its drivers, though each has focused on a different set of assets. In almost all cases,
the asset of interest is a deliverable rather than a production asset. There are no statistical studies of the
role of contract in ITO when the assets of interest are the primary production assets. And, as we stated
above, there are no studies of how contract design helps achieve the goals for outsourcing.
4. Hypothesis Development
Fundamentally, IT outsourcing arrangements are subject to a range of business and technological
uncertainties making it impossible for contracts to be fully specified. As a result, contracts focus on a
limited set of parameters which are likely to be the most relevant or most verifiable (Salanié 1997). By
design, ITO contracts specify significant decision rights and payment mechanisms for the service
provider, which determine the quantity and quality of effort expended on service delivery. While the
vendor is expected to meet specified performance requirements, a failure to do so willfully or
inadvertently can impose considerable costs associated with business disruption on the client. Such
standard problems of agency are compounded when asset ownership rights are transferred along with
decision rights. Now, the client no longer owns the assets for service delivery making it more difficult for
the client to bring service delivery back in-house and further raises the risk of hold-up by the vendor.
Moreover, the vendor is now charged with choosing the level of ongoing investment in the assets, which
may result in under-investment and decaying assets. From the vendor perspective, its exposure to holdup
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risk also increases once it has made a large transaction-specific investment. Therefore, contracts
governing such an arrangement should include measures to mitigate the risks to both parties. Even though
contracts that govern complex ITO arrangements can be lengthy and specify decision and ownership
rights, the measurement system, pricing provisions, incentive clauses, and numerous other provisions,
they are still incomplete.
Yet, just as in supply relationships in other industries, contracts have been argued to be “...the
only certain way to ensure that expectations are realized” in IT Outsourcing (Kern and Willcocks 2001).
The contract provides a detailed blueprint for the outsourcing relationship, and is critical because it
specifies the precise terms of engagement. ‘Tight’ or better-specified contracts are generally considered to
lead to reduced opportunistic behavior (Lacity and Hirschheim 1993; Lacity and Willcocks 1998) and
have been shown to predict IT outsourcing success (Saunders et al. 1997). Kern and Willcocks (2001)
distinguish between the management control dimensions of a contract and its legal nature. They identify
key elements of a post-contract management agenda: service description and exchanges, service
enforcement and monitoring, financial exchanges, financial control and monitoring, key vendor
personnel, dispute resolution, and change control and management. In this paper, we build on this
conceptual framing to focus on 18 clauses that capture the management control aspects highlighted by
Kern and Willcocks (see Table 3 for the set of clauses).
Of these 18 clauses, we expect that some clauses will be present in all ITO contracts, independent
of asset transfer. Given uncertainty in future business and technology trends, all contracts should specify
which party has the right to make specified decisions, termed the formal specification of rights and
responsibilities. Moreover, for the same reason, these contracts should also allow for scheduled
renegotiation, which specifies the dates at which the two parties may seek to revise the terms of
exchange. Service level agreements and the associated performance measurement clauses are likely to be
present in most, if not all, contracts. Dispute escalation and dispute resolution clauses should also be
specified in most contracts. Similarly, the case for a clause that specifies the terms and conditions that
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govern termination for cause is self-evident. Contracts will also specify the terms and conditions for
termination for convenience since it may be difficult to prove the non-performance of a vendor given the
complexity of service provision, the intangible nature of IT services output, and the interaction between
client and vendor effort. Of course, both clients and vendors would want a force majeure clause, which
frees both parties from liability when an extraordinary event, such as war or a large earthquake occurs.
Now consider our context of contracts with asset transfer wherein the assets are central to
production and service delivery. While production assets, such as data center hardware and software, may
seem to be general purpose, the dedication and customization of these assets to clients’ idiosyncratic
needs makes them relationship-specific. That is, these assets cannot be redeployed or sold in the
secondary market without considerable loss in value. For example, the deployment of these assets may
reflect the enterprise architecture and specific software needs of the client firm. Moreover, redeploying
these assets at potential clients is challenging, since these clients will already have significant production
capacity of their own and the associated costs of redeployment can be significant. Importantly, given
hardware price declines and the rate of obsolescence, even assuming that a contract is terminated
relatively quickly after signing, say in three or four years, the vendor’s investment in durable hardware
assets is largely sunk. In the case of human capital, these assets typically represent a bundle of
transferable, e.g. enterprise system software expertise, and firm-specific skills, e.g. knowledge of a client
firm’s processes. Of course, these vary with the job type. Data center operators are far less relationship-
specific than software professionals who have knowledge of a firm’s idiosyncratic software and
processes. That is, firm-specific capabilities are likely to be undervalued outside the client firm. Overall,
in cases of asset transfer, the vendor bears the risk of a large sunk investment, which can lead to a
stronger bargaining position for the client. For example, a client may choose to renege on the contract, or
negotiate for better pricing after contract signing, now that the vendor has made a large sunk investment.
