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Contracting in the Shadow of the Future: Bilateral Reputation and Relational Controls in

Inter-Firm Transactions

Anjana Susarla

Department of Accounting and Information Systems

Broad College of Business

Michigan State University

East Lansing, MI 48824

Phone: 517-432-8350

asusarla@broad.msu.edu

Ranjani Krishnan

Department of Accounting and Information Systems

Broad College of Business

Michigan State University

East Lansing, MI 48824

Phone: 517-353-4687

krishnan@broad.msu.edu

We thank Bob Gibbons, Ricard Gil, Bob Kaplan, Jacques Lawarree, and Steven Tadelis, for their

comments.

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Contracting in the Shadow of the Future: Bilateral Reputation and Relational Controls in

Inter-Firm Transactions

ABSTRACT

Inter-firm contracting involves balancing the costs of ex ante incentives to reduce moral hazard

with ex post hold up and adaptation costs. This tradeoff is complicated when there is potential for

deliberate obfuscation by the vendor, which cannot be detected through the client’s traditional

control mechanisms. In the presence of deliberate obfuscation relatively flexible, incomplete

contracts (such as cost-plus contracts) can reduce ex post hold up and adaptation costs. However,

moral hazard problems of cost-plus contracts may be severe enough to offset the benefits from

their lower adaptation costs leaving contracting parties with few feasible options. Under these

circumstances, relational controls based on observable but unverifiable information can help

contracting parties reach consensus. We use archival data of contracts that have potential for

deliberate obfuscation and examine if the formal contract form is influenced by two types of

relational controls. These relational controls include the possibility of a future horizon, and

bilateral reputation capital for cost containment. We predict that the likelihood of a cost-plus

contract is increasing in contracting parties’ possibility of a future horizon, and vendor bilateral

reputation for cost containment. We empirically test predictions using textual analysis of 149

SEC material contracts averaging $49.1 million in value, supplemented with hand-collected trade

and industry data. Results using recursive, simultaneous, bivariate probit estimations with

instruments for endogeneity corrections support our predictions.

JEL Codes: D23, D86, L14, M41

Keywords: Fixed price contract, cost plus contract, hold up, relational control, textual analysis.

Data Availability: Data are available from public sources cited in the text.

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1. Introduction

Literature acknowledges that performance gains accrue to firms that align their governance

and management control systems to attenuate exchange hazards (Gulati and Singh 1998; Laffont

and Tirole 1993; Mayer and Nickerson 2005; Williamson 1979). A contract is an important control

mechanism used to achieve this alignment. The optimal inter-firm contract balances the cost of

moral hazard arising from ex ante asymmetric information with the transaction costs associated

with ex post contract adaptations in the presence of exchange hazards (Williamson 1985). Various

types of contractual levers assist in the balancing process including, contract form (Bajari and

Tadelis 2001; Bajari, Houghton, and Tadelis 2014; Banerjee and Duflo 2000; Crocker and

Reynolds 1993; Corts and Singh 2004; Corts 2012), contractual governance structures (Argyres

and Mayer 2007; Faems et al. 2008; Klein 1996; Krishnan, Geyskens, Steenkamp 2016), contract

duration (Guriev and Kvasov 2005; Joskow 1987), and dispute resolution (Lumineau and Malhotra

2011; Malhotra and Lumineau 2011).

Drawing from insights from practice, we explore the effect of a novel source of exchange

hazard on contract form. This exchange hazard, which we term “deliberate obfuscation”, refers to

unverifiable actions by the vendor that increase future costs for the client. Deliberate obfuscation

implies that the vendor intentionally makes the project design or documentation opaque such that

it is difficult for the client to employ an alternate vendor to complete the project in the event of

hold up or contract termination. For example, a consulting company engaged for designing or

implementing IT systems can write computer programs that are hard to interpret or use by a third

party. Ex post it would be difficult to determine whether these choices were stylistic or intentional.

Deliberate obfuscation is a type of opportunism that is consistent with Williamson’s (1975, 6)

notion of “self-interest seeking with guile.” The unverifiable nature of such opportunistic

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behaviors stymies the ability to use contractual controls, which require the availability of verifiable

signals that can be agreed upon ex ante. We explore two types of relational controls that could

attenuate the concomitant relationship hazards.

Even in the absence of risk of deliberate obfuscation, designing a contract that optimally

balances moral hazard costs with ex post adaptation costs is a complex problem. The two most

commonly occurring contract forms in practice, namely fixed price (FP) and cost-plus (CP)

contracts can protect the contracting parties from one of the two major outcome risks (moral hazard

or adaptation costs) but leave them exposed to the other (Bajari and Tadelis 2001; Banerjee and

Duflo 2000). FP contracts specify an upfront price for a well-delineated project and minimize

moral hazard problems by providing maximum incentives for vendor efficiency. However, FP

contracts are inflexible by design. If modifications to the project specification are needed, parties

have to draft a change order and negotiate an amendment with the new set of services and pricing

clauses. A large body of literature, including the seminal works of Williamson (1975, 1979, 1985,

1996) finds evidence that factors such as uncertainty, task complexity, and asset specificity

increase the likelihood that FP contracts will be renegotiated, resulting in surplus-depleting

transaction costs (Bajari and Tadelis 2001; Corts 2012). Additionally, FP contracts do not

encourage information exchange that is crucial for a successful partnership between the client and

the vendor (Goldberg 1977). A vendor who anticipates profiting from renegotiation can withhold

valuable knowledge during the initial contract agreement and spend insufficient upfront effort on

the project to increase the chance of renegotiation. In contrast to FP contracts, CP contracts (also

known as “time and material contracts”) allow work to begin without a detailed initial

specification, and the vendor is compensated for costs incurred. CP contracts enable ex post

adaptation and foster information exchange; however CP contracts expose the client to moral

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hazard risks. The vendor in a CP contract has no incentive to keep costs low. The ensuing cost

creep and inefficiencies could be severe enough to offset the gains from the lower adaption costs.

Deliberate obfuscation increases the potential for hold-up in FP contracts. While a CP

contract can provide a solution to the hold-up problem, moral hazard and cost inefficiency

problems persist and could be severe enough to offset any adaptation gains. At the extreme,

contracting can break down altogether and expensive options such as vertical integration may be

the only route available (Carson, Madhok, and Wu 2006; Geyskens, Steenkamp, and Kumar 2006;

Gulati and Singh 1998; Mayor and Salomon 2006; Williamson 1985). We examine two unique

relational controls that could mitigate moral hazard problems that plague CP contracts. These

relational controls are: potential for future interactions (hereafter labelled “future potential”), and

vendor’s bilateral reputation capital for cost containment.

The first relational control is future potential, which enables contracting parties to uphold

contractual obligations that are difficult to specify ex ante and hard to verify ex post. The

possibility of a future horizon provides a mechanism to reward good behavior while sanctioning

deviations, and facilitates cooperative outcomes that may be infeasible in a one-shot transaction.

Future potential cannot be formally contracted upon because an existing contract cannot outline in

a legally defensible manner, the terms of a future contract that may or may not occur. We use

transaction cost economics (TCE) and develop the hypothesis that future potential reduces moral

hazard risk, and therefore increases the likelihood of CP contracts. The second relational control

is bilateral reputation capital, developed via a history of past interactions. Analytical models

indicate that bilateral reputation capital enables better information exchange and mitigates ex post

transaction costs. Past interactions develop trust by facilitating familiarity among contracting

partners (Arino et al. 2001); additionally the development of such relational capital shapes the

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economic value from exchange (Elfenbein and Zenger 2014). The moral hazard risk of CP

contracts can be attenuated through the vendor’s bilateral reputation for cost-containment. Both

these relational controls – future potential and bilateral reputation capital, have to be self-enforcing

because although they are observable to the transacting parties they are not verifiable by a third

party and therefore are non-contractible. The self-enforcement mechanism is provided through

“calculative trust” engendered by relational governance. Williamson (1993; 467) defines

calculative trust as occurring when “parties to such transactions understand a great deal about the

contractual relation of which they are a part and manage it in a calculative way.”

Obtaining measures of what transpired within a relationship, as opposed to measures of

prior interaction alone is an empirical challenge. An innovation in our study is that we use proxies

from archival data to measure the two relational controls. Through detailed archival data gathering

and text analysis, we create fine-grained measures of future potential as well as bilateral reputation

capital. Because overall experience of contracting parties rather than bilateral reputation capital

could impact contracts by making parties better at identifying contractual contingencies (e.g., Ryall

and Sampson 2009), we distinguish between general market experience of clients and vendors

versus bilateral reputation, which are measures of dyadic interaction.

Our study attempts to bridge two streams of research in inter-firm contracting. One stream

focuses on the relationship between contractual and relational governance (e.g., Gulati 1995;

Poppo and Zenger 2002) while a smaller stream of literature examines how relational assets

develop in exchanges (Bidwell and Fernandez-Mateo 2010; Elfenbein and Zenger 2014). We

contribute by identifying future potential and bilateral reputation capital as relational control

mechanisms that can influence the formal contract form. We incorporate signals of expected future

interaction as well as the history of prior interactions; in contrast most prior work confines its

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attention to relationship history. Limited attention has been paid to the manner in which bilateral

reputation capital accrues within a relationship and the mechanism by which such bilateral

reputation capital impacts the structure of contracts. An additional contribution is that we capture

a unique aspect of rent seeking by incumbent vendors that raises the cost of modification for

alternate vendors. While this form of rent seeking is especially relevant to our context of

technology-intensive contracting environments, it is also applicable to other settings such as

consulting where the vendor has discretion in determining how the task will be performed. We

specifically include such opportunistic and unverifiable behavior in the empirical analysis, which

is novel to the literature. Finally, we add to the small but growing literature that uses actual

contract structures to help obtain insights into the factors that influence contract form, structure,

and contractual provisions (Chen and Bharadwaj 2009).

