Creation in Strategic Outsourcing Relationships

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The Impact of Firm Learning on Value
Creation in Strategic Outsourcing
Relationships
DEEPA MANI AND ANITESH BARUA
DEEPA MANI is an assistant professor in the Information Systems group at the Indian
School of Business (ISB). She also serves as the joint executive director of the Srini Raju
Center for Technology and the Networked Economy at ISB. Her research interests are at
the intersection of technology, organization, and society. She is interested in studying the
impact of technology on the organization of economic activity, including firm boundary
decisions, and the impact of such organization on firm value and economic productivity.
Her research articles have been published in many journals including MIS Quarterly,
Information Systems Research, Sloan Management Review, and MIS Quarterly
Executive. Her articles have also appeared in refereed conference proceedings and as
chapters in edited books, and have been featured in popular media outlets such as
Forbes, CIO Magazine, LiveMint, Yahoo Finance, and The Street.
ANITESH BARUA is the William F. Wright Centennial Professor of Information
Technology in the Department of Information, Risk and Operations Management at
the McCombs School of Business, University of Texas at Austin. His research
interests are in the areas of economics of information systems, outsourcing governance, and social media. He has published over seventy five articles in academic
journals and refereed conference proceedings. He has served as associate editor
of Management Science and Information Systems Research, and senior editor of
Information Systems Research. He serves on the editorial board of Journal of
Management Information Systems and International Journal of Electronic Commerce.
ABSTRACT: Information technology (IT) is central to the process execution and
management of an ongoing relationship in outsourcing, both of which are fraught
with challenges, and often lead to poor business outcomes. Thus, it is important for
IT groups in organizations to understand how to deal with such difficulties for
improved outsourcing performance. We study whether firms learn over time to
deal with these two related but distinct issues in IT and business process outsourcing.
Does such learning affect financial value appropriation through outsourcing? We
build on the literature in information systems and strategy to investigate whether
value creation in outsourcing depends on relational learning that results from prior
We gratefully acknowledge the helpful comments and suggestions provided by three
anonymous reviewers and Vladimir Zwass during various stages of the review process. An
early version of this article appeared in the Proceedings of the 30th International Conference
on Information Systems.
Journal of Management Information Systems / 2015, Vol. 32, No. 1, pp. 938.
Copyright Taylor & Francis Group, LLC
ISSN 07421222 (print) / ISSN 1557928X (online)
DOI: 10.1080/07421222.2015.1029379
association with the vendor, and procedural learning that results from prior experience in managing interfirm relationships. We estimate value in terms of long-term
abnormal stock returns to the client relative to an industry, size, and book-to-market
matched sample of control firms following the implementation of the outsourcing
contract. We also analyze announcement period returns and allied wealth effects.
Using data from the hundred largest outsourcing deals between 1996 and 2005, we
find that whereas relational learning influences value creation in both simple and
complex outsourcing engagements, procedural learning impacts value only in complex initiatives. Financial markets are slow to price the value of learning. The results
suggest that caution should be exercised when firms without the experience of
managing interfirm relationships externalize complex tasks to vendors they have
not worked with in the past. Furthermore, IT groups can help improve learningbased outcomes by developing processes and systems that enable a firm to improve
outsourcing procedures in a cumulative manner and also to coordinate and collaborate with the vendor.
KEY WORDS AND PHRASES: abnormal returns, business process outsourcing, contracts,
financial value, market efficiency, organizational learning, outsourcing.