Conversely, the client exposes itself to potential opportunism arising from the loss of ownership
of assets essential to service delivery and its ongoing operations. Given the high switching costs for a
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client to move to another vendor, or to bring service delivery back in-house, the vendor’s bargaining
power has increased. In such cases, a vendor may provide services at a quality level lower than ideal in
the knowledge that the client’s switching costs make it difficult to terminate the vendor. In a more
extreme case, a vendor’s withholding of services in case of a dispute can impose substantial costs on the
client firm. It is therefore likely that, while writing contracts, both clients and vendors will want the
inclusion of additional clauses that mitigate the risk of the other party behaving opportunistically in the
presence of asset transfer.
Now, we systematically consider how asset transfer requires additional protections for both
parties. Once a vendor makes a significant investment in durable transaction-specific assets, it will want a
commitment that the client firm will buy at least a predetermined volume of services over the life of the
contract, termed a specified purchase obligation, to ensure that it can be compensated for its investment.
The client, on the other hand, will want a specified supply obligation, in which the vendor commits to
supply a predetermined volume of specified services so as to ensure that it will receive the necessary level
of services and that the vendor will not withhold any services. However, given business uncertainty, say
about demand, both parties would prefer a flexibility clause that allows supply and demand to adjust to
changes in economic conditions that specifies what deviations from initial commitments are allowable
and at what cost. Moreover, the client, recognizing the uncertainty in future technology costs will want an
assurance that it is receiving a guarantee of best price, sometimes called a most favored customer
provision. Correspondingly, the vendor may require a preferred supplier clause, which requires the client
to negotiate exclusively with the vendor in good faith for any new ITO business and further incentivizes
the vendor to make incremental investments and not engage in opportunistic behavior. The client may
also require a key people provision, which specifies in cases of human asset transfer that some number of
named employees continue to be assigned to the client’s account after transfer and not be assigned
elsewhere. In the event of contract termination, the client may incorporate an employee return clause and
retain the right to rehire certain employees. To the extent that arrangements with asset transfer are wider
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in scope and perhaps more strategic in nature, the client firm may also restrict its vendor’s relationships
with its competitors using an exclusivity clause. To summarize, 5 of the 8 clauses protect the client, 2
protect the vendor, and 1 protects both parties.
Contract Extensiveness
Based on the above discussion, we test three hypotheses that govern the service enforcement and
monitoring dimension of the management control function of the contract. Specifically, we hypothesize
that contracts with asset transfer (CA) will include more explicit clauses than contracts with no asset
transfer (CNA) to address the additional risks of opportunistic behavior. Further, we hypothesize that CA
will include more clauses than CNA to safeguard the separate interests of clients and vendors.
Hypothesis 1A: Asset transfer is positively associated with contracts that are more extensive in their
clauses.
Hypothesis 1B: Asset transfer is positively associated with the number of clauses that limit the risk of
clients holding up the vendor.
Hypothesis 1C: Asset transfer is positively associated with the number of clauses that limit the risk of vendors holding up the client.
Contract Duration
Renegotiation or haggling costs form a critical component of the ex-post cost of contracting
(Williamson 1985). Long-term contracts can therefore lower transaction costs for both parties by
reducing the need for repeated bargaining (Masten and Crocker 1985; Joskow 1987). Importantly, long-
term contracts can create an environment of better sharing of the gains from trade. In an experimental
setting, Brown et al. (2004) show that when third party verification is not possible, long-term contracts do
in fact have more generous sharing of rent and higher effort levels of the agents.
Vendors of ITO services naturally prefer long-term contracts as an assurance of a longer stream
of revenue and expected profits. In the presence of asset transfer, longer contracts gain considerable
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added importance. Since clients almost always demand immediate cost reductions, and efficiency gains
are achieved over a period of time rather than instantly, the increased duration facilitates the recouping of
the large sunk investment in the production assets and also leads to better sharing of gains. For clients, in
addition to the reduced costs of repeated haggling, their objectives of outsourcing are more likely to be
met when vendors invest in the assets. We therefore predict that ITO contracts will be of longer duration
when assets are transferred.
Hypothesis 2: Asset transfer in ITO is positively associated with longer contract duration.
Performance Outcomes: Payment Mechanisms
We now turn our attention to payment mechanisms: pricing structures and performance
incentives, to examine how they influence performance outcomes in case of asset transfer. As already
discussed, the allocation of decision rights to the residual claimant of the assets does itself provide an
implicit control mechanism. Yet, this instrument may not be sufficient especially when a typically risk-
averse vendor is expected to make further investments (Holmstrom and Milgrom 1994). In cases of asset
transfer, the choice of ongoing investment decisions made by the vendor can result in improved
performance. Therefore, a client will incentivize these investments by rewarding decisions to invest in a
manner consistent with its goals and by allowing the vendor to capture a share of the higher net value
(Jensen and Meckling 1992). Therefore, beyond asset ownership, the compensation mechanisms, which
include both the pricing structure and rewards and penalties for exceeding or missing performance targets,
are also incentive instruments.
Pricing Structure
The pricing structure in large ITO arrangements is either variable (such as cost-plus) or pre-
determined for the duration of the contract. Variable pricing allows adaptation to the actual cost and effort
levels in each period. Pre-determined prices are either pegged to a contracted deliverable (e.g. manage the
data center for $x million per period) or are specified as unit prices (e.g. per utilized MIP) and the actual
18
compensation depends on the volume of services delivered. In the former case, the vendor assumes the
risk of variability in the volume of work and its costs, while in the latter, it only needs to estimate unit
costs accurately.
