Contracting for Innovation: Defining an Exchange that Fosters Creativity While
Mitigating Opportunism
Kyle J. Mayer
Zhe (Adele) Xing
Pablo Mondal
University of Southern California
Marshall School of Business
Management & Organization Department
Bridge Hall 306
Los Angeles, CA 90089-0808
We explore how firms govern inter-firm transactions that require innovation to complete.
Designing contracts to foster innovation is challenging and becomes more complex when
exchange hazards are present along with the need for innovation. Incorporating insights from
social psychology to complement transaction cost economics, we are better able to address
how firms should design their contracts to balance the need for innovation and protection
against opportunistic behavior. Using a sample of contracts from the information technology
services industry, we find that in the presence of exchange hazards, innovation requirement
leads to less use of detailed task descriptions and hybrid payment systems, but to more
extensive contingency planning.
Dec. 2014
Preliminary draft. Please do not cite or circulate without permission.

Please email to [email protected] for any questions.
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INTRODUCTION
Innovation has been the subject of a rich body of literature in strategy, economics and other
fields. Many studies have examined the role that alliances and other inter-firm transactions
play in innovation outcomes (e.g. Ahuja, 2000; Hoetker, 2005; Shan, Walker, and Kogut,
1994; Stuart, 2000). The focus of this research is typically on whether or not engaging in
various types of inter-firm collaboration makes individual firms more innovative (i.e., effect
of learning in alliances on firm-level innovation) (e.g. Hagedoorn and Schakenraad, 1994;
Sampson, 2007). While most studies in the inter-firm context treat innovation as an output,
the topic of how firms can design and govern inter-firm transactions that require innovation
to complete has received less attention. This is an important omission, as governance has
been shown to influence transaction performance (e.g. Mayer and Nickerson, 2005) and one
aspect of performance (for some transactions) is innovation.
Given the importance of addressing governance issues in any inter-firm contexts, transaction
cost economics (TCE) (Williamson, 1975, 1985) is a framework that provides a solid
foundation to study governance and innovation (Adner and Kapoor, 2010; Argyres and
Bigelow, 2009). The challenge when applying TCE to transactions requiring innovation is
that an implicit assumption of TCE is that maximizing the likelihood of success involves
properly specifying the transaction (i.e., overcome bounded rationality) and preventing
opportunistic behavior. This assumption puts the focus on preventing a negative outcome (i.e.,
limiting opportunism and misunderstandings) while innovation is much more about creating a
positive outcome (i.e., fostering an encouraging environment for innovation). We incorporate
perspectives from social psychology to complement TCE to examine how firms design
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contracts when the transaction to be governed requires innovation to be successfully
completed. We contribute to work on contract design by addressing a new governance
problem—designing a contract that both fosters innovation and prevents opportunism.
Using proprietary data on the information technology service contracts of a large IT firm and
141 different buyers, we examine how innovation and exchange hazards influence the use of
three different governance mechanisms. First, we find that the need for innovation leads firms
to rely on more detailed descriptions of tasks in the contract, but this effect is negatively
moderated by the presence of exchange hazards. The need for an innovative outcome can
result in firms using greater amounts of detailed task description in a contract that spells out
the desired functionality of a new product or service; but the presence of exchange hazards
makes framing task descriptions that do not imply distrust or negative expectations (Ghoshal
and Moran, 1996) regarding the transaction more difficult.
Second, our results indicate that contingency planning, contractual terms specifying how to
deal with various issues that might arise during the execution of the transaction, may also
provide a mechanism to address the need for innovation in the presence of exchange hazards.
When exchange hazards are present, firms may address some of the challenges of fostering
innovation by adding more flexibility in dealing with how to adapt to different situations.
We also examine how the need for innovation influences a third aspect of the contract—the
type of payment mechanisms. We find that compared to both fixed fee and time and materials
(T&M) (a variant of cost plus that specifies an hourly or daily wage), the need for innovation
leads to the use of a hybrid of the two that specifies an hourly wage with a price cap. When
exchange hazards are also present, however, the payment cap in a hybrid contract becomes
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more difficult to identify, and a hybrid contract may give way to a T&M contract to address
the increased uncertainty.
We make three contributions to the literature on strategic management and contract design.
First, we explore how contracts can be designed when there is a need for innovation while
still mitigating exchange hazards. Whereas most prior work on alliances and innovation has
examined innovation as an outcome, we examine the need for innovation as a driver of
contract design. Second, we continue the effort to combine social psychology with TCE to
better understand how governance choices, including contract design, are influenced by the
needs of the exchange partners. Economists tend to focus on incentives in driving outcomes,
including innovation, but social psychologists have shown that pecuniary incentives are only
one part of a larger story. We demonstrate that exchange hazards moderate the relationship
between the need for innovation and three aspects of contract design—task description,
contingency planning, and the payment mechanism. Third, critiques of TCE have argued that
one type of exchange hazard is often linked to one term in the contract, and this one-to-one
match does not offer a holistic view of contract design (Reuer and Ariño, 2007). We respond
to this problem by examine how hazards and innovation influence three aspects of contract
design.
THEORY AND HYPOTHESES
Governance and innovation
Addressing the question of creating the right environment for innovation to occur in the
context of an inter-firm transaction involves at least two key literatures. First, transaction cost
economics (TCE) (Williamson, 1975, 1985) is the primary theory used to address issues of
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how inter-firm transactions are governed. The focus of TCE is on mitigating exchange
hazards by overcoming bounded rationality and preventing opportunistic behavior. TCE has
been applied in many areas including vertical integration and contract design (see Macher
and Richman, 2008 for a review), and focuses on crafting governance structures that
minimize governance costs. While TCE facilitates identification and mitigation of exchange
hazards, it is not well equipped to deal with how cognitive, emotional or social factors may
impact the likelihood of successfully completing the transaction (e.g. Ghoshal and Moran,
1996). The primary issue with applying TCE to facilitate innovation in an inter-firm
transaction is that TCE is primarily concerned with ensuring that nothing goes wrong to
derail a transaction (i.e., structure governance to prevent any negative events), while largely
ignoring issues of cognitive biases and emotions in governance that could either improve or
hinder the transaction (Weber and Mayer, 2014). The extensive micro-level literature on how
to meet innovation requirements, however, shows that the processes and context matter in the
generation of innovation from a team (e.g. George, 2007).
This leads to the second relevant research stream, which involves micro level work, mainly
from social psychology, on fostering innovation and creativity. In this area, some research
examines how to use intrinsic motivation to increase creative outcomes (e.g. Amabile, 1985 ;
Amabile and Mueller, 2007). Intrinsic motivation refers to the extent to which an individual
is excited about a work activity and engages in it for the sake of the activity itself (Utman,
1997). In the same vein, cognitive evaluation theory (CET) further developed the contextual
conditions (i.e., informational and controlling) that affect intrinsic motivation (Deci and Ryan,
1985; Ryan, 1982). More controlling aspects in a context shift an individuals’ interpretation
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of the locus of causality to external constrains, thus diminishing their belief in the value of
their own competence, whereas more focus on informational aspects facilitates an internal
perceived locus of causality, leading to enhanced intrinsic motivation and a perception that
the individual’s competence will play a greater role in the outcome (Deci and Ryan, 1985;
Shalley, Zhou, and Oldham, 2004). Thus the salience of different aspects of context (e.g.
feedback, communications, rewards) may influence the level of intrinsic motivation of an
individual, thus affecting the level of creativity, and ultimately innovative output.