Over the past decade, the outsourcing of information technology (IT) and
IT-enabled business processes has emerged as an imperative for firm competitiveness. These modern outsourcing forms are distinct from traditional outsourcing
such as contract manufacturing or facilities management; the quality of output in
the latter is largely tangible, observable and verifiable. In contrast, significantly
greater uncertainty is associated with the execution of outsourced business processes and technologies. Further, IT outsourcing (ITO) and business process outsourcing (BPO) today include diverse strategic objectives including faster time to
market, innovation, and organizational transformation [53]. The execution of these
more strategic tasks is often idiosyncratic to a firms context and may not be easily
replicable across multiple client contexts. Furthermore, value creation in these
settings may be contingent on complementary investments in communication,
coordination, and collaboration with the vendor(s). These parameters of the task
environment render ITO and BPO more complex than traditional outsourcing
forms. Indeed, a large number of firms cite negative experiences with their outsourcing projects, and emergent research [71] highlights the intrinsic complexity
and high failure rate of outsourcing initiatives.
These failures are not for want of insights to govern outsourcing arrangements. For
instance, the CMMI model (www.cmmiinstitute.com), developed by the Software
Engineering Institute, benchmarks service providers and offers guidelines for the
formalization and optimization of service delivery and execution processes. The
model appraises vendors and provides insights into practices and processes that will
allow them to progress along the maturity curve from ad hoc practices, to formally
defined steps, to managed result metrics, to active optimization of the processes.
Similarly, studies in information systems (IS) and economics [4, 25, 55, 56, 74, 79,
10 MANI AND BARUA
80] offer guidance on whether firms should outsource, and how firms should
manage and govern outsourcing relationships, including issues of contract design,
relationship management, and technology design. For example, Wang, Barron, and
Seidmann [80] show that unless an external vendor has significant cost advantages
over the internal development team, custom software development should favor
insourcing over outsourcing. Seidmann and Richmond [74] demonstrate that clients
should contract simultaneously for both design and implementation phases in software outsourcing instead of contracting for each stage separately. Gopal et al. [25]
use vendor, client, and project characteristics to guide the choice of contract in
offshore software development. Yet, there is evidence that firms incur substantial
adjustment costs in outsourcing and vary in their ability to create value. Gildner
laments: Too much time is wasted trying to help managers and employees understand how to work with the new external service provider [24]. Similarly, Mani,
Barua, and Whinston [55] find evidence of misfit between task requirements and
governance structure in outsourcing and subsequent performance deterioration.
Why would failure in the governance of outsourcing initiatives occur when the
academic literature and the business press are replete with case studies of implementation, failure, and best practices? A key premise of this study is that firms vary in the
extent of knowledge about outsourcing and of the focal vendor. Such learning influences how the firm deals with contingencies and responses thereof in the outsourcing
relationship as well as manages an ongoing relationship with the vendor. Specifically,
drawing upon the literature on learning in IT outsourcing and theories of cooperation
and coordination in strategic management, we posit that two types of learningdriven
by a clients prior association with the vendor (relational learning) and experience with
managing strategic interfirm relationships (procedural learning)may be important
drivers of value creation in outsourcing. Relational learning involves investments in
communication and collaboration with the vendor required to understand the latters
structures, processes, and technologies and to establish common ground and shared
understanding of the outsourced task. Procedural learning, which is related to experience, involves investments in identification of contingencies in the task environment as
well as the design of aligned contracts and complementary relationship management
processes and technologies. Our study is an early attempt to distinguish between these
two forms of learning in the context of IT outsourcing, and endeavors to answer
questions that have, to date, received scant empirical attention in the IS literature: Do
procedural and relational learning have an impact on the value created in ITO and
BPO? Are both types of learning important for all outsourcing deals?