The choice of variable or pre-determined pricing depends largely on task complexity (Bajari and
Tadelis, 2001) and the nature of uncertainty in the transaction. Variable pricing is preferred in the
presence of ex-ante uncertainty in cost (Kalnins and Mayer, 2004), requirements, project size, or
resources (Gopal et al. 2003), and vendor ability (Banerjee and Duflo 2000); and ex-post uncertainty in
quality (Kalnins and Mayer 2004) and outcomes (Eisenhardt 1989). Variable pricing provides both
parties with flexibility in dealing with future contingencies. The risk associated with unforeseen
contingencies, as discussed, is amplified when assets are transferred. Clearly, the need for unpredictable
future investments increases the uncertainty in the transaction.
Besides safe-guarding flexibility, clients are likely to prefer variable pricing when vendors are
expected to invest in RSA, since fixed-price contracts can induce underinvestment (Gopal and
Sivaramakrishnan 2008). For the vendor, profits are higher from variable price contracts compared to
fixed-price contracts (Ethiraj et al. 2005), while generating less overruns and paying a smaller share of the
overruns created (Banerjee and Duflo 2000). For example, when a vendor that has made an investment in
an asset, increasing the fixed component of its cost structure, is confronted with an unanticipated decrease
in demand, it will be affected more negatively when the contract specifies a pre-determined pricing
structure relative to a variable pricing structure that can take these costs into account. This will reduce its
incentives to invest in the production assets. Correspondingly, for a client, an unanticipated increase in
demand will not result in lower fees even though the vendor may enjoy greater economies of scale.
Therefore, it is likely that when assets are transferred, both clients and vendors would prefer to include
provisions for flexible pricing.
19
Taken together, the effect of uncertainty, higher profitability and investment incentives lead us to
hypothesize that when assets are transferred it is likely that clients achieve greater gains with flexible
pricing.
Hypothesis 3: Performance from the client perspective in ITO arrangements with asset transfer is higher
when the pricing structure reflected in the contract is flexible.
Performance Incentives
It is well recognized that the riskiness of vendor investment can be compensated for by incentive
payments for the achievement of objectives (Fama and Jensen, 1983). Moreover, Holmstrom and
Milgrom (1991; 1994) have argued that the strong incentives provided by asset ownership are likely to be
complemented by strong performance based incentives, which in multi-task settings have the additional
benefit of prioritizing effort where value to the client is greatest. For example, a vendor’s set of feasible
actions include the options to postpone investments or only invest in those activities that pose limited risk
even when riskier investments may be desirable (Holmstrom and Milgrom 1991). Therefore, beyond the
compensation for the costs associated with improving the assets offered through the pricing scheme,
which encourages investment but does not direct it, the client must also provide incentives to the vendor
to select the investments and engage in effort that will result in performance outcomes that the client
values.
This leads us to the following hypothesis.
Hypothesis 4: Performance from the client perspective in ITO arrangements with asset transfer is higher
when the contract provides explicit IT-related performance incentives.
5. Data
We conducted a comprehensive survey of outsourcing firms in 2005, collecting detailed
information on numerous aspects of the arrangement. 291 North American firms that had outsourced for
at least one year were identified from a dataset of outsourcing arrangements undertaken during the period
20
1993-2004. Forty-four firms responded positively to our request to be surveyed with a response rate of 15%
while, depending on model specifications, up to four observations were discarded due to missing
variables required in our analyses. Given the sensitivity of the information sought, this is an excellent
response rate. A highly experienced survey firm administered the survey telephonically.
All respondents were senior IT executives (above the level of IT director) who were
knowledgeable about the objectives and outcomes of the ITO contract. 68% of our respondents are firm-
level decision makers, a fifth are at the business unit level and less than a tenth of our respondents are at
lower levels. In terms of firm revenues, employees, industries and services outsourced, our data is
representative of the top 100 worldwide outsourcing contracts in the same time frame
(International Data Corp. 2006). Manufacturing firms account for a third of our sample and 46% are from
the service sector. Firm size ranges from 750 to 195,000 employees. Excluding financial services, the
average revenue was $9 billion4 (see table 1).
Table 1 – Summary statistics Revenue5
($Million) Employees Number of Services per contract
Contract Value ($Million)
Duration (years)
Mean 9,087 35,678 3.6 613 6.2 Minimum 150 750 1 10 1 Maximum 27,300 195,000 9 3,000 15
We captured details regarding the outsourcing arrangement including the title and reporting
structure of the outsourcing decision maker, the vendor selection process, the firm’s objectives for
outsourcing, its satisfaction levels, and the extent to which its objectives were achieved. Our survey also
recorded contract-specific details such as the duration, included services and value of the contract. For the
largest services, the respondents were asked to identify the included contract clauses from a
comprehensive list of 18 such clauses (see Table 3). While outsourcing contracts include a large number
of clauses, we focused on those that pertain to client and vendor protection. To derive the set of relevant 4 By comparison, the Fortune 250th company’s revenue in 2005 was $8.9 billion 5 This value of revenue excludes firms in the Finance, Insurance, and Real Estate industries that often report holding assets as revenue.
