التصميم المرن اضفاء الطابع الرسمي

Electronic copy available at: http://ssrn.com/abstract=2130866

Flexible formalization

1

Contracts as Organization: Designing Flexible Formalization

Anna Grandori

Bocconi University Department of Management and Technology

Milano, Italy

and Marco Furlotti1

Tilburg University Department of Organization and Strategy

Tilburg, the Netherlands

2012-01-25 Abstract

The design of a proper formalization of economic relationships, through contractual and non-contractual documents, and its interaction with informal governance, is a re-emerging issue in organization theory. In fact it is of considerable importance in an era of increasing uncertainty and risk, where protection from hazards and coordination power on one side, but also flexibility on the other, are needed. A common way of framing and solving the problem has been to consider those needs as contrasting requirements affecting the effective degree of formalization. Integrating organization theory with contract theory this study shows that a better solution exists. Uncertainty changes the nature rather than the degree of effective formalization: ‘constitutional’ agreements (including decision, exit and property rights) can and should be more specified, rather than less, as uncertainty and conflict potential grow; while the detail of ‘operational’ agreements is the kind of formalization that is at odd with uncertainty. Survey-data analyses of the formal documents regulating 440 inter-organizational projects in different countries and sectors are presented, corroborating the main hypothesis and suggesting interesting refinements also on the other commonly used predictors of formalization (size/complexity of activities, partner irreplaceability and the longevity of relationships). Key words: contracts; formalization, organizational design; projects, strategic alliances; uncertainty

1 Corresponding author ([email protected])

Electronic copy available at: http://ssrn.com/abstract=2130866


2

CONTRACTS AS ORGANIZATION: DESIGNING FLEXIBLE FORMALIZATION

INTRODUCTION

To formalize or not to formalize: that is the question… or not? The design of contracts and

other documents formalizing agreements and rules is typically framed as a dilemma between

the virtues and vices, the benefits and costs, of formalization versus informality. Are detailed

and comprehensive contracts a means for protecting the parties from abuse, or are they a way

of ossifying relations (Orr, 2006)? Are incomplete contracts more flexible and therefore more

advantageous under conditions of uncertainty (Loasby, 1976), or are they the source of all

evils (Hart, 1988)? Why rather simple contracts are suitable to regulate very complex matters

(Al-Najjar, 1995)? These are some of the puzzles of formalization in contract theory, which

are of considerable importance also in the practice of contract design.

Similar puzzles can also be identified in organizational analyses of formalization. Are

detailed formal job descriptions, transparent rules and decision making procedures – both in

internal organization or in interfirm structures (e.g. franchising and sub-contracting) – the

only way of bringing about transparency and professionalism (Weber, 1922), accountability

(Hannan & Freeman, 1984), procedural justice (Greenberg, 1987), and large scale

coordination (Blau & Scott, 1963; Pugh, Hickson & Hinings, 1969)? Or are they the source

of bureaucratic pathologies and the most severe obstacle to flexibility and innovativeness

(Burns & Stalker, 1961; Volberda, 1998)?

The issue behind those puzzles is that formalization involves an ex-ante determination of

future behaviors. By contrast, flexibility is commonly intended as the capability to

reconfigure a system in the face of unforeseeable events (Volberda, 1998). Therefore,

formalization and flexibility are usually seen as contradictory. As a result, scholars both in


3

economics and organization theory have often sided with or against the formalization of

uncertain relations, or have proposed selecting an intermediate ‘optimal’ level of

formalization, to ensure a modicum of protection and memory with some but not extreme

losses of flexibility. The core contribution of the present paper in this respect is to show that

in fact it would be possible to have high flexibility and high protection at the same time.

According to an acceptable working definition, widely employed in the study of organized

economic behavior, formalization is the codification and definition of entities, rights and

obligations, rules and actions in written, inter-subjectively verifiable documents, such as

contracts, organization charts, and task descriptions.1 As such, it may include a contractual

component (usually the focus of economic analyses) and a non contractual component

(usually the focus of the analyses of organization theory). In all transaction of some

complexity, in fact, a set of formal rules and agreements, complement and ‘continue’

contracts not only within organizations (Williamson, 1993), but also in inter-organizational

agreements (Vlaar, Van Den Bosch & Volberda, 2007). Therefore, the fact that both

components – contractual and non-contractual – are considered as applied to the governance

of the same set of transactions, is another contribution of the present study.

The paper’s main conclusion is that the way to achieve flexibility and protection

simultaneously is to respond to uncertainty by changing the ’type’ of formalization (to what

extent different types of coordination mechanisms are formalized) rather than the degree of

formalization (how much contracts and other documents are elaborate and detailed).

In principle, the general theoretical argument developed here on the different components of

formalization applies to organization in general, no matter whether internal or interfirm, as it

is the case for the theories it draws on, as contract theory, transaction cost economics and

organizational coordination theory. The empirical study presented here is on the particular

field of inter-firm governance. The analyses are conducted on a data-base of 440 multi-firm


4

projects in selected industries and countries. To study the topic of flexible formalization in

that setting has several advantages. First, projects are becoming an increasingly diffused but

yet under-researched organizational form at the interorganizational level (Windeler & Sydow,

2001). Second, temporary organizations present the trade-off between protection and

flexibility in a more clear-cut way, as parties are less helped by the reliance on the continuity

of their relationship, which would extend the ‘self-enforceability range’ (Klein, 1985) of their

agreements. Further research on how the propositions advanced here should be

refined/modified for contracts and formal documents within organized entities (firms, public

agencies etc.), is left as an implication and task for future efforts.

The remainder of the paper is organized as follows: In the next section a review of extant

literature on the properties and design of formalization is offered, to re-establish the meaning

and the relevance of a construct that over the years has progressively slipped into theoretical

obscurity. Then insights from organization theory, economics, and legal scholarship are

brought together to argue that formalization comes in qualitatively different types, and to

achieve theoretical understanding about the content of documents that might be both adaptive

and protective. Hypotheses regarding the main predictors of the use, under conditions of

efficiency, of each type of formalization follow, accompanied by an empirical analysis of

contractual and extra-contractual formal governance on a data base of 440 inter-

organizational projects.

FORMALIZATION IN ORGANIZATION THEORY, LAW AND ECONOMICS

In the beginning… there was bureaucracy (Weber, 1922). It is widely known and reported

that among the features of the bureaucratic organizational ideal-type, formalization occupied

a prominent place. The reasons of the Weberian praise of formalization are less frequently

recalled. Weber’s main concern was to free the then-modern organization of firms and

markets from the pathologies that were common in the pre-capitalistic organization: the


5

mingling of private and organizational interests and patrimony; the exercise of influence

through any sort of bargaining power rather than of legitimate authority and rules; the lack of

organizational memory and of clear responsibilities; the non-verifiability of actions; the

unreliability of promises, the difficulty of enforcing agreements with contracting parties, and

the generalized difficulty of predicting economic behaviors. His thesis of the superiority of

formal organization was based on the analysis of those dysfunctions in prior and more

‘informal’ organization. These concerns have recently resurfaced in some contributions in

organizational sociology, underscoring that formalization increases accountability (Hannan &

Freeman, 1984) as well as transparency and procedural justice (Greenberg, 1987).

Organization theorists have over time uncovered further functions of formalization,

especially in coordination and decision-making respects. As codes of behaviours, formal

rules, procedures and programs reduce communication costs (Blau & Scott, 1963) and

substitute more expensive mechanisms based on ad hoc decision-making (March & Simon,

1958; Van De Ven, Delbecq & Koenig, 1976). As expectations of behaviours, they reduce

variance in conduct and decision-making costs (Child, 1973). The process that leads to the

drafting of formal documents is also an occasion to focus attention (Delmar & Shane, 2003),

to clarify expectations (Shenkar & Zeira, 1992), and to stretch the mind and anticipate

contingencies and consequences (Kale, Dyer & Singh, 2001). Moreover, formal documents

allow the memorization and retention of information and facilitate the transfer and the

diffusion of knowledge (De Boer, Van Den Bosch & Volberda, 1999). In fact other

organization theory (henceforth, OT) contributions drawing on the Simonian information

processing tradition, suggested that ‘problem size’ – i.e. the ‘number’ of actions and actors to

be taken into account – raises the need for formal decision supports (Galbraith, 1974). This

factor is seen as the main conceptual reason why system size is always found to correlate

positively with formalization, no matter whether the system is a firm (Pugh et al., 1969) or a


6

network of firms (Alter & Hage, 1993). More precisely, a relevant point made by OT

research is that interfirm formal agreements, as much as internal ones, are likely to have

coordination functions and not only conflict resolution functions (Grandori, 1997; Gulati,

Lawrence & Puranam, 2005).

The major analyses of the advantages of formalization in terms of conflict resolution have

been produced by organizational economists who see formal governance as set in place first

and foremost by formal contracts – written documents that state the rights and obligations of

transacting or cooperating parties and that are legally enforceable (Williamson, 1975, 1979).

