Int. J. Technology Management, Vol. 16, Nos. 1/2/3, 1998
193
Innovative contractual structures for interorganizational systems Serghei Floricel Hydro-Quebec/CAE/NSERC/SSHRC Chair in Management of Technology, University of Quebec at Montreal, Pavillon Ste-Catherine Ouest, Local X-7330, C.P. 11008, Montreal (Quebec), Canada H3C 4T9
Joseph Lampel Department of Management, University of St. Andrews, St. Katharine’s West, The Scores, St. Andrews, Fife, Scotland, UK, KY16 9AL. Abstract: This paper tests the principal-agent theory in the context of contracting practices for the development of large-scale engineering projects. Five hypotheses are derived from the principal-agent theory regarding the propensity to use behaviour-based contracts versus outcome -based contracts function of the project owner’s risk aversion and mo nitoring competencies, of the goal congruence between principal and agent, of the agent’s risk aversion, and of the technological innovation required by the project. A sixth hypothesis states that more successful projects are more in line with the predictions of the first five hypotheses. All hypotheses are translated into testable propositions specific to large-scale engineering projects. For instance, outcome based contracts are assimilated to fixed-price contracts such as turnkey and EPC. Results based on a sample of 60 power plant projects confirm that participants tend to select contracts as the principal agent theory predicts. Moreover, contracts used in successful projects follow more accurately the theoretical predictions. Keywords: Principal-agent theory; agency theory; contract; large-scale engineering projects; turnkey; EPC. Reference to this paper should be made as follows: Floricel, S. and Lampel, J. (1998) ‘Innovative contractual structures for interorganizational systems’, Int. J. Technology Management, Vol. 16, Nos. 1/2/3, pp.193–206. Biographical notes: Serghei Floricel pursues doctoral studies in administration at the University of Quebec in Montreal and works for the Hydro -Québec Chair in the Management of Technology. His research focuses on the study of large-scale engineering projects. He studied innovation in North American power plant projects, and is currently participating in the International Research Pro gramme for the Management of Engineering and Construction (IMEC), which includes the benchmarking of 60 projects around the world. He holds a bachelor degree in mechanical engineering and a MBA. His past work experience
Copyright © 1998 Inderscience Enterprises Ltd.
194
S. Floricel and J. Lampel is in engineering design and in international economic assistance programs. Dr. Joseph Lampel is a lecturer in Strategic Management at St. Andrews University, Scotland. Dr. Lampel received his BSc degree in Physics from McGill University, his MSc in Technology Policy from the UniversitĂŠ de M ontrĂŠal, and his doctorate in Strategic Management from McGill University, Canada. He has published in Advances in Strategic Management, Sloan Management Review, R&D Management, International Business Review, and Journal of Product Innovation. He is currently working on a book on strategic management with Henry Mintzberg and Bruce Ahlstrand.
1
Introduction
In recent times, we have witnessed the increasing use of turnkey and other types of fixed price contracts for the implementation of complex engineering projects. Ostensibly, these contracts serve the dual purpose of limiting the exposure of owners to costs overruns, and providing contractors with clear budgetary guidelines. However, the use of turnkey and other fixed-price contracts raise questions regarding the control over the technical quality of the project, in particular over the willingness of contractors to incorporate innovative solutions into the design [1]. Therefore, turnkey and fixed price contracts may not always be an optimal solution to contractual problems. Their effective use may depend on the nature of the project itself and on the circumstances surrounding the contracting parties. This paper draws on principal-agent theory to investigate the types of contracts that are used between project owner and the prime contractors. We attempt to answer two questions. The first is whether real contracts are designed in accordance with the key principal-agent theory predictions. The second, whether projects that are successful follow more closely the prescriptions of principal-agent theory than those that are less. These questions are tested on two samples of 30 power plant projects each, one made of successful projects and the second made of less successful projects. Our results lend support to both propositions, and suggest that principal-agent theory has predictive validity in the design of contractual relationships between owners and builders of large engineering projects. A brief summary of the paper is in order before we proceed. Our first section outlines the principal-agent theory, setting forth five hypotheses derived from the theory. To these hypotheses, we add a sixth hypothesis which tests the predictions of the principalagent theory against project performance. The second section presents the indicators and measures of the main theoretical concepts. The third section presents the methodology and the statistical results. Section four discusses these results. A conclusions section which also outlines some directions for further research ends this paper.