2. Theory and Hypotheses

Inter-firm contracting is plagued by contract incompleteness, defined as contracts that are

“insufficiently contingent, requiring actions that are often inefficient” (Edlin and Reichelstein

1996 (478). Contracting problems have largely been studied using the lens of TCE and relational

governance (Cao and Lumineau 2015; Faems et al. 2008; Krishnan et al. 2016). TCE stresses the

importance of contractual governance enabled by writing detailed contracts that contain numerous

provisions to cover contingencies that could arise in the future. TCE argues that well-formulated

contracts that delineate the rights and responsibilities of contracting parties in a judicious manner

could minimize losses from exploitation (Mayers and Argyres 2004; Lumineau and Malhotra

2011; Williamson 1975, 1985). Relational governance posits that contracts by themselves could

be incapable of safeguarding parties from opportunism. Informal or trust-based governance, used

jointly with contracts or in lieu of contracts can attenuate the challenges arising from ex post

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uncertainty (Cao and Lumineau 2015; Dyer and Singh 1998; Gulati 1995). Gibbons and Kaplan

(2015) note: “informal” does not imply “casual, haphazard or capricious behavior, but instead

managerial behavior not fully determined by rules or formulas—where executives use discretion

and judgment rather than managing solely ‘by the numbers.’ Examples of informal management

include adaptation, coordination, politics and influence, leadership, and informal authority.”

Numerous studies have examined whether contractual and relational governance are substitutes or

complements in attenuating exchange hazards (Poopo and Zenger 2002; Cao and Lumineau 2015;

Krishnan et al. 2016).

Exchange hazards are especially pronounced in large and complex procurement projects

that involve asset-specific investments, including considerable intangible and human capital

assets. Many of these projects are likely to be incomplete in initial specification for several reasons.

Consider an IT or supply chain outsourcing project that includes services that are interlinked with

the organization of business processes, which is idiosyncratic to individual client organizations

(Bresnahan, Brynjolfsson, Hitt 2002). The vendor’s role is substantially beyond that of supplying

a commodity delivered to conform to a standardized set of specifications. For instance, outsourcing

the construction of a data warehouse does not imply that the vendor supplies a repository for the

storage of data, but rather that the data warehouse leads to streamlined decision-making and

improved customer relationships for the client. Similarly, a vendor contracted to deliver

technology to fulfill accounting functions is not simply enabling labor substitution but

participating in organizational restructuring to eliminate redundant processes and enhance the

effectiveness of internal accounting and control. That is, the role of the vendor is to envisage a

blueprint for organizational and process changes.

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Indeed, clients often engage in outsourcing of complex IT services to achieve substantial

reorganization and process improvements (Linder 2004), which could make it difficult to describe

the required stream of services at the outset in a formal contract. Thus, the demand for IT, supply

chain and similar services can be firm specific and must take into consideration the underlying

business needs, the firms’ interactions with external partners (e.g., customers and suppliers), and

the overall industry context. These are relation-specific investments and have little to no value

outside the relationship. Relation-specific assets are especially common in the IT industry where

clients routinely seek customized solutions and exclusive technologies (Chen and Bharadwaj

2009). The pace of technological change creates a need for newer features and compatibility

requirements by the time the project is underway, increasing the incompleteness of the initial

specification. Further, the client’s industry, regulatory environment, and business needs are often

changing, which poses challenges in the design of ex ante governance mechanisms.

One puzzling empirical observation is that formal contracts continue to be pervasive in

practice – even in relationships where relational mechanisms such as trust and social mechanisms

are likely to have developed. For example, Ryall and Sampson (2006) examine outsourcing

contracts in the telecommunications equipment industry and find that contracts contain more

extensive details (such as development specifications, time frame, personnel deployment,

technology specifications, intellectual property rights), and stronger monitoring and enforcement

terms (such as reviews, evaluations, and audits) when contracting parties have prior bilateral

experience and where trust and relational governance is likely to exist. Similarly, Poppo and

Zenger (2002) find an association between prior relationships and the level of contract detail and

customization, as do Mayer and Argyres (2004) and Argyres et al. (2007).

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We do not attempt to address the question of complementarity or substitutability of

relational and contractual controls. Rather, our interest is in exploring whether two specific forms

of relational controls - future potential and bilateral reputation capital – influence the likelihood of

observing a more flexible formal contract form in the presence of deliberate obfuscation potential.

In developing our hypotheses, we draw on the theoretical framework of Bajari and Tadelis (2001)

and Corts (2012) and incorporate project scope, contract inefficiency, deliberate obfuscation

potential, future potential, and bi-lateral reputation capital.

Contract form and risk in exchange

Consider a client and a vendor who are interested in entering into a contract.1 Consistent

with the tenets of TCE, we assume that the initial contract is incomplete. The payment method is

either CP or FP. Given the nature of a CP contract, project modifications typically do not involve

a renegotiation, while an FP contract requires renegotiation if there is need for modifications.

Many exchange hazards increase the potential for rent; these exchange hazards have been

classified into asset specificity, market uncertainty, and behavioral uncertainty (Poppo, Zhou, and

Li 2016; Schepker et al. 2014). Another form of rent seeking that is observed in practice is that the

incumbent vendor deliberately obfuscates the system through actions such as opaque or poor

documentation, or shirks in transferring know-how and knowledge of the system architecture to a

potential new vendor, increasing the latter’s integration costs. 2 In FP contracts, such deliberate

obfuscation makes it difficult or even impossible for other vendors to undertake modifications and

thus increases the potential gains to the vendor from hold-up.3 Cognizant of this vulnerability,

1 A formal model that analytically derives the hypotheses is available from the authors on request. 2 These actions fall under the umbrella of “influence activities” (Milgrom and Roberts’ 1992). 3 Because system documentation involves specialized skills and know-how, the client would not

be able to audit whether the documentation is complete, especially if the vendor disguises his

actions through proprietary technology.

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deliberate obfuscation reduces the likelihood of a FP contract. While a CP contract mitigates the

rent-seeking opportunities from hold-up, it exposes the client to vulnerability from moral hazard.

These tradeoffs between the inflexibility and concomitant potential for adaptation cost in FP

contracts vis a vis the lack of incentives for efficiency in CP contracts is acknowledged in the

literature (Crocker and Reynolds 1993; Bajari and Tadelis 2001; Susarla, Subramanyam, and

Karhade 2010; Gopal et al. 2003; Gopal and Sivaramakrishnan 2008; Corts 2012) and summarized

in Figure 1. As discussed next, future potential can attenuate moral hazard vulnerabilities and

increase contracting efficiencies from CP contracts in the presence of deliberate obfuscation

potential.

Future potential and contract form

Implicit cooperative contracts, where parties agree to implement cooperative behavior that

helps both parties can be a powerful informal control system that reduces the risk of adverse

outcomes from exchange hazards. Because they are formally uncontractible and legally

unenforceable, implicit cooperative contracts have to be self-enforcing.4 The mechanism by which

implicit cooperation is different in CP and FP contracts. FP contracts that include implicit

cooperation between the parties take the following form (Corts 2012). Parties enter into a legal FP

contract for an exchange relation where both parties have an implicit agreement that the vendor

and client will continue to do business under the contract, the vendor will accommodate the client’s

needs for changes at reasonable costs, and the client will reward the vendor for these costs. CP

contracts that include implicit cooperation are an exchange where the client and the vendor enter

into a legal cost-plus contract and form an implicit agreement that the vendor and client will

4 This is a key feature of implicit contracts – i.e., the vendor’s actions are observable to the two

parties but not contractible, and therefore implicit contracts have to be self-enforcing (Bull 1987;

Klein 1996).

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continue to do business, the vendor will contain costs, and the client will reward the vendor’s cost-

containing effort. If either party reneges, the implicit agreements break down, the parties switch

back to non-cooperative state, and the transaction is governed by spot contracts. Under either

scheme, the element that prevents reneging is the prospect of greater payoff under a cooperative

relation spanning multiple periods relative to the higher costs of spot trading.

Implicit cooperative contracts are facilitated by repeated partnerships. Indeed, theoreticians

as well practitioners emphasize the payoffs from cooperation in in inter-firm relations when firms

continue to do business for long periods of time. A key feature that can strengthen implicit

contracting is repeated interaction (Baker, Gibbons, and Murphy 2002; Chassang 2010). The

promise of future contracting (future potential) that is fostered by repeated interaction facilitates

implicit cooperation on noncontractible variables (Corts 2012). Future potential can reduce

coordination costs and increase the success of implicit contracts. For example, Gil and Marion

(2013) study the relationship between contractors and subcontractors in highway procurement

auctions and provide analytical and empirical evidence that contractors with a potentially higher

number of future interactions with their subcontractors are more likely to win auctions by posting

lower bids. The ability to post lower bids arises from better mitigation of moral hazard problems

between sub-contractors and contractors in the presence of potential for future interactions. That

is, future potential fosters implicit cooperation. Empirical research finds support of a positive

relationship between repeated interactions and profitability (Ferguson, Paulin, and Bergerson

2005; Gulati, Lawrence, and Puranam 2005; Poppo and Zenger 2002). Holloway and Parmigiani

(2016) use a dataset of 580 partnerships for 144 bridge construction projects and find that repeated

partnerships influence revenue performance positively but not profit performance.

