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Contracting for Innovation: Defining and Exchange that Fosters Creativity

While Mitigating Opportunism

Kyle J. Mayer

University of Southern California

Marshall School of Business

Management & Organization Department

Bridge Hall 306

Los Angeles, CA 90089-0808

E-mail: kmayer@marshall.usc.edu

Pablo Mondal

University of Southern California

Marshall School of Business

Management & Organization Department

Bridge Hall 306

Los Angeles, CA 90089-0808

E-mail: mondal@usc.edu

January 21, 2011

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Contracting for Innovation: Defining and Exchange that Fosters Creativity

While Mitigating Opportunism

Abstract:

We explore how firms govern exchanges that require innovation. Transaction cost economics

focuses on the role of overcoming bounded rationality and mitigating opportunism when designing

governance mechanisms such as contracts. While TCE is very powerful in illustrating how to prevent

negative events during transactions, it is less able to explain how to design contracts that can help

foster a strong positive environment that facilitates innovation. By incorporating insights from social

psychology to complement TCE, we argue that firms can improve their chances to generate innovative

outcomes in inter-firm transactions. Contracts can do more than simply eliminate negative outcomes

and can help set a frame that can encourage a positive outcome. A major challenge occurs when a

transaction involves a need for innovation and a significant exchange hazard. While innovation often

leads firms to use more detailed task descriptions, because these can be framed in ways that don’t

necessarily imply distrust or negative expectations, the presence of exchange hazards makes this

framing challenge more difficult and leads firms to rely less on detailed task descriptions. We also

explore how firms structure the payment mechanism in the contract to help foster the flexible, creative

environment that is most suitable for innovation. We examine and find support for these effects in a

sample of contracts from the information technology services industry.

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Innovation has been the subject of a tremendous amount of research for decades and while we

know a great deal about many aspects of innovation, one area that has remained largely unexplored is

how to govern a transaction in order to maximize the chances for an inter-firm transaction to yield an

innovative outcome. Most studies of innovation examine what types of firms (e.g., small firms vs.

large firm) produce different types of innovation (e.g., radical vs. incremental or modular vs.

architectural (Henderson & Clark, 1990)), study the life cycle of innovations that became dominant

designs (Abernathy & Utterback, 1978), explore the impact of innovations on incumbent firms (e.g.,

competence-enhancing vs. competence destroying innovations (Tushman & Anderson, 1986)), or a

host of other topics at both the individual, firm, industry and national levels of analysis.

More innovation is occurring in alliances and other inter-firm contexts. However, even when

alliances and other inter-firm transactions are studied in an innovation context, the focus is typically on

whether or not engaging in various types of inter-firm collaboration makes individual firms more

innovative (i.e., how much the firm learns from the alliance partner) (e.g., Hagedoorn & Schakenraad,

1994; Sampson, 2007). What has received less attention is how firms can design and govern inter-firm

transactions that are designed to produce innovative outcomes and it is this question that we address in

this paper.

Given the need to address governance issues as a part of managing innovation, transaction cost

economics (TCE) (Williamson, 1975, 1985), the foundational theory used to address designing and

governing inter-firm transactions, is a framework that continues to provide a logical fit in the study of

strategy and innovation (Adner and Kapoor, 2010; Argyres and Bigelow, 2009). The challenge when

applying TCE to transactions that foster innovation is that an implicit assumption of TCE is that if the

parties properly specify their transaction (i.e., overcome bounded rationality) and successfully prevent

opportunism, then the transaction will be successfully completed (or at least will have a greatly

enhanced chance of succeeding). While this assumption is typically fine, it does put the focus on

preventing a negative (i.e., limiting opportunism and misunderstandings) while innovation is much

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more about creating a positive. Thus we explore how to apply TCE in a way that examines how firms

design contracts when the transaction to be governed requires innovation to be successfully completed.

Argyres, Bercovitz & Mayer (2007) found that when innovation was required that firms spend

more time task description in the contract because they want to clearly specify what is required in the

final product. While excessive specification of exactly how a supplier must complete a project may

inhibit innovation, task description can also be used to better specify the specific outcome (i.e., what

the supplier’s good or service must do) but leave it up to the supplier how they will achieve the

specified performance parameters. When task description is used constructively to foster innovation,

as is the case in Argyres et al (2007), it may pose a challenge for the firm when exchange hazards are

also present. Social psychology research has shown that individual- and team-level factors play

important roles in fostering innovation and creativity (e.g., Amabile & Mueller, 2007; Grant & Berry,

2011; Spektor, Erez & Naveh, 2011). Efforts to mitigate opportunism may interfere with the micro-

level factors that foster innovation, thus firms must take special care in designing the contract that will

govern exchanges in which exchange hazards and a need for innovation are both present.

We seek to directly address the potential conflict posed by trying to simultaneously mitigate

exchange hazards (avoid a negative event) and promote innovation (foster a positive event) by

examining how exchange hazards arising from interdependence, appropriability and measurement

costs (ability to observe quality) negatively moderate the positive effect of innovation on the level of

task description in contracts. In the presence of these contractual hazards, firms may rely less on task

description as the way to craft the task description to mitigate exchange hazards is likely to involve

focusing on how the tasks will be completed, which may inhibit innovation.

In addition, we examine how the need for innovation influences the type of payment

mechanism specified in the contract. Both fixed fee and time and materials (T&M) (a variant of cost

plus that specifies an hourly or daily wage) have drawbacks that could make them problematic when

innovation is required, but a hybrid of the two that involves an hourly or daily wage but with a price

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cap offers a potentially superior alternative. Contracts specifying a fixed fee provide the supplier a

strong incentive to shirk on quality while T&M contracts provide weak incentives for efficiency

because all costs can be passed along to the buyer. A hybrid of the two (i.e., a T&M contract with a

cap, above which the supplier absorbs the cost) provides flexibility that addresses both hazards—the

supplier now has stronger incentives for efficiency (due to the cap) but not to the point that shirking on

quality is an issue (because they still pass along costs under the cap).

We empirically examine our predictions using proprietary data on the information technology

(IT) service contracts of a large IT firm (hereafter Compustar) and 141 different buyers. The IT

services industry is a good context for the theory developed in this paper because there is substantial

variance in the degree to which innovation is required to complete IT services projects and each

contract represents an independent, self-contained transaction. The contracts examined in this paper

are not the billion dollar 10-year IT outsourcing deals; rather they are smaller, shorter duration projects

that still involve significant variability in key areas including the need for innovation, exchange

hazards, the prior relationship between the buyer and suppler, and capabilities. Project-based

transactions like these that involve varying levels of innovation are prevalent in many industries (e.g.,

film production, telecommunications, pharmaceuticals and aerospace), so we believe that our results

generalize beyond the IT services industry and discuss this issue in more detail later in the paper.