Innovative contractual structures for inter-organizational systems
2
195
The principal-agent theory of contractual design
The principal-agent theory applies to situations where one party, the principal, contracts with another party, the agent, to perform tasks which the principal is unable or unwilling to do itself [2,3,4,5]. The theory models this situation in the following way. The principal’s role is limited to defining the outlines of the task, setting the rules for determining the agent’s compensation[6], and to laying down how the agent’s actions are to be monitored[2]. The agent, on the other hand, is the only one of the two parties that affects the outcome [5]. Because the outcome is also influenced by external events, the correlation between the agent’s efforts and the outcome is not perfect. Still, to increase the probability of a high payoff for the principal, the agent has to augment its effort: it must do more work, acquire more materials experiment with different solutions etc. As both parties want to maximize the benefits they receive from the contract, a conflict of goals arises between the principal, who wishes to minimize total investments, and the agent, who wishes to accomplish the task with minimum effort [4]. The burden of this conflict tends to fall on the principal, who must undertake steps to design a contract that will offer incentives for the agent to behave as desired by the principal. The costs that the principal incurs to deal with potential problems stemming from the goal conflict are generically known as ‘agency costs’ [7]. Principal-agent theory focuses on two generic types of contracts to solve the problems created by this conflict of interests : behaviour-based contracts and outcomebased contracts [3]. Behaviour-based contracts are preferable when the principal can completely prescribe and monitor the agent’s actions. To create incentives which mitigate the conflict of interests all the principal needs to do is to design a contract in which the agent is compensated for following the prescribed behaviour and penalized for deviating from it. In practice, a range of contracts correspond to this model. The most often used example is the employment contract, in which the behaviour of an employee is specified and directly monitored by his or her hierarchical superiors. The employment contract can be generalized to the relationship between two organizations such as the owner and its chosen contractor. For instance, the contracts traditionally favoured by utilities for power plant construction were essentially of this kind. The utilities hired an architect-engineer firm to perform the design, engineering and procurement and paid the firm the costs it incurred plus a fixed fee (Jason Makansi 1996, personal communication). This type of contract called ‘cost-plus-fixed-fee’, or briefly ‘cost-plus’ contract allowed a utility to manage closely the work of a contractor and specify some of its behaviour along the way. The agency costs in behaviour-based contracts are the costs the principal incurs for specifying and monitoring the agent’s behaviour. For instance, it must assign personnel to specify and control the actions of the contractor, and to monitor the accounting data on the contractor’s cost. These costs, however, are sensitive to the level of goal conflict. Thus, a reduction in goal conflict between principal and agent will reduce the costs of monitoring behaviour, because the agent will tend to behave in accordance with the interests of the principal regardless of the level of monitoring [3]. We therefore have the following hypothesis : Hypothesis I: The more goal congruence between principal and agent, the more likely it is that behaviour-based contracts will be adopted. The principal-agent theorists also stress that adequate pre -existing information gathering
196
S. Floricel and J. Lampel
systems will reduce behaviour monitoring costs[3,4]. In the case of power plant construction, information gathering is a function of principal’s competencies, since proper evaluation of agent’s behaviour depends on having sufficient knowledge of the technology and tasks. A competent principal is therefore more effective in monitoring the agent’s behaviour. For instance, it is much easier for a project owner to work towards reducing the final cost of a project, if it has the engineering capabilities needed to understand and monitor the diverse methods that the agent is supposedly using to reduce costs. This gives us the following hypothesis: Hypothesis II: The more competencies the principal has for monitoring the agent, the more likely it is that behaviour-based contracts will be used. In situations where monitoring is too costly or simply not feasible, there is an indeterminate relation between agent’s efforts and what the principal can see. A case in point is when the principal only has information about the outcome of the agent’s effort, but not about the effort itself. Given the indeterminacy of the relationship, the agent often finds that it is in its best interest to relinquish part of its efforts, or give priority to work on other contracts. Principal-agent theorists term this the ‘moral hazard’ effect [4]. At a more fundamental level, when the agent has information that is not available to the principal, the latter cannot check whether the agent used this information in a way that best serves the principal’s interests, e.g. to minimize costs [6]. The agent wishing to minimize its own resource expenditures will use this information asymmetry to its advantage by misrepresenting reality. Example of this so called "adverse selection" effect arises when the agent has a better knowledge of the relation between the agent’s efforts and the contract outcome, or the when the agent knows of cost reduction technology and methods, but will fail to share these facts with the principal. Likewise, before concluding a contract, the agent may know that the technology it proposes is immature, but deemphasizes this problem because it wishes to use the project as