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The paper aims to describe the evolution and use of project alliancing in Finland: how the model was discovered, and then, little by little, became an established practice.

The paper is based on a long-term observation of the construction sector activities, involvement in their development and a review of related research and practice documents.

The paper illustrates how a major change may be laborious. It also reveals that the application of project alliancing seems to have been successful so far, but there are still threats on the horizon.

The overview ignores many meaningful details and does not include a critical review of the positive experiences reported by the industry. There certainly is need for related research.

The study offers a point of reference for evaluation of the smoothness of the progress of industry wide changes.

This paper seems to be the first one providing a more comprehensive picture of the progress and use of alliancing in Finland, thus supplementing existing view- and project-specific examinations.

Allocating risk in public–private partnership (PPP) projects based on public–private parties’ risk management (RM) capabilities is a condition for success of these projects. In practice, however, risks are allocated to these parties beyond their respective RM capabilities. Too much risk is often assigned to the private or public party, resulting in poor RM and costly contract renegotiations and terminations. This chapter proposes a methodology based on fuzzy set theory (FST) in which decision makers (DMs) use linguistic variables to assess and calculate RM capability values of public–private parties for risk events and to arrive at risk allocation (RA) decisions. The proposed methodology is based on integrating RA decision criteria, the Delphi method and the fuzzy synthetic evaluation (FSE) technique. The application of FSE allows for the introduction of linguistic variables that express DMs’ evaluations of RM capabilities. This provides a means to deal with the problems of qualitative, multi-criteria analysis, subjectivity and uncertainty that characterise decision-making in the construction domain. The methodology is outlined and demonstrated based on empirical data collected through a three-round Delphi survey. The public–private parties’ RM capability values for land acquisition risk are calculated using the proposed methodology. The methodology is helpful for performing fuzzy-based analysis in PPP projects, even in the event of limited or no data. This chapter makes the contribution of presenting a RA decision-making methodology that is easy to understand and use in PPP contracting and that enables DMs to track calculations of RM capability values.

In this chapter, we examine the impact of pay-for-performance incentives on learning-by-doing. We exploit personnel data on fruit pickers paid under two distinct compensation contracts: a standard piece rate plan and one with an extra one-time bonus tied to output. Under the latter, we observe bunching of performance just above the bonus threshold, suggesting workers distort their behavior in response to the discrete bonus. Such bunching behavior increases as workers gain experience. At the same time, the bonus contract induces considerable learning-by-doing for workers throughout the productivity distribution who presumably hope to one day hit the target, and these improvements significantly outweigh the losses to the firm from the bunching. In contrast, under the standard piece rate contract, we find minimal evidence of bunching and only small performance improvements at the bottom of the productivity distribution. Our results suggest that contract design can help foster learning on the job, underscoring the importance of dynamic considerations in principle-agent models.

The relationship between airports and airlines is very interesting from an economics perspective, and analysis of this relationship is wide open for new research endeavors. For instance, airport and airline interactions can be viewed as a zero-sum game of deciding, say, airport landing charges, while at the same time both entities have an incentive making a joint effort to enhance their ability to generate passenger demand and to contribute to growing regional economies. Within this theoretical framework, their relationship consists of not only a binary choice of conflict or cooperation, but also suggests the possibility of complex mixtures of conflict and cooperation. While understanding the interdependence of airports and airlines is an important issue in transportation economics, research examining the complexity of airport and airline relationships is relatively new to the field. This chapter contributes to this research area, in part, by introducing one very interesting example of an airport and airline relationship that considers an element of conflict and cooperation. Specifically, this chapter examines the economic consequences of a risk sharing contract. Analysis of the risk sharing contract recognizes the relevance of microeconomic theories, such as contract theory and principal–agent theory and reveals how these concepts can be applied to traditional transport economics. Predictions of risk sharing between airlines and airports using these theories are derived using numerical examples. Findings reveal that the risk-sharing agreement based on the Noto Airport Load Factor Guarantee Mechanism (LFGM) contract enables the airport side and the airline side not only to share the monetary consequences of demand fluctuation, but also to secure air flights from a local airport to Tokyo, to jointly enhance their various demand-inducing efforts, and to increase their utilities in order to meet the common target they set in the contract. With the LFGM contract, both sides have consistently maintained the air transport network in a relatively low demand area for more than 10 years without significant outside financial assistance. The findings from this chapter also contribute to better understanding the complex relationships among aviation entities, to the recognition of importance and potential to design properly the airport and airline contract, and to the advancement of economic and public policy analysis of this sector.

The relationship between airline and airport is complex, fascinating, and wide open for new research endeavors. In Volume 6 of the series, we conducted the analyses of risk-sharing contract between airline and airport from numerical risk balance assessment and incomplete contract theory perspectives based on an interesting real example of risk-sharing contracts, the Noto Airport Load Factor Guarantee Mechanism (LFGM) contract in Japan.

In this chapter, we further advance the analyses of risk-sharing contracts, based on the real example of Noto LFGM contract, from the perspectives of game theory and principal-agent theory. The risk-sharing arrangements, such as LFGM contract, are relevant to the rapidly changing business environment in Asia’s aviation industries.

We conduct a two-stage game analysis. The first phase is the contract negotiation phase and the second phase is the effort-making phase after signing the contract. We show that the two parties can attain a Pareto optimal utility level by bargaining a simple linear risk-sharing contract in the contract negotiation phase based on the equilibrium effort levels in the effort-making phase.

Policymakers worldwide have proposed a new contract – the ‘social impact bond’ (SIB) – which they claim can allay the underperformance afflicting not-for-profits, by tying the private returns of (social) investors to the success of social programs. We investigate experimentally how SIBs perform in a first-best world, where investors are rational and able to obtain hard information on not-for-profits’ performance. Using a principal-agent multitasking framework, we compare SIBs to inputs-based contracts (IBs) and performance-based contracts (PBs). IBs are based on a piece-rate mechanism, PBs on a non-binding bonus mechanism, and SIBs on a mechanism that, due to the presence of an investor, offers full enforceability. Although SIBs can perfectly enforce good behaviour, they also require the principal (i.e., government) to relinquish control over the agent’s (i.e., not-for-profit’s) payoff to a self-regarding investor, which prevents the principal and agent from being reciprocal. In spite of these drawbacks, in our experiment SIBs outperformed IBs and PBs. We therefore conclude that, at least in our laboratory test-bed, SIBs can allay the underperformance of not-for-profits.

In M&A markets, acquirers face a hold-up problem of losing the value of investments they make in due diligence, negotiations, and post-acquisition planning if targets would pursue the options of waiting for better offers or selling to an alternative bidder. This chapter extends information economics to the literature on M&A contracting by arguing that such contracting problems are more likely to occur for targets with better outside options created by the information available on their resources and prospects. We also argue that acquirers address these contracting problems by using termination payment provisions to safeguard their investments. While previous research in corporate strategy and finance has suggested that certain factors can facilitate an acquisition by reducing a focal acquirer’s risk of adverse selection (e.g., signals, certifications), we note that these same factors can make the target attractive to other potential bidders and can exacerbate the risk of hold-up, thereby leading acquirers to use termination payment provisions as contractual safeguards.