Formal contracts are seen as the main mechanism by which parties can safeguard themselves

against non compliance by others. Thus, they are used in situations where there is an actual or

potential conflict. Conversely, in conflict-free situations, converging interests make

agreements ‘self-enforceable’ so contracts can remain informal (Baker, Gibbons & Murphy,

2002). Hence, the higher the actual or potential conflict between interests the more intensely

and completely economic relationships should be formalized.

Organizational economics also acknowledged the importance of non-contractual

formalization, through rights and obligations stated in private documents that are too specific

and unverifiable to be guaranteed by external courts, but are made enforceable by the

existence of the ‘internal court’ of hierarchy (Williamson, 1993). Although this argument was

formulated with reference to internal organization, it can also be applied to private arbitrators

and non-contractual agreements in inter-organizational relationships. An additional reason for

non-contractual formalization in interfirm relationships highlighted in some law and

economics studies is that the transacting parties themselves may intentionally not want to

include in legal contracts agreements that are too precise because they do not want to be

legally bound to such commitments (Crocker & Masten, 1991). Issues of this kind are


7

common in interfirm negotiations and they contribute to the formation of a set of non-

contractual documents that are at times quite thick (Vlaar et al., 2007).

If formalization only had advantages, though, we would live in a completely pre-defined and

formally regulated world. But, formalization does entail costs of analysis, writing and

enforcement (as emphasized especially in economic contributions), and even negative

consequences and outright dysfunctions (as underscored in OT and, as we shall see, in some

contributions in law).

The dysfunctions of bureaucracy in general and of formalization in particular, were

highlighted in early organizational sociology studies. The formalization of rules has been

shown to give rise to bureaucratic red-tape and poor adaptability to changing circumstances;

the formalization of structure to the creation of vested interests and of inter-unit conflict

(Merton, 1949); and both to organizational inertia. Drawing on those insights, OT has

become increasingly critical of formalization, for the ‘rigidity’ it infuses in organizational

systems. It has been argued that under conditions of uncertainty it increases the possibility of

maladaptation, as the detailed knowledge of circumstances that would be needed to select the

appropriate behavior cannot be obtained ex-ante (Burns & Stalker, 1961). Hence it has been

hypothesized, and generally found, that the higher the level of uncertainty, the lower the

effective ‘degree of formalization’ – i.e. the volume of written documents such as contracts,

job descriptions, rules, procedures and programs (Donaldson, 2001; Lawrence & Lorsch,

1967). The ensuing and still prevalent belief is that formalization is at odds with flexibility

and innovativeness; and therefore informal governance is better for achieving them

(Volberda, 1998).

Research on inter-organizational relations has also emphasized the virtues of informal ties

and agreements. Long-lasting relationships and a common culture are typically hypothesized

to bring about trust and self-enforceable informal relational contracting, and are seen as the


8

basic remedy for the failures of formal contracts under uncertainty (Reuer & Ariño, 2007;

Ring & Van de Ven, 1992).

A similar conclusion is also common in organizational economics (Al-Najjar, 1995; Miller,

1992; Ouchi, 1980). In fact, organizational economics also see formalization as unfit for

handling uncertainty primarily because of the costs incurred in writing and enforcing

contracts when the utility of parties can be affected in unpredictable ways by a myriad of

contingencies. Hence, as uncertainty increases, contracts are thought to become more and

more incomplete, thereby falling increasingly short of fulfilling their distinctive function of

providing protection against noncompliance (Williamson, 1979).

Acknowledging that formalization has both advantages and disadvantages, recent

contributions in organizational economics have explicitly framed the problem of ‘optimal

formalization’ as a trade-off between the marginal net protection benefits of formalization

and its marginal writing and enforcement costs (Battigalli & Maggi, 2002; Bernheim &

Whinston, 1998). Hence, the optimal degree of formalization becomes a decreasing function

of uncertainty, a conclusion in line with that of OT research. Accordingly, empirical studies

in the economics of contracts have focused on the degree of formalization as the degree of

completeness and of complexity in contracts. Among the findings of that research are that as

technological or market uncertainty increases, contracts contain less precise provisions

(Crocker & Reynolds, 1993) and a smaller number of clauses (Saussier, 2000); and that as

conflicts of interest and the potential for opportunism decrease, the probability of less

detailed contracts increases (Corts & Singh, 2004). This solution to the formalization design

problem has largely influenced empirical research on contracts also in the management field,

in which the ‘degree of complexity’ and ‘degree of completeness’ figures prominently as a

dependent variable.


9

A somewhat different view of the nature of contracts is however present in law-and-

economics (Crocker & Masten, 1991; Goldberg, 1976). These contributions have in fact

criticized the view of contracts prevalent in neo-institutional economics for being

mechanistic, and made the important observation that contracts do not necessarily concern

only the terms of exchange, but they often include agreements on the procedures to be

followed for changing those terms and regulating the parties’ relationship: they establish “a

constitution regulating the on-going relationship” (Goldberg, 1976). In this view, ‘relational’

contracting does not mean ‘informal’ contracting, as in the incomplete contract tradition. It

means that the formal contract is used to govern the relation more than the content (the terms

of exchange). This observation highlights that part of contractual provisions have the nature

of ‘procedures’ or ‘rules’, rather than substantive stipulations. In turn, this opens the door to

applying to contracts concepts that have been developed in organization theory, law and the

economics of rules, as to the design of rules and procedures. Those contributions will be used

and developed in the next section, to respond to the core question of whether and how it is

possible to analyze and design formal contracts (as well as non-contractual documents) in a

better way than through a trade-off between protection and flexibility. The core contribution

given is to demonstrate that it is actually possible to get both flexibility and protection from

opportunism, that is, of achieving flexible formalization.

A MODEL OF FLEXIBLE FORMALIZATION

Constitutional and operational agreements and rules

In contrast to marginalist economics, which focuses on differences in quantity or degree,

organizational and institutional analysis is chiefly concerned with qualitative differences, that

is with ‘differences in kind’ (Simon, 1978; Williamson, 2004). Applying this principle to the

issue at hand, let us note that formalization is an attribute that may vary in degree, but that


10

can also be applied to aspects of organization that differ in kind. It is possible to formalize

structures or processes, actions to be taken or the procedures for choosing actions, the identity

of players or the relationships between them, etc. Even mechanisms that are usually

considered to be typically formal actually have both formal and informal versions. For

instance, authority can be either legal-rational and formal, or traditional and informal; and

rules can be formal laws or informal social norms. It is even arguable that prices can be both

formal and informal, as they are sometimes publicly and formally posted, while in other cases

they are expressed by informal indicators of value such as in barter ratios, rationing quotas,

time spent in queues, etc. (Barzel, 1989). Contracts themselves, can be formal documents or

informally negotiated agreements, in the latter case still benefiting from some possibility of

legal enforcement (Fried, 1981).

If organizational mechanisms that differ in kind – such as property rights, rules, authority,

negotiations and prices – have different coordination properties, and if all of them can be

formalized into contracts and other formal documents, then the coordination properties of

those documents may also be different, depending on which mechanisms they include. To

analyze contracts and other formal documents through these additional organizational lenses

can shed new light on their nature as well as provide a way to achieve flexible formalization.

This approach requires analyzing and operationalizing the concept of formalization not as a

single variable, but as a set of distinct, albeit interrelated, variables, hence as a

multidimensional construct. In the following we are going to integrate a set of selected

studies on contract design, law design and organization design that converge in signaling that

formal documents include different components and help in defining in general terms which

they are and how they differ in terms of flexibility properties.

In empirical research on contracts, Luo (2002) argues that contractual formalization rigidity

can be avoided if the specified terms of exchange are subject to state-contingent clauses


11

and/or to general principles, procedures, and guidelines. His empirical analysis of a set of

international joint-venture contracts shows that scale items measuring the degree of

specification of action obligations and those measuring the degree of specification of

contingent and procedural provisions do load on two different factors. Crocker and Masten

(1991) distinguish the contribution to flexibility provided by contractually stated procedures

for recalculating automatically the terms of exchange as information becomes available

(called ‘redetermination’ procedures), from the flexibility gained by contractually stated

rights and obligations to new ad hoc joint decision making (called ‘renegotiation’

procedures). They also correlate the presence of these procedures with the type of uncertainty

faced. The empirical investigation in that study is on contracts in the natural gas industry, and

the finding is that uncertainty reflected in price volatility does not increase the presence of

renegotiation procedures, as it can be managed by automatic redetermination procedures,

while the broader task uncertainty that stems from long contract durations does. In a detailed

content-analysis of a large sample of biotechnology alliance agreements, Lerner and Merges

(1998) observe that rather than trying to spell out “a myriad of possible world-states, and

dictating outcomes under each of many scenarios” these contracts focus on “discrete aspects

of the fundamental ownership right over the research results.”