These questions are of significance to IT academics and professionals for several
reasons. First, by enabling communication, coordination, and collaboration, IT plays a
key role in process execution and management in both ITO and BPO. Second, with the
growing maturity of the ITO market, ITO is increasingly being bundled with BPO
offerings and subsumed into a broader business process decision. Thus, moving forward,
an understanding of the issues unique to BPO management is essential for the IT
organization. Finally, BPO is an example of how advances in IT are changing the way
firms value-chain decisions shape their competitive position. Despite the salience of BPO
IMPACT OF FIRM LEARNING ON VALUE CREATION IN STRATEGIC OUTSOURCING 11
research to IS researchers and practitioners, outsourcing research appears to be heavily
tied to IS [16, p. 90] and the field (of BPO) appears somewhat neglected compared to
ITO [7, p. 99] with little rigorous empirical work that examines the antecedents and
business value of BPO [83]. Our research addresses this gap in the literature, by
empirically analyzing the drivers of outsourcing performance. As process automation and
sophisticated delivery models rather than labor arbitrage increasingly drive performance
gains from BPO, we expect the linkage between ITand BPO to become more pronounced.
To test our theoretical arguments, we use data on the hundred largest ITO and BPO
initiatives (by contract value) announced between 1996 and 2005. The data are primarily
obtained from International Data Corporations annual reports on the largest outsourcing
contracts signed each year in the sample time period. Company data from COMPUSTAT
and SDC Platinum, and stock price data from the Center for Research in Security Prices
(CRSP) complement contract data. Using contract choice (fixed or variable prices) as a
proxy for outsourcing complexity,1 we find that relational learning positively affects value
creation in both fixed and variable price contracts. Procedural learning has a positive
impact only on the value created in complex arrangements governed by variable price
contracts. We also find that markets are slow to price the importance of the two types of
learning, resulting in . These results, although based on the
hundred largest outsourcing deals during the time period of the study, have important
implications for both theory and practice of large-scale IT outsourcing. First, the extant IS
literature on learning in outsourcing [22, 70, 82] has provided case studies to demonstrate
how firms learn to make adjustments to contracts and control features of an exchange
relationship from their outsourcing experience, but has not empirically investigated the
relation between learning and value creation. Our study represents an early effort in this
direction. Second, these studies have treated learning as a single construct without making
a distinction between different types of learning. We demonstrate that the distinction
between relational and procedural learning is particularly relevant to the outsourcing
context, which can vary from simple to complex deals.
Our results also offer a contrast to research on learning in strategic management
[1], which finds no evidence of learning to create value in simpler, more stable
strategic alliances. Prior research (e.g., [1]) has focused solely on announcement
period returns and wealth effects in assessing value creation. We argue that given the
significant information acquisition and processing costs associated with market
valuation of learning in outsourcing, financial markets may be slow to price these
potential drivers of value. Our empirical results confirm the existence of announcement period mispricing by financial markets.2
From a practitioner standpoint, our results imply that firms without prior experience in managing interfirm alliances should consider complex outsourcing with
caution because there is a significant value risk for such firms. Furthermore, in
contrast to the finding that simple tasks can be governed by arms-length relationships [55, 78], our learning perspective suggests that prior association or working
relationship with a vendor is important even for simple tasks, at least in the case of
very large outsourcing deals.
12 MANI AND BARUA
Theory and Hypotheses
Learning in Outsourcing Relationships
To motivate our study of learning in outsourcing, we note that prior research
attributes heterogeneity in the performance of outsourcing relationships to alignment
of incentives and/or actions between the outsourcing firm and the provider. Such
alignment engenders the cooperative behavior required for ex post adaptation in an
ongoing relationship [28, 47, 61]. The institutional economics literature [42, 84]
views outsourcing relationships as incomplete contracts that increase the potential
for opportunistic behavior and in turn, the magnitude of efficiency losses from costly
bargaining and privately favorable distribution of ex post surplus. This school of
research views the ability of the outsourcing firm to anticipate and respond to
contingencies in the outsourcing relationship through appropriate exchange of rights
as an important predictor of exchange performance. Research in organizational
behavior [75] views outsourcing relationships as complex work systems that increase
cognitive conflict and loss of efficiency from complex coordination. These studies
find that the ability of the outsourcing firm to anticipate and respond to contingencies in the outsourced task environment through mutual exchange of information is
an important predictor of exchange performance. The outsourcing firm expends
costly effort in anticipating these contingencies, designing responses, and implementing structures, processes, and technology applications that help the firm realize
its expectations, all of which emphasize the scope for improvement over time and
hence, learning in the relationship. Consequently, we argue that important learning
dynamics may underlie the successful management of outsourcing relationships.