Another explanation for the effects of contract design on innovation could be the construal
people use to interpret the framing of the contract. Construal level theory (CLT) suggested
that people’s construal of psychologically near or distant stimulus is important in
understanding their behavior (e.g. Trope, Liberman, and Wakslak, 2007).
Specifically, CLT
states that events that are interpreted as psychologically near are seen as more concrete and
tangible, while events perceived as more psychologically distant as seen as more high level
and abstract. Research drawing on CLT suggests that low level and concrete construal inhibits
creativity, while high level and abstract thinking promotes creativity (e.g. Finke, 1995; Wald,
1995).
Adopting social psychology theories to study governance problems, scholars looked at one
central aspect of the governance of an inter-firm transaction—the contract. The contract plays
a key role in setting the tone and serving as the blueprint for how the parties will interact
(Macneil, 1977). Some scholars have argued that using contracts to mitigate opportunism
creates a negative self-fulfilling prophecy of distrust and damages the relationship of the
firms involved (e.g. Ghoshal and Moran, 1996). However, Weber, Mayer, and Macher (2011)
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incorporated elements of social psychology to complement traditional TCE and argued that
different ways of framing safeguards can help prevent such effect and even foster positive
outcomes such as innovation. We believe that the contract needs to specify a blueprint for the
transaction that does more than define the exchange and overcome opportunism; the contract
also needs to help foster an environment that will be conducive to creativity and innovation.
In many cases, inter-firm transactions involve the execution of well-understood tasks and
thus the supplier merely needs to execute the task once she makes the decision to complete it.
In the case of needing to generate an innovative solution, however, an additional element is
important—fostering an environment in which the supplier can be creative. The environment
in which the transaction takes place is always important and the contract plays a significant
role in creating that environment. Problems in this area often take the form of lessening the
supplier’s motivation to complete the project (i.e., mitigate opportunism); when the project
involves innovation, however, it influences the supplier’s ability to complete the project by
either fostering or hindering the innovative process.
Our goal here is to understand when firms rely more or less on different parts of the contract
in the face of the need to innovatively execute the contract, given the need in these cases to
provide the supplier with an understanding of the transaction, the motivation to complete it
(incentives) and foster an environment to increase the supplier’s ability to do so, and how
these effects are moderated when significant contractual hazards are also present in the
transaction.
Innovation and Task Description
The first important aspect of a contract that we discuss is task description. Suppliers may
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choose to write a more complete and concrete contract by including more extensively
detailed descriptions of the task to be completed. Task descriptions may vary according to the
specific factors of transactions. Descriptions may take the form of processes for the supplier
to follow or they may consist of elaborate specifications of the output the supplier is to
generate (i.e., how to do the job versus what to produce).
For some kinds of transactions, the task to be completed is easily identified, and clearly
interpreted by the suppliers; however, Argyres, Bercovitz, and Mayer (2007) have also found
that in complex, high technology contracts, tasks can be quite involved and firms must decide
how much effort to devote to describing these tasks in their contracts.
The need for an innovative outcome makes inter-firm projects more difficult and complex.
One way to address the additional complexity is through the use of more detailed descriptions
that provide extensive and concrete information to the suppliers, helping them understand the
requirements of the innovation outcome and the needs that the innovation should fulfill. In
such usage, task description may take different forms, including providing detailed steps the
supplier must follow or leaving how the project will be done to the supplier while clearly
specifying the performance goals of the project. Thus, detailed task description serves a
communication role between the parties that is particularly important when innovation is
required to achieve the desired outcome.
Whether the description is about processes or outcome, the need for innovation enhances the
value of clearly communicated what is expected of the supplier. In some cases, the buyer may
not know what steps the supplier needs to follow; they may only care about the end results.
Examples of these cases would include instances when the supplier has proprietary
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technology that they understand better than the buyer, so they buyer will focus more on their
desired outcome than on how the supplier should achieve it. In other cases, the end result may
be harder to predict ex ante, so the contract may focus on what steps the supplier must
undertake to work towards the desired outcome. Examples of these might include consulting
projects to develop new processes in which the contract stipulates the kind of research on the
focal firm that the supplier will do in developing their new process. Thus transactions
requiring innovation will typically have more detailed task descriptions to ensure that both
parties understand what is desired. This is especially important, as monitoring may be more
difficult when innovation is required so misunderstandings over what to do might take longer
to notice than in more standard transactions. Thus, in line with Argyres et al. (2007), we
argue that innovation should lead to more extensive task description in the contract.
Hypothesis 1: The higher the level of innovation required in an inter-firm transaction,
the greater the amount of task description used in the contract governing the
transaction.
While the main effect may be that innovation leads to more detailed task descriptions that
focus on the construal of goals and means, incorporating the literature on construal level
theory (CLT) and cognitive evaluation theory (CET) also implies that such task descriptions
will only aid in the innovation process if they create the right kind of environment for the
transaction (e.g. by encouraging prosocial behavior or fostering creativity). The contract can
play a role by helping set the frame under which the transaction will be executed. However,
the problem is when one or more exchange hazards are present, whether innovation
requirement still favors large amount of task description.
As the need to innovate does not inherently pose a specific contractual hazard, the parties can
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tailor the type and level of task description to the needs arising from the level of innovation
required to complete the transaction. We do not argue that exchange hazards cannot be
present with innovation, but merely that the need to innovate to complete a transaction does
not itself pose an exchange hazard. For example, if an innovative outcome didn’t involve
proprietary knowledge, interdependence or significant specific investments and the outcome
was easily measured, then uncertainty would be present from the need to innovate to
complete the transaction, but exchange hazards that increase the likelihood of opportunism
would be absent.1 However, if exchange hazards arising from other sources were also present
in the transaction, the impact on the level of task description would be more complex. In this
situation, we need to describe the tasks in a way that safeguards transactional hazards.
While it may be possible to frame safeguards in a promotion manner that fosters innovation
(e.g. Weber et al., 2011), it is not always possible to do so. Framing task descriptions to
ensure that opportunism is prevented while fostering innovation is difficult to do because
opportunism and innovation each deals with different parts of the task—the means and the
goals. In this situation, CLT implies that a contract with detailed process control would lead
to concrete thinking (Dhar and Kim, 2007), which may constrain the supplier from acting
opportunistically, but at the expense of the creativity required for innovation. Fostering
innovation, on the other hand, only involves clearly specifying what is required (the goals), to
facilitate abstract thinking and promote creativity. In the same vein, CET also proposes that
adding controlling aspects (i.e., to mitigate exchange hazards) in a context impairs
individual’s intrinsic motivation and thus impedes creativity (e.g. Shalley et al., 2004). The
1
There would, however, still be agency issues to address involving effort, but the ease of measuring the output
would largely alleviate even these concerns.
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issue is that exchange hazards are likely to lead to process controls in a variety of situation,
including when protecting proprietary technology from leakage (to avoid exposing the
technology) and when output is difficult to measure (hard to verify output).
Therefore, adding more details to frame the outcome of a task (i.e., to foster innovation)
while simultaneously including more descriptions on the process of that task (i.e., to mitigate
the exchange hazard) will indeed hurt one or the other. The type of details required to
mitigate hazards is likely to be incompatible with the creativity needed to foster innovation.
Consequently, innovation is stifled if we incorporate too much process control into the task
description to reduce opportunistic behavior when exchange hazards are present. Moreover,
as opportunistic behavior may be perceived more likely in a transaction with exchange
hazards, the supplier may easily misconstrue the informational aspects for controlling aspects
on the description of a task (required by innovation), hurting creativity. In addition, if the firm
puts in only goal oriented detail, then they may open themselves up to failing to recognize
misaligned expectations, shirking or opportunistic behavior. Thus we argue when innovation
is required for a transaction that also involves exchange hazards, it will negatively moderate
the impact of innovation on detail in the task description.