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Our interest is in examining whether future potential influences contract form. Implicit

cooperation in the presence of future potential, which can be construed as “contracting in the

shadow of the future” has benefits; however these benefits do not accrue uniformly to contracting

parties. In FP contracts, implicit cooperation confers greater benefits to the client relative to the

vendor, while the reverse is true for CP contracts. In FP contracts, the greatest risk is hold-up,

which benefits the vendor and hurts the client. Thus, the vendor forsakes the hold-up rent and

assumes cost-overrun risks to obtain benefits such as less volatile revenue streams and capacity

utilization benefits of repeated contracting. For an established vendor, these benefits are important,

but absence of them does not threaten their survival. When the potential for holdup occurs in a FP

contract, the vendor has to tradeoff the holdup gain with the loss of a potential future FP contract

with the same client. Not only does a future FP or spot contract leave the risk sharing outcomes

unchanged because the vendor continues to absorb all the risk, but also the future contracts may

not have holdup opportunities. In this case, the vendor is likely to prefer the sure holdup gain from

the current FP contract. That is, in the presence of deliberate obfuscation potential, even future

potential is unlikely to protect the client from vendor opportunism in FP contracts.

As opposed to this, the benefits of implicit cooperation in the presence of future potential

accrue to a greater extent to the vendor than to the client. The cost-plus contract offers more

attractive risk sharing to the vendor. The vendor therefore has to trade off the short-term moral

hazard gains with a reduced likelihood of obtaining desirable future CP contracts. Inefficiency in

a CP contract could lead to the client switching to a FP or spot contract (or ceasing business

altogether with the client). In this case, the vendor would not prefer to jeopardize the gains from

future CP contracts. The self-enforcement benefits of future potential in CP contracts arises from

calculative trust, which operates as (Williamson 1993; 467): ‘a situation in which the affected

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parties (1) are aware of the range of possible outcomes and their associated probabilities, (2) take

cost-effective actions to mitigate hazards and enhance benefits, (3) proceed with the transaction

only if expected net gains can be projected.” Thus, future potential benefits CP contracts to a

greater extent, increasing the likelihood of observing CP contracts as stated below.

Hypothesis 1: Future potential increases the likelihood of CP contracts.

Reputation capital and contract form

The above discussion focuses on the self-enforcement aspect of implicit cooperative

contracts once the implicit agreement is formed. Implicit cooperative contracts assume that the

two parties will start by behaving cooperatively, continue transacting indefinitely, but terminate

when either one reneges. In this section we consider the role of reputation capital on contract form.

Economic theory posits that reputation can be a mechanism for safeguarding the contracting

parties’ interests (Klein and Murphy 1997). Reputation capital evolves between contracting parties

through previous contracting relationships. If the firms have contracted before and have behaved

reliably (i.e., adhered to the terms of the contract, managed cost appropriately such that there are

no overruns, and not held up the other party), then a stock of bilateral reputation capital

accumulates for each party. Suppose vendors have different stocks of reputation capital with

clients. A vendor with high bilateral reputation capital in cost-containment has higher likelihood

of executing the project efficiently and with low costs. Inefficiency on a project depletes the stock

of bilateral reputation capital, which the vendor would like to avoid. Cost inefficiency, the most

significant risk in a CP contract, is lower for a vendor with cost containment reputation capital.

The vendor’s reputation for cost containment does not influence the client’s surplus in a FP

contract because the vendor absorbs all the risks of cost overruns. Conversely, expected returns to

the client from a CP contract are increasing in the vendor’s reputation capital for cost containment.

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This leads to the prediction that a vendor with a past history of good performance in containing

costs is more likely to be awarded a CP contract as stated below.

Hypothesis 2: Vendor’s bilateral reputation capital for cost containment increases the likelihood

of CP contracts.

Note that the discussions center on the role of bilateral reputation rather than the parties’

reputation in the market. We conceptualize the reputation as bilateral because, under many

circumstances, the nuances of a relationship and what transpired within a contract are not

observable by parties outside the relationship. The empirical analysis controls for the market

history of the client and the vendor, which acts as a proxy for reputation capital in the market.

3. Sample Selection and Variable Definition

Data source

Data are drawn from public filings of companies from the U.S. Securities and Exchange

Commission (SEC). The SEC mandates that firms disclose material contracts, defined as a contract

with a “substantial likelihood that a reasonable shareholder would consider it important in making

an investment decision,” as a part of their 10-K, 8Q, or 10Q filings. Material contracts span a large

range of services, including leasing of property and equipment, compensation contracts, profit

sharing, collective bargaining, property encumbrances, loan guarantees, etc. For the following

reasons, we restricted our analysis to material IT contracts. First, firms have been outsourcing IT

services for decades; as a result, IT outsourcing is a mature industry and competitive both on the

demand side and the supply side. Second, with the digitization of virtually every activity

undertaken by firms, IT outsourcing can encompass a range of processes and functions, including

complex business functions. Thus, contracts for IT services could be for well-defined activities

(such as digitization of a set of records) as well as for complex activities (such as systems design

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or business process design). Finally, restricting the analysis to one type of business activity reduces

the noise in the analysis.

Contracts in our sample were written during the period 1998 to 2005. We stop at 2005

because we wanted to make sure that we could examine the post-contractual period and identify if

parties terminated the relationship, or ran into problems that required substantial renegotiation of

the contract. These terminations could signal relationship problems that could ex ante influence

contract form. Thus, contracts in our sample relate to projects that have been completed. We first

identified vendors of outsourced services by examining all registrants that were classified in the

SIC category 73, which denotes that the registrant provides computer related services. We

identified large clients based on datasets of press releases of outsourcing announcements compiled

by a professional advisory firm and a trade journal that lists publicly announced outsourcing deals.

A total of 1,724 vendors and 1,024 clients were identified in this manner. Contracts classified as

material consist of a range of contracts, such as asset purchase agreements, license transfers,

executive compensation, contracts for non-IT related services, etc.; therefore, we limited the

sample to include agreements that represent IT outsourcing. We then screened the sample to

include only those contracts where the identities of the vendor and the client were clearly specified.

Filings where a substantial amount of the contract details were missing were removed from the

sample.

From an overall sample of about 3,800 material contracts, the screening process resulted

in 466 contracts. We then limited the sample to exclude contracts that also involved mergers or

acquisition related agreements because these involve higher level of joint governance than a

regular procurement contract. The final sample contained 149 outsourcing relationships between

a total of 239 clients and vendors with clearly defined service obligations. We supplemented this

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with data from a number of publicly available databases that aggregate news and press releases,

(e.g., Dow Jones Interactive, Factiva database, and industry reports, trade and business press that

reports on outsourcing deals), as well as industry databases (e.g., the One Source Online Business

Information database, the Hoovers database). Whenever possible, we verified this data by

examining press releases from either clients or vendors, as well as press releases posted on the

archived websites of vendors and clients obtained from the Internet archives (www.archive.org).

Typically, a contract between a client and a vendor consists of a formal contract that identifies

responsibilities of both parties and a payment schedule, along with a statement of work (SOW)

that focuses on the technical details of the system. Table 1 provides the details of the data used for

the analysis.

--- Insert Table 1 here ---

Textual analysis procedure

Several of the variables used in the analysis are extracted from textual disclosures in the

contract document and other text sources. We conduct textual analysis to extract relevant phases

and construct variables that can be used in econometric analysis (Li 2010). We use a combination

of established methods of textual data extraction. These include the TextRank algorithm method

(Mihalcea and Tarau 2004) and the co-word analysis algorithm (Leydesdorff 1989). The

TextRank algorithm method is a popular extractive summarization technique, which identifies

sentences related to a construct of interest from an original text document. It can extract keywords

from a body of words (such as a paragraph or a section), or sentences from a document. After

extracting the words or sentences, it uses a graph-based approach in which the sentences/words

are used to form vertices of a graph, and the lexical or semantic similarity between the words is

used to assign weights to the graph using Python language (Balcerzak, Jaworski, and Wierzbick

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2014). The advantage of the TextRank method is that it can recognize the most informative

statements from a corpus and compute a credibility score to text extracted from the corpus. The

TextRank method requires generation of a user-defined combination of words. We use the co-

word analysis to generate the combinations. Co-word analysis identifies combinations of words

using text-mining software (Leydesdorff 1989). Co-word analysis, which is a content analysis

technique, uses patterns of co-occurrence of pairs of words or phrases from a body of text to form

variables that can be used in econometric analysis (He 1999).

To construct the keyword dictionary, we followed the recommendations of prior studies

regarding contractual contingencies (e.g. Anderson and Dekker 2005). We chose a smaller sample

of twenty comprehensive contracts from our sample and analyzed the contract provisions. Based

on the analysis, we developed a coding scheme that could be applied on the entire sample. While

constructing the key word dictionary, we focused on relatively unique terms and eliminated

boilerplate contract language that were common to most contracts and which would not capture

the type of nuances that were required to test hypotheses. Two independent coders, both with IT

consulting experience, coded the contracts; the inter-rater reliability on all variables constructed

using textual analysis, measured by Cohen's kappa coefficient, was above 90%. The contracts

where there were disagreements in coding were settled via a discussion process to reach consensus.

Additional details of the specific words used are provided in the following section.

Dependent variable

Contract Price (CP or FP)

The primary dependent variable is a dummy variable indicating the contract form, i.e., FP or CP.

FP contracts (assigned a value of one) specify a defined payment schedule for services specified

in the contract while CP contracts pay the vendor a markup based on realized costs, including

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compensation to the vendor for costs incurred when the client requires additional services that are

not defined in the original agreement. Contract price and is coded from the SEC data using the

TextRank algorithm method using co-occurrence of phrases such as “contract price”, “term”,

“upon submission of invoices”, “fee for service”, “payment schedule”, “reimbursement for

services”, “payment may include”, “indirect costs”, “other direct costs”, “change order

documentation”, and “time and materials”. Table 2 provides examples of CP and FP contracts.

--- Insert Table 2 here ---

Independent variables

Future Potential

We use the presence of extensibility clauses to measure future potential. Future potential

introduces a mechanism to reward cooperative behavior of transacting parties. Contracts can

include a provision to extend the contract with minimal renegotiation costs at the end of the

contracting horizon and to specify a future horizon of interaction. Such provisions provide an

indication of parties’ expectations of future interaction after the current contract is completed. We

identified the presence of extensibility clauses as follows. Some contracts included a separate

section titled “extension option” or similar words. Examples of phrases used for determining

extensibility clause from the body of the document include “may extend the term of this contract

by written notice”, “the extended contract shall be considered to include”, “extended for

additional”, etc. We crosscheck the future potential variable with press releases from clients and

news reports in the trade and business press suggesting that parties expect to continue their

contractual relationship into the future. Additionally, as explained in the subsequent section, we

control for other aspects of the relationship that may drive future potential.