21
clauses, we began with the seminal book on ITO contracts by Halvey and Melby (1996), which presents a
comprehensive listing of contractual clauses and explains their use. We then used the Kern and Willcocks
(2001) framework to extract the clauses that are relevant to our research. A brief description of these
clauses is presented in section 3.
Preliminary analysis
Before proceeding with the formal analysis of the effect of asset transfer on contract structure and
ITO performance, we conduct a general comparison of contracts with and without asset transfer to
examine whether asset transfer does in fact matter. First, we compare the average size of CA to that of
CNA. Since contract size can be measured in various ways, we examine four alternate specifications of
size: total contract value, annualized value, the number of services, and the number of clauses in the
contract. The average size of CA is $1,066 million compared to $386 million for CNA (see table 2).
Accounting for contract duration, the annualized values are $118 million and $61 million respectively.
The mean contract duration of the arrangements in our sample is 6.2 years, with a mean of 8.3 for CA and
5.3 for CNA. The average number of services included is five for CA and three for CNA. On average,
contracts with asset transfer contain 4.75 more clauses than contracts without asset transfer. We see that
CA are larger than CNA on all measures.
Table 2- Contract differences when assets are transferred CNA
(32 firms) CA (12 firms)
Sig.
Value $386 million $1,066 million *** Annualized value $61 million $118 million * Contract Duration 5.33 years 8.33 years *** Objectives (average score out of 5) 2.7 3.2 *** Average number of services per contract 3 5 *** Average number of clauses 11 15.75 ** Company level initiation 47% of firms 75% of firms ** Competitive bidding 53% 75% * *** significantly different at .01 level ** significantly different at .05 level * significantly different at .1 level
22
Of the set of 18 clauses, 11 are present in more than two-thirds of the contracts. These 11 cover
baseline specifications of service description, enforcement, dispute resolution, and change control.
Consistent with the discussion of contract clauses in Section 3 above, the other 7, which include such
clauses as purchase commitment, supply commitment, price guarantee, employee return etc., seem to
reflect an additional level of control over and above the base-line specification. When contracts are
categorized by asset transfer, we see that these additional controls are present much more frequently in
the set of contracts that include asset transfer. Having observed that, in general, contracts differ quite
substantially at the conventional significance levels when assets are transferred, we conclude that it is
worthwhile to proceed with the formal econometric analysis to test our hypotheses on the association of
asset transfer with contract structure and its impact on ITO performance.
Table 3 – Contract clauses used
Baseline clauses Total CA CNA Sig.
1. Service level agreements 91% 92% 91% 2. Termination clause for cause 91% 92% 91% 3. Confidentiality clause regarding business processes, data, and IP 89% 92% 88% 4. Dispute escalation procedures 89% 92% 88% 5. Dispute resolution procedures 84% 92% 81% 6. Performance measurement/benchmarking 82% 92% 78% 7. Formal specification of rights and responsibilities 80% 83% 78% 8. Force majeure 75% 83% 72% 9. Termination clause for convenience 75% 83% 72% 10. Scheduled renegotiation 66% 58% 69% 11. Flexibility clause (allows supply and demand to adjust to changes in
economic conditions) 64% 75% 59%
Additional control clauses 12. Specified purchase obligations (commitment to use min. volume) 55% 75% 47% ** 13. Key people provision (specific employees to be retained for a specific
period) 55% 92% 41% ***
14. Specified supply obligations (i.e., commitment to guarantee supply) 39% 92% 19% *** 15. Best price guarantee 36% 67% 25% *** 16. Preferred supplier clause 32% 50% 25% * 17. Employee return (right to rehire specific employees) 27% 58% 16% *** 18. Restrictions on vendors’ relationships with your organization’s
competitors 20% 42% 13% **
*** significantly different at .01 level, ** at .05 level, & * at .1 level
23
6. Empirical Analysis
Measures
Our survey captured detailed information regarding the ITO contract. The data used in this paper
is based on responses to closed-ended questions about objectives, duration, the existence of specific
clauses, the use of performance incentives, the performance measures used, price structure, and asset
transfer. Recall that our objectives are to examine the association of asset transfer with contract structure
and to assess the joint impact of asset transfer and contractual features on performance.
In our survey, we ask directly whether or not IT assets are transferred. The asset transfer variable
is coded as one in case of asset transfer and zero if assets are not transferred. Contract extensiveness is
measured as the number of contract clauses from the set of eighteen clauses mentioned above. As
discussed earlier, seven of the contract clauses (numbered 12 through 18 in table 3) capture additional
ways in which both clients and vendors limit opportunistic behavior. We then separate these seven clauses
into two groups, one that corresponds to clauses that restrict opportunistic behavior by vendors and the
other that restricts opportunism by clients. In the former group, we include clauses that require the vendor
to guarantee the supply of services (even when there is a dispute), offer the best price that it offers to any
clients for the same service, to retain key people identified by the client on the engagement, return the
employees in case of termination, and limit the vendors’ relationships with the firm’s competitors.