Hypothesis 2: When exchange hazards are high, innovation will lead to less task
description than is the case when exchange hazards are low (i.e., innovation will only
lead to more task description when exchange hazards are low; this positive
relationship will disappear when exchange hazards are high).
Innovation and contingency planning
Given the challenges in crafting effective detailed task descriptions while both innovation and
hazard are present, alternative contractual safeguards may be used. Contingency planning
refers to the provisions addressing contingencies that may arise during execution of the
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transaction that could interfere with its successful completion. Contingency planning clauses
can be defined as “the parts of a contract that are designed to support within-agreement
adjustments by proscribing the ways in which the contractual partners will deal with
problematic contingencies that might arise during the execution of the contract (Argyres et al.,
2007).” In some situations, contingencies can be easily predicted and codified in advance, so
that both parties are fully aware of their tasks and duties when a certain situation happens,
and then they can take actions according to the predefined clauses and procedures to preserve
each party’s interest in the transaction. Without these adjustment clauses, the firms may
abandon the transaction prior to its successful completion due to either honest disagreement
over how to proceed or the perception that one party is trying take advantage of the other.
Contingency planning can be used to facilitate innovation in three ways. First, open-ended
clauses can provide suppliers with a greater level of flexibility. Studies show that it is critical
to inspire people’s creativity by encouraging their participation in decision-making, providing
them with more autonomy and independent decision rights ( Amabile, 1988; Amabile et al.,
2004); in contrast, trying to micro-manage people’s behavior or adding a great amount of
controlling concerns will impair their intrinsic motivation which then reduces creativity
(Shalley et al., 2004). Thus with the open-ended options that contingency planning makes
possible, suppliers can be allowed to retain the ability to self-specify how they will
accomplish the innovation tasks under the looser constraints of processes that focus on
adaptation rather than specific actions.
Second, contingency planning clauses can be relatively generic, specifying processes or
procedures to follow in case any type of contingency occurs. This kind of clause provides
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changes to possible situations, ensuring a protective environment for the suppliers to
complete the task creatively.
Third, contingency planning clauses can also be more specific, identifying specific events
that might occur. For instance, these clauses may clarify which party owns what kind of
rights and takes what kind of responsibilities if a sudden technological change turns the
supplier’s innovation into obsolesce. There may also be clauses specifying additional benefits
if the suppliers create breakthroughs. Thus when innovation is required, contingency
planning not only provides a safe environment for the suppliers, but also leaves them
sufficient freedom and autonomy for creativity.
Hypothesis 3: The higher the level of innovation required in an inter-firm transaction,
the greater the amount of contingency planning used in the contract governing the
inter-firm transaction.
When a transaction that requires innovation also involves exchange hazards, it posed
challenges for using detailed task description as discussed above. This complex situation,
however, may actually favor the use of additional contingency planning. While Argyres et al.
(2007) found that contingency planning and task description generally complement one other
in mitigating exchange hazards, they may not always be complements and in particular we
argue that contingency planning may substitute for detailed task description in the instance
when a transaction involves both exchange hazards and the need for innovation.
Task description to mitigate opportunism may involve too much process detail to facilitate
innovation, but this issue is unlikely to exist for contingency planning. In fact, the time taken
to identify more open ended processes to deal with adaptation issues may actually be more
valuable when both innovation and exchange hazards are present. The issue of uncertainty
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that may arise increases the value of processes to guide adaptation, including basic types of
adaptation such as engineering change processes to more intricate clauses involving
allocation of decision rights to different actors in various types of situations.
One danger in transactions that require innovation in the presence of exchange hazards is that
issues of oversight or unintentional conflict (i.e., problems of bounded rationality) will be
mistakenly interpreted as having for more strategic and/self-serving motives (i.e., they will be
seen as problems of opportunism). Having procedures in place to facilitate adaptation can
help the parties navigate the uncertainty involved in their exchange in a way that doesn’t
promote distrust nor impose (seemingly) restrictive controls but also avoids the other extreme
of a completely underspecified contract that provides ample room for inconsistent
interpretations and divergent expectations. In part because they can be more process-based
such as in communication and adaptation, areas not seen as controlling, contingency planning
clauses may be easier to frame in a more promotion-oriented manner. We argued above that
the process controls in describing the task could stifle innovation, but the same is not true
when the process is simply a guideline of steps to take to help reach agreement on how to
address the need to adapt. These processes are more easily framed as adaptation mechanisms
that avoid stifling creativity.
These open-ended contingency planning clauses motivate suppliers to innovate with freedom
and autonomy. When hazards are present, contingency planning can help to identify possible
solutions in response to possible changes in the future but does not signal distrust or a desire
to control the supplier, thus offering safeguards while facilitating the supplier completing the
task with as innovative an output as possible.
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Hypothesis 4: Exchange hazards positively moderate the relationship between the
level of innovation required in the transaction and the level of contingency planning
in the contract that governs the exchange.
Innovation and the payment mechanism
Another element of the contract that is likely to be influenced by the need for innovation is
the payment mechanism. The two typical payment mechanisms in most commercial contracts
are a fixed fee or an hourly wage. A fixed fee is straightforward as the contract specifies
precisely how much the buyer will pay the supplier upon completion of the task. An hourly
wage contract (often referred to as a time and materials or T&M contract) is a variant of a
cost plus contract and relieves the parties of the obligation to specify a total price ex ante and
instead specifies an hourly or daily rate (typically plus expenses) until the task is completed.
While both payment mechanisms are prevalent in a wide variety of industries, they also pose
specific challenges that need to be addressed (Kalnins and Mayer, 2004).
Fixed fee contracts create a shirking hazard as the supplier can retain any money saved that
they can avoid investing in the project. Shirking can lead to cutting corners and finding
non-obvious ways to reduce costs because the supplier gains all the benefits from cost
reduction. This is problematic for a project requiring innovation for three reasons. First, Enzle
and Ross (1978) suggested that task contingent rewards (i.e., given simply for doing the task)
was a controlling factor that reduced intrinsic motivation to innovate. Second it puts the
supplier’s focus on costs and trying to complete the transaction as cheaply as possible so that
the supplier can emerge with the most possible profit. Finally, the supplier may not be able to
predict how much effort will be required to create an innovative solution, so she is likely to
offer a very high fixed fee to ensure that they don’t lose money on the transaction.
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A T&M contract overcomes the challenges that plague fixed fee contracts because there is not
incentive to excessively reduce costs since all costs are passed along to the customer; nor is
there a need to quote a high total price because the only price quoted is an hourly or daily
wage and the buyer pays for the precise amount of work required to complete the transaction.
The problem with a T&M contract is that it creates weak incentives for the supplier to work
hard to either complete the task by a particular date or to be efficient in resource utilization
because they pass all their costs along to the buyer. Such a contract is particularly problematic
when innovation is required because it will be difficult for the buyer to determine if delays
and additional work are the result of the supplier padding their fee or truly a challenge in
coming up with the right innovative solution.