From a legal perspective, Smith (2002) also distinguished provisions regulating the

ownership of resources from those regulating their admissible uses. ‘Proprietary’ provisions

are based on exclusion, i.e., they protect a broad range of unspecified uses of a resource from

unspecified third parties. Alternatively, the parties can delineate their rights on resources by

specifying admissible activities and uses of resources by specified actors. Both types of

contractual provisions are enforceable. However, each of them relies on different proxies

(indicators) for identifying right holding and right infringement, and these proxies entail

different measurement and verification costs. Smith observes that the proxies of a property


12

right are often easier to monitor than the proxies of specific admissible activities, and

concludes that property rights are contractually more enforceable than action rights, rather

than less (differently from what most property right theorists seem to think).

Legal studies have drawn another pertinent distinction (Fon & Parisi, 2007): the distinction

between ‘general principles’ that should be applied exercising discretionary judgments, such

as ‘reasonable care’, ‘due diligence, ‘fair play’ (called ‘standards’ in this literature) and

statements specifying what actions fall outside the norm (e.g., driving faster than 55 miles per

hour) (called ‘rules’ in these contributions).

It can be noticed that those works recognize that a) there are qualitative differences among

the type of norms that can be formalized, and that b) some are more flexible than others - in

the sense that under uncertain and variable conditions formalization has dysfunctional

consequences in terms of maladaptation, beyond and on top of the costs of writing and

enforcement.

Analogous distinctions have been classic in organization design. In particular, it is well

established that the more stable and known tasks and problems are, the more actions can be

automatically guided by programmed decision making; whereas, as problems become more

uncertain, more discretion and ad hoc decision making are needed (March & Simon, 1958;

Simon, 1969). Hence, uncertainty calls for rules, procedures, responsibilities and task

descriptions that are less detailed and less action–specific (Lawrence & Lorsch, 1967).

In summary, what are the core theoretical distinctions, then, for designing flexible but

protective governance? Bringing all the above insights together it can observed that what can

really hinder and constrain action is not formalization per se, but the degree of detail or

‘action-specificity’ of rules and agreements.2 Then, the content of formal documents that

might be both adaptive and protective can be hypothesized to exhibit the following features:


13

- the specification of general, rather than detailed, formal rules;

- the specification of the actors entitled to decide, rather than of the actions to be taken;

- the specification of procedures for ad hoc decision making, rather than the specification

of automatic programs and state-contingent clauses;

- the specification of rights over resources (in rem rights, i.e. rights on things, valid erga

omnes), rather than rights over specific uses and actions (do ut des and facio ut facias

obligations among specific parties).

These types of provisions, share the property of being enforceable, hence protective, while

leaving and actually guaranteeing discretion to the players, thereby providing flexibility. Let

us call the ensemble of these provisions, constitutional formalization (henceforth, CF), as it

plays a role similar to that of a constitution in a law system.

These provisions can be conceptually distinguished from provisions sharing the opposite

feature of determining action, such as descriptions of tasks, terms of exchange and programs

for contingent automatic adjustment. Being an ‘operationalization’ of the principles and

rights stated at the constitutional level, at a more applied and particular level, this component

of formal agreements may be called operational formalization (henceforth, OF). The core

ensuing conjecture is that CF is the flexible component of formal agreements and rules.

The difference can be practically illustrated with a case: the 2004 agreement between Sunesis

Pharmaceutical, Inc. and Biogen Idec for the development and commercialization of

advanced human therapeutics. This agreement can be said to be highly operational, as it

identifies 59 distinct activities, allocates resources among them, and determines their

respective start and end dates through a Gantt chart. Moreover, it provides clear criteria to be

used in the assessment of whether to bring a certain molecule to the next phase of

development or not (e.g. “inhibitory concentration < 50%”). In contrast, a contract in the very


14

same field, in which the constitutional component can be said to prevail, is the 2005

agreement between Nuvelo Inc. and the pharmaceutical division of the Kirin Brewery

Company. It deals with similar issues essentially by determining the identity of the party

entitled to make decisions and by specifying the extent of such discretion.

Antecedents

The uncertainty of the activities to be regulated is the major source of the need for flexibility,

hence the main antecedent considered here. Uncertainty is used in many other studies on

formalization and contracts, but here it plays a more central role. In fact, in most other studies

on the issue, transaction specificity, as a source of opportunism potential, is considered the

core predictor of contractual complexity (sometimes moderated by prior relationship

mitigating opportunism). These two factors will be dutifully controlled for in the empirical

investigation, but they will not be the centerpiece of the theoretical explanation offered here,

for the following reasons.

Transaction cost economics is the theoretical source of the hypothesis that asset specificity is

a cause of contractual complexity. However, at a closer scrutiny, transaction cost economics

ascribes the degree of completeness and complexity of contracts more to uncertainty than to

asset specificity per se. In fact, assets can be very specific, but were it not for uncertainty it

would be possible to write complete contracts; whereas with uncertainty contracts become

incomplete, even if assets are not specific (Williamson 1975, 1979). In transaction cost

economics asset specificity is fundamental for the type of remedy to be chosen to manage

uncertainty and the contract incompleteness that comes with it, namely, for the degree of

integration of the transacting parties. As asset specificity increases under uncertainty, it is

posited that the exchange relationship evolves into a dedicated stable association of partners

and resources, and, in the limit, into a firm. Hence, when uncertainty is high, asset specificity

can be expected to possibly reinforce the constitutional, property right sharing component of


15

contracts (rather than the number of contract clauses, as the costs of writing and enforcing

them raise with uncertainty). We say ‘possibly’, as, in addition, doubts have been casted on

the conjecture that asset specificity raises contractual hazards: since it generates surplus and

expands the ‘pie’ to be shared, asset specificity may actually favor integrative negotiations

rather than opportunism3. The present study contributes in solving these doubts and

inconsistencies, not only through a restyling of the dependent variable (the kind of

formalization rather than its degree) but also of the independent variables (information

complexity of various kinds as a more important predictor than asset specificity).

As to the length and intensity of past relationships, it is usually expected to lower the needs

for contractual protection. However, the reasons for this hypothesis are that past relations

increase partner-specific knowledge, hence the capacity to predict their behavior, as well as

that they raise the expectation of future relations, thereby introducing reputation effects.

Hence, we are back to uncertainty and self-enforceability issues. In addition, a usually

neglected counter-effect of prior relationships is that they should also be expected to raise the

specificity of transactions, whereby their net effect on formalization is ambiguous (if

specificity is considered a source of opportunism).

Finally, the present study restitutes prominence to a variable that used to be considered and

found to be a major predictor of formalization, but almost disappeared in the study of

contracts; namely, ‘size’. ‘Size matters’ for formalization (as highlighted in our OT literature

review) as it increases the number of variables to be taken into account and the number of

values they can assume, as well as the differences and interdependences between relevant

elements to be managed. In addition, higher stakes and hazards go along with larger size, as

size involves more substantial investments. Hence, the size of action should increase the level

of formalization, both for coordination and for protection reasons.


16

In summary, if the model of formalization developed here is correct, we should find that the

contracts and the related non-contractual documents effectively formalizing the governance

of economic activities are:

(Hypothesis 1) richer in constitutional provisions, and relatively less operationally

specified, when they regulate more uncertain activities, as in the case of activities

characterized by higher research intensity, creativity and innovativeness.

(Hypothesis 2) more elaborate in both their constitutional and operational components,

when they regulate more complex activities – i.e. systems of larger size that encompass a

higher number and a greater diversity of matters and partners, and employ larger

amounts of resources.

These two conjectures about the patterns of relationships between types of uncertainty and

types of formalization have been developed irrespective of whether formalization is

contractual or non-contractual, and therefore they are expected to be valid in both cases.

Nonetheless, these two vehicles of formalization should differ in other respects. In particular,

contracts should have stronger coordination and protection functions, whereas non-

contractual agreements should have the advantages of being less costly to change and of

exposing less to legal liability. Given these countervailing factors and the dearth of prior

work on this topic, the differences between these two vehicles of formalization vis-à-vis the

aforesaid predictors will be explored empirically in the study presented next in this paper.

AN EMPIRICAL STUDY

The investigation presented here concerns the formalization of inter-organizational projects

taking place in different task environments.4 The research design is a comparative case study,

on the differences in formalization as related to three discrete clusters of industries,

intensively organized through projects: machinery engineering and construction industries

(‘machinery’ here on), creative industries and high technology industries. The data base,


17

illustrated in section 4.1, was constituted between 2006 and 2007 through an assisted

questionnaire administered to firms in different locations.5 Each industry was observed in at

least two countries. This design allows controlling for possible societal effects on

formalization, often deemed to be relevant. Section 4.2 illustrates the measurement and

meaning of the independent variables – the uncertainty of industry task environment and the

complexity of the project. The operationalization of the dependent variable – formalization –

is presented in section 4.3. The findings on the existence of a constitutional and operational

component in contracts and extra-contractual documents, and their relations with industry

uncertainty and project complexity are presented in section 4.4.