Prior empirical research in outsourcing has emphasized the role of learning. Cha,
Pingry, and Thatcher [9] analyze how a clients knowledge of the vendor affects the
optimal level of outsourcing. Similarly, Whitaker, Mithas, and Krishnan [82] study
learning from onshore IT outsourcing and its impacts on the decision to outsource or
offshore business processes. Scott [73] and Stein and Vandenbosch [77] suggest that
learning helps firms cope with complexity and collaborate effectively in outsourcing
relationships. Prior research in outsourcing [22, 66] has also alluded to the contribution of learning to outsourcing performance. Rottman and Lacity [70] refer to the
challenge of learning to achieve compatibility between the clients internal project
management processes and those of the vendor(s), and its impact on the performance
of the exchange relationship.
Contracting and knowledge transfer are at the heart of recent studies that focus on
how firms learn from a particular interfirm relationship. Learning through contracting is relatively underresearched and the research offers little direct empirical
evidence on whether and how firms learn to contract. A notable exception is
Mayer and Argyres [59], who find, in a detailed case study of eleven contracts in
the personal computer industry, many modifications to the contract that are not fully
explained by changes in the task or risks. Mayer and Argyres [59] note: these
changes are largely the result of processes in which the firms were learning how to
IMPACT OF FIRM LEARNING ON VALUE CREATION IN STRATEGIC OUTSOURCING 13
work together, including learning how to contract with each other [59, p. 394].
They conclude that firms learn about contingencies and hazards as they experience
them, and in the process, are able to craft better contracts in the future. The potential
for learning through contracting is acknowledged in the transaction cost economics
literature, which concedes that many economic agents have the capacities to learn
and to look ahead, perceive hazards, and factor these back into the contractual
relation, thereafter to devise responsive institutions. In effect, limited but intentional
rationality is translated into incomplete but farsighted contracting [84, p. 9].
In contrast to the limited work on learning through contracting, the literature on
learning in alliances extensively focuses on whether and how partners transfer
knowledge that is hard to formalize and communicate [17, 40, 41, 48]. These studies
suggest that the strength of relational capital between partner firms facilitates interfirm learning [31]. Such relational capital, in turn, is a function of characteristics of
the relationship rather than of individual firm attributes [41, 48]. In the specific
context of outsourcing, Lee [49, 50] finds that partnership quality, defined by the
extent of shared vision and goals of the outsourcing firm and provider, and the
mutual belief that partners will not act opportunistically, is an important determinant
of transfer of tacit knowledge between the firms. Similarly, Maskell and Malmberg
[58] find that in the case of integrative tasks, whose ownership and control cannot be
transferred easily to the vendor, greater levels of interdependence between the
outsourcing firm and the vendor yield more knowledge sharing and interactive
problem solving and in turn, mutual learning opportunities [62].
Related research also examines how learning occurs within strategic outsourcing
relationships. In addition to mutual trust between the participant firms [41, 57],
which may be enhanced based on a prior working relationship, other factors have
also received attention in this context. For learning to occur, it is important to have in
place necessary organizational and relational processes that implement the contract
and facilitate the necessary amount and frequency of information exchange and
transformation.3 Such processes are often defined by the extent of joint action,
degree of formalization, or common ground between the participant firms [6, 11,
56]. Mani, Barua, and Whinston [56] find that knowledge transfer and the above
relational processes are especially pertinent to complex, strategic outsourcing relationships. In such situations, the outsourcing firm typically shares ownership and
control of the outsourced process, rendering knowledge transfer and absorption
critical. Case studies as well as empirical research indicate that firms do not always
invest in such critical relational processes and technologies [55, 59].