In the presence of the need for innovation, a third option can help the firms overcome the
challenges of each type of payment mechanism. A T&M contract with a cap represents a
hybrid between fixed fee and T&M contracts. A T&M contract with a cap operates just like a
regular T&M contract until the cost of the project hits a certain amount, after which point the
supplier incurs all additional costs. Thus the buyer has protection from the supplier inflating
costs (beyond the cap) and the supplier has some incentives for efficiency but without having
to specify an exact price ex ante. The hybrid payment solution introduces flexibility that
offers the supplier the opportunity to be creative and seek the most innovative solution
possible while also apply some efficiency incentives.
Hypothesis 5: The higher the level of innovation required in an inter-firm transaction,
the higher the likelihood that a hybrid payment mechanism will be used in the
contract governing the inter-firm transaction.
While a hybrid payment mechanism can enhance innovation, we again raise the question of
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what will happen when both exchange hazards and innovation are present in the same
exchange. We argue that the preference for hybrid contracts as innovation increases will
diminish when the exchange also involves significant exchange hazards.
The first issue that arises is determining the appropriate cap. The benefits of the hybrid
payment scheme rest on having a well-chosen ceiling amount, above which the supplier must
absorb all additional costs. If the ceiling is low such the supplier believe that it is highly
likely their costs will reach that level, then the contract takes on more characteristics of a
fixed fee contract, as the supplier will seek to reduce costs and may be tempted to resort to
shirking. If the ceiling is so high it could never realistically be reached, then the exchange is
effectively simply a time and materials contract in which the supplier charges by the hour or
the day of work. Thus it becomes crucial to specific a viable ceiling amount in order for a
hybrid contract to have values.
The challenges of agreeing on a ceiling amount, above which the supplier will cover all costs,
are exacerbated in the presence of both exchange hazards and the need for innovation. With
issues arising from two very different sources, it becomes increasingly difficult for the two
parties to agree on an appropriate ceiling. The supplier always wants a very high ceiling to
avoid the cost penalty of hitting the cap, while the buyer would like a low enough ceiling that
it effectively begins to feel like a fixed price contract.
When both exchange hazards and the needs for innovation are present, the firms are more
likely to resort to a time and materials contract. The T&M contract frees the parties from
having to specify a fixed price or even a cost ceiling. The challenge in this situation is
ensuring high effort from the supplier, but that may be easier to do in terms of utilizing
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various types of contingency clauses that could address issues of how to deal with varying
rates of progress or abilities to meet various milestones or with monitoring provisions.
Hypothesis 6: Exchange hazards negatively moderate the positive relationship
between the level of innovation required and the likelihood that a hybrid payment
mechanism is used in the contract governing transaction.
EMPIRICAL METHODS
Data and sample
We test our hypotheses with data from Compustar, a provider of computer-related hardware
and IT services. IT services is a very suitable industry to test these hypotheses as it is a key
sector of the economy and there is significant variability in the extent to which innovation is
required to complete various transactions. The IT services industry involves the storage,
transfer and management of information, typically using mainframes, servers and other
related hardware. IT service firms perform many types of projects for their customers,
including but not limited to designing customized software systems, dealing with network
design and security, and updating and/or maintaining existing systems. IT services are
generally performed on a project basis. Buyers identify an IT project and then secure a
supplier to complete it. Every project is distinct, allowing buyers to engage one supplier for
one transaction and another supplier for the next transaction. Most projects are complex, and
many require innovation to complete while others merely involve executing well-understood
capabilities or tools. As the contract serves a key role in defining the exchange, its design is
particularly important and can play an important role in influencing execution of the deal.
Compustar has produced mainframes and related hardware since the 1970s, and entered the
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platform-independent IT services business in the mid – 1980s.2 By 1997, Compustar’s IT
services division accounted for worldwide revenues of roughly $100 million. Compustar’s
buyers are primarily Fortune 1000 firms, as its core mainframe business naturally coincided
with the needs of larger clients. Compustar provided access to IT services contracts they
fulfilled, as well as corresponding internal documentation and other records in its corporate
contracts library. One of the authors inspected IT services contracts spanning the years
1986-1998. This sample includes IT services contracts between Compustar and 141
customers, and represents roughly 25% of the IT service deal in the contract library. An
evaluation by Compustar personnel indicated that this sample was representative along key
dimensions (e.g. customer industries, customer size, number of contracts between Compustar
and the customer, etc.). Several contracts could not be used because of missing data and 11
more were removed because they involved a unique type of contract payment mechanisms
that Compustar discontinued because it wasn’t working as planned.3 The 385 remaining
contracts in the sample each represent a discrete project for which Compustar supplied IT
services. A typical IT services contract in our sample is about five pages long and is designed
to accomplish a specific task. It contains a project description, including the type of service
required and the responsibilities of each party (in varying degrees of detail). Project duration
can range from one week to over a year, while project dollar values range from
approximately one thousand to several hundred thousand dollars.
2
Platform-independent means that the firm supplies services across a variety of hardware types. These
services included network support, programming, data migration, etc.
3
The omitted contract type calls for the supplier to be compensated as a percentage of the money that the
supplier saves the buyer. These contracts led to conflicts between Compustar and their customers over the exact
amount of realized savings and thus how much Compustar should be compensated.
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Two experienced Compustar engineers familiar with the IT services industry, Compustar, and
contracting coded several variables. To ensure measurement validity, the following coding
process was used. Each engineer first coded the same eighty randomly selected contracts. The
two engineers and one of the authors then examined all eighty contracts and identified
discrepancies (measurement programming, and innovation—variables described below). The
engineers then discussed conflicts and converged on the same criteria to code the remaining
contracts. One of the authors also interviewed a variety of IT professionals, many of them
outside of Compustar to discuss the measures and solicit additional comments and feedback.
Measurement
Dependent variables. The first dependent variable is task description. It was coded by our
two engineers on a one to seven Likert-type scale, where one represents cases in which the
contracts contains very little detail in the description of the task to be accomplished and seven
if very extensive technical description was included. Examples of technical detail include
references to particular types of databases or other software systems on which Compustar
will work, specific responsibilities the customer must fulfill in order for the project to be
completed, or details of what would constitute a completed task.
Our second set of predictions focused on the level of contingency planning in the contracts.
Many of Computar’s contracts made no provision for contingency planning while others
contained clearly identified efforts to plan for future contingencies. Contingency planning
was code one if processes were included to address contingencies and zero if no contingency
was mentioned. 41 percent of our sample contracts contained no contingency planning and
the vast majority of those that did plan for contingencies did so using processes to address
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whatever contingencies might arise.
Our last dependent variable explores the payment mechanism specified in the contracts.
Fixed fee contracts involve Compustar completing a specific task in exchange for a
predetermined total price. Time and materials (T&M) contracts involve Compustar being
compensated based on an hourly or daily rate plus expenses until the task is complete. We
code hybrid as a dichotomous variable that is coded as one if the contract involves a hybrid
payment structure (i.e., T&M with a cap) and zero if payment is a fixed fee or “pure” T&M.
Independent variables. Innovation is an ordinal variable ranging from one for projects that
“require no innovation to complete” to seven for projects that “cannot be completed without a
technological breakthrough.”4 This variable does not merely capture complexity, but instead
measures the requirements to push technology forward for successful project completion.
Hazard is a count variable ranging from zero to three. We identified three types of contractual
hazards present in the IT services industry: measurement cost, proprietary technology, and
interdependency. Hazard denotes the number of exchange hazards each contract contains.
Measurement cost captures the cost of measuring quality after project completion, and is
based primarily on technological factors. Due to the largely subjective nature of measurement
costs, Compustar personnel coded measurement issues as one if quality is difficult to
determine immediately after the project is completed and zero if it is relatively ease to
determine. The coding criterion used was whether a brief, inexpensive test or inspection
could determine the quality of Compustar’s work. Proprietary captures appropriability
concerns and was coded as one if one or more of Compustar’s proprietary technologies is
4
There were no projects that were coded by Compustar engineers as a 7. The actual range is from 1 to 6.