an opportunity to improve and test the technology (for a similar problem in oil field exploration see Wolfson [8]). Moreover, behaviour based, namely cost-plus contracts may attract precisely agents with imperfect technologies, or induce agents to use a less perfected technologies among those available to them. A solution to the above information problems are contracts in which the agent’s reward is based on outcome rather than behaviour. An example of outcome-based contract is when the principal pays the agent a fixed price upon delivery of a pre-specified product. These contracts are also called incentive contracts because, by making the agent the residual claimant for any cost savings, they spur the agent to be more efficient. By contrast, a cost-plus contract has no incentive for cost reduction because the agent does not appropriate any part of the cost savings it produces [9, p.40]. In outcome-based contracts, the principal incurs costs for specifying the desired outcome in a verifiable manner, and for verifying that the realized outcome corresponds to the specification, and eventually for proving to third party enforcers that it does not. One outcome-based example is the so-called turnkey contract, illustrated by the words of an executive from a contractor company specialized in building transportation systems: "The turnkey approach, which is becoming popular even in transportation systems, gives a lot more flexibility. For instance in another contract in which we have participated recently, [a Metro system in South East Asia], the client was very open. There was a general spec, and performance requirements to meet, but inside this – a
Innovative contractual structures for inter-organizational systems
197
lot of scope for innovation. Of course at the end you had to meet the requirements, but you had a lot of flexibility. The client was not interested in monitoring our work in detail and the interface with it was minimal."
However, outcome-based contracts shift the risks for the fulfilment of the contract on the agent. The contract outcomes are beset by many uncertainties. For instance, in large engineering projects a major uncertainty is the final cost of the project. The total cost is not solely dependent on the agent’s effort, but is also a function of unforeseen factors that are beyond the agent’s control [10]. If the final cost is higher than the lump sum paid by the principal, the agent is likely to suffer a loss. A risk averse agent may require a premium for bearing such additional risk, and this premium is a direct cost for the principal. The more risk averse an agent, the higher is the premium it will require for bearing it. This cost may outweigh the benefits the principal has from an outcome-based contract. Hypothesis III: will be used.
The more risk averse the agent, the less likely it is that outcome-based contracts
In engineering projects, one of the major sources of uncertainty is the incorporation of untested technological solutions [11]. Principals must pay agents high risk premiums in order to persuade them to bear the risk of a project based on technologies that agents perceive as untested. Because of this, fixed price contracts are rarely used in technology research and development projects [9]. Hypothesis IV: The more innovative are the technologies incorporated in the project, the more likely it is that behaviour-based contracts will be used. At first sight, outcome variability clearly suggests the use of behaviour-based contracts. However, this same outcome variability is a risk for the principal. In behaviour-based contracts, bearing this risk represents an additional cost for the principal. In general, the higher the principal’s risk aversion, the larger this cost will be [3,5]. The principal may find that paying a risk premium to the agent is preferable to bearing the risk. Hypothesis V: The more risk averse is the principal, the more likely it is that outcome-based contracts will be used. To summarize, the principal-agent theory suggests that neither outcome -based nor behaviour-based contracts are optimal in all situations. The parties will select among these alternatives the one that minimizes the total agency cost. This requires comparing cost of measuring behaviour plus the principal’s risk-bearing cost on the one hand, with the cost of measuring outcome plus the agent’s risk premium, on the other [3]. In a given situation these costs vary with the goal alignment between principal and agent, the extent of principal competencies, the risk aversion of the principal, the risk aversion of the agent and the technological uncertainties. As we have seen above, conditions related to these factors may favour one type of contract over another. The hypotheses outlined so far are concerned with designing an optimal contract between principal and agent given their motivational, knowledge and risk conditions. We test them to see to what extent the calculations and behaviour of owners and contractors in engineering projects conform to the principal-agent paradigm. There is, however, a larger issue that commands our interest: to what extent the conformity of the contracts to the prescriptions of the principal-agent theory leads to a better performance for the
198
S. Floricel and J. Lampel
principal [12]? To answer this question we must bear in mind that a project owner may not be interested exclusively in reducing the cost of the contractor’s compensation, not even in reducing solely the overall project construction costs, but also in the costs of exploitation and maintenance as well as potential liabilities over the entire life-cycle of the plant. A sound contractual arrangement is one that will enable a joint decision process to produce a project that satisfies these objectives. Provided that the success of a project is defined by the accomp lishment of these objectives, we can propose the following hypothesis: Hypothesis VI: A successful project is more likely to be based on a contract that conforms to the prescriptions of principal-agent theory.