Endogeneity Correction

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Using extensibility clauses in formal contracts to proxy for future potential carries with it a

potential endogeneity problem. This endogeneity occurs because CP contracts include well-

defined payment methods that make it easier for the transacting parties to extend their relation,

i.e., CP contracts make the extensibility clause less costly, and thus more likely. We address this

potential endogeneity problem by conducting instrumental variable (IV) analyses (Larcker and

Rusticus 2010). IV analysis identifies a set of instrumental variables that are assumed to be

exogenous, i.e., correlated with the endogenous regressor (future potential) but uncorrelated with

the error in the structural equation that predicts contract form (CP or FP). These instruments are

used in the first stage of two-stage-least-squares (2SLS), and the fitted value from the first stage is

used to estimate the coefficients in the second stage regression model. The empirical challenge in

IV analysis is to find exogenous instruments that impacts the continuation value of the relationship

(and therefore the potential for future interaction), but would not impact the choice of contract

form (CP or FP). Below we outline the process used for developing the instruments.

Contracts for IT outsourcing are usually preceded by lengthy negotiations between parties,

whereby parties first identify the vendor and services to be outsourced, and only then decide on

the formal contract type (i.e., FP or CP). We therefore identify two types of vendor selection

practices that might be reasonably expected to influence future potential. We use press releases to

identify details of outsourcing deals along with the details of pre-contract negotiation. We consider

two instruments that reasonably impact the contracting parties’ future potential but not the choice

of contract form.5 These instruments are multisourcing, and extension or expansion of previous

contract. Multisourcing involves contracting a service to multiple vendors who have to collaborate

5 For example, Gil and Marion (2013) rely upon an identification strategy whereby an exogenous

factor that impacts the future value of ongoing relationships serves as an instrument.

21

and synchronize the delivery of the service. If an outsourcing agreement is part of a multi-sourcing

arrangement the continuation value of the relationship depends upon other vendors that are a part

of the agreement. Multisourcing thus influences future potential, but not the contract form, which

is determined by negotiation between the vendor and the client. The second instrument is whether

the present outsourcing arrangement is considered an extension or expansion of a previous

contracting engagement between parties. Extension or expansion contracts by definition influence

future potential, but the terms of the current contract will vary depending on the scope and nature

of the service. These two instruments are exogenous to the current contract, and are gathered from

sources outside the contract. The multisourcing variable is obtained from press releases prior to

the signing of the current contract, and the extension/expansion instrument is obtained from

previous contract documents between the client and the vendor.

To improve the fit and theory-consistency of the first stage estimates, we include several

control variables that could be associated with the likelihood of future potential. Practitioners

suggest that contracts should include provisions for dispute resolution and price adjustments that

enable smooth resolution to contentious issues ex post. In particular, we consider the role of

arbitration clauses whereby parties have an agreed upon framework for resolving disputes,

insurance terms that protect vendors against major schedule slippages that are outside the vendor’s

control, and re-pricing provisions that provide an index for re-pricing of services and make it easier

to extend a contract, without affecting the pricing scheme directly.6 We create indicator variables

for all of these above factors.

6 Mayer and Argyres (2004) observed that disputes over project costs or guidelines for

specification of requirements could seriously disturb not only the project schedule but also erode

the value from the contract.

22

Instead of using the extensibility clause to promise a future horizon, clients may

intentionally break up the whole business into several parts and use the extensibility clause to

continue business only if the vendor’s performance is satisfactory. In examining the presence of

future interaction, we include as controls the presence of exit clauses that facilitate smooth

termination and therefore pose lower risk to the client in offering an extensibility clause. Another

issue is whether parties can take actions that are crucial to the success of the project. The actions

taken by both parties to increase the likelihood of successful outcomes are likely to be correlated

with the use of future interaction clauses. We therefore control for clauses detailing a client’s

participation in setting standards for delivery time and quality as evidence of actions taken by a

client in reaching the desired contractual goals. Finally, we include vendor- and client-specific

controls, such as size and bargaining power, which could influence their willingness to transact in

the future. We use the above instruments and control variables in the first stage regressions as

recommended by the literature (e.g. Larcker and Rusticus 2010) and discussed in Section 4.

Bilateral Reputation Capital for Fair Cost Performance: To obtain data on vendors’ behaviors in

maintaining a lower level of realized costs, we relied on the annual financial reports and investor

statements released by clients and vendors. Vendors regularly highlight such favorable

performance in their press releases. We corroborate this information using the investor briefings

and annual reports disclosed as part of 10-K filings where clients release assessments of vendors’

performance. In constructing this measure, we need to distinguish fair cost performance by a

vendor from the expected performance that is endogenously related to the decision to contract.

Therefore, we examined the start date and duration of the prior contract between parties. A press

release or financial statement released before or at the beginning stages of a contract is likely to

23

mention expected performance, while press releases or statements that are near the end of a

contract or post contract execution refer to realized costs.

Control variables

Potential for Deliberate Obfuscation and Task Complexity

We consider four different task dimensions that denote the potential for deliberate obfuscation.

These include: (a) use of the vendor's proprietary platform (e.g., Kalnins and Mayer 2004), (b) use

of vendor's proprietary technology (Mayer and Nickerson, 2005), (c) technology standards that are

owned by the vendor and need to be licensed to the client for use in the contracted task, and (d)

level of process maturity. We use the TextRank algorithm method to extract keywords from the

part of the contract document that details the purpose of the contract. We use co-word analysis to

code measures of proprietary platforms or technologies to denote how well the client understands

the technology, process, and systems architecture used by the vendor. These variables are

constructed from the task description and the contract scope. For instance, the co-occurrence of

the words “proprietary” and “technology” as well as co-occurrence of “prior systems” and

“ownership” could indicate that the contracted task depends upon a client’s pre-existing

technological infrastructure. Similarly, the co-occurrence of the words “proprietary” and

“architecture” could indicate that the contracted task depends upon a client’s pre-existing

technological architecture/platform. We similarly construct a measure of standards licensing by

the client. Finally, we measure the process maturity of the contract by conducting a keyword

analysis of the purpose of the contract. When outsourcing business processes that are well

understood by the client, including maintenance/automation of existing processes, the client has

detailed knowledge of how to audit the operational and administrative details of business

functions. Table 2 provides a description of variables with illustrations from the contracts.

24

A complication is that vendor potential for rent seeking through deliberate obfuscation

could be empirically related to task complexity. For example, suppose that a vendor builds an IT

system using her proprietary technologies and platforms. Whereas the client could benefit from

the dedicated technological expertise of a vendor, the client could also be subject to hold up by the

vendor during modifications. Furthermore, if the client has to change partners before the

completion of the project, a new vendor would incur substantial costs, which could include having

to build the system all over and neutralize all existing progress. A complex task may be more likely

to use technologies that are less portable, thereby increasing the chance of the vendor holding up

the client. Therefore, not only is task complexity an important control variable, but additionally, it

is important to distinguish it from potential for deliberate obfuscation.

We coded five measures to assess the complexity of the contracted task. First, we examined

the business objectives of the underlying task. Industry parlance refers to contracts as

“transformational”7 when the business objective is significant reengineering of processes and job

functions in the client organization, where the ambiguity in specifying contract outcomes increases

contract incompleteness (e.g., Linder 2004). We constructed a dictionary of keywords denoting

when a task could be transformational, and used text mining to code the contract as

transformational when the language used to describe contract objectives match the keywords such

as “strategic” or “reengineering”. Second, we conducted similar textual analysis to obtain a

measure for systems development by searching for keywords in the task description that denote

that a significantly new system is being developed as part of the contract. Since new systems

7 For instance, one of the contracts specifies that the vendor, EDS, “conduct a comprehensive

assessment of the client’s information technology systems in light of the business priorities and

competitive market conditions and growth requirements” before creating a technology plan and

implement the proposed solutions over a period of time.

25

development involves considerable complexity in terms of reorganizing business functions and

organizational transformation (making it difficult to envisage benchmarks and performance

standards), we looked for keywords and key phrases such as “systems requirements”, “analyze

systems requirement,” “implementation,” etc. Third, we coded a measure of nascent technological

standards used in the contract (i.e., technologies that date to post-2000s and after the advent of the

World Wide Web). Projects that rely on newer technologies and process architectures are more

complex than ones that rely on familiar and established technologies. Fourth, extant literature

considers the scope of products and services covered within a transaction as a driver of task

complexity because different elements of the task may interact in unpredictable ways (Anderson

and Dekker 2005). To capture this dimension of task complexity, we classify services delivered

along a typology of 14 different types of sub-services that constitutes IT outsourcing (e.g., Lee,

Miranda, and Kim 2004). Service breadth is the summation of the number of sub-services

delivered by the vendor. Contracts with a greater service breath pose greater challenges in planning

deliverables and executing milestones and therefore increase task complexity. Finally, the number

of pages of the contract provides an indication of the underlying complexity.

We conducted principal component analysis to determine whether task complexity and

potential for deliberate obfuscation are theoretically distinct, and to obtain composite, weighted

measures. We extracted two principal components from this analysis. The first principal

component explained 45 percent of the variation in our five variables, and the two principal

components cumulatively explained 77 percent of the variation. The first principal component

captures the impact of complexity of the services and includes the following: transformational,

new systems development, nascent technology, and service breadth. We label this component as

26

task complexity. The second principal component, which we label potential for deliberate

obfuscation, includes proprietary platform, proprietary technology, and process maturity.