21
required for the project. Interdependency captures instances when the buyer is directly
involved in the project in such a way that Compustar depends upon the buyer to complete its
task(s) and is also coded as zero or one. Thus the presence of each hazard is identified by a
dummy variable and hazard is a sum of these three dummy variables.
Control variables. Capabilities may influence what is included in a contract including the
payment mechanism and the level of detail. Compustar has superior internal capabilities
relative to its competitors in servicing hardware that it designed and manufactured.
Compustar hardware is a dummy variable coded as one if the project involves Compustar
hardware, and zero otherwise. Compustar engineers are acknowledged experts at servicing
mainframes from other vendors due to their experience and training in all aspects of
mainframe technology. Mainframe is a dummy variable coded as one if the contract involves
mainframe computers, and zero otherwise. While Compustar has relative strengths in these
areas, the technology used is not proprietary.
Compustar’s capabilities are acknowledged as weaker or at best equivalent to its competitors
in servicing other vendor’s non-mainframe hardware and in programming5. Other hardware
is coded as one if the contract involves hardware from another vendor, and zero otherwise.
Compustar was founded as a hardware firm and has limited experience in programming.
Programming is a dichotomous variable coded as one if the project involves programming.
Other project-level attributes that may affect contract design are also included. Another factor
than can lead to more complete contracts is when failure is very costly. Disrupt is a dummy
variable (coded by Compustar engineers) as one if a project has the potential to shut down a
5
Many IT firms service storage devices and other non-mainframe IT hardware, including the firms that originally
manufactured this equipment.
22
“significant portion” of a customer’s data center. Accidental data center shutdowns are very
costly for customers and tend to be visible events, thus causing significant reputational
damage to suppliers such as Compustar. When a project could result in an outage, Compustar
will describe exactly what must be done to minimize the chances of a data center outage. We
also took the current value of the project into account. Dollar value was captured by the total
monetary value of the project, and we used the mean value to fill in missing data. Since the
distribution of dollar value is quite skewed, we used the logarithm of this variable.
We also control for the effect of prior transactions in which this buyer engaged Compustar for
IT services. Prior projects is the number of projects that Compustar has completed for the
buyer prior to the current transaction, and since the distribution of this variable was skewed,
we entered the logarithm of prior projects.
Non-IT services purchases represent other links between the firms. How much business each
customer has completed with Compustar prior to the focal project may influence task
description or the payment mechanism. Compustar was reluctant to provide customer dollar
values, but did develop a Likert variable that captures relationship breadth. Breadth measures
the extent of non-IT services provided by Compustar for each customer, and ranges from one
(no prior ties in other lines of business) to seven (one of the largest customers outside of IT
services). Year dummies were also included to test for time effects.
[Insert Table 1 here]
Methodology
Since task description is a continuous variable, we use Ordinary Least Square regression to
test our first two hypotheses. Probit models were used for contingency planning and hybrid.
23
To add interactions of innovation and hazard, we adopted a simulation-based approach
proposed by King, Tomz, and Wittenberg (2000) and Zelner (2009) because the coefficient of
interaction term in probit models may not represent the true interaction effect (Norton, Wang
and Ai, 2004); Accordingly, we create and interpret graphical representations of the
interaction effect as recommended by Zelner (2009).
RESULTS
Table 2 provides the OLS regressions on task description. Model (1) is the baseline model
including all control variables, and Model (2) and Model (3) add innovation and number of
hazards respectively. Model (4) captures the joint effect of innovation and hazard on task
description. From Model (1) to Model (4), innovation is significantly positively associated
with the degree of task description (p<0.05), providing strong support for Hypothesis 1. The
positive relationship between innovation and task description is significant (p<0.01) when we
add the interaction term of innovation and hazard in Model (5). Our results are consistent
with our hypothesis that exchange hazards negatively moderate the positive relationship
between innovation and task description. We plot this interaction effect in Figure 1 using one
standard deviation below and above the mean of our moderator and predictor, and we can see
that when fewer exchange hazards are present, innovation has a stronger positive impact on
task description. The results in Figure 1 support H2.
[Insert Table 2 and Figure 1 here]
Table 3 and Figure 2 contain the analysis of contingency planning (H3 and H4). Models (1)
through Model (4) in Table 3 show the impact of level of innovation and hazards on
contingency planning, and we do not find a significant main effect of the level of innovation
24
on contingency planning. In model (5) we add the interaction term and specify 1,000
iterations to estimate our graphical model. The negative and statistically significant
coefficient of innovation in Model (5) and those non-significant coefficients through Model
(1) to Model (4) fail to support Hypothesis 3.
To test the interaction effect predicted by Hypothesis 4, we interpret the graphical
presentation of the interaction presented in Figure 2 below. Figure 2(a) plots the predicted
probability of using contingency planning between contracts having a high number of
exchange hazards and those having a low number of exchange hazards, while all other
explanatory variables are held at the mean values estimated by the probit model (5) in Table 3.
The bars and scattered dots indicate the 95% confidence intervals of the two predicted
probabilities. The figure shows that innovation has a stronger positive impact on the
likelihood of contingency planning when exchange hazards are high. The y-axis in Figure 2(b)
represents the difference in the predicted probability of using contingency planning between
contracts having high number of exchange hazards and those having a low number, again
holding explanatory variables to the mean values estimated in the probit model (5) from
Table 3. The symbols indicate the regions in which the difference of the predicated
probability differs from zero at the 95% level. Figure 2b shows that contingency planning is
used more often when the number of exchange hazards is high as innovation required goes up,
compared to when the number of exchange hazards is low. This relationship is statistically
significant (p<0.05) when the level of innovation required to complete the exchange is
relatively high. In addition, the general increasing trend of the differences in Figure 2(b) is
significant at the 95% level. These results provide strong support for H4. Additionally, our
25
results suggest that the interaction of the number exchange hazards and the level of
innovation strongly affects the presence of contingency planning and subsequently washes
out the main effects that either the number of exchange hazards or the level of innovation
have on their own on contingency planning. Thus, we suggest that this is the reason why we
do not find any statistically significant main effect of innovation in Model (1) through (4) in
Table 3.
[Insert Table 3 and Figure 2 here]
We use probit models to test our last two hypotheses (H5 and H6) on the payment
mechanisms firms specify in the presence of innovation and we present our results in Table 4
and in Figure 36. Our analysis in Model (1) through Model (4) of Table 4 suggests that
increases in the level of innovation as a desired outcome increases firm reliance on the use of
hybrid payment mechanisms, supporting H5.
In Model (5) (of Table 4), consistent with H6, the coefficient of the interaction term is
negative and significant. However, it is not accurate to interpret the interaction effect in a
probit model by simply reading the sign of coefficients Zelner (2009); thus, we rely on
simulation based estimations represented graphically to analyze the interaction between
innovation and hazard. Figure 3(a) plots the predicted probability of using contingency
planning between contracts having a high number of exchange hazards and those having a
low number, and both lines plotted for low and high hazards fall within the 95% significant
level as denoted by the bars (i.e., the solid line plotted within the bars for a low number of
hazards) and scattered dots (i.e., the dashed line within the dotted area). Figure 3(b) shows
6
We did not use ordered probit analysis because it dose not allow simulations on interaction terms.