Essentially, these clauses are meant to prevent the vendor from engaging in behavior that is typical of ex-
post hold-up. Similarly, clauses that encourage client cooperation include the obligation to purchase a pre-
specified quantity of services, and to source new activities from the contracted vendor using a preferred-
supplier arrangement. Both clauses are focused on mitigating the vendor’s risk associated with its
relationship-specific investments. The duration of an ITO arrangement is obtained as the answer to a
direct question on the length of a contract.
24
The three variables - asset transfer, contract extensiveness, and duration – may be influenced by
the client’s objectives for outsourcing. Based on prior literature, we compiled a list of 12 drivers of
outsourcing, covering both IT-related and business-related goals. Respondents rated the importance of
each of 12 drivers in the decision to outsource on a 5-point scale. The drivers (and the associated
reference in the literature) are presented in the appendix. Using factor analysis and varimax rotation, we
reduce the dimensions of the drivers to obtain two orthogonal factors (table A-2 of the appendix)6. The
objectives that load the highest on the first factor are ‘to improve IT service quality’, ‘to improve business
process performance’, and ‘to align IT with Business’. We label this factor ‘strategic-benefits’ since the
objectives correspond closely to frequently observed strategic intents for outsourcing associated with
improving either IS or business performance, (DiRomualdo and Gurbaxani 1998). The second factor
captures the objectives of ‘reducing IT costs’ and ‘generating cash from the sale of assets’.
Correspondingly, we label this factor as ‘cost-reduction’. An extensive review of the literature validates
the role and importance of these two factors; cost reduction and strategic benefits are the two most
common motivations for outsourcing (Dibbern et al. 2004).
We introduce task scope as a variable, operationalizing it as the number of outsourced tasks
consistent with prior research (Lee et al., 2004, Susarla et al., 2010). We also use four variables as
instruments in our empirical analyses.7 These are the share of IT outsourcing expenditures relative to the
total IT expenditure, the existence of a scheduled renegotiation clause in the contract, whether revenue
generation from IT resources is a goal, and whether the client and vendor had a prior relationship.
Finally, we measure ITO performance along two dimensions: first, using a 5-point scale on the
extent to which a firm reduces IT costs relative to its expectation, and second, the extent to which firms
6 We also conducted an exploratory factor analysis without fixing the number of factors. Four factors were returned of which the first 3 corresponded to strategic drivers and the fourth was clearly related only to cost reduction. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO MSA) of .71 and p < 0.01 for the Bartlett’s test validates the use of factor analysis. Details of the factor analysis are presented in the appendix along with the complete set of drivers and their reference in prior literature. 7 We will discuss this issue in more detail later.
25
are satisfied overall with the outsourcing initiatives on a Likert-scale of 1 to 5. To capture the variation in
outsourcing performance, we incorporate the use of IT incentives and the use of flexible pricing. We
coded the use of IT incentives as a binary variable that takes the value of 1 if the contract included an IT-
based bonus or penalty, and zero otherwise. Similarly, if the pricing scheme is not fixed or pre-
determined, we consider the pricing to be flexible and code the variable with the value of 1.
The correlation coefficients for the key variables described above are presented in table 4. We
observe that asset transfer is highly correlated with contract extensiveness, the total number of included
contract clauses, as well as those that mitigate the risks to the vendor and the client, Vcop, and Ccop,
respectively, and with duration.
Table 4: Correlation for key variables (i) (ii) (iii) (iv) (v) (vi) (vii)
where Perf denotes either IT cost reduction or overall satisfaction, ITinc is IT incentives and FlexPrice is
flexible pricing and all the other variables are the same as those in equations (1A/B/C) through (3).
8 We also check the robustness of our results by estimating three equations separately using the two-stage least square method (2SLS) with the same set of instruments. The estimates are qualitatively similar to ours with 3SLS but their significance levels are weaker since 2SLS implicitly imposes independence among equations (i.e., the contract extensiveness, duration and asset transfer equations). We also estimate three equations using the seemingly unrelated regression equations (SURE). Since SURE does not account for endogeneity among variables, we reject the null hypothesis that all the variables are exogenous at 0.01 level. Taken together, these results increase our confidence in our 3SLS models.
30
For the purpose of estimation, the ordered probit model constructs the probability of observing
outcome j via the estimated linear functions within the range of the cutpoints as below. Then, we estimate
the coefficients by incorporating all cutpoints using the maximum likelihood method.
where j=1,2…5 which reflects a 5-point Likert scale and X includes the independent variables
specified in equations (4).
Results
We begin by presenting the results of our 3SLS estimations of equations (1A), (1B) and (1C), which
examine the impact of asset transfer on contract extensiveness and bilateral safeguards (see tables 5
through 7).
Contract extensiveness
We find that, on average, contracts with asset transfer include 6.81 more clauses than contracts
without it (see column (i) of table 5), supporting the hypothesis that these contracts account for more
contingencies. Our results also suggest that firms with a higher ratio of outsourcing relative to their IT
expenditures require more control for contract contingencies (0.026, p<0.1). Moreover, as expected, the
negative coefficient of duration implies that longer-term contracts are less likely to be more extensive (-
0.606, p<0.01 for duration). Similarly, ITO arrangements undertaken primarily to reduce costs are likely
to have less extensive contracts (-1.145, p<0.1). However, our results show that the presence in an ITO
arrangement of what we label a strategic objective is not associated with the number of contract clauses.