Whereas the literature reviewed above points to the importance of learning in
outsourcing relationships, it focuses largely on the process of learning within outsourcing relationships. Akin to the concept of learning to learn [19, 20],4 we also
focus on the learning exhibited by the outsourcing firm across a portfolio of similar
interfirm strategic alliances. Cohen and Levinthal [12] observe two related ideas that
are central to this notion of learning to learn. They suggest that learning is cumulative and most effective when the subject of learning is related to what is already
known. As a consequence, a repertoire of experiences provides a robust basis for
14 MANI AND BARUA
learning because it increases the likelihood that the new information encountered by
the firm relates to what is already known, and in turn, the likelihood of finding a
potentially useful solution. Similarly, Bower and Hilgard [8] suggest that the greater
the number of stored instances in an individuals memory, the easier it is for her to
learn from new experiences. Thus, the greater the experience of the firm in managing interfirm relationships, the easier it may be to interpret and respond to unforeseen contingencies in subsequent outsourcing engagements.
Despite the above theoretical support for the view that learning to manage strategic
outsourcing relationships may be an important source of value creation in outsourcing, there is little empirical analysis of this issue in the IS literature. In strategic
management, Gulati [27] demonstrates that pairs of firms appear to learn to manage
their collaborative activities more efficiently over time. Anand and Khanna [1] find
that contractual relationships between firms that have shared a prior association
appear to be systematically different from initial pairings. Anand and Khanna [1]
also note that firms learn to manage interfirm alliances as experience accumulates,
with these learning effects being more pronounced in the case of joint ventures
versus licensing contracts. Thus, the strategy and organizational behavior literature
[1, 8, 12, 27, 59] offers ample support that experience can be used as a proxy for
procedural learning, insofar as a firms ability to deal with the procedural aspects of
interfirm initiatives increases with the experience of managing similar deals.
The above studies do not distinguish between learning about a specific provider
and learning that occurs across a portfolio of similar relationships about the process
of outsourcing through experience. Furthermore, in determining the performance
effects of learning dynamics, these studies assume market efficiency in pricing
learning, and only consider announcement period returns. Our study questions
both of these assumptions in determining whether firms learn to create value in
their outsourcing relationships.
Do Outsourcing Firms Learn to Create Value?
We argue that relational and procedural learning contribute to outsourcing performance in different ways. The distinction between these two dimensions of learning
and their differential role in value creation is important for two reasons. First, each
dimension of learning involves different outsourcing investments. Relational learning is associated with investments in communication and collaboration with the
vendor that are required to understand the latters structures, processes, and technologies as well as to establish common ground and a shared understanding of the
outsourced task. Procedural learning involves investments in identification of contingencies in the task environment and in the design of aligned contracts and
complementary relationship management processes and technologies. In addition,
there is significant variance in the nature of outsourced tasks, and each dimension of
learning has a differential impact on value creation in different task settings. Below,
we explore the contribution of the two types of learning to outsourcing performance
in different outsourcing task environments.
IMPACT OF FIRM LEARNING ON VALUE CREATION IN STRATEGIC OUTSOURCING 15
Relational learning involves the development of a relationship-specific memory
through information sharing between the outsourcing firm and the provider [11]. By
changing the range or likelihood of potential relationship-specific behavior, such
memory has an impact on outsourcing performance. Extant research finds that
contracts between firms with prior working relationships appear systematically
different from de novo associations [1], and that pairs of firms learn over time to
collaborate effectively [27, 38]. We argue that learning about the provider helps the
outsourcing firm to lower the costs of contracting and to better coordinate with the
provider to integrate effort and outcomes. Memory or knowledge of the providers
behavior and actions helps the firm better to predict appropriation concerns and
specify contingent actions, rights, and responsibilities [29, 30]. Firms, through
repeated interactions with a provider, learn how to contract with each other [59].