The data base

The data base was constructed starting from official lists of firms in the target sectors in the

considered countries: the country’s Statistical Business Register within certain NACE codes

(Denmark), or lists of member firms provided by relevant industry associations, such as

Germany’s Verband Deutscher Maschinen und Anlagenbau (German Engineering

Federation). All firms in the lists were contacted; or extractions were made through simple

random sampling when the lists were very large.6 To reduce undercoverage of the underlying

populations the rosters of multiple business associations were used. Appendix A provides an

overview of the sampling framework and of the reassuring results of the assessment of

possible non-respondent biases.

A thick questionnaire was administered, in an assisted way, to different roles in different

industries (e.g., account managers in advertisement, CEO/owner in small high-tech firms,

project managers in machinery firms), as the persons who have the best overview of projects

have different job titles in different industries.7. Interviewees were asked to select a project

with the following features: it had been completed within the last three years, it had produced

a relevant and valuable output and had been economically viable; it had involved different


18

legal entities and it had the respondent organization as one of the first three key partners.

‘Key partners’ were defined as organizations taking part in the project that ranked highest in

terms of the amount and importance of the resources they provided, and were identified by

the respondent.8 From the 2404 firms originally contacted, the 440 questionnaires in four

countries (response rate: 18.5%) with valid responses on the questions of interest constitute

the core dataset for this study (see Table 1).

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

Insert Table 1 about here

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

Given the variety of the contexts covered, the research team paid special attention to the

validity of measures and decided to design questionnaire items focused on facts potentially

verifiable from other sources (e.g. budget size) and on indicators expressible in natural

measurement scales (e.g. the number prior ties among the partners) rather than on perceptual

ordinal scales that could generate artifactual covariance among self-reported measures

(Podsakoff & Organ, 1986). In any case, when applying Harman’s one-factor test to assess

the extent of common variance (Harman, 1967) we found no ‘general factor’, so that common

method biases can be excluded.9

The independent variables

That high technology industries are characterized by higher innovation and uncertainty than

the machinery industry hardly needs to be argued.10 The way uncertainty in creative

industries compares to that in machinery requires more detailed discussion. The grouping of a

number of cultural and business activities under the Creative industries banner is common

both in academic research (Jones et al 2004, Caves 2000) and in economic policy practice11.

The sectors of activities typically included under the collective Creative umbrella are


19

advertising, architecture, design, film and video, interactive leisure software, music,

television and radio. These industries account for a considerable share of Gross Value Added

in many advanced countries. In core work on the subject, Caves (2000) summarized the

structural properties that distinguish arts and entertainment from other economic sectors. The

first such property is the uncertainty faced by the producer of creative works (will high

quality results necessarily ensue from the use of good quality inputs? according to which

criteria will/can quality be judged? how can value be estimated? how much will customer be

willing to pay? to what extent and with which modifications past experience can be applied to

current projects?). Other authors, found that creative industries are among the most

innovative sectors of the economy (Müller, Rammer & Trüby, 2009). Therefore, it seems

accurate to characterize creative industries as a rather uncertain business environment. This

characterization is substantiated also by other variables in the data base that allow comparing

projects in the three focal industry groupings on a few visible attributes relating to the

uncertainty of their respective task environments. First, projects differ across the three

industries in the innovativeness of the products or services they deliver (Product

innovativeness). Second, they differ in the lack of clarity of the information concerning the

task requirements, as reflected in the percentage of activities that in the course of the project

needed to undergo revisions of sorts (Revised activities). Further, they differ in the extent to

which project activities entail uncertain means-ends relationships, and can be accomplished

only after new knowledge is generated (Innovative activities), and after methods and know-

how are exchanged among the partners (Knowledge exchange). The questionnaire items

through which these attributes of the task environment were measured are reported in

Appendix B. Figure 1 reports the scores of uncertainty items for each industry sector.

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

Insert Figure 1 about here


20

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

An interesting feature in the scores of these items is the fact that their correlation coefficients

are relatively modest, which points to the multidimensionality of uncertainty.12 The figure

reveals at a glance that the ranking of the industry sectors is consistent across the indicators,

with machinery and construction scoring lowest, and high technology scoring highest.

Almost all between-industry differences are statistically significant. Therefore, industries

themselves offer a better synthetic characterization of tasks environments with varying levels

of uncertainty than summated scales based of direct measures of project activities. As

machinery and construction sectors score lowest on uncertainty, they are used as the base-line

category and analyses are carried out with the dummies Creative and High Tech, checking for

robustness with alternative operationalizions of uncertainty, with the items for which all the

inter-sectoral differences with machinery are clearest (Innovative activities and Knowledge

exchange).

Conceptually, also the life span of the project may increase the uncertainty of activities and

the need for ad hoc adjustment (Crocker & Masten, 1991). However, it may also increase the

number of activities (and indeed project duration is considerably correlated with project size

in the sample used here). Hence, in the model we will include Project duration (logarithm of

the project’s life span in weeks) as a predictor, but we leave to the empirical analyses to

establish the exact nature of this indicator.

The number and size of the activities to be coordinated, and their diversity (both expected to

be antecedents of formalization) are measured respectively by the variables Project size

(logarithm of the total budget of the project in Euros) and Partner diversity (an ordinal

variable describing whether the partners of the project belonged to the same region, to the

same nation or to different countries).


21

Results have been controlled for the longevity of relationships and the irreplaceability of the

parties. This study measured one among several correlated aspects of the longevity of the

relation, namely the number of prior collaborations of the respondent firm with the other two

key partners (Shadow of the past). As to the partners’ irreplaceability, we calculated a

composite index based on the number of partners which could have been chosen as an

alternative to each of the key partners for the focal project (Irreplaceability). Finally, the

dummies Denmark, Italy and Silicon Valley, were introduced to control for location context

effects, with Germany providing the base case location.

The dependent variable

As to formalization, the questionnaire included three questions of similar structure, asking

respondents to assess to what extent certain matters were specified respectively into the

contract(s) regulating the project, into the non-contractual written documents employed at the

interorganizational level (exemplified in charts, procedures and job descriptions); or were

regulated through informal agreements and norms. A qualifying feature of this measurement

is that it takes into account the possibility that both formal and informal governance

mechanisms are intensively used (Poppo & Zenger, 2002) by explicitly measuring the

intensity of informal regulation, rather than assuming that an increase in formalization by

definition implies a corresponding decrease in informal regulation.

The relevant matters to which formalization is applied were identified starting from an initial

rich list of possible items produced through direct consultation of legal experts, content

analysis of actual contracts and a review of the empirical literature on contracts (published in

2006 and 2007). Then, different aspects of the same mechanism were grouped into a single

class (for example, ownership of inputs and ownership of outputs were clustered into rights

of ownership). This resulted in the following seven items: rights of ownership; decision and


22

control rights; task descriptions; duration; separation procedures; warranties and

indemnities; prices, fees and royalties.

On each matter, and separately for contractual and non-contractual documents, respondents

were asked to select the most appropriate description of the extent to which each was

specified ("Not specified ", " Specified only in terms of general principles", "Extensively but

selectively specified” and "Completely specified"). Appendix B summarizes the

operationalization of the variables.

Results

Table 2 reports descriptive statistics for each of the items measuring contractual and non-

contractual formalization. For contractual formalization the mean of most indicators is

approximated by category 3 ("Extensively but selectively specified”), whereas the means of

non-contractual formalization hover around 2.5. Informal governance has considerably lower

means (between 1.5 and 2), indicating that on average it is not used at all, or that it is used to

specify governance principles only in general terms.

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


------------------------------ The first result, already apparent from these data, is therefore that formal governance is used

more intensively than informal governance and contractual formalization more intensively

than non-contractual formalization.13 Given that projects are generally used to govern

relatively complex and uncertain activities, this pattern interestingly deviates from

conventional propositions about the limits of formalization, while it squares well with the

argument that formalization does not necessarily fail altogether under complexity and

uncertainty.


23

Results on the components of formalization. The core conjecture on the twofold

nature of formalization – the existence of the two qualitatively different constitutional and

operational components - was investigated through two exploratory factor analyses (EFAs)

and two confirmatory factor analyses (CFAs) carried out separately on items of contractual

and non-contractual formalization. These analyses indicate that the items exhibit a pattern of

co-variation that is supportive of the distinction between CF and OF.

In fact, in both EFAs, right assigning and procedural items (‘rights of ownership’, ‘decision

and control rights’ and ‘separation procedures’) load on one factor, while more action-

specific ones (‘task descriptions’, ‘duration’ and ‘prices, fees and royalties’) load on a second

one. ‘Warranties and indemnities’ are conceptually more difficult to classify and their nature

remains unclear also after the EFAs, as in both analyses this item loads on both factors almost

to the same extent.14 On account of this ambiguity we drop the item from subsequent

analyses.