26
that the difference between using a hybrid payment mechanism when then number of
exchange hazards is high versus when the number of exchange hazards is low become
statistically significant as the level of innovation as a desired outcome becomes moderate or
high. The general decreasing trend of the differences in Figure 3(b) is significant at 95% level,
strongly supports H6.
[Insert Table 5 and Figure 3 here]
Our analysis so far suggests that innovation leads to the use of hybrid payment when the
number of exchange hazards is low. Our data also allows us to do some follow up analysis on
what kind of payment mechanisms firms prefer when both the level of innovation required
and the number of exchange hazards are high. To investigate, we split our sample and test the
probability of using hybrid versus T&M payment mechanism when fixed-fee is not included,
and also the probability of using fixed-fee versus hybrid payment mechanism when T&M is
not included. Figures 4(a) and 4(b) show that when level of innovation and number of
exchange hazards are both high, firms are more likely to use a T&M payment mechanism
compared to hybrid payment mechanism. Figures 4(c) and 4(d) do not show a statistically
significant difference between hybrid and fixed-fee payment mechanisms. These results are
consistent with our prior hypotheses about the payment mechanisms that firms specify when
both the level of innovation required and the number of exchange hazards are high; that is,
firms use T&M payment mechanisms to avoid the difficulty of identifying the payment caps
in a hybrid payment mechanism when the number of exchange hazards is high. T&M
mechanisms also provide the supplier firm with more flexibility to be creative in pursuing
innovation outcomes.
27
[Insert Figure 4 here]
DISCUSSION
The purpose of this paper is to better understand how firms use contracts to govern
transactions that require innovation. While there are a variety of components to a contract, we
selected three that we believe are particularly important for innovative projects. A control
variable in prior work (Argyres et al., 2007) suggested relationships between innovation
requirement and both task description and contingency planning, and we have sought to build
on their work. While to our knowledge prior research has not directly addressed the link
between the need for innovation and the payment mechanism, this portion of the contract
plays a huge role in determining overall incentives—especially those related to effort, which
complements creativity and intrinsic motivation in driving innovation.
Facilitating supplier innovation to completely an exchange requires more than just defining
expectations and mitigating hazards; it involves creating an environment that encourages
people to think creatively (e.g. Miron-spektor, Erez, and Naveh, 2011). We know that team
and individual level factors, including how teams are governed and staffed, influence the
innovativeness of team, but to our knowledge this insight has never been applied to the role
contracts play in governing inter-firm transactions, which are also completed by teams of
people striving for innovative solutions.
This paper takes one important step filling the gap by bringing in some of the micro-level
literature on fostering innovation and creativity for an important but under-studied
issue—how to effectively govern transactions requiring innovation. We show that compared
to lack of exchange hazards, innovation requirement leads to less use of detailed task
28
descriptions and hybrid payment systems, but led to more extensive contingency planning
when exchange hazards are present. Simultaneously mitigating hazards while fostering
innovation requires a creative approach to contract design and may include more reliance on
relational governance (e.g. Poppo and Zenger, 2002) and a better understanding of
micro-level factors like construal and framing have the potential to help bridge the gap
between those who advocate minimizing the use of contracts in favor of relational
governance (e.g. Ghoshal and Moran, 1996) and TCE scholars who focus on contracts as a
purely rational response to exchange hazards (e.g. Williamson, 1985). More work is needed
to explore the governance of transactions involving innovation, including the role played the
relationship between the firms. In our data, both of our proxies for a relationship between the
buyer and supplier (the number of prior projects that the supplier has completed for the buyer
and the number of product lines the buyer purchases from the supplier) have low but negative
correlations with transactions requiring innovation. Thus it does not appear that relational
governance is playing a significant role in governing the innovative projects in our data, but
more work is needed to explore this possibility.
Years after the exchange between Ghoshal and Moran (1996) and Williamson (1996) in the
Academy of Management Review, we still lack a strong integration of social/emotional issues
with the rational governance approach of TCE (Weber and Mayer, 2011, 2014 being
exceptions). The critique that Ghoshal and Moran (1996) leveled at Williamson and TCE was
that emotions were being ignored, which would lead to problems that would be missed if
people were assumed to operate in a purely rational way. Ghoshal and Moran (1996) pointed
out that the contract could engender a very negative response if people perceive the presence
29
of distrust and suspicion based on what is put in the contract. TCE has been slow to
incorporate any real effect of emotions on governance. This may be due to the lack of training
most TCE scholars have in social psychology and other areas where these micro-level
emotions are studied extensively or, as Williamson has sometimes implied (e.g. Williamson,
1996), to the belief that emotions don’t matter in commercial exchanges. Perhaps a third leg
needs to be added to TCE; in addition to overcoming bounded rationality and mitigating
opportunism, we also need people designing contracts and governing inter-firm relationships
to manage the emotional environment of the transaction (the partner’s emotional response).
Doing this requires insight from social psychology and possibly sociology as well. By
incorporating a more complete understanding of the impact the contract can have on the
exchange, firms will be better positioned to design better contracts and enjoy more successful
inter-firm transactions.
We believe that this paper is just the start of research exploring how inter-firm projects
requiring innovation should be governed. Governance does more than prevent negative
events; it can also foster the creation of positive events. Similar to Lindenberg's (2000)
distinction between creating trust and avoiding mistrust, firms can work to create a positive
as well as avoid a negative. While we don’t explicitly address the issue of trust in this paper,
we cite Lindenberg’s work to highlight distinction between the creating of something positive
and the avoidance of something negative; both are important but current work in TCE tends
to be focused on avoiding a negative (i.e., avoiding opportunism and problems arising from
bounded rationality) rather than creating a positive environment. The assumption has been
that if negative events are presented, then a positive outcome will ensue. In some cases,
30
however, a positive outcome requires more than just avoiding negative events—it requires
creating a positive environment.
This paper moves us one step closer to understanding how to govern inter-firm transactions
that require innovation and the potential for combining the boundedly rational governance
approach of TCE with micro-level research on individual behavior and team processes (e.g.
Grant and Berry, 2011; Miron-spektor et al., 2011). While we focus on fostering innovation,
there are many other areas where better understanding individual and team level factors can
produce a more successful transaction. We hope this is the first of many studies to draw
insights from micro and macro level research to both extend theory and explain important
phenomena.
Limitations & Future Research
As with all studies, potential limitations must be addressed. First, lawyers did not negotiate
the contracts examined in this study—managers and engineers were the primary contract
drafters. Lawyers did conduct a final stage review of the contracts (making few changes), but
the contracts might be different if lawyers were the primary negotiators. How the contracts
might differ based on who negotiates is a promising topic for future research.
Second, while most contracts are based on templates, the templates used here don’t specify
one payment that must be used nor do they specify the details required for any specific
exchange. Thus whether templates were used, and typically Computar’s template was
employed, should not impact the results of this study, as the contractual aspects we examine
were negotiated for each transaction. The role of the contract template and how it influences
both negotiation and execution is potentially productive avenue for future research.
31
One strength of this study— microanalytic data from a single firm—is also a limitation. Our
rich transaction-level data enables us to offer insights into contractual choices rarely available
with studies of a large number or firms. Some may be concerned that the results only reflect
Compustar’s contracting policy, but most of Compustar’s buyers are large companies with
many alternatives for IT service suppliers. Thus we believe that, on average, buyers have
significant leverage that the negotiated contracts do not solely reflect Compustar policy but
also significantly integrate buyer concerns. Critics may also suggest that results from a single
firm do not generalize to other industries and settings. Because a large percentage of
contracts—particularly those in high technology industries—govern project-based exchanges
involving some level of complexity and uncertainty, we suggest that our theory does
generalize to other project based industries (e.g. software, telecomm, and consulting).