We make three contribution so the literature on strategic management. First, we explore how

the governance of inter-firm transactions can enhance the potential for innovation. Prior work on

governance focused on defining the exchange, mitigating opportunism and seeking to build a

relationship, but fostering innovation is a different challenge that has yet to be explored. Second, we

empirically demonstrate the exchange hazards moderate the relationship between the need for

innovation and the extensiveness of task descriptions in the contract. Third, we examine how firms

design payment mechanisms when innovation is required. Traditional fixed fee contracts are

challenging when innovation is required because they put the focus on cost reduction, while hourly

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wage (and other cost-plus) contracts are problematic because they don’t provide strong incentives to

complete the innovative project in a timely manner. We find a specific type of payment mechanism

(i.e., an hourly wage with a cap) that provides a strong combination of incentives with flexibility that

can promote innovation. Fourth, we continue the movement of combining social psychology theories

with transaction cost economics to better understand how governance choices, including contract

design influence the actions of the exchange partners through their emotional reactions. Economists

tend to focus on incentives in driving outcomes, including innovation, but social psychologists have

shown that other individual- and team-level factors also play important roles in fostering innovation.

The paper proceeds as follows. We briefly review TCE and innovation literatures as they

pertain to transaction level governance. We then proceed to develop our theory and hypotheses; data

and methods are then discussed and then we proceed to present and discuss our results, and discuss

limitations and future research. Concluding remarks follow.

INNOVATION AND GOVERNANCE

One important segment of the innovation literature examines when firms improve their

innovation capabilities by engaging in alliances and other inter-firm transactions and/or being part of

inter-firm networks (e.g., Ahuja, 2000; Sampson, 2007; Stuart, 2000). While it is important for firms

to have sufficient absorptive capacity in order to maximize their learning from these inter-firm

connections (Cohen & Levinthal, 1990), the primary value of the connections is viewed as making the

focal firm more innovative during and after the alliance (or after the tie has been established).

We seek to address a slightly different question—how can firms utilize contracts to maximize

the innovative output of inter-firm transactions? Not all inter-firm transactions require innovation, but

when innovation is required, firms need to foster an environment in which innovation is more likely to

occur in order to maximize the chances of a successful innovative transaction.

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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 how inter-firm

transactions are governed. The focus of TCE is on mitigating exchange hazards by properly defining

the exchange (i.e., overcoming bounded rationality) and preventing opportunistic behavior. TCE has

been applied in many areas including vertical integration and contract design (see Macher & Richman,

2008 for a review), and focuses on crafting governance structures that minimize governance costs.

TCE is clearly relevant to the governance of inter-firm transactions because it takes the transaction as

the unit of analysis and seeks to determine how firms will govern each transaction to maximize its

chances of success. While TCE is well equipped to identify exchange hazards and consider how to

mitigate them, it is not suited to address the roles of individual level or team level attributes and how

they play a role in fostering or preventing a successful transaction.

The second relevant research stream involves micro level work, mainly from social psychology,

on fostering innovation and creativity. This research examines how individual level attributes such as

intrinsic motivation (e.g., Amabile, 1985; Amabile & Mueller, 2007), prosocial behavior (Grant &

Berry, 2011) or demographic characteristics such as education, functional background and tenure with

the organization (e.g., Hulsheger, Anderon, & Salgado, 2009) and team level processes or team

composition (e.g., Spektor, Erez & Naveh, 2011) facilitate more innovative output within

organizations.

Work on team level factors has shown that organizations are increasingly relying on teams

whose members have different knowledge sets, capabilities and perspectives (Lovelace, Shapiro &

Weingart, 2001). While demographic issues of team composition play a role in team performance,

personality attributes of the team members appear to play a much more significant role (Bell, 2007;

Harrison, Price, Gavin & Florey, 2002). Work on personal attributes and team innovativeness has

produced mixed results. While personal attributes can play an important role in idea generation

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(Taggar, 2001; 2002), these attributes play a much less important role in the implementation of new

ideas (e.g., Miron, Erez & Naveh, 2004), which is necessary for innovation. Heterogeneity in

cognitive styles (Chan, 1996) within a team, however, has been associated with higher levels of

innovative output (Bilton, 2007).

At the individual level, one factor that has been extensively examined relative to creativity and

innovation is framing. Regulatory focus theory (RFT) (Higgins, 1998) examines how framing effects

(prevention frames involving vigilance and promotion frames involving creativity) influence the way

that people pursue goals such as innovation. Individuals are predisposed to a particular frame but RFT

research has shown that prevention and promotion frames can also be induced in particular situations.

Recent work has also examined the role of motivated information processing theory to

understand the role played by individual’s cognitive processes in selectively noticing, absorbing and

retaining information and the effect this plays in fostering innovation (Grant & Berry, 2011). While

these papers only scratch the surface of work on individual attributes and creativity/innovation, we

draw upon this work to highlight the fact that how a transaction is governed and the motivation and

characteristics of the individuals and team carrying out the task can play a critical role in determining

whether the group succeeds in producing an innovative outcome.

In addition to factors identified in team-level and individual-level research, there are many

governance attributes and choices that can play a role in the innovative output of an inter-firm

transaction. One central aspect of the governance of an inter-firm transaction is the contract used to

govern the exchange. The contract plays a key role in setting the tone and serving as the blueprint for

how the parties will interact (Macneil, 1978). Contracts have been a central element of TCE research

for well over 20 years (e.g., see Shelanski & Klein (1995) for a review of early TCE empirical research

that includes the role of contracts) but only recently have ideas from social psychology been directly

applied to the design of inter-firm contracts (e.g., Weber, Mayer & Macher, 2011; Weber & Mayer,

2011a). We incorporate elements of social psychology to complement traditional TCE in order to

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better explain the challenges of mitigating negative events, which is the traditional focus of TCE, and

fostering positive events such as innovation. TCE has always assumed that individuals are boundedly

rational, but has conceptualized bounded rationality purely as bounds on cognitive processing abilities

and not as cognitive biases that influence behavior (Weber & Mayer, 2011b).

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) and that TCE ignores issue of cognitive biases

and emotions in governance (Weber & Mayer, 2011b). By overcoming bounded rationality (i.e.,

ensuring aligned expectations) and opportunism (i.e., ensuring that one party will not try to take

advantage of the other but will fulfill their obligations under the contract), firms can enjoy successful

inter-firm transactions. The problem lies with the fact that an underlying assumption of TCE is that all

that is required to complete the transaction is for each firm to execute on well-defined and well-

understood responsibilities (i.e., each firm knows exactly what to do and there remains only to actually

do it). When the task is for the parties to create something innovative, the situation is not the same as

simply executing a well-understood task. The extensive micro-level literature on how to foster

innovation collectively shows that the processes and context matter in the generation of innovation

from a team. Therefore the contract needs to specify a blueprint for the transaction that does more than

defines the exchange and overcomes opportunism, but also helps to foster an environment that will be

conducive to innovation.

Some scholars have argued that using contracts to mitigate opportunism creates a negative self-

fulfilling prophecy of distrust and creates a toxic environment for the firms involved (e.g., Ghoshal &

Moran, 1996), others have argued that different ways of framing safeguards can help prevent such an

effect (Weber, Macher & Mayer, 2011).

Innovation is an area where this distinction becomes important in the context of inter-firm

transactions and the contracts that define and govern them. Many inter-firm transactions involve the

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execution of well-understood tasks and thus involve relatively little uncertainty about the ability of the

supplier to complete the task once she understands it and decides she will do it. In such a case, the

supplier merely needs to understand the task and make the decision to complete it. In the case of

needing to generate an innovative solution, an additional element is important—fostering an

environment in which the supplier can be effective. While the environment in which the transaction

takes place is always important, problems in this area often take the form of lessening the supplier’s

motivation to complete the project; 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 innovation, 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 complete the transaction, and how these effects are moderated when significant

contractual hazards are also present in the transaction.