Contractual Contingencies and Monitoring Terms

We included a number of contractual controls gleaned from the literature (e.g. Chen and Bharadwaj

2009). These include, contract value and contract length (number of pages). We coded whether the

contract contains: (i) contract clauses facilitating monitoring, such as audit rights and inspections,

(ii) performance milestones tied to specific outcomes (e.g., Lichtenstein 2004), and (iii) service

level agreements that guarantee a level of services to be provided by the vendor. We control for

these variables because monitoring by the client could impact vendor rent seeking (Anderson and

Dekker 2005) and thereby, contract form. Contracts can stipulate channels of communication that

help inter-firm interactions and lessen some of the difficulties in contracting, and therefore affect

the form of the contract.8 The purpose of creating such roles and responsibilities is to designate a

single point of contact that is authorized to act as the primary contact for each company. Contracts

also stipulate the frequency of meetings between key personnel.9 Therefore, we coded two

measures denoting whether contracts (a) include processes for inter-firm communication, and (b)

designate clear roles and responsibilities enabling joint management of outsourced tasks.

Contemporaneous Relationships

Public databases provide a rich source of data to examine whether contracting parties have other

ongoing relationships, such as marketing alliances, business partnerships, and strategic

8 For example, a contract between Coors and EDS states that each will designate an individual as

its project executive, stipulating that such individuals have day-to-day authority of handling project

and contract management. 9 An example is a clause that states: “meetings will be held to discuss daily performance and

planned or anticipated activities and changes that might adversely affect performance.”

27

relationships, in tandem with the current contract. We use an indicator variable for

contemporaneous relationships between clients and vendors.

Prior Relationship

Prior relationship with the same party can influence future potential. We collect information about

interaction history from prior SEC contract filings. For parties with a history of interactions, a

detailed examination of public data sources, financial statements, and documents filed with the

SEC provide evidence of fair bargaining and vendor cost performance.

Prior Contract Termination

When contracts are terminated early, clients (and usually vendors) disclose such terminations in

their press filings and investor briefings. We used this to include an indicator variable regarding

contract cancellations in a prior relationship.

Firm Size, Bargaining Power, and Risk

We include controls for client size and vendor size, which were obtained from the Hoovers

database. Risk-sharing theories posit that contracts with a larger vendor are more likely to be FP

because the vendor has higher ability bear risk. Vendor size could also signal perceived

trustworthiness and competence, which affects contract form. We measured vendor and client size

using the log of number of employees, and whether they are Fortune 1000 companies. Client

market power was assessed using the SEC filings data on whether the client accounts for more

than 10 percent of a vendor’s revenue.10 We measured whether the vendor is a publicly traded

company because access to capital markets might impact risk preferences and, therefore, contract

form. To control for bargaining power, we use a measure of industry accreditation of the vendor,

coded from firms such as Gartner and Forrester that publish quarterly rankings of the vendor.

10 SEC mandates that firms disclose this information.

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Fair Bargaining Capital: Higher reputation capital in accommodating changes in a fair manner

increases the likelihood of FP contracts. The reason is that if a vendor with higher reputation

capital holds up the client by refusing to accommodate changes in an FP contract, it will destroy

the vendor’s reputation capital with the client and the future surplus from repeated interactions.

We use an indicator variable for fair bargaining reputation capital based on previous amicable

agreements. First, we collect data on instances when parties amicably resolved a contract dispute

or overrun without a formal amendment. Because overruns are fairly frequent in large projects,

we examine the annual filings of the vendor company and note any references to contractual

overruns. Trade and industry reports provide details on the progress of complex outsourcing

deals. We used these reports as an additional method of gathering data on amicable amendments

in a prior agreement. For instance, a trade journal could report that parties amicably resolved ex

post changes without a formal amendment. Second, when a publicly filed contract is

renegotiated, parties are required to file the amendments with the SEC. We therefore examine

amendments in a previous contract as a proxy for amicable bargaining between parties. We

create an indicator variable that takes the value of 1 if there are amicable amendment agreements

filed for an earlier contract between parties.

Market History of Vendor and Client

Data from public databases and the trade and industry press provide details about the other

contracts signed by clients. A measure of interactions between a particular client and its alternate

vendors provides a proxy for the ease of switching a particular vendor. To obtain the market history

of each vendor, we examined whether vendors had signed contracts with clients in the same

industry in a five-year horizon preceding and succeeding the date of contract signing. The market

experience of a vendor in the client’s industry provides an indication of generalized reputation

29

capital of the vendor. We also considered mergers or acquisition (M&A) activity in the vendor

company, because such activities could disturb relationship continuity and thereby diminish the

value of future interactions. We obtained M&A data from the Hoovers and Compustat databases.

Table 2 summarizes the variable design and definitions.

4. Econometric Approach and Results

Descriptive statistics

Table 3 provides the descriptive statistics of contract terms. The sample exhibits

considerable variation in the types of vendors and clients, as well as the type of services. About 61

percent of the contracts are FP and the balance are CP. The value of an average contract is $49

million and lasts 47 months. An average client (vendor) in the sample has 13,444 (12,860)

employees. Prior relationships occur in 49 percent of contracts. In 21 percent of the contracts, the

client and vendor had a successful amendment to their previous contracts. In 20 percent of the

contracts, the client is satisfied with the vendor’s performance in reducing costs in their previous

contract. In about 10 percent of the contracts, the client and the vendor cancelled their previous

contract. In about 53 percent of the contracts, the parties expect to transact with each other in the

future.

--- Insert Table 3 here ---

Table 4 presents simple t-tests of contract form as a function of future potential and bilateral

reputation. The simple t-tests are consistent with H1 and H2: future potential, and vendor

reputation for fair cost performance increase the likelihood of CP contracts.

--- Insert Table 4 here ---

Dynamic Analysis

30

The empirical model is a recursive, simultaneous-equation bivariate probit, estimated as

follows:

𝑃𝑟(𝑦𝑖𝑗) = 𝛽𝑋𝑋𝑖𝑗 + 𝛽𝑉𝑉𝑗 + 𝛽𝐶𝐶𝑖 + 𝛽𝐹𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗 + 𝛽𝜔𝜔𝑖𝑗 + 𝜀𝑖𝑗,

and

Pr (𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗) = 𝛾𝑍𝑍𝑖𝑗 + 𝛾𝑉𝑉𝑗 + 𝛾𝐶𝐶𝑖 + 𝛾𝜔𝜔𝑖𝑗 + 𝜖𝐹,𝑖𝑗 ,

where Pr represents probit analysis, y represents FP contract, i represents the client, j represents

the vendor, 𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗 is an indicator variable for the use of extensibility clauses, 𝑍𝑖𝑗 are

the instrumental variables for the Future Potential variable, 𝑉𝑗 include the vendor-specific

variables, 𝐶𝑖 include the client-specific variables, 𝑋𝑖𝑗 are contract specific variables, and 𝜔𝑖𝑗 are

the control variables that influence both contract form and future potential.

As stated earlier, we use instrumental variable analysis to mitigate bias arising from the

simultaneity between y and Future Potential. In the first stage, we estimate Future Potential using

Multisourcing, and Extension of earlier agreement as instrumental variables (𝑍𝑖𝑗). The vendor-

specific variables (𝑉𝑗) include: Vendor is a Fortune 1000 firm, Vendor is a publicly traded firm,

Vendor size, and Vendor industry accreditation. The client-specific variables (𝐶𝑖) include: Client

is a Fortune 1000 firm, Client size, and Client market power. Contract specific control variables

(𝜔𝑖𝑗) include Arbitration provisions, Insurance terms, Re-pricing provisions, Exit clauses, Client

participation in delivery time standards, and Client participation in quality standards.

The recursive, simultaneous-equation bivariate probit estimation (Greene 2003) considers

whether the future potential is endogenous to the structure of the formal contract. This specification

allows us to simultaneously examine the likelihood that contracts contain clauses to extend as well

as factors that impact contract form. A likelihood ratio test of the correlation of the residuals in a

recursive-simultaneous bivariate probit specification with that of a bivariate probit model that

31

ignores the association between these two choices is significant. Thus, we rule out the null

hypotheses that contract form and future potential are independent. In other words, we find

evidence that future potential is not exogenous to the structure of the formal contract. Instrumental

variables for future potential are thus needed.

First stage results

Table 5 shows the results from the first-stage regression. The pseudo R2 of the first stage

model is 0.2714. Both the instrumental variables are significant drivers of future potential

(measured via the use of extensibility clauses). Exit clauses, vendor size, and vendor accreditation

matter for future potential.

--- Insert Table 5 here ---

Second stage results

The full model is presented in Table 6. Model 1 does not include the market history

variables, model 2 includes the market history of the client, and model 3 includes the market

history of both client and vendor. The pseudo R2, computed as the ratio in difference between the

constant-only model and the full model (including instruments) is 0.2163.

Hypothesis 1 posits that future potential increases the likelihood of CP contracts compared

to FP contracts. In Table 6, the coefficient for future potential is negative, which indicates lower

likelihood of FP contracts, and correspondingly, higher likelihood of CP contracts. These results

support hypothesis 1. When future business is at stake, a vendor knows that poor performance in

controlling costs in a current CP contract reduces its chances of obtaining future business from the

client. Thus, future potential serves as a control mechanism and attenuates the vendor’s tendency

for cost inefficiency, which is one of the primary problems in a CP contract. In FP contracts,

however, the vendor has to tradeoff the losses from uncompensated modification costs of the

32

current contract with uncertain gains from future contracts. Thus, future potential is less useful as

a control mechanism in an FP contract relative to a CP contract. Hypothesis 2 states that vendor’s

bilateral reputation capital for cost containment increases the likelihood of CP contracts. The

coefficient on the vendor’s reputation in fair cost performance is negative, indicating support for

hypothesis 2 and suggests that when there is a history of favorable cost performance by the vendor,

contracting parties are substantially more likely to use CP contracts compared to transactions

where parties do not have such a relationship history.11

Note that in testing hypothesis 2, we distinguish between specific measures of inter-firm

reputation capital accrued through prior interactions and the more general measure of prior history

of interactions. Since the indicator variable of prior relationship is included in the regression, the

coefficient on fair bargaining performance captures the effect of the reputation capital on

bargaining performance in the form of contracts among transacting relationships that have already

transacted before.