3
Constructs and measures
Procurement in complex engineering projects has many characteristics of the principalagent situation. The owner delegates the execution of the project to specialized contractors, or to another unit inside the company because it lacks the required competencies or productive capacity. Testing the above hypotheses in the context of engineering projects in general, and in the context of power plant construction in particular, depends on finding specific measurable indicators for the concepts of the agency theory presented above.
3.1 Nature of contract Contractual structures for power plants range from projects that are completely designed and built by their owners, to projects for which the owner prepares only a concise specification of the functional requirements that must to be met, and contracts out all the remaining activities. To operationalize the nature of contract we used the dichotomous variable TURNKEY. The variable takes the value 1 if most of the work scope for the project implementation was awarded by the owner to one contractor under a fixed price contract. We consider this as the outcome-based category. It includes the contracts known in the industry as turnkey and EPC (which stands for engineering-procurementconstruction contract). The difference is that in turnkey contracts, only one entity, the turnkey contractor is liable to the owner for the entire project, although parts may be subcontracted to others. In the EPC contract, the owner may have to deal directly with subcontractors in case of problems (Jason Makansi, personal communication). The variable TURNKEY takes the value 0 in all other cases, which we equate with behaviour-based contracts. We include here the projects where the owner built the project internally. The owner, personified by the head office, has employment contracts with all participants, or hierarchical relations with a separate division which is in charge of the design and construction of the project. All the work is done practically on a cost plus basis. Also on the behaviour-based side we place the contracts in which the owner does most of the design work, breaks the work scope into several parts that are contracted out to different firms, and then manages the project internally. Although these small contracts may be fixed price, the most significant part of the project work is done on a cost plus basis. Also in this category we included the case where the owner contracts with an
Innovative contractual structures for inter-organizational systems
199
architect-engineer firm, on a cost-plus basis the design, engineering and procurement, and contracts with a separate firm for construction management.
3.2 Goal congruence between principal and agent (H I) We supposed that for a project in which the supplier of a big technology was also owner or part-owner of the project, there will be more congruence between the interests of the principal and those of the agent. This is explained by the fact that in such a situation at least a part of the work is done by a firm which is directly interested in the long-term success of the project. Such a participant will need less monitoring from the principal. This reduces the chances that moral hazard and adverse selection effects will appear in the agent’s behaviour.
3.3 Principal’s ability to monitor agent’s behaviour (H II) Research in experimental economics [13] shows that a principal’s experience as an agent leads to a better understanding of the choice problems faced by the agents. The same experiments have shown that repeated contracting experience improves the principal’s understanding of incentive mechanisms. We supposed that both kinds of experience also improve the principal’s monitoring of the agent. This pointed to two indicators of the principal’s ability to monitor the agent’s behaviour. First, if a principal has IN-HOUSE ENGINEERING CAPABILITIES it has a kind of experience that is similar to its agent’s. Therefore the principal acquires knowledge useful in monitoring the agent’s behaviour. This reduces monitoring costs and makes more likely a behaviour-based contract. We also hypothesized that the NUMBER OF PLANTS OWNED is an indicator of the owner’s contracting experience. More experience means more efficient monitoring and makes more likely a behaviour-based contract.
3.4 Agent risk aversion (H III) We hypothesized that the SIZE OF THE MAIN CONTRACTOR is inversely proportional to its risk aversion. We measure the size by the total billings of the contractor in 1994 as indicated in the surveys of ENR magazine. When the project was executed by a consortium we used the figure for the biggest participant. The cases in which the project was implemented by the owner were excluded from the analysis. We also surmised that if a SUPPLIER of a critical technology is PART OF THE TURNKEY CONSORTIUM the risk aversion of the agent will diminish, at least for the risks that are under its control [10]. This variable only makes sense if the project was a turnkey (as defined above).