THEORY AND HYPOTHESES

We begin by examining what elements of a contract may be applicable for fostering (or

hindering) innovation. Argyres et al (2007) found that IT firms used more detailed task descriptions

when inter-firm transactions called for more innovative output. This result, however, was not the focus

of their paper; innovation was merely used as a control variable and the subsequent results showed that

when innovation is required the parties will take pains to highlight what the buyer needs and what

steps are required of the supplier in terms of the desired output of their innovative effort.

Argyres et al (2007) also examine the effect of innovation on the level of contingency planning

(i.e., the effort the parties put into identifying contingencies in the contract and how they will handle

these issues if they arise), but find that innovation has a much stronger effect on task description than

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contingency planning. Again, as this is not the focus of their paper, the causes and implications of the

results related to innovation receive little attention.

While the main effect may be that innovation leads to more detailed task descriptions that focus

on clarifying performance outcomes, incorporating literature from social psychology 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., encourage prosocial behavior or foster creativity). The contract can play a role by

helping set the frame under which the transaction will be executed. Regulatory focus theory (RFT)

(Higgins, 1998) is a social psychology theory that addresses how framing effects influence the way

that people pursue goals such as innovation.

Regulatory focus theory is used widely in many fields, including marketing (e.g., Pham &

Higgins 2005; Wang & Lee 2006) and entrepreneurship (e.g., Baron 2004; Brockner, Higgins & Low

2004). RFT suggests that different framing of a goal leads to different emotional responses to meeting

or missing that goal and to different behaviors in pursuing it. If a goal is framed in a prevention manner,

then an individual will view it as a minimal goal (Higgins 1991) that must be met. In contrast, if the

same goal is framed in a promotion manner, then an individual will view it as a maximal goal that

represents an ideal outcome. An individual will experience high-intensity happiness if a promotion-

framed goal was achieved (i.e., achieving this goal represents a profound accomplishment); whereas an

individual experiences low-intensity calm if the same achieved goal was prevention-framed. However,

if that same goal is not achieved, the individual feels low-intensity sadness if it was promotion-framed,

since failing to reach a maximal goal is seen as falling short of an ideal (but not failing); but if the

same goal was prevention-framed, the individual feels high-intensity agitation by falling short of a

minimum requirement (i.e., failing to meet the minimum bar).

The most pertinent application for innovation is that different emotional reactions based on

goal framing also lead to different goal pursuit behaviors, as motivations differ in each case. When a

goal is prevention-focused, an individual will display vigilant behavior in an effort to prevent mistakes

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(i.e., avoid errors of commission). The high-intensity agitation felt if the minimal goal is missed

creates a strong drive to avoid failure that takes precedence over the weaker drive to achieve success,

created by the low-intensity calm felt in meeting the minimal goal. Such a failure-prevention focus

does not fit well with the types of behaviors that are typically described as fostering innovation (e.g.,

Grant & Berry, 2011), either in intra-firm teams or in the context of an inter-firm transaction.

Alternatively, when the same goal is promotion focused, an individual will display creativity

and flexibility in an effort to avoid missing possible solutions (i.e., avoid errors of omission). The high-

intensity happiness experienced in meeting an ideal goal creates a strong drive to achieve success that

overwhelms the weaker drive to avoid failure, created by the low-intensity sadness felt at missing the

goal. As the sting of failure is not as intense as the jubilation of success, an individual with a

promotion focus is more likely to pursue creative and flexible options in an effort to meet the ideal

goal and is less likely to be overly concerned with failing. This type of flexibility and creativity is

much more in line with descriptions of environments that promote innovation in teams and other

settings (e.g., Spektor et al, 2011), potentially including inter-firm transactions that require innovation.

Thus more detailed task description in the contract governing an exchange may be helpful in

facilitating innovation not because it prevents opportunism, but rather because it may facilitate a more

creative, flexible environment by explicitly leaving how the project will be done to the supplier while

clearly specifying the performance goals of the project. The impact would depend upon how the task

description was framed—in a promotion or prevention manner. As the need to innovate does not

inherently pose a specific contractual hazard, the parties can tailor the task description to the needs

arising from the type 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 in 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

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transaction, but exchange hazards that increase the likelihood of opportunism would be absent.1

However, if a specific exchange hazard were also present in the transaction, the impact on the level of

task description would be more complex.

While it may be possible to frame safeguards in a promotion manner (e.g., Weber, Mayer &

Macher, 2011), it is not always possible to do so. Duration clauses can be framed as extendibility

options rather than early termination options, or contingent payment can be framed as a smaller fixed

fee with a bonus or a larger fixed fee with a penalty, but framing task descriptions in such a way to

ensure that opportunism is prevented while encouraging innovation is more difficult to do because

mitigating opportunism involves specifying how the task will be completed while fostering innovation

involves clearly specifying what is required and leaving the supplier flexibility in how to achieve those

end goals.

Thus we argue that when innovation is required for a transaction that also involves an exchange

hazard, innovation will no longer lead to as much detail in the description of the task. The challenge of

trying to frame the detail in a positive light (promotion frame) to foster innovation while

simultaneously mitigating the exchange hazard will prove too difficult. Putting in the necessary detail

to safeguard against opportunism (typically focused on how the task will be completed) may impede

the creativity necessary for innovation by imposing a prevention frame in the transaction. While some

firms may be capable of designing a very detailed task description that retains a strong promotion

frame while mitigating opportunism, we believe that most firms lack such nuanced capabilities and

thus will forego detailed task descriptions in favor of more high level descriptions of what the end

product of the effort should do and other contractual safeguards related to contingency planning,

duration safeguards, contingent payments, etc.

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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We now turn our attention to three specific hazards that are prevalent in a wide variety of

industries that we argue will negatively moderate the positive relationship between innovation and

extensive task descriptions: (1) measurement costs, (2) interdependence, and (3) appropriability.

Measurement costs (or the inability to easily verify quality after a task has been completed)

creates a clear exchange hazard from shirking. Measurement costs create a moral hazard by generating

noise in the relationship between effort and outcome (Alchian & Demsetz, 1972; Holmstrom, 1979). If

any key dimension of the output of the task is difficult to measure, an outcome-based contract is

problematic and the buyer may prefer to utilize more administrative oversight (i.e., focus on

controlling or monitoring the input process rather than the output) (Holmstrom & Milgrom, 1991;

Ouchi, 1979) and/or incentives from extendibility provisions (Weber et al, 2011).

Part of the challenge of innovation is the uncertainty inherent in the need to create something

new in order to satisfy a customer requirement. Measurement costs introduce another source of

uncertainty. The challenges of innovation often get conflated with uncertainty and creativity, when

they are in fact much more nuanced. By examining the role played by measurement costs in the

presence of the need for innovation, we can separate the effects of these two factors and observe what

happens when they coincide. The need to monitor the supplier’s work during the process is a very

different type of safeguard than using elaborate description of what exactly is required for the project.

Inspections of the process while the supplier is working on the project not only allow the buyer to

investigate interim progress but also provide strong incentives for the supplier to work diligently on the

innovative task. Without the measurement cost, the buyer could simply stipulate very clear

performance criteria or other measureable factors that the innovative output would have to meet and

simply verify these at the end of the project; but when such measurement is problem, the firms will

reduce their reliance on task description in the contract.