The results also indicate that potential for deliberate obfuscation increases the likelihood

of CP contracts relative to FP contracts as evidenced by the negative coefficient in all the models

in Table 6. Recall that the potential for deliberate obfuscation captures the impact of factors that

enable a vendor to extract greater rents from the client such as the use of proprietary platforms and

technology, and process maturity. Likelihood of hold up increases contracting costs if the FP

contract has to be renegotiated; therefore, FP contracts become less attractive relative to CP

contracts. Among control variables, contract value, contract length, and prior contract termination

are associated with CP contracts, while contemporaneous relationship, prior relationship, and

11Williamson 1979 (104) posits that a “specialized language develops as experience accumulates,”

enabling better communication and realize gains from exchange.

33

market history are associated with FP contracts. The coefficient on fair bargaining is positive in

Table 6, suggesting that for vendors that have high reputation capital in fair bargaining, FP

contracts are more likely to be used. The estimated coefficient on the fair bargaining coefficient

suggests that, on average, for two projects that are of equal complexity, experience of successful

amendments in a past transaction increases the likelihood of FP contracts by about 42 percent

relative to a transaction where both parties do not have a prior history of successful amendments.

Results in Table 6 also indicate that the principal component measuring task complexity is

negatively associated with FP contracts, and consequently, positively associated with CP contracts

in all the specifications. These results confirm the predictions from extant analytical as well as

empirical literature (Bajari and Tadelis 2001; Crocker and Reynolds 1993; Levin and Tadelis

2010). In the presence of task complexity, FP contracts are plagued by ex post transaction costs

because the vendor can take advantage of the need for renegotiation and increase its rent by

engaging in wasteful actions during renegotiation.

--- Insert Table 6 here ---

Robustness analysis

Estimation issues: We conducted two sets of estimations using two-stage least squares estimation

(2SLS) and Generalized Method of Moments (GMM) estimation to examine the validity of the

instruments. Using the 2SLS and GMM results, we conducted exogeneity tests to determine

whether the endogenous regressors in our first stage estimation are in fact exogenous (Hansen

1982). The Durbin Chi-square and the Wu-Hausman F test-statistic were not significant for the

2SLS estimation. For the GMM estimation, the C statistic was not significant. The lack of

significance of these tests indicates that the instruments satisfy the exogeneity condition. Second,

since our IV estimation is overidentified (and therefore we do not have a weak instrument

34

problem),12 we conducted tests for overidentifying restrictions. The Sargan’s Chi-square statistic

for the 2SLS estimation and the Hansen’s (1982) Chi-square statistic for the GMM estimation

were not significant, indicating that the instruments are valid (Sargan 1958).13

Feasibility of Other Contract Types: Other than FP and CP, we did not observe any other types of

hybrid contacts wherein the payment terms within the same contract were different for different

components of the same task. This is consistent with prior research that examines IT contracting

(e.g. Banerjee and Duflo 2000; Gopal and Sivaramakrishnan 2008; Gopal and Koka 2012). In fact

Banerjee and Duflo (2000) find that when mixed contracts are needed, clients and vendors exhibit

a preference to divide the contract into two phases, each of which is governed by a separate CP or

FP contract.

Discussion and Conclusions

An extensive literature examines the contracting hazards that plague inter-firm contracts

and offers design choices to limit the losses from these hazards. Prior literature has addressed this

question using two broad theoretical frameworks. The first set, originating from the seminal work

of Williamson (1975), uses TCE and stresses the important role of contract-based governance in

safeguarding the interests of the contracting parties against opportunism. This stream of research

acknowledges the role of trust and reputation, but posits that formal contract-based governance is

necessary because reputational capital is difficult to build, which limits the self-enforcing range of

contracts (Klein 1996). The other body of literature points out the limitations of contract-based

governance and stresses the importance of trust-based governance, which relies on contracting

12 Larcker and Rusticus (2010) provide an overview of the weak instrument problem in the

context of accounting literature. 13 We include factors related to pre-contract negotiation as instruments in the first stage, which

could also account for potential selection issues between contract form and some important

control variables such as task complexity and monitoring.

35

parties’ expectations that the other will not act opportunistically and adhere to a mutual expectation

of cooperative behavior (e.g. Gulati 1995). Another stream of literature includes trust within the

umbrella of relational governance and argues that trust is engendered by “information available to

the trustor from within the relationship itself,” (Caglio and Ditillo 2012, 122). Research has

attempted to address the association between these governance forms and examined whether

contract-based and trust-based governance are complements or substitutes (Cao and Lumineau

2015; Faems et al. 2008; Krishnan, Geyskens, Steenkamp 2016; Poppo and Zenger 2002; Puranam

and Vanneste 2009), compatible or incompatible (Malhotra and Murnighan 2002), mutually

reinforcing or opposing (Gulati and Nickerson 2008), control tools versus coordination tools

(Malhotra and Lumineau 2011).

Despite the rich literature in inter-firm contracting, Chen and Bharadwaj note (2009; 484)

“There has been much less emphasis on examining contract structures with a view to

understanding the specific provisions that are emphasized in ITO and the transaction

characteristics that affect the choice of contract structures.” We address this lacunae by using text

and data from actual contracts to examine an important design element of the contract – that is

whether the contract is fixed price or cost plus. Our focus is to examine how relational governance

engenders bilateral reputation within a relationship in the presence of complex contracting hazards.

Our contribution to the literature is fourfold. First, we examine an important contracting hazard

that has been hitherto unexplored, namely the potential for deliberate obfuscation. While this

hazard primarily increases vendor rents in FP contracts, it is not amenable to a simple solution of

CP contracts because they expose the client to the attendant cost of moral hazard. Second, we

highlight the important contracting role of future potential as a relational governance mechanism,

which has received relatively limited empirical scrutiny. Third, we provide a richer set of

36

conceptualization of bilateral reputation capital that is amenable to empirical testing using archival

data. Finally, we offer a finer calibration of the impact of future potential and bilateral reputation

as well as task complexity and rent seeking on contract form.

We conceptualize a range of novel theoretical constructs to identify not only the sources of

relational capital but also on how such relational capital constrains opportunism and expands the

welfare from inter-firm relationships. While we conceptualize future potential and bilateral

reputation capital as relational controls, note that the mechanism through which these two

governance mechanisms operate is different in this study compared to some of the previous

literature. Relational governance, especially trust, is generally conceptualized as a “bilateral

expectation that partners will not exploit each other’s vulnerabilities” (Krishnan et al. 2016). In

our setting, the benefits of a future horizon in cooperative CP contracts derive from their attractive

risk sharing properties for the vendor and lower moral hazard to the client. These payoffs facilitate

the self-enforcing property of these contracts. Empirical evidence that future payoffs are the reason

that the vendor is less likely to exploit the client’s vulnerability is provided by the results - past

interactions seems to matter less when including future interactions. We also find that the

coefficient of future potential is lower once we introduce market experience of parties. Both these

results have implications for the self-enforcement of relational contracts and the value from future

interaction. While we find that relational interaction is important, we also find that a breadth of

interaction with many vendors is good for clients, which in fact would lower their incentive to

form self-enforcing relationships with a particular seller.

Our work posits a role for bilateral reputation developed in the course of an inter-firm

relationship in enabling contracts to be self-enforcing. Weber and Mayer (2011) draw upon

expectancy violation theory with (TCE) to examine how contracts are framed. Our work offers a

37

parallel manner in which we can explore the micro-foundations of how bilateral reputation serves

an instrumental role in expanding the range of contracting opportunities, enhancing inter-firm

welfare. When implicit contracts are fostered through the promise of relationship continuity, it is

not necessary for clients and vendors to incur costs in delineating contingencies in contracts.

Rather, contracts could be initiated with an incomplete specification ex ante, where parties would

leave open the possibility of renegotiating future trading opportunities as contingencies unfold.

However, firms with greater experience in outsourcing could be more sophisticated in drafting

contract amendments when modifications are required. The difficulty of writing exhaustive

contracts facilitating formal enforcement may then be mitigated by parties’ ability to cooperatively

engage in dispute resolution. In contracting with a future horizon, the concern not only for future

revenues, but also a desire by contracting parties to continue the existing risk allocation, results in

lower likelihood of opportunism and greater likelihood of reaching smooth adaptation when

modifications are required.

We interpret the benefit of future horizon and bilateral reputation in cooperative CP

contracts as arising from “calculative trust”. Recent work by Poppo et al. (2016) calibrate two

distinct types of trust. Calculative trust arises from an assessment of benefits and costs of self-

interested opportunistic actions versus cooperative actions, whereas relational trust aligns core

values of the contracting partners derived from social relationships. Williamson (1993; 471) argues

that calculative trust is essentially determinative. Poppo et al. (2016; 725) note that “Calculative

trust informs expectations by deliberately and rationally assessing forward-looking conditions: It

requires calculations of benefits and costs, and hinges on the relative values of cheating (e.g., net

costs of termination) and cooperation.” As opposed to this relational trust refers a state in which

Poppo et al. (2016; 726) “each partner can expect to act according to the other’s preferences and

38

priorities….develop a mutual understanding and shared identity.” Future work can analyze how

trust is developed and the trajectory it follows when there is an opportunity for future interaction.

