Appropriate Financial Instruments for Public-Private Partnership to Boost Cross-Border Infrastructural Development-EU Experience

The member states of the European Union (EU) and the EU institutions have increasingly been using public-private partnerships (PPPs) to accelerate the development of (ambitious) trans-national infrastructure. This paper argues that in the EU (i) private sector partners remain risk-averse; and (ii) risk-pooling across a larger number of tax-payers tends to reduce the cost of risk to zero, making EU funds highly desirable and sought after for public infrastructure development. This paper argues that private equity has not been forthcoming to the extent that had been expected by those propagating this method of finance. In those instances where private non-publicly guaranteed resources have been used, the distribution of risks between public and private partners remained asymmetric, with public governmental bodies carrying the financial risks, which ultimately may become a contingent liability for the country’s public finances. However, EU and European Investment Bank (EIB) public funding is used not simply because the risks are spread more widely, but rather because EU rules and regulations for using such funds lead to better preparation of projects and greater efficiency gains in project implementation and delivery.public-private partnerships; trans-national infrastructure; european union institutions; european union; public infrastructure development

Integrating Consumer Flexibility in Smart Grid and Mobility Systems - An Online Optimization and Online Mechanism Design Approach

Consumer flexibility may provide an important lever to align supply and demand in service systems. However, harnessing dispersed flexibility endowments in the presence of self-interested agents requires appropriate incentive structures. This thesis quantifies the potential value of consumers\u27 flexibility in smart grid and mobility systems. In order to include incentives, online optimization approaches are augmented with methods from online mechanism design

A Mechanism Design Approach to Bandwidth Allocation in Tactical Data Networks

The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems\u27. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today\u27s software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest to the defense community. In this thesis, we consider a scenario where a number of military platforms have been tasked with the goal of detecting and tracking targets. The sensors onboard a military platform have a partial and inaccurate view of the operating picture and need to make use of data transmitted from neighboring sensors in order to improve the accuracy of their own measurements. The communication takes place over tactical data networks with scarce bandwidth. The problem is compounded by the possibility that the local goals of military platforms might not be aligned with the global system goal. Such a scenario might occur in multi-flag, multi-platform military exercises, where the military commanders of each platform are more concerned with the well-being of their own platform over others. Therefore there is a need to design a mechanism that efficiently allocates the flow of data within the network to ensure that the resulting global performance maximizes the information gain of the entire system, despite the self-interested actions of the individual actors. We propose a two-stage mechanism based on modified strictly-proper scoring rules, with unknown costs, whereby multiple sensor platforms can provide estimates of limited precisions and the center does not have to rely on knowledge of the actual outcome when calculating payments. In particular, our work emphasizes the importance of applying robust optimization techniques to deal with the uncertainty in the operating environment. We apply our robust optimization - based scoring rules algorithm to an agent-based model framework of the combat tactical data network, and analyze the results obtained. Through the work we hope to demonstrate how mechanism design, perched at the intersection of game theory and microeconomics, is aptly suited to address one set of challenges of the ULS system paradigm - challenges not amenable to traditional system engineering approaches

An Investigation of Buyers’ Forecast Sharing and Ordering Behavior in a Two-Stage Supply Chain

Profitably balancing demand and supply is a continuous challenge for companies under changing market conditions, and the potential benefit of collaboration between supply chain partners cannot be overlooked by any firm who strives to succeed. One of the key elements to successful collaboration is sharing of forecast information between supply chain partners. However, when supply shortage is expected, buyers may inflate order quantities and/or order forecasts to secure sufficient supply. An important question that arises is how the supplier should allocate inventory to customers when shortage exists. Literature shows that certain allocation policies can reduce buyers’ order inflation behavior. However, this has not yet been empirically shown for order forecast inflation behavior, nor incorporating the behavioral aspects of decision makers. In this dissertation, through behavioral experiments using a supply chain simulation game, we investigate the impact of different capacity allocation mechanisms and information disclosures of a supplier on buyers’ forecast sharing and ordering behavior. We first investigate the buyers’ order forecast sharing behavior in a single-suppliertwo- buyer supply chain. Our behavioral study shows that forecast-accuracy based allocation, where the supplier allocates more capacity to the buyer with better forecast accuracy, can significantly improve order forecast accuracy relative to uniform allocation, where the supplier equally allocates capacity to the buyers. Under both policies, particularly uniform allocation, the order forecast accuracy is improved with the supplier’s information disclosure on the policy. Next, we focus on buyers’ ordering behavior, and formulate a single-supplier-single-buyer base-stock inventory model under constrained supply. We validate our analytical results through numerical simulation, which is then extended to the single-supplier-two-buyer case. We next compare the buyers’ optimal decisions from the simulation with the actual decisions in our behavioral study, and find that buyers in the experiment show a significantly lower profit performance ranging from 0.8% to 14.1%. Using structural estimation modeling techniques, we estimate the buyers’ perceived overage/underage cost ratios from the experiment, and conclude by conducting a detailed analysis on the factors that affect buyers’ ordering decisions. In addition to academic contributions, our results provide insights for practitioners to understand buyers’ strategic behavior and help with designing capacity allocation strategies

Information Sharing in a Long-Term Supply Chain Relationship: The Role of Customer Review Strategy

In this paper, we study the practice of forecast sharing and supply chain coordination with a game-theoretical model. We find that in a one-shot version of the game, forecasts are not shared truthfully by the customer. The supplier will rationally discount the forecast information in her capacity allocation. This results in Pareto suboptimality for both supply chain parties. However, we show that a more efficient, truth-sharing outcome can emerge as an equilibrium from a long-term relationship. In this equilibrium, forecast information is transmitted truthfully and trusted by the supplier, who in turn allocates the system-optimal capacity. This leaves both the customer and the supplier better-off, compared to the nontruthful-sharing equilibrium. We identify a multiperiod review strategy profile that supports the truthful-sharing equilibrium. The key element of this strategy is that the supplier computes a scoring index of the customer\u27s behavior that is updated over time and used to evaluate if the customer has sufficient incentive to share his private information truthfully in each transaction of the repeated game. Compared to trigger strategies, review strategies are more tolerant but require diligence and more monitoring effort

Report on visit to four North American airlines

The object of the visits was to discuss the current state-of-the-art with the Engineering Departments of several North American airlines which were known to be leading the field in the application of certain advanced techniques. In the limited time available it was decided to confine the talks mainly to those topics on which the chosen operators were known to have had unique experience. This note is presented in chronological sequence and is only intended to be a record of the information gathered; no derivations, or comparisons with other operators, are made. United Air Lines were visited first and reliability programmes are detailed, although the application of critical path techniques to aircraft and engine overhaul is summarised. Continental Air Lines are noted for their use of the continuous maintenance philosophy, and this is reported next. The third visit was to Air Canada where talks ranged from the applications of operations research and electronic data processing (EDP) techniques to aircraft evaluation procedures. Finally the PanAm aircraft system reliability programme is reviewed, together with a note on their general LDP engineering and maintenance activities. A bibliography is given, although it should be appreciated that some of the items listed contain information which may be commercially secure