Hypothesis 1: High measurement costs (i.e., it is costly or impossible to measure quality after the task

has been completed) will negatively moderate the relationship between innovation and

task description.

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Another hazard that afflicts many firms in a wide variety of industries arises from the need for

interdependence to complete the transaction. Interdependencies within or among projects create an

exchange hazard because they lead to bilateral dependency between the buyer and supplier (or among

multiple suppliers) involved with the project. Such interdependencies may arise because the size of the

project requires more resources than the supplier currently has available or because the project requires

a greater variety of skills than any single firm possesses.

Interdependencies also make verification of the effort to mutually adjust difficult since the

performance of one aspect of the task depends on another, which creates an incentive to strategically

shift costs from one organization to another. For instance, if there is more than one way to adapt to an

unexpected problem, then the groups in charge of the affected modules are likely to prefer solutions

that require others to make any necessary changes.

Thus interdependence poses a clear exchange hazard that requires a strong safeguard. The

positive link between innovation and task description is again challenged because the task description

required to mitigate the bilateral dependence problem are likely to be prevention focused as they will

seek to ensure that no mistakes are made as the parties work together. When interdependence is high,

there is a strong desire to describe the task and responsibilities in a way that specifies what not to do

and highlights penalties for missing deadlines or not performing to specifications. Such a prevention

frame is not conducive to innovation and thus the parties will chose to rely on other safeguards to

mitigate the hazard.

Hypothesis 2: High levels of interdependence between the buyer and supplier in completing the task

will negatively moderate the relationship between innovation and task description.

One aspect of interdependence that is different than the hazards arising from measurement

costs is that the parties must find some mechanism to specify how they will interact. Specifying

monitoring rights may be sufficient when measurement costs are involved, but are insufficient to

address problems arising from interdependence. One option for the parties is to shift their focus from

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specifying extensive task descriptions to specifying relevant contingencies and how they will handle

them. While this might involve some prevention-framed language, the parties may be better able to

frame relevant issues in a more promotion-oriented light than when describing very detailed tasks.

Weber et al (2011) describe framing a duration contingency as either an option to extend (promotion-

framed) or an option for the buyer to terminate early (prevention-framed). Thus when a transaction

requires both innovation and interdependence, the parties may choose to increase their use of

contingency planning.

Hypothesis 2a: High levels of interdependence between the buyer and supplier in completing the task

will positively moderate the relationship between innovation and contingency planning.

The final hazard will we will examine involves appropriability concerns over the use of the

supplier’s proprietary technology (e.g., Oxley, 1997; Pisano, 1990). When a supplier must use its

proprietary technology to complete a task for a buyer, the supplier will seek to protect its technology so

the buyer cannot reuse it in other contexts. Appropriability concerns have led firms to adopt a variety

of safeguards, including more hierarchical forms of alliances (Oxley, 1997), avoiding the use of

subcontractors (Mayer & Nickerson, 2005) and relying on fixed fee contracts (Kalnins & Mayer, 2004).

When firms must both use their proprietary technology and produce an innovative solution for

the buyer, then we face the same challenges with task description as discussed above for measurement

costs and interdependence. The type of specificity required to protect the firm would tend to have a

prevention-frame while innovation requires a promotion-frame. Thus the firms will choose to use

relatively sparse task descriptions and rely upon another safeguard to protect the supplier’s proprietary

technology.

Hypothesis 3: The need to utilize the supplier’s proprietary technology will negatively moderate the

relationship between innovation and task description.

Innovation and the Payment Mechanism

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While the discussion to this point has focused on the role of exchange hazards in negatively

moderating the relationship between innovation and task description, but there are other parts of the

contract that may be influenced directly by innovation. One element of the contract that is likely to be

influence 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 hazards that

need to be addressed (Kalnins & Mayer, 2004).

Fixed fee contracts create a shirking hazard as the supplier can retain any money saved that

does not need to be invested in the project. Shirking can lead to cutting corners and finding non-

obvious ways to decrease costs because only the supplier benefits from cost reduction. This is

problematic for a project requiring innovation for two reasons. First it puts the supplier’s focus on

costs and trying do complete the transaction as cheaply as possible so they can emerge with the most

possible profit. Second, 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.

A T&M contract overcomes the challenges that plague fixed fee contracts because there is not

incentive to excessively reduce costs because the 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 exactly as much work is required to complete the transaction. The problem with a T&M

contract is that the supplier has no incentive to work hard to either complete the task by a particular

date or be efficient in resource utilization because they pass all their costs along to the buyer. Such a

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contract is particularly problematic when innovation is required because it will be difficult for the

buyer to determine if delays and additional work is 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 of a

fixed fee and a pure T&M contract. 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, and the supplier then incurs all costs above

that amount. Thus the buyer has protection from the supplier inflating costs and the supplier has some

incentives for efficiency but without having to specify an exact price ex ante. The hybrid solution

introduces flexibility that offers the supplier the opportunity to be creative and seek the most

innovative solution possible while also applying some efficiency incentives.

Hypothesis 4: When a project requires innovation, the supplier is more likely to be paid using a T&M

contract with a cap than with a fixed fee or with an uncapped T&M contract.

EMPIRICAL ANALYSIS

Industry Context: The Information Technology (IT) Services Industry

IT services is an ideal 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 services firms perform a variety of

projects for their customers that can include designing customized software systems, updating and

maintaining existing software or hardware systems, and assisting with network design and security.

IT services work is primarily performed on a project basis. Buyers identify an IT project and

then secure resources to complete it. Each project is distinct and buyers can engage one supplier for

one transaction and another supplier for the next transaction. Most projects are complex, and many

19

require innovation to complete while others merely involve executing well-understood capabilities. As

the contract serves a key role in defining the exchange, contract design is particularly important and

can play an important role in influencing how the transaction is executed.

Data

We test our hypotheses with data from Compustar, a provider of computer-related hardware

and IT services. Compustar has produced mainframes and related hardware since the 1970s, and

entered the platform-independent IT services business in the mid-1980s.2 By 1997, Compustar’s IT

services division accounted for revenues of approximately $100 million worldwide. Compustar’s

buyers are mostly Fortune 1000 firms, as its core mainframe business naturally coincided with the

needs of larger clients.

Compustar provided access to IT services contracts with buyers, 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 approximately 25% of the Compustar

contract population. A review by Compustar personnel indicated that this sample was representative, in

terms of customer industries represented, customer size, number of contracts between Compustar and

the firm, 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 document a

discrete project for which Compustar supplied IT services. A typical IT services contract is about five

pages long and is designed to accomplish a specific task. It contains a detailed project description,

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.

20

including the type of service required and the responsibilities of each party (in varying degrees of

detail). Project duration can range anywhere from one week to more than a year, while project values

range from one thousand to several hundred thousand dollars.

Two experienced Compustar engineers familiar with the contracts library coded several sample

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 (3), PROGRAMMING

(2) and INNOVATION (1)—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 IT

professionals inside and outside of Compustar to discuss the measures and solicit additional comments

and feedback.