In addition to contract form, another important design variable is duration. Relational

controls such as future potential and bilateral reputation capital could influence the likelihood of

observing longer duration contracts. We do not examine the effect of relational controls on contract

duration because contract form and duration are two alternate design mechanisms that firms use

to address ex ante and ex post information problems. Guriev and Kvasov 2005 (1370) note that

contract duration is “not only a dimension along which the relationship unfolds, but also a

continuous verifiable variable that can be included in contracts.” Future work could incorporate

the fact that parties contract on time before the contract begins, as well as invest in continuous

time during the contract.

39

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44

Figure 1 Comparison of Tradeoffs in Cost-Plus and Fixed-price Contracts

Cost-Plus (CP) Fixed-Price (FP)

Nature of contract The client reimburses the vendor

for cost incurred

The client offers the vendor a

pre-specified price

Impact of ex post cost

variation

Client is the residual claimant of

gains or losses from cost

variations

Vendor is the residual claimant

of gains or losses from cost

variations

Vendor’s incentive to reduce

cost

Low because client is the residual

claimant to all efficiency gains

High because vendor is the

residual claimant to all

efficiency gains

Likelihood of ex post

renegotiations

Low because contract is flexible

and adaptable to change.

High because changes entail

change-orders and re-

contracting.

Contract benefit Low ex-post adaptation cost Low moral hazard (cost

efficiency)

Contract risk High moral hazard because

vendor has no inventive to be

efficient.

High ex-post adaptation cost in

the event of future

contingencies

Potential for deliberate

obfuscation

Does not affect cost inefficiency Increases hold-up rent

Attractiveness of future

relationship to the vendor

High because of favorability of

risk sharing to the vendor

Low because risk is absorbed

by the vendor

Bilateral reputation for cost-

efficiency

Reduces risk of moral hazard No effect (contract has low risk

of moral hazard)

Notes to Figure 1: This figure provides a comparison of cost-plus and fixed price contracts from the

perspective of the incentives of each party, adaptation cost, efficiency gains and losses, and risks accrued.

45

Figure 2 Timeline of Variables Used in the Analysis

Period Prior to Contract

(All variables from prior

period contracts)

Period Prior to Contract

(All variables from other

sources)

Contract Period

Variables from

Contract

Variables from other

Sources

- Bilateral reputation

capital for fair

bargaining

- Bilateral reputation

capital for fair cost

performance

- Prior relationship

- Prior contract

termination

- Clients’ similar

contracts with vendors

in same industry

- Vendors’ similar

contracts with clients

in same industry

- Contract form

(FP/CP)

- Vendor rent-

seeking potential

- Future potential

- Task

Complexity

- Future potential

(cross check)

- Client size

- Vendor size

- Vendor industry

accreditation

- M&A activity of

vendor

Variables from pre-

contract negotiation

- Multisourcing

- Extension of previous

agreement

Notes to Figure 2: This figure provides the timeline of variables used in the analyses. The instruments

used for the two-stage analysis are Multisourcing, and Extension of previous agreement, are obtained

from business press and previous contracts between the vendor and client.

46

Table 1 Sample

Panel A: Sample Construction

Sample construction from SEC filings Observations

Total number of registrants 1,724

Total number of clients 1,024

Total number of material contracts filed with the SEC from the above list of

registrants (clients and vendors)

3,800

Sample after removing all non-IT outsourcing contracts such as asset purchase

agreements, compensation, non-IT outsourcing, wage agreements, etc.

466

Sample after removing other types of arrangements that do not constitute

outsourcing

173

Sample after removing contracts without detailed information about vendors

and clients

169

Sample after removing contracts without financials related data and company

Information (Data from Hoovers and One Source Business Databases)

161

Final sample after removing contracts without a detailed history of

interaction (Contracts cross-validated against data from Public Databases that

aggregate news and press releases such as Factiva, ABI Informs Trade and

Industry)

149

Panel B: Breadth of Services Performed in the Contract

Type of Service Percentage of Contracts

Systems planning 28.5

Application analysis and design 21.9

Application development 28.8

Systems integration 13.2

Operations and maintenance 37.2

Data center operations 19.3

Telecommunications Management 11.2

Software and data licensing 47.5

Hardware products 24.2

IT facilities management 18.8

Basic support 60.5

Training and documentation 32.3

Advanced support 52.7

E-marketing and e-advertising 20.6

47

Table 2 Variable Definitions and Excerpts from Contract Clauses, Press Releases and Financial Statements

Variable Data source Measure development Text Examples

Contract form

Fixed price contract Contract document Fixed-Price (FP) is coded as 1. Client shall pay Vendor the agreed upon charge per month as set forth in

Schedule C.

Cost-plus (CP) is coded as 0. PROVIDING PARTY shall invoice RECEIVING PARTY on a monthly

basis for the Corporate Service Fees, plus the Transition Assistance Fees,

as calculated in accordance with Section 3.1 and Schedule 1.1(a).

Future potential

Expectation of future

potential

Contract documents

and press releases

Coded as 1 if the contract indicates that

the relationship might continue into the

future (and cross checked with press

releases and reports indicating parties’

expectation to continue contractual

relationship).

...The term of this Agreement will be extended for additional …. periods

unless Client or Vendor gives notice to the other at least ….months prior

to the then-current Termination Date of its intention to allow this

Agreement to expire at the end of the Initial Term or then-current Renewal

Term.

Bilateral reputation capital

Fair bargaining EDGAR, press

releases

Coded as 1 when parties to a contract

have had amicable amendments in a

prior contracting relationship that led to

(i) enhancements in service scope, and

(ii) incorporating service modifications.

The Services and the matters addressed in the (earlier) Agreement

including the Transaction Documents and the Supplement and Schedules

are superseded and merged into the (current) Agreement including the

Transaction Documents and the Supplement and Schedules thereto.

Schedule A, Section 1 will be replaced by (Additional service

specification and vendor deliverables added)..Acceptance of deliverable at

milestone 1 (estimated date)…Acceptance of deliverable at milestone 2

(estimated date)….

Additional services described in the amendments

PIN Based Transactions at $*** (Increase of $*** from original

agreement).

Off Line Debit Transactions at $*** (Increase of $*** from original

agreement).

Fair cost performance 10-K statements

cross-checked with

press releases

Coded as 1 when the client indicates

satisfaction with the vendor’s cost

performance in a prior contract.

(Vendor) provided (Client) significant cost savings and operational

flexibility by consolidating, automating and managing a large portion of

its mainframe operating systems and hardware operations…

Instruments for First Stage

Multisourcing Press Releases Coded as 1 if client or vendor denotes

that they were a part of a multisourcing

48

agreement between the client and other

vendors.

Extension/Expansion

of previous contract

Previous Contracts,

cross checked with

current contract.

Coded as 1 when contract indicates that

the contract will be expanded or

extended into a future horizon.

Contractual variables, contingencies, and monitoring terms

Contract value Contract

Documents and

Press Releases

Log transformed monetary value of the contract.

Audit rights Contract document Coded as 1 when clauses denote Audit rights whereby clients have the right to inspect and validate service delivery

by the vendor.

Performance

milestones

Contract document Coded as 1 when the contract contains

clauses relating to performance

milestones tied to specific outcomes.

Customer will demarcate particular milestones in a statement of work

(SOW) as dependent upon completion of tasks and/or performance by the

Vendor.

Service-level

agreements

Contract document Coded as 1 when the contract contains

clauses detailing acceptable service

levels by the vendor.

Exhibit B establishes Service Levels for certain specified Services and

groupings of Services to be provided by Vendor from the applicable

Effective Date throughout the remainder of the Term.

Communication Contract document Coded as 1 if clauses specified the

frequency of interactions between the

client and supplier

Frequent status and review meetings and channels of communication such

as designating key personnel to oversee responsibilities.

Joint management Contract document Coded as 1 if clauses specified joint

management and problem resolution.

Client will specify and designate authorized personnel on or before the

date of the implementation for reporting problems and the vendor shall

make reasonable efforts to resolve the problem.

Relationship history

Contemporaneous

relationship

Contract document

and press releases

Coded as 1 if the parties have an ongoing relationships, such as marketing alliances, business partnerships, and

strategic relationships

Prior relationship Contract documents

and press releases

Coded as 1 when parties to a contract have a prior contracting relationship.

Prior contract

termination

Press releases,

litigation filings,

10-K

Coded as 1 when a prior contract was

terminated prior to the term.

To enable this function (application development) to be more responsive

to the business, (the project) has been transferred back to Client to support

high-level design activities.

Market history of client

Contracts with

vendors in the Past

(future)

Press releases Coded as 1 if the client had signed similar contracts with other vendors in the same industry in a five-year horizon

preceding (succeeding) the date of contract.

Market history of vendor

Past (future) contracts

in client industry,

Hoovers and

Compustat

Coded as 1 if the vendor had signed similar contracts with other clients in the same industry in a five-year horizon

preceding (succeeding) the date of contract

49

mergers and

acquisitions

Coded as 1 if the vendor had merger and acquisition activity.

Task complexity Transformational Contract document

Coded as 1 when the contract objectives

are strategic or transformational.

Vendor will deliver innovative and emerging ideas and strategies for more

effective use of IT and related business transformation, with an objective

that these innovative ideas and strategies can more effectively impact the

enterprise transformation of the Client’s business.

New systems

development

Contract document

Coded as 1 when the contract involves

new systems development.

Analyze and review systems requirements ………implementing the

standardized, strategic architecture ………obtaining an end state that

results in a best-in-class solution…..

Nascent technology Contract document

Coded as 1 when technological

standards are nascent or emergent.

Vendor will provide Client with newly improved or enhanced

commercially available information technology that could reasonably be

expected to have a positive impact in terms of increased efficiency,

increased quality, or reduced costs for the Client.

Service breadth Contract document Number of different IT tasks to be performed within a contract.