Nevertheless, future research to assess the generalizability of this study would be valuable.
The idea that the design of the contract can play an important role in fostering innovation not
just by creating economics incentives but by helping create a particular type of environment
is important and calls for additional research to better understand this effect. We are not
arguing that a well-designed contract is a sufficient condition for a successful exchange, the
parties must still manage the exchange and the individuals involved, but it is an important
first step that can set the exchange off on the right foot and increase the chances of success.
Future research examining the link between contract design and subsequent behavior during
the transaction would be valuable, as would studies that include data on transaction
performance, including innovativeness.
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35
Year 1998
Year 1997
Year 1996
Year 1995
Year 1994
Year 1993
Year 1992
Year 1991
Projects
Number of Prior
Dollar Value
Breadth
Ability to Disrupt
Other Firm Hardware
Programming
Mainframe
Compustar HW
Hazard
Innovation
Hybrid
Task Description
Contingency Planning
Tables and Figures
Table 1: Summary of Statistics & Correlations Between Variables
Task Description
1.000
Contingency Planning
0.211
1.000
Hybrid
0.044
-0.089
1.000
Innovation
0.145
-0.100
0.169
1.000
Hazard
-0.070
-0.082
0.049
0.302
1.000
Compustar HW
-0.036
0.101
-0.120
-0.288
-0.196
1.000
Mainframe
-0.007
-0.072
0.081
-0.087
0.052
0.418
1.000
Programming
-0.104
-0.118
0.130
0.260
0.228
-0.234
0.035
1.000
Other Firm Hardware
0.195
0.091
-0.015
-0.123
-0.207
0.097
0.068
0.021
1.000
Ability to Disrupt
-0.006
0.122
-0.102
-0.002
-0.064
0.385
0.331
0.035
-0.019
1.000
Breadth
0.119
0.110
-0.027
-0.067
-0.049
0.059
-0.119
-0.004
0.008
-0.037
1.000
Dollar Value
0.429
0.175
0.041
0.211
-0.076
0.040
0.079
0.146
0.225
0.145
0.222
1.000
Number of Prior Projects
0.071
0.313
0.045
-0.033
-0.055
0.013
-0.082
-0.009
-0.028
-0.067
0.587
0.189
1.000
Year 1991
0.013
-0.076
0.017
-0.042
0.029
0.092
0.126
0.022
-0.010
0.060
-0.072
0.001
-0.144
1.000
Year 1992
0.045
-0.038
-0.047
-0.041
0.042
-0.055
-0.030
0.152
-0.014
-0.056
-0.134
-0.038
-0.169
-0.066
1.000
Year 1993
0.023
-0.061
-0.099
0.194
-0.013
-0.035
-0.037
0.033
0.014
-0.028
0.022
0.089
-0.062
-0.056
-0.080
1.000
Year 1994
0.028
-0.049
0.065
0.119
-0.019
-0.074
-0.122
0.110
0.090
-0.142
0.036
-0.068
0.054
-0.081
-0.118
-0.099
1.000
Year 1995
-0.064
0.097
0.036
-0.077
0.011
-0.025
0.077
0.009
0.031
-0.026
0.054
-0.009
0.083
-0.090
-0.130
-0.110
-0.161
1.000
Year 1996
-0.047
0.213
-0.052
-0.087
0.003
0.099
-0.079
-0.134
0.031
0.050
0.274
0.124
0.238
-0.101
-0.147
-0.124
-0.181
-0.200
1.000
Year 1997
-0.013
0.166
-0.125
-0.128
-0.080
0.078
0.032
-0.025
-0.094
0.194
-0.003
-0.012
0.167
-0.086
-0.125
-0.105
-0.154
-0.170
-0.192
1.000
Year 1998
-0.013
0.089
0.017
0.093
-0.082
0.018
0.090
-0.012
-0.067
0.224
-0.072
0.030
0.047
-0.046
-0.066
-0.056
-0.081
-0.090
-0.101
-0.086
1.000
Mean
3.402
0.481
0.107
2.521
0.714
0.232
0.262
0.459
0.091
0.472
4.249
10.536
1.023
0.04
0.074
0.067
0.123
0.178
0.185
0.156
0.047
Standard Deviation
1.866
0.5
0.309
1.203
0.708
0.423
0.44
0.499
0.288
0.5
2.766
1.56
1.01
0.195
0.262
0.25
0.329
0.383
0.389
0.363
0.212
36
Table 2: OLS regression on task description
Innovation
Task Description
Model (1) Model (2)
0.187**
(0.089)
Hazard
Innovation*Hazard
Compustar HW
-0.461*
(0.264)
Mainframe
0.049
(0.250)
Programming
-0.845***
(0.209)
Other Firm Hardware
0.755**
(0.348)
Ability to Disrupt
0.079
(0.232)
Breadth
0.060
(0.045)
Dollar Value
0.529***
(0.066)
Number of Prior Projects
0.029
(0.126)
Constant
-1.390**
(0.692)
Year Effect
YES
R-squared
0.268
Adjusted R-squared
0.227
F Statistics
6.547***
Observations
303
Note: (1) Standard errors in parentheses
Table 3: Probit Models on Contingency Planning
Model (3)
Model (4)
0.195**
(0.092)
-0.054
(0.143)
Model (5)
0.518***
(0.134)
0.016
0.947***
(0.140)
(0.339)
-0.374***
(0.115)
-0.344
-0.456*
-0.355
-0.234
(0.268)
(0.267)
(0.270)
(0.268)
0.056
0.045
0.070
-0.009
(0.248)
(0.252)
(0.251)
(0.248)
-0.930*** -0.850*** -0.918*** -1.023***
(0.212)
(0.214)
(0.215)
(0.214)
0.879**
0.763**
0.856**
0.944***
(0.351)
(0.357)
(0.357)
(0.352)
0.030
0.079
0.027
0.050
(0.231)
(0.232)
(0.232)
(0.228)
0.067
0.060
0.067
0.054
(0.045)
(0.045)
(0.045)
(0.044)
0.498***
0.529***
0.496***
0.472***
(0.067)
(0.066)
(0.068)
(0.067)
0.023
0.029
0.022
0.080
(0.125)
(0.126)
(0.125)
(0.125)
-1.612**
-1.407**
-1.568**
-1.999***
(0.696)
(0.707)
(0.707)
(0.708)
YES
YES
YES
YES
0.279
0.268
0.279
0.305
0.236
0.224
0.234
0.259
6.492***
6.142***
6.120***
6.549***
303
303
303
303
(2) *** p<0.01, ** p<0.05, * p<0.1 for two-tail test
Contingency Planning
Model (1) Model (2) Model (3)
-0.026
(0.078)
0.048
(0.117)
Model (4)
-0.034
(0.080)
0.059
(0.120)
Model (5)
Innovation
-0.275**
(0.120)
Hazard
-0.695**
(0.303)
Innovation*Hazard
0.283***
(0.099)
Compustar HW
0.220
0.202
0.237
0.216
0.107
(0.225)
(0.232)
(0.229)
(0.234)
(0.238)
Mainframe
-0.403*
-0.404*
-0.417*
-0.420*
-0.378*
(0.216)
(0.216)
(0.219)
(0.219)
(0.212)
Programming
-0.307*
-0.297
-0.321*
-0.311*
-0.247
(0.178)
(0.181)
(0.182)
(0.183)
(0.183)
Other Firm Hardware
0.546*
0.531*
0.574*
0.560*
0.498
(0.301)
(0.304)
(0.308)
(0.310)
(0.326)
Ability to Disrupt
0.207
0.215
0.208
0.220
0.226
(0.197)
(0.199)
(0.197)
(0.199)
(0.195)
Breadth
-0.082** -0.083** -0.082** -0.083** -0.073*
(0.039)
(0.039)
(0.039)
(0.039)
(0.040)
Dollar Value
0.100*
0.105*
0.101*
0.108*
0.129**
(0.056)
(0.058)
(0.056)
(0.058)
(0.056)
Number of Prior Projects
0.353*** 0.354*** 0.355*** 0.356*** 0.316***
(0.109)
(0.109)
(0.109)
(0.109)
(0.109)
Constant
-2.385*** -2.362*** -2.436*** -2.416*** -2.137***
(0.643)
(0.648)