Moving on to safeguards for vendors and clients, we estimate two simultaneous equation models
using 3SLS: (1B) with equations (2) and (3); and (1C) with equations (2) and (3). As reported in columns
31
(ii) and (iii) of table 5, we find positive and significant estimates for asset transfer on both vendor and
client cooperation clauses, thus supporting hypothesis 1B and 1C. The significant estimates of the
coefficient of asset transfer on both vendor and client cooperation clauses show that the contract serves to
control the risk of ex-post opportunism by both parties. Prior literature, on the other hand (e.g.
Barthélemy and Quélin 2006; Wang 2002), has tended to focus on opportunism as a trait of only the
vendor. However our results show that vendors are also protected by contractual clauses that limit clients’
opportunistic actions. Clients’ interests are protected by a variety of clauses that are significantly more
likely when assets are transferred. These clauses restrict vendors from replacing or removing key
employees, require guaranteed supply at competitive prices, and restrict trade with the clients’
competitors. Our analysis highlights the clauses that distinguish CA from CNA and points towards the
specific manner in which contingencies are anticipated and planned for to mitigate the risk of bilateral
hold up.
Table 5 also reports the heterogeneous effects of the relative share of IT outsourcing in total IT
expenditure on contract extensiveness. Consistent with our expectation, clients require more specific and
complete contracts that limit vendor actions when the relative size of the deal is larger (0.007, p<0.1), but
there is no impact on the vendor’s contractual requirements (0.002, n.s.).
Table 5: The Contract Extensiveness equation (eq. 1A/B/C) Number of clauses (i) Client Cooperation
Clauses (ii) Vendor Cooperation Clauses (iii)
Asset Transfer 6.807 *** (1.413)
1.292*** (0.288)
3.375*** (0.404)
Duration -0.606*** (0.197)
-0.069 (0.043)
-0.144** (0.061)
% of ITO out of IT expenditure 0.026* (0.015)
0.002 (0.003)
0.007* (0.004)
Strategic Objective 0.064 (0.576)
-0.116 (0.124)
0.074 (0.180)
Cost Objective -1.145* (0.625)
-0.242* (0.133)
-0.205 (0.190)
Scope 0.132 (0.253)
-0.012 (0.052)
0.004 (0.067)
Prior relationship 0.275 (1.083)
0.188 (0.225)
-0.228 (0.289)
Constant 11.84*** (1.594)
0.904 (0.342)
1.385*** (0.482)
32
R square 0.147 0.039 0.502 Instrument validity (p-value) 0.219 0.185 0.281 *p<0.1, **p<0.05, ***p<0.01, Industry dummies are not reported for expositional brevity.
Contract duration
Our analysis with 3SLS also allows us to examine the association between asset transfer and
contract duration (see eq. 2). As discussed above, as long as asset transfer is perceived as risky, both
clients and vendors prefer long-term contracts. Clients can achieve efficiency gains resulting from
vendors’ investments in assets without repeated search and negotiation. Vendors can profit from their
investments over a longer horizon. Our estimates of the coefficient of asset transfer in the duration
equation (eq.2) are positive and statistically significant at the 1% level without regard for specification
(see table 6).
Table 6: The Duration equation (eq. 2) Duration (i) Duration (ii) Duration (iii) Contract extensiveness (i) Client Cooperation Clauses (ii) Vendor Cooperation Clauses (iii)
-0.325** (0.148)
-1.136 (0.848)
-0.925** (0.416)
Asset Transfer 5.489*** (1.301)
4.537*** (1.246)
6.008*** (1.567)
Scheduled Renegotiation -1.006 (1.025)
-1.311 (0.955)
-1.196 (0.953)
Strategic Objective 0.369 (0.478)
0.244 (0.489)
0.446 (0.477)
Cost Objective -0.710 (0.555)
-0.552 (0.546)
-0.476 (0.528)
Scope 0.430** (0.190)
0.419** (0.188)
0.441** (0.190)
Prior relationship 1.056 (0.985)
1.227 (1.026)
1.038 (1.018)
Constant 7.002*** (1.850)
4.584*** (1.574)
4.611*** (1.511)
Observations 40 40 40 R square 0.303 0.357 0.344 *p<0.1, **p<0.05, ***p<0.01, Industry dummies are not reported for expositional brevity.
Our estimates suggest that in the presence of asset transfer, firms are likely to engage in contracts
with longer duration, supporting hypothesis 2. Our results also provide us with valuable insights as to the
33
association of deal parameters with duration. As expected, the coefficient of contract scope is positively
significant at the 1% level. However, a firm’s objective for outsourcing, neither cost nor strategic, has a
statistically significant impact on duration, though the sign of the coefficient is consistent with our
expectations.