3.5 Level of technology (H IV) We considered that in an industry as mature as the power industry only projects defined up-front as a new TECHNOLOGY DEMONSTRATION have a degree of uncertainty that would alert a contractor that it is facing potentially excessive burden on its resources under a fixed price contract. We considered as technology demonstration only those projects that were done under the auspices of the R&D programs of the Department of
200
S. Floricel and J. Lampel
Energy or the Electric Power Research Institute, or that were classified as such by various States for tax incentive purposes.
3.6 Principal’s risk aversion (H V) We used the size of the principal organization as the main proxy of its risk aversion. Our assumption is that the bigger the firm, the less risk averse it is likely to be. Size was used as a proxy for risk aversion in two studies of Japanese auto-maker subcontractors (Kawasaki & McMillan [14]; Asanuma & Kikutani [15] – both quoted in Milgrom & Roberts [16]). Our hypothesis is based on the reasoning that since big companies can diversify the risks across more projects, the loss on one project may be offset by gains in other projects. Also, big companies finance the projects using corporate debt and equity. The subsidiaries of big companies use debt guaranteed by the parent company. By contrast, small (especially non-utility) companies use project financing[17]. In this case debt is guaranteed only by the future flows of revenue from the project. This, and the high leverage (up to 95% debt) makes the lenders very risk averse. They have little upside gain, but a lot of downside loss. They impose their risk aversion on the owner. A manager from a small non-utility company describes this phenomenon: "We used project finance and we had to convince the bankers that the degree of innovativenness was sound. In other words, we had to balance the innovativenness with the risks as perceived by the bankers. Essentially, it was Be chtel [the owner’s engineering consultant] that negotiated with Black and Veatch [the bankers’ engineering consultant] to find an accepted level of innovativenness. We wanted a high level of innovativenness but the banks were concerned with unrealistic goals." (Michael Lucy, J. Makowsky & Co.)
We measured the OWNER SIZE using the total power generating capacity owned by the organization. If the plant has multiple owners we considered the size of the largest owner if all owners were active, or of the active partner if the plant is owned by a limited partnership. In addition to this measure of size, we also produced a MODIFIED OWNER SIZE by adding a shadow capacity of 5000MW to the capacity of the organizations which are subsidiaries of companies whose main line of business is in other areas. The logic behind this fact is that subsidiaries of companies having the bulk of their business outside power generation represent in fact bigger entities. In accordance with our hypothesis they should also be less risk averse. This was the case for subsidiaries of industrial or engineering companies, as well as for non-utility subsidiaries of utility companies. Besides using size, we assumed for owners that being a UTILITY also reduces the principal’s risk aversion. A non-utility company has to bid for a contract to sell electricity to an utility. This contract is fixed price and often contains very demanding requirements of technical and environmental performance. Since it is the result of competitive bidding, the contract leaves little financial slack to cover higher than expected costs. By contrast, a regulated utility can expect any cost considered reasonable by the regulator to be transferable to the final consumer. We also created a COMPOSITE INDEX OF RISK TOLERANCE. Risk tolerance is the reverse of risk aversion. We added 1 to an owner’s index every time one of the following conditions held:
Innovative contractual structures for inter-organizational systems
201
(a) the owner is a utility; (b) the owner is an affiliate of a bigger company; (c) the total generating capacity it owns is over 1500MW (the median value of the variable SIZE in our sample). We also hypothesized that the availability of GOVERNMENT OR INDUSTRY SPONSORSHIP reduces the risk aversion of the owner by creating a financial cushion for the project that can diminish losses. We classified a project as sponsored if it received financial assistance from the government or from an industry association. Finally we hypothesized that when the project owner is a collective entity made up of a number of organizations risk aversion is lower, because the risks are spread among several partners. We created the variable PARTNERSHIP which takes the value 1 if the project has several owners, and 0 if there is only one owner. The hypothesized relation between each of the indicators defined above (in capitals) and the variable TURNKEY is presented in the second column of Table 1. Table 1
Results of the statistical analyses
202
S. Floricel and J. Lampel
3.7 Project outcome (H VI) We hypothesized that the project’s outcome was successful if it received the POWERPLANT AWARD of the Power Magazine. The Powerplant Award was initiated in 1971 and is bestowed each year to six outstanding power plant projects in US and Canada. The decision is taken by the editors of Power, widely seen as the most prestigious magazine in the industry. An executive whose area of responsibility includes the magazine told us:
Innovative contractual structures for inter-organizational systems
203
"Our editors are all the time out in the power plants. They all have engineering degrees and experience in the power industry. They attend major events, they participate in meetings." (Robert Schwieger, McGraw-Hill).