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

Insert Figure 2 about here

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

CFA allows us testing two measurement models based on the CF and OF distinction.15 The

resulting specification of the model, identical for both contractual and non-contractual

formalization, is represented in Figure 2. In the case of contractual formalization the model

has an acceptable goodness of fit (chi-square (7, N=440) = 28.89 (p < 0.01), SRMR = 0.061

RMSEA = 0.084, CFI = 1.00, NNFI = 1.02). The standardized factor loadings of ownership

rights, decision rights and separation procedure are 0.58, 0.67 and 0.88 respectively, and

those of tasks, duration and prices are 0.76, 0.86 and 0.81. Therefore all the indicators are

related to their factors as expected. The constructs of OF and CF have a composite reliability


24

of 0.85 and 0.76 respectively, above the commonly used threshold of 0.70. The correlation

between the two factors is substantial (0.78) but it is below the 0.80-0.85 threshold that is

frequently used as a criterion to define poor discriminant validity.

In the case of non-contractual formalization the model has a similar, or marginally better,

goodness of fit, (chi-square (7, N=440) = 25.48 (p < 0.01), SRMR = 0.062 RMSEA = 0.078,

CFI = 1.00, NNFI = 1.01). The standardized lambda coefficients of ownership rights,

decision rights and separation procedure are respectively 0.78, 0.80 and 0.88 and those of

tasks, duration and prices are 0.84, 0.91 and 0.89. Again, they are related to their factors as

expected. The composite reliability of OF and CF are 0.91 and 0.86. The correlation between

the two factors (0.86) marginally exceeds the conventional threshold. However, the two-

factor model improves the chi-square (∆ df: 1) by 19.27 with respect to a one-factor model,

so that discriminant validity is statistically supported at the 0.0001 level.16

These results justify moving forward and analyzing the antecedents of the two types of

formalization. They also justify using the latent variable scores from the CFA models to

measure CF and OF. The corresponding variables in contracts and non-contractual documents

will be designated as CFcontr, CFnon, OFcontr, and OFnon, respectively.17

Results on the antecedents of constitutional and operational formalization. The

four models that test the factors associated with formalization share the same structure and

are specified as follows:

F = 0 + 1 Creative + 2 High Tech + 3 Project size +

4 Partner diversity + 5 Project duration + Controls,

where F (Formalization) can be CF and OF, in contracts and in non-contractual document,

Controls is the vector of the control variables. As hypothesis 1) requires the comparison of

coefficients across equations, we estimate the models with multivariate multiple regression.


25

As it estimates between-equation covariance, multivariate regression makes it possible

imposing and testing constraints across-equations.

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


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

Table 3 reports the correlations between the variables comprising the multivariate models.

Concerns for multicollinearity can be excluded: a variance inflation factor (VIF) analysis

gives a highest value of 2.26, well below the threshold of 10, which has been suggested in the

literature.18 Table 4 presents the results of the multivariate regressions. Models 1 and 3

incorporate only the control variables and so serve as baseline models. Models 2 and 4 also

include the five variables of interest, Creative, High tech, Project size, Partner diversity, and

Project duration. Chi-square difference tests indicate the joint significance of these covariates

in the equations of Models 2 and 4.

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


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

Salient results of the analysis are the following:

- Project size increases formalization of all kinds (the coefficient of Project size is

significant at the 0.01 level or better in all models), as predicted.

- Partner diversity has a positive influence on contractual formalization (the coefficient of

Partner diversity is significant respectively at the 0.05 and 0.01 level in the first and in

the second equation of model 2), as expected.


26

- The governance of projects in Creative and High tech entails more intensely specified

constitutional contractual provisions (coefficients positive and significant in the CF

equation of Model 2, both with p < 0.05), as predicted. However, somewhat contrary to

expectations, it does not seem to reduce in absolute terms the operational components of

both contracts and non-contractual documents.

- Operational non-contractual formalization is reduced, instead, albeit only in its non

contractual component, by the time span of a project (the coefficient of Project duration

is negative and significant at p < 0.1 in model 4).

- In unreported analyses we tested the differences of coefficients across the two equations

of each model. This exercise helped clarifying two points. First, in the case of Creative

and High tech the coefficient differences are significant in both modes of formalization,

thus lending further support to the core hypothesis that uncertainty favors a greater

incidence of CF over OF. Second, the tests confirm that the same holds true of the

coefficients of Project duration, albeit only in the case of non-contractual documents.

Therefore, project duration seems to behave as an indicator and a correlate of uncertainty

rather than of size/complexity (as in the Croker and Masten’s study).

- The effects of the variables of interest hold true on top of and above the influence of

different national or regional settings. Yet, Table 4 shows that country/region dummies

generally have significant effects on formalization (with being in Germany driving

relatively more formalization than being in other contexts).

- As to other controls, we do find a negative effect of relation longevity on formalization,

but, as far as the full models are concerned, this holds true only for contractual

constitutional provisions (for the corresponding coefficient of Shadow of the past, p <

0.1).


27

- No effect of the irreplaceability of partners on formalization of any type was found

(Irreplaceability is insignificant in all models).

Table 5 provides the results of some robustness tests for both contractual and non-contractual

formalization. Models 5-8 replace sectors dummies, with two alternative indicators of

uncertainty from the set of items of the questionnaire: Innovative activities and Knowledge

exchange. The effect of these project-level variables on contractual formalization is rather

muted, as was probably to be expected given the sectoral heterogeneity of the sample.19

However, in no model we find statistically significant coefficients for these variables with

sign in the direction opposite to the theoretical claims. Although sectoral uncertainty better

predicts variations in contractual profiles, these project-level measures allow to see a negative

significant impact of task uncertainty (p<0.01), on operational formalization, at least in non-

contractual documents (models 7 and 8), as we had expected but could not confirm in the

models’ main specifications. The results for the other variables are nearly equivalent to those

in Table 4 (models 2 and 4).

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


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

DISCUSSION AND CONCLUSIONS

The empirical findings on inter-organizational contracts and related documents corroborate

the core assertion that ‘flexible formalization’ is possible and indeed necessary under

uncertainty. Formalization can be flexible due to its higher order constitutional components,

consisting of rights of ownership on inputs and/or outputs, and of decision and control

procedures (including those concerning the exit from the relationship) specified into contracts

and non-contractual documents.


28

Two refinements however emerged from the analysis with respect to the hypotheses. First

constitutional governance is infused, in more uncertain sectors, especially into contracts,

rather than into non-contractual documents. This result suggests that the function of providing

both flexibility and protection under uncertainty through more intense specification of

constitutional provisions is better performed by formal contracts, i.e. the legally enforceable

component of formalization. By contrast, it is the degree of specification of non-contractual

documents which decreases under uncertainty, in particular under the type of uncertainty

brought about by the expected duration of the ‘ongoing cooperation’. Hence, the function of

providing flexibility through the reduction of the detail of operational ex-ante coordination

seems to be distinctively performed by non-contractual formalization. Taken together, the

two findings actually supports the core hypothesis on the effects of uncertainty on

formalization in its original strong version – uncertainty not only increases CF but also

decreases OF – but this pattern is visible only if contractual and non-contractual documents

are considered together.

The second hypothesis – that a good part of the observed variations in the degree of

complexity and formalization of contracts and other documents should be attributable to the

size and complexity of activities, rather than to the specificity of resources – received

straightforward support from the analysis. This supports the interpretation of transaction cost

theory discussed in the theory section, rather than the more common interpretation attributing

contractual complexity mostly to transaction specificity and opportunism problems. It can

additionally be observed that many of the studies in which such an association was found,

have actually operationalized specificity as the amount of resources invested in a relationship,

which is arguably more a proxy for size and complexity than for asset specificity. In fact, in

studies where ‘small numbers’ are measured more directly, through an index based on the

number of possible partners, as in Crocker and Masten (1991) and in the data base used in the


29

present study, a relationship between small numbers and the degree of specification of

contractual clauses is not found.

As to the other predictor usually employed in empirical research on contracts – prior

relations – it has been found here to have an uneven impact over different kinds of

formalization. This may help clarify why different studies have reached opposite conclusions

on the role of prior ties for contractual articulation. In fact, results suggest that if partners

have previously worked together on other projects, the need for protection under uncertainty

is reduced – whereby contractual CF decreases – but not the need for coordination under

complexity – as in fact the operational component of both contracts and non-contractual

formalization are insensitive to prior relations.