Table 7: The Asset Transfer equation (eq. 3) Asset Transfer (i) Asset Transfer (ii) Asset Transfer (iii) Contract extensiveness (i) Client Cooperation Clauses (ii) Vendor Cooperation Clauses (iii)
0.073*** (0.018)
0.434*** (0.098)
0.232*** (0.031)
Duration 0.074*** (0.019)
0.065*** (0.021)
0.049*** (0.016)
Strategic Objective -0.020 (0.071)
0.055 (0.072)
-0.034 (0.056)
Cost Objective 0.134** (0.067)
0.168** (0.069)
0.068 (0.054)
Generate revenue from IT resources -0.013 (0.081)
-0.049 (0.072)
0.003 (0.053)
Constant -1.076*** (0.314)
-0.489** (0.205)
-0.449*** (0.154)
R square 0.318 0.201 0.304 *p<0.1, **p<0.05, ***p<0.01, Industry dummies are not reported for expositional brevity.
As discussed above, our two main hypotheses, H1 and H2, are tested by examining the contract
extensiveness equation (eq. 1A/B/C) and the duration equation (eq. 2). However, we include the asset
transfer equation (eq. 3) in our simultaneous equations model to explicitly control for endogeneity issues
arising from contract extensiveness and asset transfer. Table 7 presents the results from the asset transfer
equation, which is also simultaneously estimated with the contract extensiveness and duration equations.
While this is not our main interest, it is worthwhile to note that the sign of the cost objective coefficient is
positive; two of the three are significant at the 5% level. This implies that a firm is more likely to transfer
its IT assets to a vendor when its primary objective is cost reduction.
Performance
So far, our focus has been on whether there is a systematic difference between contracts with and
without asset transfer. We now turn our attention to the role of contractual features on performance in the
34
presence of asset transfer. As discussed in Section 3, pricing structure and performance incentives have
been posited as mechanisms that are complementary to asset transfer. That is, a vendor will make
appropriate investments in delivery assets when it is assured of compensation through the pricing
mechanism that account for its higher costs, and via incentives for driving better performance.
Specifically, we examine the role of contract parameters in creating value for clients in outsourcing
arrangements with asset transfer.
We use the extent of reduced IT costs relative to expectation and overall satisfaction as proxies
for IT outsourcing performance. We have earlier discussed that this measure of performance is likely to
be associated with IT incentives and flexible pricing in contracts where assets have been transferred. We
use the ordered probit specification to test these hypotheses (3 and 4). The results are presented in Table
8.
Table 8: The impact of asset transfer with contract structure on reduced IT costs relative to expectation and overall satisfaction (eq. 4) Extent of reduced IT
costs Extent of reduced IT
costs Overall
Satisfaction Overall
Satisfaction Asset Transfer 0.222
(0.348) -1.865** (0.710)
0.222 (0.436)
-1.222 (0.754)
IT incentive 0.294 (0.442)
-0.055 (0.505)
0.275 (0.402)
0.297 (0.475)
Flexible pricing 0.319 (0.358)
0.266 (0.411)
0.187 (0.378)
-0.167 (0.404)
Strategic Objective 0.063 (0.215)
0.102 (0.235)
-0.069 (0.249)
-0.078 (0.259)
Cost Objective 0.567** (0.273)
0.561** (0.283)
0.020 (0.216)
0.030 (0.227)
Asset Transfer X IT incentive
2.417*** (0.738)
0.678 (0.780)
Asset Transfer X Flexible pricing
1.680** (0.753)
1.604** (0.799)
Scope -0.160 (0.110)
-0.129 (0.111)
0.082 (0.092)
0.099 (0.099)
Prior relationship -0.256 (0.370)
-0.403 (0.452)
0.435 (0.563)
0.160 (0.614)
Log pseudo likelihood -54.00 -51.78 -41.22 -40.33 Observations 40 40 40 40 *p<0.1, **p<0.05, ***p<0.01, Industry dummies are not reported for expositional brevity.
We see in the first column that the coefficient of asset transfer is positive but not statistically
significant. However, when the interaction terms with asset transfer are included, our results (column 2)
35
provide us with even more interesting insights. While the main effect of asset transfer is negative9, its
interaction terms with the contractual features of IT-related performance incentives and a flexible pricing
scheme are positive and statistically significant, implying that asset transfer contributes to IT cost
reduction when it is complemented by IT-related performance incentives and by a flexible pricing
scheme. Specifically, our results suggest the role of IT-related performance incentives and flexible pricing
as crucial contractual mechanisms that not only provide safeguards in the presence of asset transfer but
also lead to better cost outcomes (2.417, p<0.01 and 1.680, p<0.05). Our results with overall satisfaction
are not qualitatively different from ones with reduced IT cost. An exception is that the interaction term
between asset transfer and IT incentives is not statistically distinguishable from zero. We conjecture that
overall satisfaction is more difficult to improve when cost is emphasized.