Our 6th hypothesis becomes the following: across the projects that received the POWERPLANT AWARD, the hypothesized relationship between the above variables and the variable TURNKEY is stronger than across the projects that did not receive the award. For instance the relationship is significant for successful projects versus not significant for non-successful, or if both are significant, the significance of the award relationship is greater by an order of magnitude.
4
Methodology and analyses
To test our hypotheses, we used 60 power plant projects that went on line between 1990 and 1995 in the USA and Canada. Half of these, or 30 projects, represent all the projects that have received the Powerplant Award of Power Magazine between 1991 and 1995 inclusively. The other 30 projects are a random sample selected among power plant projects that went on line during the same period and which received a wide coverage in the industry press, but did not receive the Powerplant Award. We take this coverage to mean that the project was not a small standard project for which technological uncertainty would clearly be low. Therefore the successful and non-successful samples are comparable in terms of minimum technological complexity. Both samples are roughly balanced in terms of turnkey and non-turnkey projects (as the variable turnkey is defined above). Also, both samples include comparable proportions of greenfield and nongreenfield projects (i.e. rehabilitation, repowering etc.) Each case was coded for the variables we used in our analysis. The data for the projects were compiled from articles in the industry press, from recent industry reference publications and survey reports, from owners’ staff papers etc. The secondary data sources were supplemented in 12 cases with data from semi-structured interviews with participating managers, and in 17 cases with written answers to a questionnaire. The dichotomous variables, such as TURNKEY, were coded by the authors by triangulating data from the diverse sources available for each case. For the relationships that involved two dichotomous variables we used the crosstabulation and the Pearson chi-square statistic. For the relationship that involved continuous variables we used a One-way ANOVA and the F Probability to determine the significance. The statistical analyses were performed separately on each of the 30-project samples. Because the variable SUPPLIER PART OF THE TURNKEY CONSORTIUM has no sense if there was no turnkey contract, we only compared the proportion among the turnkey consortia which included a supplier, in the successful and non-successful projects. Table 1 presents the results of the analyses.
5
Discussion
The relationships that tested the principal-agent theory for engineering projects all have the predicted sign with the exception of the relationship between the variable
204
S. Floricel and J. Lampel
PARTNERSHIP, which captures whether there was a single owner or multiple owners and the variable TURNKEY, in which a relation that had an opposite sign resulted. However, in both half-samples, this relationship was not significant. With the exception of the variables UTILITY and GOVERNMENT SPONSORSHIP for all other variables (nine in all) the relationship was stronger in the predicted sense for successful projects than for non successful projects. Of these, the relationships were exactly as predicted (i.e. with a net difference in significance in favour of the successful projects) for the variables OWNER ENGINEERING CAPABILITIES, NUMBER OF PLANTS OWNED, OWNER SIZE, MODIFIED OWNER SIZE, COMPOSITE INDEX OF RISK TOLERANCE. For the remaining variables, the relationships were not significant for both successful and nonsuccessful projects. The results for the SUPPLIER PART OF TURNKEY CONSORTIUM variable also support our hypothesis that successful projects are more in line with the predictions of the principal-agent theory. The less conclusive results in the case of the CONTRACTOR SIZE may be explained by the fact that in the currently depressed power industry, the client is in fact dominant. Contractors that compete for work are often forced to accept the type of contract that is offered. If this is true, for this type of industries, the predictions of the agency theory with respect to the agent’s risk characteristics are better tested across several industries by taking into consideration the average type of contractor in each industry. However an alternative explanation is that the number of cases was reduced by the exclusion of projects in which the owner implemented itself the project. The weak relation between TECHNOLOGY DEMONSTRATION and TURNKEY may be explained by the reduced number of demonstration projects in both samples: six for award projects and two for nonaward projects, which reduces the reliability of the statistical results. The reverse sign obtained for the relation between multiple ownership and turnkey may be due to the fact that only one partnership was between utility companies, all others were between non-utility companies. In other words, it is possible that companies form a partnership because they are already very risk-averse (e.g. because of their size or of their non-utility status), and not that they are less risk-averse because they are in partnership. Another explanation is that, prior to 1986, when some of the projects were conceived, many partnerships were formed for tax purposes rather than risk-mitigation. The relation between utility and turnkey was significant for less-successful projects and not significant for successful projects. We cannot offer any explanation at this point, except the conjecture that more successful companies may be those that break the frames of their categories. All the variables for which we obtained clear confirmations of our hypotheses, including the engineering capabilities variable, are correlated with the owner’s size. For instance the relation between engineering capabilities and size becomes evident if we consider that only big companies have the ability to maintain in-house engineering capabilities for plant design. This raises the question whether there are two distinct types of owner in the industry, big and small. The big ones are both less risk averse and have monitoring capabilities. These capabilities allow them to manage behaviour-based contracts. In other words, they can either design and build the projects internally or design internally, contract out smaller non-turnkey packages and manage the contractors closely. In fact this route may be the only one that leads them to success. For instance, utilities can undertake technology demonstration projects aimed at solving specific problems faced by their systems like the excessive reliance on polluting coal-fired power plants. On the other hand there are the small owners who are risk averse and lack