Furthermore, when relational learning is an outcome of relational capital between the
outsourcing firm and the provider, it may indicate trust between the firms that
mitigates concerns of moral hazard and privately favorable distribution of surplus
[3, 13]. Finally, the greater competence in transacting with each other that accompanies relational learning helps to build domain consensus and a shared understanding of the outsourced task between the outsourcing firm and the provider,
thereby reducing information processing costs.
Merrill Lynchs outsourcing of the restructuring of its wealth management workstation platform to Thomson Financial illustrates the role of relational learning in
complex outsourcing initiatives. The relational contract between Merrill and
Thomson involved joint ownership of the restructuring process, with frequent communication between senior management at the two companies [15]. Given the tight
interdependence between the client and vendor and the joint ownership and control
of the outsourced task, familiarity with the vendor played a key role in the vendor
selection process: The most important driver was the comfort level Merrill execs
had with Thomson execs, and Merrills belief that Thomsons senior management
team would stay intimately involved in the project [15, p.]. Indeed, familiarity with
the vendor may not only promote trustworthiness but also allow for coordination of
behavior to achieve an integrated response to changes in the task environment [30,
51]. Thus, we hypothesize:
Hypothesis 1a: The stronger the relational learning, the greater the value
created by outsourcing.
While relational learning refers to that occurring within a clientvendor dyad,
procedural learning refers to broad, experiential learning that occurs across a portfolio of similar outsourcing initiatives. Thus, the focus in procedural learning is on
learning to learn [1] from prior experiences. Experiential learning acquired
through repeated exposure to similar alliances allows for wider specification of
contingencies and responses thereof. Such exposure also enhances ex post adaptation by facilitating interpretation and response to unforeseen contingencies.
Whitaker, Mithas, and Krishnan note that through prior experience with outsourcing,
firms develop processes and routines that enable them to collaborate with a range of
16 MANI AND BARUA
outsourcing vendors effectively: Experienced firms can more effectively identify
and select trustworthy suppliers, negotiate and organize relationships, monitor and
enforce terms, and anticipate and respond to contingencies based on learning from
prior sourcing engagements [82, p. 16] Fisher, Rudy, and Robert [22] illustrate
these benefits of procedural learning in the context of the outsourcing and contracting decisions at Alpha, an Australian communications company that outsourced IT
over a nine-year period. Based on its outsourcing experience in early stages with the
first vendor, Alpha developed a better understanding of what to outsource, and also
learned from prior mistakes to create more tightly controlled contracts with new
vendors in later phases.
Procedural learning through prior experience also helps the outsourcing firm to
identify appropriate relational processes and technologies that enhance its information processing capabilities to better coordinate actions with the provider. Thus, we
hypothesize:
Hypothesis 1b: The greater the procedural learning, the greater the value
created by outsourcing.
Are Both Relational and Procedural Learning Equally Important?
We argue that the relative importance of relational and procedural learning depends
on the complexity and ambiguity of the outsourcing context owing to the dynamics
of the clientvendor relationship, as well as on the extent of changes required inside
the client organization to adopt and adapt to the new mode of work. If the outsourced task is simple and unambiguous, ownership, control, coordination, and ex
post adaptation requirements could be specified through a relatively complete fixed
price contract with little scope or need for learning to anticipate contingencies and
responses. The task itself is relatively modular with well-defined inputs and outputs,
and thus lends itself to observability and verifiability. In such a situation, procedural
learning that takes place through experience in managing a portfolio of outsourcing
initiatives may have no significant role in value creation owing to the simplicity of
the task and the ensuing ability to disentangle it from the value chain for externalization. Relational learning may still impact value creation in the outsourcing of
simple tasks. The Outsourcing Center (www.outsourcing-center.com) attributes over
26 percent of outsourcing failures to client and vendor interests becoming misaligned and the relationship not remaining mutually beneficial over time. Thus, even
though a fixed price contract and an arms-length governance mode may be adequate
to manage the outsourcing of simple tasks, the client must still engage in periodic
interactions with the vendor to ensure that goals, plans, and actions remain aligned
over time, which draws on relational learning.