7. Discussion and Concluding Remarks
This paper examines the role and performance impacts of contractual mechanisms in large
outsourcing arrangements where assets essential to service delivery are transferred to the vendor. Clearly,
clients outsource IT services to achieve better delivery outcomes. However, vendor ownership of the
assets introduces complex tradeoffs into the outsourcing arrangement. We know from PRT that asset
ownership by the vendor provides it with the crucial incentive to continue to invest in these production
assets that are necessary to improve the outcomes of IT service delivery. On the other hand, the transfer of
critical service delivery assets to the vendor raises the likelihood that one or both parties will engage in
post-contractual opportunism. It is then apparent that outsourcing arrangements with asset transfer must
incorporate additional contractual mechanisms to mitigate the risk to both parties. Vendors must provide
assurances to their clients via contractual features that they will not exploit their ownership of the key
production assets. Clients must provide their vendors with incentives to continue to invest in the assets
9 When an interaction term is included, it is not unusual to see the coefficient of the main variable (i.e., asset transfer) being altered (Kennedy, 2008). In the presence of the interaction term, the impact of asset transfer on ITO performance is captured through both the coefficient of the main and interaction variables. Here, the interaction terms outweigh the main effect.
36
and to not act opportunistically. Since asset ownership, performance incentives and job design are
complementary mechanisms in motivating vendor performance, contracts should reflect simultaneous use
of these mechanisms, which should then lead to better performance outcomes.
We build a conceptual framework based in property rights theory and transaction cost economics
to develop hypotheses on the role and impact of various contractual features in mitigating the risks
associated with asset transfer and in driving improved performance. We tested the predictions of the
theoretical framework on data collected using a unique and comprehensive survey. We find that ITO
contracts with asset transfer are more extensive than those without. Specifically, such contracts are more
extensive in that they provide measures to prevent ex-post opportunism. Consistent with prior literature
(Lacity and Hirschheim 1993; Nam et al. 1996; Wang 2002; Barthélemy and Quélin 2006), we find
evidence of vendors accepting contractual restrictions in their actions to safeguard the interests of their
clients. We also find evidence of clauses that mitigate the risk to vendors when they make large
investments in IT assets. Moreover, we now have a better understanding of how specific contract clauses
can be used to mitigate the risks associated with asset transfer. Outsourcing arrangements that include
asset transfer are of longer duration than those without. We also demonstrate that well designed contracts
take into account not just the risk-mitigation elements of asset transfer, but the complementarity between
incentives for investment and asset transfer, which jointly lead to improved performance from the client
perspective. The contractual mechanisms of IT-related performance incentives and a flexible pricing
scheme are seen to complement vendor performance and lead to superior outcomes.
While our sample size is small, it is unusually comprehensive. Given the sensitivity of and
confidentiality associated with outsourcing arrangements, data that reveals the specifics of contracts is
especially difficult to access. Our survey-based dataset is unique in that it not only includes contract
features in detail but it also captures non-contractual parameters of the decision such as objectives for
outsourcing, details about relationship structure, and performance outcomes. Prior research has typically
used publicly available secondary data on contracts, which pools many different kinds of ITO each of
37
which feature different contractual risks, and does not include data on the outsourcing intent, such as cost
reduction and strategic benefits, which is an important control. Given this context, our study is unique in
that we examine the underlying mechanism of contractual governance in large ITO arrangements while
controlling for the strategic intent for outsourcing. Avoiding this omitted variable bias provides added
robustness to our results.
From a managerial standpoint, our study offers valuable insights into structuring contracts for
outsourcing relationships. We offer sufficient evidence that in ITO arrangements with asset transfer,
contracts ought to focus on the mitigating the risk to both parties. The contract itself is better considered a
comprehensive set of measures that together mitigate ex-post opportunism and assure both client and
vendor cooperation, rather than as a collection of measures used to monitor the vendor alone. Finally,
when assets are transferred to the vendor, it becomes important to introduce governance mechanisms,
such as flexible pricing and IT-related performance incentives, that complement vendor ownership.
8. Limitations and Future Research
While our dataset is unique in its depth of contract details, and the sample represents mature
outsourcers of various industries and sizes, the number of observations is nevertheless small. Therefore,
we chose aggregate measures for objectives, cooperation clauses and performance measures to preserve
degrees of freedom. This limits the extent to which individual performance metrics or contract clauses can
be compared. Confidentiality agreements prevent us from knowing the identity of the client firms in our
dataset. Knowledge of the client would have allowed us to augment our data with public information
about the firm. While the sample size is small, it is not surprising given the reluctance that clients and
vendors have in revealing contract details. The literature dealing with ITO relationships has often relied
on small samples. For example, Lacity and Willcocks (1998) study 60 outsourcing decisions at 40 firms,
Lacity and Hirschheim (1993) studied 14 firms, Aubert et al. (1996) examine 10 organizations, and
Marcolin and McLellan (1998) examine 6 banks.
38
This field of study is emerging and is clearly of relevance given the consistent growth in
outsourcing. Further extensions of this stream of research require more detailed data on a larger number
of contracts. In addition to providing statistical power, more data provides an opportunity to study
heterogeneity in contract structure. A common problem that arises due to non-comparable datasets is non-
uniform measures and, at times, contradictory findings. Larger datasets can provide the option to compare
and contrast different contracting choice. Another direction for future work is to explore the details of an
outsourcing contract at a finer level of granularity. A typical contract contains a vast number of clauses,
performance metrics, incentives, and bundles of services. For example, understanding effective contract
structure for different service bundles may offer useful insights to reducing contracting costs. In
summary, while contracting in ITO has recently received much needed scholarly attention, there is
considerable value to further exploring the governance of successful outsourcing.
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