Innovative contractual structures for inter-organizational systems
205
engineering capabilities. These conditions force them to use turnkey contracts and stay away from demonstration projects, although is may not preclude them from realizing moderately innovative and successful projects as proven by the awards such companies received. The strongest confirmation of the principal-agent hypotheses were obtained for the negative relation linking the owner’s engineering capabilities and turnkey contracts. This may suggest that several mechanisms were acting in the same direction. For instance, why a company that has internal engineering capabilities would award an engineering contract to an outside firm? Except for contracts requiring specific competencies, for instance in solving the largely chemical engineering hurdles facing power plant construction today, it will be difficult to justify such a decision. In general, inside the owner company there are usually strong political influences favouring the preservation of the internal engineering department. In other words there may be strong inertial forces [19] inside the organization that may block or delay a switch, motivated by efficiency considerations, to the use of outside contractors. Sometimes, the same forces will act by transforming attempts to change into failures, through a sort of self-fulfilling prophecy mechanism. For example, firms with engineering capabilities will attempt turnkey projects but the engineering department will interfere too much with the contractor’s work. These ‘hybrids’ will either lead to truly low performing projects or, in case of relatively successful projects, the engineers will use every occasion they have to accentuate the eventual inconsistencies of the artifact with the existing practices and norms of the organization.
6
Conclusion
The distinction between outcome-based and behaviour-based contracts owes much to principal-agent theory economic antecedents. Empirically, however, it is clear that the relationships between owners and contractors can take a variety of forms. The variety of intermediate forms that we observe in the construction of large engineering projects owes much to the influence of different technological and environmental factors, not to mention the different perceptions that the actors themselves have of the problems. In this paper we have followed a contingency approach to the question of contract design. In other words, we attempted to see how owner, agent, and project variables predict the type of contract that is used. A contingency approach has two virtues. First, it allows us to test general predictions derived from principal-agency theory. The results of this paper show that, on average, respecting these theoretical predictions leads to a better performance. This must sensitize the managers in project owner organizations to the virtues of carefully considering the circumstances surrounding the project when deciding what type of contract to adopt. Second, a contingency approach is the most effective way of laying the groundwork for a typology of contractual types. A more nuanced typology of contractual types allows us to identify additional contingency variables, and after additional research and reflection, to see if these contingency variables are systemically related. The contingency approach holds promise when it comes to analysis of the economic and institutional systems in which large projects are negotiated and built. It is, however, limited by virtue of its static nature. There is an implicit assumption that a set of initial conditions match given outcomes. This static perspective is in accord with one interpretation of agency theory, but is by no means the only one. Agency theory also
206
S. Floricel and J. Lampel
points to the relationship between principal and agent as a dynamic phenomenon which has its temporal dimensions. At the most general level, the evolution of this relationship is linear: principal and agent must first find each other, engage in a bargaining process which leads to agreement, and the agreement is implemented in the project. In practice, what we often see is an iterative process in which principals explore certain agents with particular agreements in mind, and then switch to other agents when it appears that agreements or the capabilities of the agents are insufficient. This moving back and forth across the spectrum of contractual possibilities is sensitive to a variety of influences and events that are often unique and specific to a particular time and place. A contingency approach will not capture the evolutionary aspects of principal-agent relationship. These aspects can only be captured by adopting different methodologies, and by enlarging the conceptual framework to include a wider variety of mechanisms which govern the interaction between principals and agents. Some of these mechanisms are ‘objective’ in the sense that they are clearly grounded in economic and technical factors. Others, however, are more ‘subjective’. They are defined and regulated by beliefs and attitudes that shape interpretation of risk, evaluation of competencies, climate of cooperation, and judgements of performance. Understanding these factors, especially within an evolutionary context, is what managers ultimately need for practical application of the agency perspective. At this point, this goal appears distant. Much more work is clearly needed.
