Often, design problems are strongly coupled and their concurrent resolution by interacting (though decentralized) stakeholders is required. The ensuing interactions are characterized predominantly by degree of interdependence and level of cooperation. Since tradeoffs, made within and among sub-systems, inherently contribute to system level performance, bridging the associated gaps is crucial. With this in mind, effective collaboration, centered on continued communication, concise coordination, and non-biased achievement of system level objectives, is becoming increasingly important. Thus far, research in distributed and decentralized decision-making has focused primarily on conflict resolution. Game theoretic protocols and negotiation tactics have been used extensively as a means of making the required tradeoffs, often in a manner that emphasizes the maximization of stakeholder payoff over system level performance. More importantly, virtually all of the currently instantiated mechanisms are based upon the a priori assumption of the existence of solutions that are acceptable to all interacting parties. No explicit consideration has been given thus far to ensuring the convergence of stakeholder design activities leading up to the coupled decision and the associated determination of values for uncoupled and coupled design parameters. Consequently, unnecessary and costly iteration is almost certain to result from mismatched and potentially irreconcilable objectives. In this dissertation, an alternative coordination mechanism, centered on sharing key pieces of information throughout the process of determining a solution to a coupled system is presented. Specifically, the focus is on (1) establishing and assessing collaborative design spaces, (2) identifying and exploring regions of acceptable performance, and (3) preserving stakeholder dominion over design sub-system resolution throughout the duration of a given design process. The fundamental goal is to establish a consistent framework for agile collaboration that more accurately represents the mechanics underlying product development and supports interacting stakeholders in achieving their respective objectives in light of system level priorities. This aim is accomplished via improved resource management and design space exploration, augmented awareness of system level implications emanating from sub-system decisions, and increased modularity of decentralized design processes. Stakeholder synergy in design processes is enhanced via stakeholder focalization, based on the systematic communication of decision-critical information content.

Game theory and mechanism design have emerged as an important tool to model, analyze,and solve decentralized design problems involving multiple agents that interact strategically in a rational and intelligent way. Some examples of these design problems include: auctions and markets in electronic commerce; network economics; dynamic pricing; routing protocols in wireless networks; resource allocation in computational grids; algorithms for selfish agents;etc. The motivation for this doctoral work springs from the high level of current interest indesigning innovative mechanisms for solving emerging game theoretic problems in the area of electronic commerce. In this thesis, we focus on three such problems and advance the current art in mechanism design while developing new, innovative mechanisms to solve the problems. The first problem we explore is the highly strategic problem of forming a high value E-business supply chain by choosing the best mix of supply chain partners. In our research, we formulate the supply chain formation problem as a mechanism design problem in a generic wayand show that the well known VCG (Vickrey-Clarke-Groves) mechanisms provide an apt frame-work for solving this problem. We provide a compelling example of a three stage automotive distribution network to illustrate the power and e±cacy of the proposed methodology. The second problem we model and solve is that of designing a revenue maximizing sponsored search auction. This is a problem that is faced by every Internet search engine, such as Google,MSN, and Yahoo!, whenever it receives a search query. In our research, we take a comprehensivelook at existing auction mechanisms for this problem. Our work leads to an innovative new auction mechanism, which we call OPT (optimal mechanism), that exhibits a superior level ofperformance. The proposed mechanism extends, in a non-trivial way, the well known Myersonoptimal auction to the specific setting of sponsored search auctions. The proposed mechanism maximizes the revenue to the search engine and also satisfies two crucial properties, Bayesian incentive compatibility and interim individual rationality. The third contribution is in respect of Stackelberg problems, which are game theoretic problems that involve hierarchical and sequential decision making. By focusing attention on an important subclass of these problems, namely the Single-Leader-Rest-Followers (SLRF) problems, we extend all relevant aspects of classical mechanism design theory to the case of SLRF problems. We derive many important results in respect of procurement auctions with reserve prices using the developed theory. The research carried out as part of this doctoral work, we believe, advances the current art in mechanism design while developing innovative mechanisms to solve those problems.