Measures

Dependent Variables. The focus of hypotheses H1, H2 and H3 is the level of task description in the

contract. TASK DESCRIPTION, was coded by our engineers on a 1-7 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, or specific responsibilities the customer must fulfill in order for the project to be

completed. This latter category might include information and resources required from the customer in

order to determine the software applications that need to be migrated.

Hypothesis 2a focuses on the level of contingency planning in the contract. Many of

Computar’s contracts made no provision for contingency planning while others contained clearly

identified efforts to plan for future contingencies. Because the engineers had limited time, they agreed

to code our CONTINGENCY PLANNING variable on a 0 to 2 scale: as zero if the contract in question

21

contained no contingency planning, 1 if processes were included to address generic contingencies, and

2 if specific contingencies were addressed. Forty-one 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 whatever contingencies might arise (coded as 1) rather than addressing specific

contingencies in the contract.4

Hypothesis 4 explores the payment mechanism and the two archetype payment mechanisms

used by Compustar in these contracts. Fixed fee contracts involve Compustar completing a specific

task in exchange for a predetermined total price. Time and materials contracts involve Compustar

being compensated based on an hourly or daily rate plus expenses until the task is complete. Some

time and materials contracts involve a maximum amount that can be charged to the buyer (with

Compustar covering expenses above this amount) while others have no such ceiling. We code

CONTRACT TYPE as a dichotomous variable that is coded as one if the contract involves a time and

materials payment mechanism and zero if it involves a fixed fee payment.

Independent Variables. INNOVATION is an ordinal variable that ranges from one for projects that

―require no innovation to complete‖ to seven for projects that ―cannot be completed without a

technological breakthrough.‖5 This variable does not merely capture complexity, but instead measures

the requirements to push technology forward for successful project completion. When innovation

requirements are high, greater uncertainty surrounds Compustar’s ability to successfully complete the

task(s).

Some types of innovation may involve output whose ultimate quality is difficult to initially

ascertain. We want to isolate the effect of innovation from projects that have simply have output

whose quality is difficult to measure. MEASUREMENT captures the cost of measuring quality after

project completion, and is based primarily on technological aspects. Due to the largely subjective

4 The results are unchanged if we combine both types of contingency planning and create a dichotomous measure.

5 There were no projects that were coded by Compustar engineers as a 7. The actual range is from 1 to 6.

22

nature of measurement costs, Compustar personnel coded MEASUREMENT as one if quality is

difficult to determine and zero if it is readily apparent. The coding criterion used was whether a brief,

inexpensive test or inspection could determine the quality of the work done.

Compustar personnel created a list of proprietary technologies important to its IT services

competitive advantage. Compustar engineers coded this variable based on the list of proprietary

technologies and an examination of the contracts. PROPRIETARY is a dichotomous variable coded as

one if one or more of Compustar’s proprietary technologies is required for a project, and zero

otherwise.

Interdependencies are clear from the contracts and were coded by the Compustar engineers.

INTERDEPENDENCE is coded as one if the buyer is directly involved in the project such that

Compustar depends upon the buyer to complete its task(s), and zero otherwise.

Control Variables. Capabilities may influence many elements of a contract including the payment

mechanism and the level of detail it contains. Compustar has superior internal capabilities relative to

its competitors in servicing hardware that it designed and manufactured. COMPUSTAR HARDWARE

is a dichotomous 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 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.

Areas where Compustar’s capabilities are acknowledged as weaker or at best equivalent to its

competitors are servicing other vendor’s non-mainframe hardware and programming6

. 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 relatively limited experience in

6 Many IT firms service storage devices and other non-mainframe IT hardware, including the firms that originally

manufactured this equipment.

23

programming. PROGRAMMING is a dummy variable that is coded as one if the project involves

programming, and zero otherwise.

Other project-level attributes that may affect contract design are also included. Another factor

than can lead to more complete contracts is when there is a high cost to failure in the project.

DISRUPT is a dichotomous variable that was coded by Compustar engineers as one if a project has the

potential to shut down a ―significant portion‖ of a customer’s data center, and zero otherwise.

Unexpected data center shutdowns are very costly for customers and tend to be highly visible events,

thus causing significant reputational damage to suppliers such as Compustar. When such an outcome

is possible, Compustar will take pains to describe exactly what must be done to minimize the chances

of such a negative outcome.

We also control for the influence of the prior relationship between the buyer and supplier in IT

services (i.e., prior transactions in which this buyer engaged Compustar for IT services). PRIOR

PROJECTS represents the number of projects that Compustar has completed for the buyer prior to the

current transaction.

Another aspect of the relationship between the parties is the number of links between the firms.

Information on the level of business each customer has completed with Compustar prior to the focal

project measures this effect. 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).

We also included year dummies to test for time effects.

Summary statics for all variables are in Table 1 while correlations are in Table 2. Correlation

levels are generally low and suggest that multicollinearity is not a problem in these data.

-------------------------------------- Insert Tables 1 & 2 about here

24

--------------------------------------

Results

In the base model for task description (Model 1 of Table 3) we do indeed find that innovation

(p<0.01) leads to less detailed task description in the contract, which duplicates the result found by

Argyres et al (2007) and forms the basis from which we examine the moderating effects of exchange

hazards. In addition, we find that projects involve programming (p<0.01) lead to less detailed task

descriptions, while projects involving hardware from other firms (p<0.01) and buyers with extensive

ties to Compustar (p<0.01) involve more detailed task descriptions.

One interesting result of the base model is that the three exchange hazards that we posit will

negatively moderate the relationship between innovation and task description each individually have

different influences on task description. Measurement costs lead to less task description (p<0.01),

interdependence weakly leads to more task description (p<0.10), while appropriability has no

significant effect. The common link between these three factors, however, is that they pose exchange

hazards for the transaction and thus we hypothesize that they will all have a common effect as

moderators of the relationship between innovation and task description.

-------------------------------------- Insert Table 3 about here

--------------------------------------

Models 2 – 4 add the interaction variables that allow us to test H1, H2 and H3. The interaction

between INNOVATION and MEASUREMENT in Model 2 is negative and significant (p<0.10),

which supports H1. The significance of the interaction is weak, however, as the significance just

misses the 0.05 threshold (p=0.056), but it still provides qualified support for H1. We observe stronger

support for H2 in Model 3 as the interaction between INNNOVATION and INTERDEPENDENCE is

negative and significant at the p<0.05 level. H3 receives even stronger support as the interaction

between INNOVATION and PROPRIETARY is negative and highly significant (p<0.01) in Model 4.

25

Thus we find strong support for the overall proposition that exchange hazards negatively moderate the

positive relationship between innovation and task description.

Model 5 is the base model for CONTINGENCY PLANNING and sets the stage for us to test

H2a. We see from Model 5 that INNOVATION has a positive and weakly significant (p<0.10) effect

on the level of contingency planning. When we add the interaction between INNOVATION and

INTERDEPENDENCE in Model 6, we find a positive and significant effect (p<0.01), which provides

support for H2a.

Models 7 and 8 examine the payment mechanism to allow us to test H4. In these models we

examine when the firms choose to use a hybrid contract (T&M contract with a cap) instead of either a

fixed fee contract or a pure T&M contract. We can see from Model 8 that INNOVATION is positive

and significant (p<0.01), which provides support for H4. Few other factors lead to a preference for

hybrid contracts over one of the two ―pure‖ types, but projects involving working on mainframes

(p<0.01) and projects for buyers the firm has done work for in the past (p<0.01) also lead to the kind of

flexibility of hybrid contracts.