The framework and the results also suggest further research questions. For example, how

does the relative incidence of formal –contractual and non contractual - and informal

governance in their constitutional and operational components, vary across contexts? For

inter-firm projects the recourse to informal agreements and norms turned out to be minor with

respect to formal governance, but results on the incidence of informal governance may be

different for intra-firm governance) or even for different types of inter-firm relations (e.g.

long term buyer-seller relations). Results on location effects invite inquiry on which are the

features of institutional contexts systematically affecting the level and kind of formalization,

and in which direction do they affect it. The framework presented here would allow to go

beyond the mere assertion that there is institutional embeddedness variety, and to formulate

non ad hoc hypotheses on which institutions have which effect on contracts and

formalization. Examples of such hypotheses are that legal and societal requirements for

transparency and accountability may increase contractual formalization, while court

discretion and the constitutional richness of the law system may decrease it as less regulatory

burden would insist on any specific contractual agreement.20


30

In conclusion, the framework and the results presented here seem to have significant

conceptual and practical relevance for organizational and contractual design, and for an

appreciation of the rich organizational content of contracts. Not only the theory and results

presented here confirm that the old organizational and legal precept of being as formal as

possible, attempting to cover all conceivable contingencies, and writing clauses for every

possible action, is not a good design principle They also indicate that being informal is

definitely not the whole story and not necessarily a good recipe for managing uncertain

activities. Neither is an intermediate degree of formalization the optimal solution. The answer

to the question of how to design “living agreements for a risky world” (Orr, 2006) – a

question of increasing interest also among legal professionals – is to design contracts, and the

non-contractual documents complementing them, as organizational treatises with a

constitutional and an operational component, which should have different incidence

according to the state of uncertainty and the complexity of activities.


31

REFERENCES

Al-Najjar, N. I. 1995. Incomplete contracts and the governance of complex contractual

relationships. American Economic Review, 85: 432-436.

Alter, C., & Hage, J. 1993. Organizations Working Together. Newbury Park, CA: SAGE

Publications, Inc.

Armstrong, J. S., & Overton, T. 1977. Estimating nonresponse bias in mail surveys. Journal

of Marketing Research, 14: 396-402.

Baker, G., Gibbons, R., & Murphy, K. J. 2002. Relational Contracts and the Theory of the

Firm. Quarterly Journal of Economics, 117: 39-84.

Barzel, Y. 1989. Economic analysis of property rights. Cambridge, New York and

Melbourne: Cambridge University Press.

Battigalli, P., & Maggi, G. 2002. Rigidity, Discretion, and the Costs of Writing Contracts.

American Economic Review, 92: 798-817.

Bernheim, B. D., & Whinston, M. D. 1998. Incomplete Contracts and Strategic Ambiguity.

American Economic Review, 88: 902-932.

Blau, P. M., & Scott, W. R. 1963. Formal Organizations. A Comparative Approach. London:

Routledge & Kegan Paul Ltd.

Burns, T., & Stalker, G. M. 1961. The Management of Innovation. London: Tavistock

Publications.

Caves, R. E. 2000. Creative industries: contracts between art and commerce. Cambridge and

London: Harvard University Press.

Child, J. 1973. Strategies of Control and Organizational Behavior. Administrative Science

Quarterly, 18: 1-17.


32

Corts, K. S., & Singh, J. 2004. The Effect of Repeated Interaction on Contract Choice:

Evidence from Offshore Drilling. Journal of Law, Economics & Organization, 20:

230-260.

Crocker, K. J., & Masten, S. E. 1991. Pretia Ex Machina? Prices and Process in Long-Term

Contracts. Journal of Law & Economics, 34: 69-99.

Crocker, K. J., & Reynolds, K. J. 1993. The efficiency of incomplete contracts: an empirical

analysis of air force engine procurement. RAND Journal of Economics, 24: 126-146.

De Boer, M., Van Den Bosch, F. A. J., & Volberda, H. W. 1999. Managing Organizational

Knowledge Integration in the Emerging Multimedia Complex. Journal of

Management Studies, 36: 379-398.

Delmar, F., & Shane, S. 2003. Does business planning facilitate the development of new

ventures? Strategic Management Journal, 24: 1165-1185.

Donaldson, L. 2001. The Contingency Theory of Organizations. Thousand Oaks: Sage.

Fon, V., & Parisi, F. 2007. On the Optimal Specificity of Legal Rules. Journal of

Institutional Economics, 3: 147-164.

Fried, C. 1981. Contract as Promise: A Theory of Contractual Obligation. Cambridge, MA:

Harvard University Press.

Galbraith, J. R. 1974. Organization Design: An Information Processing View. Interfaces, 4:

28-36.

Goldberg, V. P. 1976. Toward an Expanded Economic Theory of Contract. Journal of

Economic Issues, 10: 45-61.

Grandori, A. 1997. An Organizational Assessment of Interfirm Coordination Modes.

Organization Studies, 18: 897-925.


33

Greenberg, J. 1987. A taxonomy of organizational justice theories. Academy of Management

Review, 12: 9-22.

Gulati, R., Lawrence, P. R., & Puranam, P. 2005. Adaptation in vertical relationships:

Beyond incentive conflict. Strategic Management Journal, 26: 415-440.

Hannan, M. T., & Freeman, J. 1984. Structural Inertia and Organizational Change. American

Sociological Review, 49: 149-164.

Harman, H. H. 1967. Modern Factor Analysis. Chicago,IL: University of Chicago Press.

Hart, O. D. 1988. Incomplete Contracts and the Theory of the Firm. Journal of Law,

Economics & Organization, 4: 119-139.

Jones, P., Comfort, D., Eastwood, I., & Hillier, D. 2004. Creative industries: economic

contributions, management challenges and support initiatives. Management Research

News, 27: 134.

Kale, P., Dyer, J., & Singh, H. 2001. Value creation and success in strategic alliances:

alliancing skills and the role of alliance structure and systems. European Management

Journal, 19: 463-471.

Klein, B. 1985. Self-enforcing contracts. Journal of Institutional and Theoretical Economics,

141: 594-600.

Lawrence, P. R., & Lorsch, J. W. 1967. Organization and Environment: Managing

Differentiation and Integration. Boston, MA: Harvard Business School Press.

Lerner, J., & Merges, R. P. 1998. The Control of Technology Alliances: an Empirical

Analysis of the Biotechnology Industry. Journal of Industrial Economics, 46: 125-

156.


34

Loasby, B. J. 1976. Choice, Complexity, and Ignorance. Cambridge: Cambridge University

Press.

Luo, Y. D. 2002. Contract, Cooperation, and Performance in International Joint Ventures.

Strategic Management Journal, 23: 903-919.

March, J. G., & Simon, H. A. 1958. Organizations. New York: Wiley.

Merton, R. K. 1949. Social Theory and Social Structure. New York: The Free Press of

Glencoe.

Miller, G. J. 1992. Managerial dilemmas: The political economy of hierarchy. Cambridge,

New York and Melbourne: Cambridge University Press.

Müller, K., Rammer, C., & Trüby, J. 2009. The role of creative industries in industrial

innovation. Innovation: Management, Policy & Practice, 11: 148-168.

Orr, J. R. 2006. Living Agreements for a Risky World. Harvard Business Review.

Ouchi, W. G. 1980. Markets, bureaucracies, and clans. Administrative Science Quarterly, 25:

129-141.

Podsakoff, P. M., & Organ, D. W. 1986. Self-reports in organizational research: problems

and prospects. Journal of Management, 12: 531-544.

Poppo, L., & Zenger, T. 2002. Do Formal Contracts and Relational Governance Function as

Substitutes or Complements? Strategic Management Journal, 23: 707.

Pugh, D. S., Hickson, D. J., & Hinings, C. R. 1969. An Empirical Taxonomy of Structures of

Work Organizations. Administrative Science Quarterly, 14: 115-126.

Reuer, J. J., & Ariño, A. 2007. Strategic alliance contracts: dimensions and determinants of

contractual complexity. Strategic Management Journal, 28: 313-330.


35

Ring, P. S., & Van de Ven, A. H. 1992. Structuring Cooperative Relationships between

Organizations. Strategic Management Journal, 13: 483-498.

Saussier, S. 2000. Transaction Costs and Contractual Incompleteness: The Case of Electricite

de France. Journal of Economic Behavior and Organization, 42: 189-206.

Shenkar, O., & Zeira, Y. 1992. Role Conflict and Role Ambiguity of Chief Executive

Officers in International Joint Ventures. Journal of International Business Studies, 23:

55-75.

Simon, H. A. 1969. The Sciences of the Artificial. Cambridge, MA: MIT Press.

Simon, H. A. 1978. Rationality as Process and as Product of Thought. American Economic

Review, 68: 1-16.

Smith, H. E. 2002. Exclusion Versus Governance: Two Strategies for Delineating Property

Rights. Journal of Legal Studies, XXXI: S453-S487.

Van De Ven, A. H., Delbecq, A. L., & Koenig, R., Jr. 1976. Determinants of Coordination

Modes within Organizations. American Sociological Review, 41: 322-338.

Vlaar, P. W. L., Van Den Bosch, F. A. J., & Volberda, H. W. 2007. Towards a Dialectic

Perspective on Formalization in Interorganizational Relationships: How Alliance

Managers Capitalize on the Duality Inherent in Contracts, Rules and Procedures.

Organization Studies, 28: 437-466.

Volberda, H. W. 1998. Building The Flexible Firm: How To Remain Competitive. Oxford:

Oxford University Press.

Weber, M. 1922. Wirtschaft und Gesellschaft. Tubingen: Mohr.

Williamson, O. E. 1975. Markets and Hierarchies: Analysis and Antitrust Implications: A

Study in the Economics of Internal Organization. New York: Free Press.