Studies in economics have long emphasized the potentially deleterious effects of
contractual incompleteness including investment distortions, costly bargaining, and
private favorable distribution of ex post surplus, and coordination failures in division
of labor. More recent research in economics finds that firms self-select a contractual
IMPACT OF FIRM LEARNING ON VALUE CREATION IN STRATEGIC OUTSOURCING 17
form to minimize economic trade-offs between (1) ex ante provision of incentives and
ex post renegotiation of contractual specifications [2], (2) ex ante contractual specification of the outsourced task and ex post inefficiencies of costly bargaining and privately
favorable redistribution of surplus [13], or (3) contractual completeness and coordination failures [84, 85]. When the outsourced task and relational environments are
characterized by greater complexity and uncertainty, variable price contracts, accompanied by lower levels of completeness in task specification (and a higher probability
that adaptations are needed ex post), are preferred to fixed price contracts [2, 56].
Prior research [1] argues that the potential for learning depends on the complexity
and ambiguity of contingencies facing the firm, with learning effects being more
pronounced in situations characterized by greater contractual ambiguity. Thus, we
expect that the impacts of learning will be stronger for more complex variable price
contracts. In this case, relational learning helps the user firm anticipate and plan for
contingencies in the outsourced task and relationship that determine potential cost
overruns. Relational learning may also help the user firm build trust to better manage
the risks of cost overruns and private distribution of ex post surplus. Procedural
learning helps the user firm to better assess the cost experience of the provider and
engage in adequate information processing that reduces cost overruns in the task
environment and achieves required levels of performance. Thus, we hypothesize:
Hypothesis 2a: The stronger the relational learning, the higher the value
created in both fixed and variable price outsourcing. Relational learning has
a higher impact on value in variable price outsourcing contracts than in fixed
price contracts.
Hypothesis 2b: Procedural learning has no impact on fixed price outsourcing.
The stronger the procedural learning, the higher the value created in variable
price contracts.
Data and Methodology
Data
Our empirical analysis is based on the hundred largest IT and IT-enabled services
outsourcing initiatives implemented between 1996 and 2005 on a worldwide basis.
The average lifetime contract value in our sample is $922 million. The aggregate
contract value of $92.2 billion represents approximately 18 percent of the total
outsourcing contract value for the sample period. A data set comprising such large
outsourcing deals not only includes financially material contracts but also reduces
the likelihood of confounding events as firms are unlikely to engage in as large or
strategic initiatives immediately around such contracts. Our approach to sample
selection is consistent with prior research in financial economics [32]. We also
checked for potentially confounding events (specifically, diversification programs
and acquisitions, research and development [R&D] increases, and structural changes
such as the hiring or firing of C-level leadership) and did not find comparable
18 MANI AND BARUA
nonoutsourcing events in the estimation window. However, it is not feasible to
account for all possible confounding events, a limitation we discuss later.
The data set draws on multiple sources. Information on the hundred largest outsourcing initiatives and their governing contracts is obtained from International Data
Corporations (IDC) services contracts database. IDC tracks outsourcing contracts
signed around the world with a database comprising more than 14,000 service
contracts. As outsourcing began to gain momentum and contract value began to
increase, IDC began to offer a detailed look at the top hundred outsourcing contracts,
ranked by total contract value. These data date back to 1996, and are the primary
input to this study. IDC data on the top hundred outsourcing contracts include
contract value, length, announcement and signing dates, geography, industry, outsourcing type, and a detailed description of the service provided. We use LexisNexis and the Dow Jones News Retrieval Service to verify and supplement IDC
information on announcement and signing dates. We use the Center for Research on
Security Prices (CRSP) files to compute abnormal stock returns, and the Compustat
Basic and Research files to assess firm characteristics, develop operating performance measures and estimate insider trading activity.