Robustness

Interpreting coefficients in non-linear models is problematic (Hoetker, 2007; Zelner, 2009). As

our primary dependent variable ranges from 1 to 7, Models 1 through 4 of Table 4 replicate the first

four models of Table 3 but use OLS instead of an ordered probit. The results are remarkably

consistent with our original results. The statistical significance of the INTERDEPENDENCE *

INNOVATION interaction drops just below the 0.05 level of significance (to 0.058) while the

significance of the MEASUREMENT * INNOVATION interaction improves to just outside of 0.01 (to

0.19). The APPROPRIABILITY * INNOVATION interaction remains highly significant (p<0.01).

Thus the results provide support for the moderating effect of exchange hazards in both ordered probit

and OLS specifications (i.e., Hypotheses 1-3 are find at least qualified support in all models in both

specifications—the p-values for all variables remains below 0.06, but do rise above 0.05 in two cases).

26

-------------------------------------- Insert Table 4 about here

--------------------------------------

DISCUSSION

The purpose of this paper is to better understand how firms use contracts to govern innovative

transactions. While there are a variety of components to a contract, we selected two that we believe

are particularly important for innovative projects. Prior work (Argyres et al, 2007) showed a strong

direct relationship between innovation and task description, so were able to build on their work. While

to our knowledge prior work 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.

We also considered efforts to plan for contingencies, a topic also touched on by Argyres et al (2007).

As there is no clearly agreed upon way to break down a contract into its component pieces, we lack a

clear guide on how to break down the contract to study the effect of innovation on contract design. By

focusing on the specification of what is to be done and how the buyer will compensate the supplier, we

believe we have examined both foundational aspects of the contract and ones likely to play a key role

in the success of projects with a need for innovation.

Theoretically, we argue that there is a need to integrate individual and team-level research on

innovation (e.g., Spektor et al, 2011) with transaction cost economics (TCE) in order to fully

understand how contract design influences the potential for the parties in an inter-firm transaction to

produce an innovative result. TCE is a powerful theory with tremendous empirical support (see

Macher & Richman, 2008 for one recent review) but it hasn’t been extensively applied to innovation

except as a means of seeking to mitigate hazards arising from appropriability (see Adner and Kapoor,

2010; Argyres and Bigelow, 2009 for two exceptions).

TCE has an implicit assumption that draws back to Macaulay (1963) who noted that contracts

have two purposes: to define the exchange and to enforce it. Williamson (1975, 1985) builds on this as

27

he develops TCE by focusing on the importance of overcoming bounded rationality (defined as limits

on processing information, not cognitive biases) and mitigating opportunism. Both of these goals are

fundamental to completing inter-firm transactions, and designing effective contracts, but while they are

necessary, they are not sufficient conditions to ensure the success of an inter-firm transaction that

requires innovation. The contract does indeed form a blueprint for the exchange (Macneil, 1978), but

it does more than define the tasks and prevent opportunism. The contract can be an important element

in the emotional response of individuals to the transaction and to their exchange partner (Weber et al,

2011; Weber & Mayer, 2011a).

Research on framing in regulatory focus theory (e.g., Higgins, 1998) and individual cognitive

processes (e.g., Grant & Berry, 2011) and determinants of team success (e.g., Spektor et al, 2011) can

play important roles in complementing the rational governance perspective of TCE. If the contract can

be designed in such a way that not only do the parties have aligned expectations and proper incentives

to fulfill their obligations in the transaction, but also to foster an environment that maximizes the

chances for success by setting the right frames, invoking the cognitive processes most suitable for the

transaction and directing team interaction in the most productive way possible. The fundamental

premise of TCE is absolutely correct—there needs to be an alignment between the attributes of the

transaction and the governance structure, but by incorporating research from social psychology we can

conceptualize alignment in a different way. The key is to look more broadly at what is required for a

successful transaction and the importance of emotion, cognitive, social and team factors. A

straightforward transaction like procuring nuts and bolts or buying commodities requires little attention

to social psychology factors (i.e., there is little uncertainty, no need for creativity/innovation, few

exchange hazards and typically many alternative suppliers); but transactions involving more complex

interaction between firms and/or in which one firm must do something challenging or uncertain could

benefit from considering the role of social psychology factors in determining the best way to govern

the transaction by expanding the factors to consider in creating alignment between the attributes of the

28

exchange and the governance structure. Alignment is often more than mitigating opportunism and

defining the roles of each party, and micro level research from social psychology can help inform

governance-transaction alignment in a much more nuanced way for many different types of

transactions, including those involving innovation.

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 mode. Ghoshal and Moran (1996) pointed out that the contract could

engender a very negative response if people perceive the presence 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.

What is important going forward is the realization that by combining individual and team-level

theories with TCE, we can do a better job of understand how to design contracts in such a way that

they can still mitigate hazards but in a way that is sensitive to the potential emotional responses of the

other party and manage this response to best position the transaction for success.

Generating innovation requires more than just defining what is expected and mitigating

hazards; it involves creating an environment that encourages people to think creatively and produce

innovative output (e.g., Spektor et al, 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 innovation. Just because a firm

boundary is crossed doesn’t mean the effects found in studies of intra-firm teams don’t apply.

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

29

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 focus specifically on transactions requiring innovation because of the well-established

importance of the environment in fostering (or hindering) innovation. We show that the presence of

contractual hazards and the need for innovation in the same transaction changes how the firms utilize

the contract to govern the exchange. We believe that this effect is driven by a desire to use the contract

to help create an environment that will foster innovation. Effective governance is not merely the

elimination of a negative outcome (mitigate opportunism), it is frequently also about creating a

positive outcome. TCE has an inherent prevention focus (Weber & Mayer, 2011a), but fostering

innovation requires more a promotion focus. Learning how to design contracts that create the right

kind of frame can improve the performance of a firm’s inter-firm transactions and ultimately play a

role in establishing a competitive advantage.

We largely focused on examining the moderating effect of contractual hazards on the

relationship between innovation and task description, but we want to note that the moderating effect

we find does not eliminate the need to mitigate opportunism, nor does it mean that firms can’t create a

strong environment for innovation in the presence of such hazards. We believe our findings indicate

that the presence of contractual hazards changes how firms will design contracts for innovative

projects but does not mean that the simultaneous presence of innovation and hazards prevents

innovation from taking place. Innovation is an aspect of what is required to produce the desired

outcome that is a kind of irreducible uncertainty (i.e., the technology to fulfill the need simply does not

currently exist), while exchange hazards involve a type of uncertainty (individual actions) that can be

addressed through incentives and other safeguards. We do believe exchange hazards make it more

30

challenging to innovate, but more work is needed to better understand the breadth of contractual

responses in this situation.

We did examine two other responses—the extent of contingency planning and the payment

mechanism. In the presence of interdependence we find that innovation leads to greater efforts to plan

for contingencies that might arise. Thus we see that when projects involve both innovation and

interdependence, firms shift from using more task description to making more effort to plan for

contingencies. While many interpretations of this result may be possible, we believe the underlying

reason is that firms can better utilize contingency planning as a safeguard in a way that doesn’t create a

prevention-frame, which would damage the chances of a successful innovation outcome when both

innovation and interdependence are required to complete the transaction.