Contractual detail Contract document Number of pages in the contract

Potential for deliberate obfuscation

Proprietary platform Contract document Coded as 1 when the vendor employs proprietary platforms

Proprietary technology Contract document Coded as 1 when the vendor employs proprietary technologies

Standards licensing Contract document Coded as 1 when the vendor employs standards that are owned by the vendor and need to be licensed to the client.

Process maturity Contract document Coded as 1 when the technology and the

platforms are relatively stable and

known to the client

Coded from the service description, the deliverables provided by the

vendor and the responsibilities of the client.

Controls

Firm size, vendor size Hoovers and One

Source, Fortune

magazine

Client’s number of employees (log transformed).

Vendor’s number of employees (log transformed).

Client listed in Fortune 1000 list.

Vendor listed in Fortune 1000 list.

Client market power (measures whether the client accounts for more than 10% of revenue for a vendor in the year the

contract was signed).

Vendor is a publicly traded company (denotes that vendor has access to capital markets).

Vendor industry

accreditation

Trade and business

press, 10K, press

releases.

Measures whether vendor has industry accreditation such as ISO, CMM type of standards or ranked as a capable

vendor by trade and industry press (e.g., Gartner’s Magic Quadrant, Information Week rankings, DataMonitor

Group’s Black Book of Outsourcing etc.).

Notes to Table 2: This table contains details of the variables and their data sources. Variables from the contract documents are for a sample of 149

material contracts filed with the SEC during the period 1998-2005. Additional data sources include the Dow Jones Interactive, Factiva, and industry

reports, trade and business press, and industry databases such as the One Source Online Business Information database and the Hoovers database. We

verified this data by examining press releases from either clients or vendors as well as press releases posted on the archived websites of vendors and

clients obtained from the Internet archives (www.archive.org).

50

Table 3 Descriptive Statistics

Variable Mean Std. Dev. Min Max

Contract form (coded as 1 if fixed price) 0.61 0.49 0 1

Future potential 0.53 0.47 0 1

Fair bargaining 0.21 0.40 0 1

Fair cost performance 0.20 0.32 0 1

Contract value ($ million) 49.12 18.50 0.5 180

Contract length (number of pages) 32 34.85 4 194

Contract duration (in months) 46.64 1.60 3 120

Contemporaneous relationship 0.20 0.39 0 1

Prior relationship 0.49 0.50 0 1

Prior contract termination 0.10 0.29 0 1

Similar contracts of client in past 0.22 0.41 0 1

Similar contracts of client in future 0.31 0.46 0 1

Mergers and acquisitions 0.48 0.50 0 1

Past contracts in client industry 0.29 0.25 0 1

Future contracts in client industry 0.47 0.49 0 1

Task complexity principal component 0.95 1.06 -2.64 4.66

Potential for deliberate obfuscation - 1.61 1.36 -4.57 1.99

Audit rights 0.61 0.48 0 1

Performance milestones 0.27 0.45 0 1

Service level agreements 0.36 0.49 0 1

Communication 0.58 0.49 0 1

Joint management 0.48 0.52 0 1

Client size (employees) 13,444 42,490 120 475,000

Vendor size (employees) 12,680 43,587 32 332,548

Industry accreditation 0.33 0.45 0 1

Multisourcing 0.14 0.25 0 1 Extension/Expansion of previous contract 0.09 0.29 0 1

Notes to Table 3: Variables from the contract documents are for a sample of 149 material contracts filed

with the SEC supplemented with other data sources. Please see Table 2 for variable definitions.

51

Table 4 Contract Form Likelihood as a Function of Observable but Non-verifiable

Information Signals

Notes to Table 4: Data are from 149 SEC material contracts. The 2nd column shows the likelihood of cost-

plus contracts being used if the characteristic in column 1 is true. The 3rd column shows the likelihood of

cost-plus contracts being used if the characteristic in column 1 is not true. Please see Table 2 for variable

definitions.

Characteristic Likelihood of cost-

plus contracts

Test of difference

If Yes If No t-statistic (p

value)

Future potential (H1) 0.51 0.16 4.13 (0.00)

Vendor fair cost performance reputation (H2) 0.92 0.32 5.31 (0.00)

52

Table 5 First Stage Regressions for Constructing Future Potential Instrument

Future potential

Instrumental variables (from pre-contract negotiation)

Multisourcing 0.156 (0.041)**

Extension/Expansion of previous contract -0.424 (0.203)**

Client-specific variables

Client is a Fortune 1000 firm 0.128 (0.328)

Ln employees (client size) -0.011 (0.052)

Client market power -0.068 (0.292)

Vendor-specific variables

Vendor is a Fortune 1000 firm -0.527 (0.288)*

Vendor is a publicly traded Firm -0.207 (0.292)

Ln Employees (vendor size) 0.095 (0.056)*

Vendor industry accreditation 0.249 (0.155)*

Control variables

Arbitration provisions -0.008 (0.165)*

Insurance terms 0.178 (0.114)*

Re-pricing provisions 0.266 (0.116) **

Exit clauses -0.365 (0.163) **

Client participation in delivery time standards 0.007 (0.005)

Client participation in quality standards 0.085 (0.290)

Constant 0.241 (0.500)

Notes to Table 5: This table presents results of regressions explaining the drivers of future potential, proxied

by extensibility clauses in contracts. The model is a bivariate probit of the form: Pr (𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗) = 𝛾𝑍𝑍𝑖𝑗 + 𝛾𝑉𝑉𝑗 + 𝛾𝐶𝐶𝑖 + 𝛾𝜔𝜔𝑖𝑗 + 𝜖𝐹,𝑖𝑗 ,

where Pr represents probit analysis, i represents the client, j represents the vendor, 𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗 is

an indicator variable for the use of extensibility clauses, 𝑍𝑖𝑗 are the instrumental variables that drive Future

Potential, 𝑉𝑗 include vendor-specific variables, 𝐶𝑖 include client-specific variables, , and 𝜔𝑖𝑗 are the control

variables. The pseudo R2 of the above model is 0.2719. Please see Table 2 for variable definitions.

53

Table 6 Drivers of Contract Form (Recursive Simultaneous Bivariate Probit)

(i) (ii) (iii)

Fixed price Expectation of

future potential

Fixed price Expectation of

future potential

Fixed price Expectation of

future potential

Constant 2.450 (0.756)* 0.104 (0.424) 2.470 (0.779)*** 0.004 (0.427) 2.444 (0.730)*** 0.052 (0 .016)

Tests of hypotheses

Future potential (H1) - 1.718 (0.458)** -1.721 (0.212)*** -1.697 (0.205)***

Bilateral Reputation - fair cost performance (H2) -0.513 (0.213)** -0.442 (0.351)* -0.672 (0.146)*

Contract variables

Log(Contract value) -0.102 (0.084)* -0.102 (0.140) -0.100 (0.08)*

Ln(Contract length) -0.352 (0.161)** -0.368(0.183)*** -0.274 (0.112)**

Relationship history

Contemporaneous relationship 0.345 (0.318)* 0.364 (0.292)* 0.304 (0.203)*

Prior relationship 0.367 (0.225)* 0.347 (0.183)* 0.397 (0.230)*

Prior contract termination -0.399 (0.365) * -0.387(0.327)* -0.482 (0.351)*

Prior history of fair bargaining 0.183 (0.104)* 0.177 (0.134)* 0.223 (0.146)*

Market history of client

Similar contracts of client in past 0.007 (0.005)* 0.086 (0.021)**

Similar contracts of client in future 0.225 (0.087)** 0.044 (0.026)*

Market history of vendor

Mergers and acquisitions 0.042 (0.072)

Past contracts in client industry 0.079 (0.035)**

Future contracts in client industry 0.416 (0.260)**

Controls

Task complexity principal component - 0.213 (0.092)*** -0.210 (0.085)*** -0.224 (0.074)***

Potential for deliberate obfuscation -0.052 (0.036)* -0.064 (0.450) -0.097 (0.089) *

Controls for monitoring terms √ √ √

Instruments for future interaction √ √ √

Future responsibilities & exit clauses √ √ √ √ √ √

Controls for size and bargaining power √ √ √ √ √ √

54

Notes to Table 6: Data are from 149 SEC material contracts. The regression method is Recursive Simultaneous Bivariate Probit with instruments

for endogeneity corrections and is of the following form:

Pr(𝑦𝑖𝑗) = 𝛽𝑋𝑋𝑖𝑗 + 𝛽𝑉𝑉𝑗 + 𝛽𝐶𝐶𝑖 + 𝛽𝐹𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗 + 𝛽𝜔𝜔𝑖𝑗 + 𝜀𝑖𝑗,

and

Pr (𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗) = 𝛾𝑍𝑍𝑖𝑗 + 𝛾𝑉𝑉𝑗 + 𝛾𝐶𝐶𝑖 + 𝛾𝜔𝜔𝑖𝑗 + 𝜖𝐹,𝑖𝑗 ,

where Pr represents probit analysis, y represents fixed-price contract, i represents the client, j represents the vendor, 𝐹𝑢𝑡𝑢𝑟𝑒 𝑃𝑜𝑒𝑛𝑡𝑖𝑎𝑙𝑖𝑗 is an

indicator variable for the use of extensibility clauses, 𝑍𝑖𝑗 are the instrumental variables for the Future Potential variable, 𝑉𝑗 include the vendor-

specific variables, 𝐶𝑖 include the client-specific variables, 𝑋𝑖𝑗 are contract specific control variables, and 𝜔𝑖𝑗 are the control variables that influence

both contract form and future potential. Coefficients shown are based on two-tailed t-tests (*** 1%, ** 5%, * 10% significance respectively).

Standard errors are displayed in parentheses. The size and bargaining power variables are: Client Fortune 1000, Client size (log employees), Client

market power, Vendor Fortune 1000, Vendor publicly traded, Vendor size (log employees), and Vendor accreditation. The pseudo R2, computed as

the ratio in difference between the constant-only model and the full model (including instruments) is 0.2163. Please see Table 2 for variable

definitions.