36

Williamson, O. E. 1979. Transaction-Cost Economics: the Governance of Contractual

Relations. Journal of Law & Economics, 22: 233-261.

Williamson, O. E. 1993. Transaction Cost Economics and Organization Theory. Industrial

and Corporate Change, 2: 107-156.

Williamson, O. E. 2004. Herbert Simon and organization theory: Lessons for the theory of

the firm. In M. Augier and J. G. March (Eds.), Models of a man. Cambridge, MA:

MIT Press.

Windeler, A., & Sydow, J. 2001. Project networks and changing industry practices -

Collaborative content production in the German television market. Organisation

Studies, 22: 1035-1060.


37

FOOTNOTES

1 Today, electronic data storage complements and partially replaces paper documents as the repository of formalization. However, the change in the medium does not alter the fundamental functions that formalization is expected to perform. 2All this is perfectly in line with a common finding of the studies on organizational cultures: detailed, action-specific routines and precepts, even if informal, can in fact be as rigid as the formal ones and often even more so. 3 The first appearance of this argument seems to be in Croker and Masten Crocker, K. J., & Masten, S. E. 1991. Pretia Ex Machina? Prices and Process in Long-Term Contracts. Journal of Law & Economics, 34: 69-99.. 4 While, as argued, inter-firm projects are interesting to study, they do not belong to any definite ‘population’ of objects; hence, we have opted for a research design providing high internal validity and good causal leverage, rather than pointing at the external validity of results in terms of generalizability of projects features to a population. 5 The data were collected as a part of an international research project on the governance of interfirm projects in several industries and countries, including Denmark, Germany, Italy, California, Canada, France, (see Acknowledgments). Only the questionnaires from the first four locations included complete information on the variables of interest and were used here. 6 A lower bound of 10 employees per firm was applied. 7 It can be acknowledged that a documental analysis of contract themselves could have been better in some respects for the purposes of the present analysis. On the other side, it would have entailed the loss of much complementary evidence and the possibility to match a number of features of the activities with the documents intended to regulate them. 8 The dataset is composed by project collaborations between three or more organizations in 93.5% of cases and by dyadic collaborations in the remaining ones. 9 An unrotated factor analysis of the questionnaire items yielded eight factors with eigenvalue greater than one, the largest of which explained only 19 percent of total variance. 10 For example, in the US in the year 2006 the research and development (R&D) intensity (R&D expenditures as a percentage of value added) in a prototypical high technology industry such as the manufacturing of computing equipment (ISIC C30) was 33.5, versus 8.2 in machinery (ISIC C29) (Source: OECD 2011. STAN: OECD Structural Analysis Statistics (database)). 11 For example, a Creative Industries Task Force has been instituted by initiative of the Department for Culture, Media and Sport of the government of the UK since 1997. 12 Data available from the authors. 13 In paired sample tests of differences of means, every difference between an item of contractual formalization and its correspondent in non-contractual documents is statistically significant, and so are five out of seven differences between non-contractual formalization and informal governance. Data available from the authors. 14 Data available from the authors. 15 As the items are measured on ordinal scales and violate the assumption of multivariate normality required by CFA, the analysis was conducted on matrices of polychoric correlations and of asymptotic


38

covariances, using a weighted least squares estimator. Polychoric correlations calculated with Lisrel (v. 8.80) are reported in Table 2. 16 In unreported analyses we tested whether the measurement models are invariant across industry clusters or are just a statistical artifact. Overall, the analyses supported the statement that the structure of both contracts and extra-contractual documents is well described by a two-factor model comprising the facets of CF and OF, for projects in machinery, high-tech and creative industries alike. 17 As a robustness check we reestimated our models of CF and OF using summated scales instead of latent variable scores. Results were substantively the same as those reported below. 18 Breusch-Pagan’s tests and residual plot analyses give mild indications of heteroskedasticity or error term distribution. Therefore we used bootstrap to produce standard errors that are valid under weaker assumptions than homoschedasticity. 19 Results were fundamentally equivalent if we subtracted from Innovative activities and Knowledge exchange their average values calculated over each sector’s subsample. 20 The latter implication for further research in Law & Economics that could be inspired by this paper, has been suggested by Francesco Parisi in a commentary at the ISNIE annual conference 2010.


39

Table 1

Sample distribution by industry and country

Country Creative Machinery High tech Total

Germany 61 134 19 214 (28.50) (62.62) (8.88) (100.00) Denmark 38 21 32 91 (41.76) (23.08) (35.16) (100.00) Italy 1 79 5 85 (1.18) (92.94) (5.88) (100.00) Silicon Valley 0 0 50 50 (0.00) (0.00) (100.00) (100.00) Total 100 234 106 440 (22.73) (53.18) (24.09) (100.00)

Notes: row frequencies in parentheses


40

Table 2

Indicators of formalization: descriptive statistics and polychoric correlations

Panel 1: Contractual formalization items

Mean Std.Dev. 1 2 3 4 5 6 7

1. DCF prices, fees and royalties 3.25 0.89 1

2. DCF duration 2.99 0.99 0.621 1

3. DCF warranties and indemnities 2.90 1.09 0.603 0.539 1

4. DCF tasks 2.81 0.98 0.482 0.643 0.472 1

5. DCF rights of ownership 2.76 1.17 0.381 0.253 0.447 0.239 1

6. DCF separation procedures 2.55 1.16 0.496 0.522 0.728 0.489 0.508 1

7. DCF decision and control rights 2.45 1.11 0.422 0.328 0.447 0.400 0.541 0.550 1

Panel 2: Non-contractual formalization items

Mean Std.Dev. 1 2 3 4 5 6 7

1. DEF prices, fees and royalties 2.43 1.24 1

2. DEF duration 2.48 1.15 0.757 1

3. DEF warranties and indemnities 2.19 1.21 0.862 0.760 1

4. DEF tasks 2.50 1.06 0.608 0.752 0.625 1

5. DEF rights of ownership 1.89 1.13 0.617 0.533 0.654 0.446 1

6. DEF separation procedures 1.96 1.13 0.687 0.613 0.751 0.536 0.675 1

7. DEF decision and control rights 2.04 1.07 0.525 0.534 0.595 0.582 0.686 0.642 1

Notes: N= 440. All correlations significant at the 0.01 level. “DCF”: Degree of contractual formalization; “DEF”: Degree of non-contractual formalization


41

Table 3

Descriptive statistics and correlation matrix

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1. CFcontr 1 2. OFcontr 0.73 1 3. CFnon 0.39 0.29 1 4. OFnon 0.25 0.34 0.80 1 5. Creative -0.04 -0.10 -0.10 -0.11 1 6. High tech 0.02 -0.09 -0.01 -0.12 -0.31 1 7. Project size 0.29 0.28 0.22 0.20 -0.37 -0.17 1 8. Partner diversity 0.17 0.19 0.06 0.11 -0.08 -0.07 0.19 1 9. Project duration 0.14 0.14 0.12 0.07 -0.31 -0.10 0.56 0.16 1

10. Irreplaceability 0.05 0.05 0.08 0.12 -0.11 0.17 0.02 0.15 0.06 1 11. Shadow of the past -0.10 -0.09 -0.08 -0.06 0.17 -0.11 -0.05 -0.02 -0.10 -0.17 1 12. Denmark -0.08 -0.15 -0.15 -0.24 0.23 0.13 -0.12 -0.08 -0.06 -0.28 0.20 1 13. Italy -0.09 -0.02 -0.03 -0.02 -0.25 -0.21 0.13 0.09 0.11 0.00 -0.04 -0.25 114. Silicon Valley -0.03 -0.08 0.01 -0.07 -0.19 0.64 -0.24 -0.11 -0.24 0.18 -0.23 -0.18 -0.18 115. Innovative activities -0.01 -0.03 -0.03 -0.13 0.05 0.32 -0.10 0.04 0.05 0.18 -0.08 0.00 -0.07 0.22 1 16. Knowledge exchange -0.12 -0.13 -0.11 -0.23 0.16 0.21 -0.13 -0.10 0.01 0.00 0.05 0.31 -0.12 0.18 0.33 1 Mean 3.18 3.60 2.41 2.74 0.23 0.24 6.03 2.07 1.67 3.29 0.58 0.21 0.19 0.11 25.81 44.29 S.D. 1.09 0.93 1.06 1.10 0.42 0.43 1.27 0.82 0.51 0.88 1.17 0.41 0.40 0.32 23.35 31.10

Notes: N= 440


42

Table 4 – Determinants of constitutional and operational formalization in contracts and non-contractual documents

Contracts Non-contractual documents (1) (2) (3) (4)