(0.655)
(0.657)
(0.624)
Year Effect
YES
YES
YES
YES
YES
Chi2
95.12*** 95.23*** 95.29*** 95.47*** 87.94***
Pseudo R-squared
0.226
0.226
0.226
0.227
0.246
Observations
304
304
304
304
304
Note: (1) Standard errors in parentheses (2) *** p<0.01, ** p<0.05, * p<0.1 for two-tail test
37
Table 4: Probit Models on Contract Type
Innovation
Hazard
Contract Type (Hybrid Contract=1)
Model (1) Model (2)
Model (3)
0.220**
(0.096)
-0.038
(0.152)
Model (4)
0.249**
(0.101)
-0.155
(0.162)
-0.767**
(0.335)
0.723***
(0.270)
0.431*
(0.223)
-0.199
(0.398)
-0.263
(0.253)
-0.047
(0.048)
0.056
(0.078)
0.353**
(0.142)
-1.331*
(0.790)
YES
39.56***
0.170
289
-0.698**
(0.342)
0.822***
(0.278)
0.359
(0.230)
-0.068
(0.410)
-0.306
(0.256)
-0.034
(0.049)
0.009
(0.082)
0.352**
(0.144)
-1.500*
(0.837)
YES
45.82***
0.197
289
Innovation*Hazard
Compustar HW
Mainframe
Programming
Other Firm
Hardware
Ability to Disrupt
Breadth
Dollar Value
Number of Prior
Projects
Constant
Year Effect
Chi2
Pseudo R-square
Observations
-0.682**
(0.342)
0.786***
(0.275)
0.340
(0.229)
-0.015
(0.407)
-0.312
(0.256)
-0.036
(0.049)
0.019
(0.082)
0.355**
(0.143)
-1.637**
(0.826)
YES
44.89***
0.193
289
Note: (1) Standard errors in parentheses
-0.773**
(0.336)
0.730***
(0.271)
0.439*
(0.226)
-0.217
(0.404)
-0.261
(0.253)
-0.046
(0.048)
0.055
(0.078)
0.351**
(0.142)
-1.288
(0.808)
YES
39.63***
0.171
289
Model (5)
0.443***
(0.147)
0.774**
(0.377)
-0.305**
(0.122)
-0.622*
(0.346)
0.766***
(0.276)
0.205
(0.210)
-0.076
(0.398)
-0.322
(0.221)
-0.046
(0.047)
-0.011
(0.081)
0.325**
(0.144)
-2.031**
(0.877)
YES
41.98***
0.183
308
Figure 1: The Moderating Effect of Hazard of Innovation on Task
Description
(2) *** p<0.01, ** p<0.05, * p<0.1 for two-tail test
38
.3
0
.1
.2
Predicted Probabilities of Using Contingency Plan
2
3
4
5
6
-.1
.8
.6
.4
.2
1
innovation
Predicted probability when hazard takes value of .674
Predicted probability when hazard takes value of 1.412
1
2
3
4
5
6
innovation
Figure 2 (a)
Figure 2(b)
Figure 2: Graphic Presentations of Interaction Effect of Innovation and Hazard on Contingency Planning
Note:
(1) Figures 2(a) plot the predicted probability of using contingency planning between contracts having high
hazards and those of low hazards, while all other explanatory variables are held at their mean values in the
probit model (5) in Table 3. The bars and scattered dots denote the 95% confidence intervals of the two
predicted probabilities.
(2) The y-axis in Figures 2(b) represents the difference in the predicted probability of using contingency
planning between contracts having high hazards and those of low hazards, while all other explanatory
variables are held at their mean values in the probit model (5) Table 3. The symbols denote the regions in
which the difference of the predicated probability differs from zero at the 95% level.
.05
0
-.05
-.1
-.15
2
3
4
5
6
innovation
Predicted probability when hazard takes value of .668
Predicted probability when hazard takes value of 1.340
Figure 3 (a)
-.2
1
Predicted Probabilities of Using Hybrid Contract
0
.2
.4
.6
(3) The general increasing trend of the differences in Figure 2(b) is significant at 95% level.
1
2
3
4
5
6
innovation
Figure 3(b)
Figure 3: Graphic Presentations of Interaction Effect of Innovation and Hazard on Contract Type
Note:
(1) Figures 3(a) plot the predicted probability of using hybrid contract between contracts having high hazards
and those of low hazards, while all other explanatory variables are held at their mean values in the probit
model (5) in Table 4. The bars and scattered dots denote the 95% confidence intervals of the two predicted
probabilities.
(2) The y-axis in Figures 3(b) represents the difference in the predicted probability of using hybrid contract
between contracts having high hazards and those of low hazards, while all other explanatory variables are
held at their mean values in the probit model (5) Table 4. The symbols denote the regions in which the
39
difference of the predicated probability differs from zero at the 95% level.
1
2
.2
0
-.2
-.4
3
4
5
6
innovation
-.6
0
.2
.4
.6
.8
Predicted Probabilities of Using Hybrid Contract
.4
1
(3) The general decreasing trend of the differences in Figure 3(b) is significant at 95% level.
Predicted probability when hazard takes value of .864
Predicted probability when hazard takes value of 1.594
4
5
6
Figure 4(b)
0
-.05
-.1
2
3
4
5
innovation
6
-.15
Predicted Probabilities of Using Hybrid Contract
3
innovation
.6
.4
.2
0
1
2
.05
Figure 4(a)
1
Predicted probability when hazard takes value of .613
Predicted probability when hazard takes value of 1.320
1
2
3
4
5
6
innovation
Figure 4(c)
Figure 4(d)
Figure 4: Graphic Presentations of Interaction Effect of Innovation and Hazard on Contract
Type (Fixed-Fee and T&M)
Note:
(1) Figure 4(a) and 4(b) present the probability of using hybrid payment versus using T&M payment,
while Figure 4(c) and 4(d) examine the probability of using hybrid payment versus using Fixed
Fee payment.
(2) Figures 4(a) and 4(c) plot the predicted probability of using hybrid contract between contracts having high
hazards and those of low hazards, while all other explanatory variables are held at their mean values. The
bars and scattered dots denote the 95% confidence intervals of the two predicted probabilities.
(3) The y-axis in Figures 4(b) and 4(d) represent the difference in the predicted probability of using hybrid
contract between contracts having high hazards and those of low hazards, while all other explanatory
variables are held at their mean values. The symbols denote the regions in which the difference of the
predicated probability differs from zero at the 95% level.
(4) The general decreasing trend of the differences in Figure 4(b) and 4(d) are significant at 95% level.
40