Acknowledgement The authors wish to thank Jason Makansi, Editor in Chief of Power magazine for his helpful clarifications regarding the types of contracts used in the US power plant construction industry.
References 1
Lampel, J., Miller, R., and Floricel, S. (1996). ‘Information asymmetries and technological innovation in large engineering construction projects’. R&D Management, 26: pp.357–69.
2
Baiman, S. (1982). ‘Agency research in managerial accounting’. Journal of Accounting Literature, 1: pp.154–213.
3
Eisenhardt, K.M. (1989) ‘Agency theory: An assessment and review’. Academy of Management Review, 14: pp.57–74.
4
Holmstrom, B. (1979). ‘Moral hazard and observability’. Bell Journal of Economics, 10: pp.74–91.
5
Shavell, S. (1979). ‘Risk sharing and incentives in the principal and agent relationship’. The Bell Journal of Economics, 10: pp.55–73.
6
Arrow, K.J. (1985). ‘The economics of agency’. In J. W. Pratt and R. J. Zekhauser (Eds.), Principals and Agents: The Structure of Business: pp.37–54. Boston: Harvard Business School Press.
7
Jensen, M. and Meckling, W. (1976). ‘Theory of the firm: Managerial behaviour, agency costs, and ownership structure’. Journal of Financial Economics, 11: pp.5–50.
Innovative contractual structures for inter-organizational systems
207
8
Wolfson, M.A. (1985). ‘Empirical evidence of incentive problems and their mitigation in oil and gas shelter programs’. In J.W. Pratt, and R. J. Zekhauser (Eds.), Principals and Agents: The Structure of Business: pp.101–126. Boston: Harvard Business School Press.
9
Laffont, J.-J. and Tirole, J. (1993). A Theory of Incentives in Procurement and Regulation. Cambridge, Mass.: The MIT Press.
10
Chapman, C.B. and Ward, S.C. (1994). ‘The efficient allocation of risk in contracts’. Omega, International Journal of Management Science, 22: pp.537–552.
11
Merrow, E.W. (1988). Understanding the Outcomes of Megaprojects. Santa Monica, Ca.: Rand.
12
Roth, K. and O’Donnel, S. (1996). ‘Foreign subsidiary compensation strategy: An agency theory perspective’. Academy of Management Journal, 39: pp.678–703.
13
Berg, J.E., Daley L.A., Dickhaut, J.W., and O’Brien, J. (1992). ‘Moral hazard and risk sharing experimental evidence’. Research in Experimental Economics, 5: pp.1–34.
14
Kawasaki, S. and McMillan, J. (1987). ‘The design of contracts: Evidence from Japanese subcontracting’. Journal of Japanese and International Economies, 1: pp.1327– 49.
15
Asanuma, B. and Kikutani, T. (1991). ‘Risk absorption in Japanese subcontracting: A microeconometric study on the automobile industry’. Journal of Japanese and International Economies.
16
Milgrom, P. a nd Roberts J. (1992). Economics, Organization and Management. Englewood Cliffs, N.J.: Prentice Hall.
17
Beidleman, C.R., Fletcher, D. and Veshosky, D. (1990). ‘On allocating risk: The essence of project finance’. Sloan Management Review, Spring: pp.47–55.
18
Hannan, M.T. and Freeman, J. (1984). ‘Structural inertia and organizational change’. American Sociological Review, 49: pp.149–164.