We turned our attention from moderating effects to direct effects when looking at the impact of

innovation on the payment mechanism specified in the contract. Incorporating this element into the

paper gives us a broader picture of how innovation influences contract design. We find that both fixed

fee and time and materials (T&M) contracts have problems in fostering innovation that may be fixed

by utilizing a hybrid of the two that involves using a T&M contract with a cap, above which the

supplier bears the costs to complete the project. In keeping with micro-level work on the importance

of fostering creativity and flexibility to promote innovative outcomes, using a payment mechanism that

involves some flexibility with some incentives seems to strike the right balance between mitigating

opportunism by creating strong incentives while also fostering creativity through flexibility.

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 & Mayer, 2011a, 2011b being exceptions). This paper

takes one important step in that direction 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 while transactions involving innovation have more

31

detailed task descriptions, the presence of exchange hazards in the transaction negatively moderates

this relationship. Simultaneously mitigating hazards while fostering innovation requires a creative

approach to contract design and may include more reliance on relational governance (e.g., Poppo &

Zenger, 2002) and a better understanding of micro-level factors like emotions 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 & Moran, 1996) and TCE scholars who focus on contracts as a

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.

Limitations & Future Research

As with all studies, potential limitations must be addressed. First, managers and engineers,

rather than lawyers, negotiated the contracts examined in this study. Lawyers did conduct a final stage

review of the contracts and rarely requested changes, but the contracts might be different if lawyers

were the primary negotiators, which is an interesting topic for future research.

Second, while most contracts are based on templates, the templates don’t specify one payment

that must be used nor can they specify the details required for the particular 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 must be negotiated for each transaction. The role

of elements of the contract template in fostering innovation is potentiall very productive avenue for

future research.

32

One of the strengths of this study—the microanalytic data from within a single firm—is also a

limitation. The detailed, transaction-level data enables us to offer insights into contractual choices

rarely available with larger inter-industry studies. Critics may suggest that the results only reflect

Compustar’s contracting policy, and not that of its buyers. Because most of Compustar’s buyers are

large companies with many alternatives for IT service suppliers, however, we are confident the

negotiated contracts do not solely reflect Compustar policy but also significantly integrates 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 generalizes to other types of projects, including product development,

telecom and other infrastructure, consulting, joint development, among others. Nevertheless, future

research to explore the generalizability of this study would still 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 to more closely examine the link

between contract design and subsequent behavior during the transaction would be very valuable, as

would studies that include data on transaction performance, including innovativeness.

Conclusion

We believe that this paper is just the start of research exploring how inter-firm projects

requiring innovation should be governed. While we believe that examining the role of basic

contractual elements such as task description and the payment mechanism are natural places to start,

33

we believe much more research is required to integrate ideas from micro-level research on individuals

and teams into TCE’s focus on effective governance.

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., avoid opportunism and avoid problems arising

from bounded rationality such as misaligned expectations) rather than creating a positive environment.

The contract governing any inter-firm transaction must be aligned with what the transaction is

expected to accomplish. If the transaction is simple, then an arms-length contract or even a simple

purchase order may be a perfectly adequate governance choice. As Williamson (1975, 1985)

articulates the need for more elaborate, and often hierarchical, governance in the face of exchange

hazards, but the challenges for inter-firm transactions posed by innovation that require more than

mitigating a hazard or ensuring the parties understand their roles have yet to be extensively examined.

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 & Berry, 2011;

Spektor, 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.

34

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40

Table 1: Summary Statistics

Variable Obs. Mean Std. Dev. Min Max

Task Description 396 3.402 1.866 1 7

Contingency Planning 397 0.557 0.632 0 2

Hybrid 394 0.107 0.309 0 1

Innovation 405 2.521 1.203 1 6

Compustar HW 405 0.232 0.423 0 1

Mainframe 405 0.262 0.440 0 1

Programming 405 0.459 0.499 0 1

Other Firm Hardware 405 0.091 0.288 0 1

Measurement Cost 405 0.440 0.497 0 1

Interdependence 405 0.121 0.327 0 1

Proprietary 405 0.153 0.361 0 1

Ability to Disrupt 405 0.472 0.500 0 1

Number of prior projects 405 4.106 7.438 0 41

Breadth 405 4.249 2.766 0 9

Table 2: Correlation Statistics

Task D

escrip

tion

Conting

ency P

lan

nin

g

Hybri

d

Inn

ovation

Com

pusta

r H

W

Main

fram

e

Pro

gra

mm

ing

Oth

er

Fir

m H

ard

ware

Mea

su

rem

en

t C

ost

Inte

rdep

end

ence

Pro

prieta

ry

Abili

ty to

Dis

rupt

Num

ber

of

pri

or

pro

jects

Bre

adth

Task Description 1.00

Contingency Planning 0.25 1.00

Hybrid 0.08 -0.06 1.00

Innovation 0.17 -0.03 0.15 1.00

Compustar HW 0.02 0.05 -0.05 -0.26 1.00

Mainframe -0.02 -0.12 0.06 -0.08 0.34 1.00

Programming -0.21 -0.08 0.05 0.25 -0.29 0.04 1.00

Other Firm Hardware 0.16 0.13 -0.02 -0.13 0.06 0.00 0.04 1.00

Measurement Cost -0.18 -0.16 0.03 0.34 -0.25 0.04 0.25 -0.23 1.00

Interdependence 0.05 0.12 -0.02 0.15 -0.10 0.04 0.15 0.01 0.20 1.00

Proprietary 0.02 0.13 0.00 -0.05 0.05 0.06 0.01 -0.07 -0.07 0.03 1.00

Ability to Disrupt -0.02 0.08 -0.08 0.03 0.31 0.27 0.06 -0.07 -0.07 0.00 0.05 1.00

Number of prior projects -0.02 0.14 0.16 -0.05 0.04 -0.07 -0.05 -0.05 -0.08 -0.03 0.26 -0.06 1.00

Breadth 0.14 0.05 0.03 -0.02 0.12 -0.08 -0.09 -0.09 -0.23 -0.07 0.24 -0.01 0.53 1.00

41

Table 3: Empirical Results

Ordered Probit Estimation Probit Estimation

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8

Dependent Variable TD TD TD TD CP CP Hybrid Hybrid

Innovation 0.329*** 0.436*** 0.375*** 0.391*** 0.111* 0.037 0.313***

(0.053) (0.077) (0.058) (0.057) (0.061) (0.067) (0.096)

Innovation * Measurement -0.192*

(0.101)

Innovation * -0.258** 0.413***

Interdependence (0.127) (0.151)

Interaction * Proprietary -0.425***

(0.14)

Compustar HW -0.153 -0.132 -0.138 -0.158 0.109 0.072 -0.451 -0.385

(0.152) (0.152) (0.152) (0) (0.178) (0.179) (0.308) (0.317)

Mainframe 0.080 0.054 0.052 0.134 -0.36** -0.309* 0.624** 0.725***

(0.135) (0.136) (0.136) (0) (0.161) (0.162) (0.247) (0.257)

Programming -0.698*** -0.754*** -0.737*** -0.643*** -0.261* -0.207 0.385* 0.263

(0.123) (0.126) (0.124) (0) (0.141) (0.143) (0.218) (0.222)