CFcontr OFcontr CFcontr OFcontr CFnon OFnon CFnon OFnon

Irreplaceability 0.030 0.012 -0.019 -0.010 0.042 0.086 0.033 0.088 (0.061) (0.052) (0.058) (0.053) (0.059) (0.061) (0.058) (0.062) Shadow of the past -0.097* -0.077* -0.085+ -0.063 -0.049 -0.034 -0.032 -0.025 (0.048) (0.037) (0.048) (0.039) (0.046) (0.041) (0.046) (0.040) Denmark -0.296* -0.399** -0.324* -0.297* -0.414** -0.737*** -0.353* -0.603*** (0.136) (0.125) (0.137) (0.133) (0.143) (0.146) (0.146) (0.155) Italy -0.383** -0.216+ -0.348* -0.271** -0.205 -0.334* -0.226+ -0.422** (0.146) (0.117) (0.140) (0.105) (0.127) (0.133) (0.135) (0.132) Silicon Valley -0.355* -0.435** -0.308 -0.198 -0.161 -0.560*** 0.015 -0.360+ (0.153) (0.142) (0.226) (0.212) (0.144) (0.147) (0.207) (0.218) Creative 0.314* -0.048 0.029 -0.231 (0.160) (0.139) (0.151) (0.158) HighTech 0.414* -0.040 0.044 -0.191 (0.162) (0.143) (0.172) (0.157) Project size 0.294*** 0.187*** 0.183*** 0.143** (0.051) (0.048) (0.048) (0.052) Partner diversity 0.164* 0.154** 0.019 0.071 (0.064) (0.057) (0.057) (0.059) Project duration -0.097 -0.102 0.005 -0.200+ (0.124) (0.128) (0.107) (0.115) Constant 3.316*** 3.781*** 1.341*** 2.548*** 2.445*** 2.761*** 1.273*** 2.140*** (0.230) (0.198) (0.407) (0.368) (0.232) (0.228) (0.377) (0.402) R-squared 0.037 0.048 0.145 0.127 0.032 0.089 0.076 0.124chi2 16.13** 27.88*** 80.96*** 68.72*** 13.67** 43.36*** 33.01*** 63.79*** ∆ chi2 54.47*** 39.00*** 21.15*** 16.62*

Notes:+ p<0.10; * p<0.05; ** p<0.01; *** p<0.001. Bootstrap standard errors in parentheses. Model specification: multivariate regression. N=440


43

Table 5

Robustness controls

Contracts Non-contractual documents (5) (6) (7) (8) CFcontr OFcontr CFcontr OFcontr CFnon OFnon CFnon OFnon Irreplaceability 0.003 -0.012 0.009 -0.009 0.041 0.099 0.040 0.089 (0.058) (0.053) (0.059) (0.053) (0.061) (0.064) (0.060) (0.062) Shadow of the past -0.078 -0.063+ -0.075 -0.061 -0.032 -0.030 -0.028 -0.021 (0.050) (0.038) (0.050) (0.039) (0.046) (0.041) (0.046) (0.041) Denmark -0.183 -0.311* -0.114 -0.272* -0.331* -0.650*** -0.275+ -0.539*** (0.135) (0.127) (0.149) (0.133) (0.142) (0.147) (0.148) (0.153) Italy -0.436*** -0.258* -0.432*** -0.256* -0.235+ -0.364** -0.230+ -0.351** (0.132) (0.102) (0.131) (0.102) (0.128) (0.127) (0.127) (0.128) Silicon Valley -0.072 -0.212 -0.003 -0.178 0.068 -0.346* 0.101 -0.311+ (0.176) (0.169) (0.178) (0.170) (0.152) (0.161) (0.156) (0.165) Innovative activities 0.000 -0.000 -0.002 -0.006** (0.002) (0.002) (0.002) (0.002) Knowledge exchange -0.002 -0.001 -0.002 -0.005** (0.002) (0.002) (0.002) (0.002) Project size 0.261*** 0.192*** 0.253*** 0.189*** 0.175*** 0.152** 0.174*** 0.154** (0.049) (0.045) (0.049) (0.044) (0.044) (0.049) (0.045) (0.049) Partner diversity 0.162* 0.154** 0.158* 0.151** 0.021 0.080 0.014 0.062 (0.063) (0.056) (0.064) (0.056) (0.056) (0.058) (0.056) (0.058) Project duration -0.119 -0.096 -0.091 -0.083 0.016 -0.133 0.026 -0.129 (0.128) (0.131) (0.125) (0.127) (0.104) (0.114) (0.105) (0.115) Constant 1.628*** 2.500*** 1.706*** 2.541*** 1.317*** 1.965*** 1.366*** 2.048*** (0.369) (0.335) (0.378) (0.346) (0.342) (0.376) (0.348) (0.384) R-squared 0.130 0.126 0.134 0.128 0.077 0.131 0.079 0.133 chi2 62.81*** 69.56*** 80.20*** 75.25*** 33.27*** 72.21*** 34.28*** 67.20*** Notes:+ p<0.10; * p<0.05; ** p<0.01; *** p<0.001. Bootstrap standard errors in parentheses. Model specification: multivariate regression. In every model N=440.


44

Figure 1

Measures of uncertainty: Means by industrial sector

0 20 40 60Mean

Knowledge exchange

Innovative activities

Revised activities

Product innovativeness

MC

HT

MC

HT

MC

HT

MC

HT

Notes: HT: 'High tech'; C: 'Creative'; M: 'Machinery'


45

Figure 2

Measurement model of formalization


46

Appendix A

Industry groupings and sampling frame

Industry groupings Sampling frame Creative Events (fairs, exhibitions, congresses; operation of arts facilities) Motion pictures Business-to-business design Games Advertising Publishing Recorded music

Denmark: registered enterprises within NACE/DB03 industry codes 221110, 365000, 744010, 744090, 921100, 923110, 923200 Germany: list obtained from various industry associations (Federal Association of German Galleries, the Association of Concert Agencies, etc.), industry rankings (e.g.: Werben & Verkaufen ranking of major advertising companies) and prior academic research (e.g. DFG-Project “Production in Projects” – Bonn U.)

Machinery Machinery and equipment Engineering activities Construction

Germany: list of member firms of the German Engineering Federation; Italy: list of member firms of the following industry associations: ANIMP, OICE, UCIMU, APRI, AIAD, UCIMA, UCOMESA

High technology Semiconductors Computer/Communication hardware Innovation services Biomedical Electronic components Software consultancy and supply

Denmark: registered enterprises within NACE/DB03 industry codes 722100 and 722200 Germany: list from prior academic research project (DFG-Project “Production in Projects” - Bonn University) California: list of firms from the Silicon Valley Venture Capitalists Association

To assess potential non-response bias, tests for differences between early and late respondents were run, on the assumption that the latter are more similar than the former to non respondents (Armstrong & Overton, 1977). The tests were implemented using “time to respond” as a regression variable. In particular, this variable was used as a predictor of project characteristics such as budget size, the number of partners or the number of employees, and firm characteristics such as turnover. In each of these analyses the coefficient of time to response was not significant.


47

Appendix B

Operationalization of variables and indicators

Variable Operationalization

Degree of contractual formalization (DCF)

DCF rights of ownership Q.: How were the following matters regulated in written, legal, enforceable contracts between the three key partners? 1 = Not specified; 2= General principles specified; 3 = Extensive specification of rights and obligations under conceivable specified conditions; 4 = Complete specification of rights and obligations so that they hold under any condition

DCF decision and control rights DCF tasks DCF duration DCF separation procedures DCF warranties and indemnities DCF prices, fees and royalties

Degree of non-contractual formalization (DEC)

DEC rights of ownership Q.: To what extent were the following matters regulated by written internal charts, procedures and job descriptions (e.g. of the type used in internal organization) in the relation between the three key partners? 1 = Not at all; 2= General principles 3 = Extensively; 4 = Completely

DEC decision and control rights DEC tasks DEC duration DEC separation procedures DEC warranties and indemnities DEC prices, fees and royalties

Explanatory variables

Project size Log10 of project budget in Euros Project duration Log10 of project duration in weeks Partner diversity Whether parties were from same region (1), same country (2) or

different countries (3) Irreplaceability Max (I1, I2, I3), where Ii = number of organizations (on 4 point

scale, in decreasing order of numerosity) which could have been chosen for the focal project in alternative to key partner i.

Shadow of the past Log10(N * (C2 + C3)), where C2 and C3 = number of prior collaborations of respondent firm respectively with key partner 2 and 3; N = 2 if number of key partners = 2; N = 1, otherwise

Product innovativeness *

The product or service developed in the project was:

a variation of an existing product or service (1) a new generation of an existing product or service line (2) a new product or service line for the partners (3) a new-to-the-industry product or service (4) a new-to-the-world product or service (5)

Revised activities Please indicate the percentage of activities of the whole project for which it was necessary to revise when, how or which activities should be carried out: ____%

Innovative activities Please indicate the percentage of activities of the whole project for which it was necessary to generate new knowledge (e.g., new approaches, new analytic schemes): ____%

Knowledge exchange Please indicate the percentage of activities of the whole project for which it was necessary to exchange knowledge (e.g. methods, know-how) among partners: ____%

* Treated as a [1-5] scale and rescaled on [0,100] range for comparability with other items

Documents

التصميم المرن اضفاء الطابع الرسمي