We begin with a sample of 1,000 outsourcing contracts spanning the period
19962005. This initial sample comprises public, private, and government contracts
signed in nearly thirty countries. Our final sample comprises the 100 largest outsourcing contracts that satisfy two requirements. First, the firm must be publicly
traded on a major U.S. stock exchange. Second, information on the contract used to
govern the outsourcing initiative must be available. The sample of 100 contracts
includes 66 firms.5
Measurement of Variables
Outsourcing Value: Since our data reflect the largest outsourcing contracts signed
by large publicly traded firms, we measure the value of outsourcing in terms of
short- and long-term market reactions to the announcement of these deals. Prior
research in IS has largely examined announcement period returns to an IT event as a
measure of market value of the event [36, 57]. Following this literature, we estimate
abnormal returns and wealth effects in the period following the announcement of the
outsourcing initiative. A variety of fields in management research are increasingly
acknowledging the potential mispricing of market value that can occur in the short
term [21, 26]. Oler, Harrison, and Allen [46] use a sample of horizontal acquisitions
implemented between 1975 and 1999 to show that the positive initial market
response to an acquisition announcement is contradicted by negative long-run
post-acquisition returns, suggesting that the initial market response is incorrect and
rectified later. The finding is consistent with other studies [54, 64, 68], which find
that stock acquirers earn negative long-term abnormal returns. Other important
strategic events for which evidence of short-term market inefficiency has been
observed include spinoffs [43], quality improvement initiatives [35], stock
repurchases [37], and investments in innovation [10, 18]. These studies find
IMPACT OF FIRM LEARNING ON VALUE CREATION IN STRATEGIC OUTSOURCING 19
significant long-term abnormal returns with short-term returns as being either insignificant or significant but an imprecise measure of market value. Following these
studies, we analyze both short- and long-term estimates of value of our sample
outsourcing events. We find significant long-term returns associated with both
relational and procedural learning.
Announcement Period Returns and Wealth Effects: Daily abnormal returns are
estimated as:
^it rit ^rit;
where ^it are firm-specific abnormal returns. Here, rit denotes the daily returns for
firm i on day t whereas ^rit are the predicted daily returns. Following prior research
on strategic alliances [57], we estimate the following market model:
rit i i
rmt it;
where rmt denotes the corresponding daily returns to the value weighted S&P 500.
An estimation period of 150 days [170, 21] prior to the announcement date is used
to estimate the market model [81]. Significance of the returns is based on the market
model standardized residual method with ScholesWilliams [72] betas. The estimates from this model are then used to predict daily returns for each firm i over a
fourteen-day period [10, +3] surrounding the outsourcing announcement.
Announcement period wealth effects or the dollar change in wealth are computed
by multiplying each user firms market value of equity by its announcement period
abnormal return and then averaging the product across the user firms in the sample.
Long-Term (Event-Time) Abnormal Stock Returns: We use two main methods
for estimating post-event risk-adjusted returnsa characteristic-based matching
approach, also known as the event-time portfolio approach, and Jensens alpha
approach, also known as the calendar-time portfolio approach. Mitchell and
Stafford describe event time buy-and-hold abnormal return (BHAR) as the average
multi-year return from a strategy of investing in all firms that complete an event and
selling at the end of a pre-specified holding period versus a comparable strategy
using otherwise similar nonevent firms [64, p. 296]. Thus, the BHAR for stock i
over holding period T is:
BHARi;T BHRi;T BHRm;T ; (1)
where BHRi,T is the of the sample firm and BHRm,T is the
buy-and-hold return of the matching control firm over the same period. Here, the
buy-and-hold return for holding period T beginning time a through time b is:
BHRi;T Y
b
ta
1 rit 1
” #; (2)
20 MANI AND BARUA

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