Other Firm’s Hardware 0.789*** 0.805*** 0.791*** 0.846*** 0.55** 0.569*** -0.178 -0.082

(0.196) (0.196) (0.196) (0) (0.217) (0.217) (0.376) (0.383)

Measurement Cost -0.568*** -0.064 -0.582*** -0.577*** -0.318** -0.3** -0.108 -0.302

(0.13) (0.294) (0.13) (0) (0.151) (0.151) (0.219) (0.235)

Interdependence 0.307* 0.316* 1.075*** 0.257 0.684*** -0.543 -0.354 -0.396

(0.165) (0.165) (0.412) (0) (0.192) (0.491) (0.32) (0.315)

Proprietary 0.250 0.27* 0.226 1.163*** 0.160 0.206 -0.492 -0.614*

(0.156) (0.156) (0.156) (0) (0.18) (0.181) (0.358) (0.373)

Ability to Disrupt 0.031 0.013 0.040 0.083 0.208 0.212 -0.152 -0.200

(0.123) (0.124) (0.123) (0) (0.143) (0.144) (0.236) (0.238)

Number of prior projects -0.008 -0.009 -0.006 -0.004 0.017 0.015 0.066*** 0.071***

(0.01) (0.01) (0.01) (0) (0.011) (0.011) (0.017) (0.017)

Breadth 0.063*** 0.061** 0.059** 0.076*** -0.027 -0.020 -0.033 -0.042

(0.024) (0.024) (0.024) (0) (0.028) (0.028) (0.045) (0.047)

Year 1991 -0.235 -0.269 -0.215 -0.181 0.82** 0.784* -0.432 -0.344

(0.306) (0.306) (0.307) (0) (0.417) (0.42) (0.489) (0.506)

Year 1992 0.321 0.303 0.366 0.313 1.541*** 1.496*** -0.919** -0.831*

(0.243) (0.243) (0.244) (0) (0.335) (0.337) (0.426) (0.435)

Year 1993 -0.419 -0.443* -0.418 -0.495* 1.11*** 1.114*** (omit) (omit)

(0.256) (0.256) (0.256) (0) (0.349) (0.351) (omit) (omit)

Year 1994 -0.304 -0.328 -0.286 -0.353* 0.975*** 0.953*** -0.508 -0.569*

(0.214) (0.214) (0.214) (0) (0.311) (0.313) (0.333) (0.34)

Year 1995 -0.365* -0.371* -0.393** -0.392** 1.364*** 1.415*** -0.654** -0.583*

(0.199) (0.199) (0.199) (0) (0.292) (0.293) (0.314) (0.322)

Year 1996 -0.585*** -0.594*** -0.579*** -0.66*** 1.42*** 1.415*** -1.42*** -1.277***

(0.205) (0.205) (0.205) (0) (0.297) (0.297) (0.377) (0.38)

Year 1997 -0.316 -0.314 -0.320 -0.394* 1.635*** 1.646*** -1.9*** -1.825***

(0.209) (0.209) (0.209) (0) (0.299) (0.3) (0.502) (0.493)

Year 1998 -0.863*** -0.908*** -0.876*** -0.999*** 1.129*** 1.144*** -0.866* -1.075*

(0.308) (0.31) (0.308) (0) (0.387) (0.388) (0.504) (0.552)

Constant -0.793*** -0.617** -0.72*** -0.568** 1.414*** 1.294*** -0.722** -1.452***

(0.229) (0.246) (0.231) (0) (0.32) (0.323) (0.311) (0.396)

N 396 396 396 396 397 397 367 367

LogL -688.81 -686.99 -686.75 -684.21 -312.58 -308.74 -105.87 -100.39

χ2 117.59 121.24 121.72 126.79 90.71 98.39 49.35 60.3

Pseudo-R2 0.079 0.081 0.081 0.085 0.127 0.137 0.189 0.231

*** p<0.01 ** p<0.05 * p<0.10

TD = Task Description, Hybrid = Hybrid contract (i.e., T&M with cap), CP = Contingency Planning

42

Table 4: Empirical Results – OLS Estimations

DV: Task Description

model 0 model 1 model 2 model 3 model 4

Innovation 0.466*** 0.676*** 0.531*** 0.555***

(0.085) (0.127) (0.093) (0.09)

Innovation * -0.375**

Measurement (0.172)

Innovation * -0.391*

Interdependence (0.223)

Innovation * -0.68***

Proprietary (0.234)

Compustar HW -0.464* -0.281 -0.235 -0.259 -0.286

(0.243) (0.233) (0.234) (0.234) (0.234)

Mainframe 0.123 0.175 0.125 0.132 0.258

(0.206) (0.198) (0.195) (0.198) (0.201)

Programming -0.909*** -1.057*** -1.165*** -1.108*** -0.955***

(0.199) (0.194) (0.202) (0.193) (0.196)

Other Firm Hardware 1.176*** 1.247*** 1.266*** 1.239*** 1.317***

(0.336) (0.324) (0.325) (0.325) (0.321)

Measurement Cost -0.391* -0.71*** 0.271 -0.724*** -0.711***

(0.219) (0.225) (0.497) (0.223) (0.222)

Interdependence 0.552* 0.43 0.448 1.586** 0.347

(0.286) (0.294) (0.297) (0.707) (0.286)

Proprietary 0.106 0.27 0.311 0.231 1.726***

(0.267) (0.279) (0.283) (0.275) (0.527)

Ability to Disrupt 0.195 0.056 0.021 0.068 0.134

(0.208) (0.2) (0.199) (0.2) (0.202)

Number of -0.017 -0.018 -0.021 -0.016 -0.011

prior projects (0.016) (0.016) (0.016) (0.016) (0.017)

Breadth 0.132*** 0.113*** 0.108** 0.105** 0.131***

(0.042) (0.043) (0.042) (0.043) (0.043)

Year 1991 -0.377 -0.296 -0.367 -0.261 -0.206

(0.555) (0.564) (0.57) (0.552) (0.546)

Year 1992 0.42 0.562 0.522 0.621 0.537

(0.459) (0.449) (0.444) (0.452) (0.438)

Year 1993 -0.275 -0.546 -0.593 -0.54 -0.657

(0.507) (0.479) (0.494) (0.479) (0.464)

Year 1994 -0.257 -0.339 -0.39 -0.311 -0.409

(0.392) (0.381) (0.38) (0.375) (0.368)

Year 1995 -0.757** -0.564 -0.573* -0.601* -0.6*

(0.334) (0.344) (0.342) (0.339) (0.336)

Year 1996 -0.899*** -0.729** -0.746** -0.712** -0.841***

(0.329) (0.325) (0.321) (0.319) (0.318)

Year 1997 -0.474 -0.318 -0.318 -0.321 -0.435

(0.369) (0.359) (0.355) (0.353) (0.356)

Year 1998 -0.812* -0.918** -0.984** -0.93** -1.12***

(0.452) (0.414) (0.405) (0.414) (0.416)

Constant 3.743*** 2.783*** 2.429*** 2.672*** 2.423***

(0.363) (0.402) (0.411) (0.404) (0.423)

N 396 396 396 396 396

F value 4.69*** 6.96*** 6.86*** 6.9*** 7.26***

R-Squared 0.161 0.226 0.238 0.234 0.245

*** p<0.01 ** p<0.05 * p<0.10