Natural selection favours those individuals that respond best to novel features of their selective environment. For many, a critical challenge is responding to evolutionary change in mutualistic species. These responses create complex feedbacks, so only coevolutionary approaches are able to fully answer key questions about the maintenance or disruption of mutualistic behaviour, and explain the range of mechanisms that allow individuals to benefit from these associations. I first consider the hypothesis that economic models studying multiple classes of traders, where each trader seeks to optimise its own payoffs will yield insights into mutualistic systems. I show that individuals can be favoured to discriminate amongst potential partners based on the price for which they provide resources. Then, I show that market mechanisms can maintain cooperation and drive specialisation in mutualistic systems. I extend this market model to allow individuals to restrict a mutualistic partner's access to resources, and show that this strategy can stabilise cooperation and increase the fitness of both partners. I also explicitly incorporate relatedness in my market model. I show that high relatedness sometimes increases cooperativeness in members of a mutualistic species, but sometimes decreases cooperativeness as it narrow the scope for partner choice to maintain cooperation. Having studied market mechanisms, I consider indiscriminate costly help to members of another species. I discover that this trait can be favoured by natural selection and can be classified as either altruism between or altruism within species. Finally, I consider a framework for analysing coevolved phenotypic responses to a partner's cooperativeness, a challenging process to model. I demonstrate that this framework can yield firm predictions about behaviour whenever partners hold private information about their costs and benefits.

Four essays, or chapters, model the capital structure, governance, and investment decisions as part of a sequential game. Each chapter is separate in its context, assumptions, and conclusions. The titles of the chapters are below. Abstracts of each essay or chapter can be found at the beginning of each chapter. The titles of the chapters or essays are as follows: I. Managerial Ownership with Rent-Seeking Employees, II. Financing Professional Partnerships, III. Sunk Cost Efficiency with Identical Competitors, and IV. Business Stealing and Bankruptcy. With the exception of Chapter III, which is meant to complement Chapter IV, these essays argue that the structure of financial contracts can affect the real behavior of firms. The first chapter argues that financial governance policies affect the behavior of rank-and-file employees. In Chapter II, the governance and capital structure of professional service firms affects clients’ expectations of the firm’s quality. In Chapter IV, the enforcement of financial contracts by bankruptcy courts affects the number of firms that enter and exit the industry.

In this work we present a general duality-theory framework for revenue maximization in additive Bayesian auctions involving multiple items and many bidders whose values for the goods follow arbitrary continuous joint distributions over some multi-dimensional real interval. Although the single-item case has been resolved in a very elegant way by the seminal work of Myerson [1981], optimal solutions involving more items still remain elusive. The framework extends linear programming duality and complementarity to constraints with partial derivatives. The dual system reveals the natural geometric nature of the problem and highlights its connection with the theory of bipartite graph matchings. We demonstrate the power of the framework by applying it to various special monopoly settings where a seller of multiple heterogeneous goods faces a buyer with independent item values drawn from various distributions of interest, to design both exact and approximately optimal selling mechanisms. Previous optimal solutions were only known for up to two and three goods, and a very limited range of distributional priors. The duality framework is used not only for proving optimality, but perhaps more importantly, for deriving the optimal mechanisms themselves. Some of our main results include: the proposal of a simple deterministic mechanism, which we call Straight-Jacket Auction (SJA) and is defined in a greedy, recursive way through natural geometric constraints, for many uniformly distributed goods, where exact optimality is proven for up to six items and general optimality is conjectured; a scheme of sufficient conditions for exact optimality for two-good settings and general independent distributions; a technique for upper-bounding the optimal revenue for arbitrarily many goods, with an application to uniform and exponential priors; and the proof that offering deterministically all items in a single full bundle is the optimal way of selling multiple exponentially i.i.d. items.

This thesis is concerned with mathematical modelling and optimal control of constrained systems. Each of the systems under consideration is a system that can be controlled by one of the variables, and this control is subject to constraints. First, we consider middle-distance running where a runner's horizontal propulsive force is the control which is constrained to be within a given range. Middle-distance running is typically a strategy-intensive race as slipstreaming effects come into play since speeds are still relatively fast and runners can leave their starting lane. We formulate a two-runner coupled model and determine optimal strategies using optimal control theory. Second, we consider two applications of control systems with delay related to R&D expenditure. The first of these applications relates to the defence industry. The second relates to the pharmaceutical industry. Both applications are characterised by a long delay between initial investment in R&D and seeing the benefits of R&D realised. We formulate models tailored to each application and use optimal control theory to determine the optimal proportion of available funds to invest in R&D over a given time horizon. Third, we consider a mathematical model of urban burglary based on the Short model. We make some modifications to this model including the addition of deterrence due to police officer presence. Police officer density is the control variable, which is constrained due to a finite number of police officers. We look at different control strategies for the police and their effect on burglary hot-spot formation.

Online reputation systems are certainly the most overlooked 'heroes' of today's social Web. While these mechanisms are a vital element of every online transaction, they have received less consideration than some of their more well-known cousins, such as recommender systems or social networks, whose success would often not have been possible and tenable without their discrete but active backing. It then follows that despite their value and importance, the implementation of current reputation mechanisms has mostly been the result of trial-and-error. Resting on an economic perspective, this thesis regroups three chapters whose frameworks and findings aim at helping mechanism designers and researchers understand key mechanisms at play and develop more efficient online reputation systems. The first chapter examines the optimal number of ratings a reputation mechanism must make publicly available within an online marketplace in order to minimize cheating and maximize Pareto efficiency. I develop a moral hazard stage game featuring fictitious players which has the compelling property to prevent reputation effects from disappearing in the long run. I show that the number of ratings displayed by a reputation system is a fundamental predictor of market efficiency, and that the latter number should be kept minimal in order to maximize social welfare in the market – especially for economies proposing interactions with a high profit margin. The second chapter studies how different classes of reporting behaviours commonly found online affect the reliability of a reputation mechanism. I develop an iterative stochastic approximation model which I use to construct a behavioural measure of efficiency, so-called 'reporting bias'. I demonstrate that reporting bias tends towards its maximum when raters comply with the reports left by their predecessors. Following this result, I recommend to keep the rating interface separated from the rest of the reputation system. I also find that fake ratings are particularly harmful when one type of behaviour is present in the economy and suggest to counterbalance sybil attacks by displaying pairs of contrasted ratings. Finally, I defend the use of the arithmetic mean against the median as a way to compute reputation scores. The third chapter analyses how 5-star rating scales can lead to the formation of bimodal distributions of ratings within online marketplaces. Using a 2-time period model featuring altruistic raters, I identify the existence of a 'blind spot' of unrated transactions whose magnitude increases in the cost of rating and decreases in the number of buyers inhabiting the economy. Developing an additional model featuring Bayesian agents suffering from confirmatory bias, I show that non-binary rating scales can leave space to ambiguity and possibly wrong posteriors, even in the long run. Overall, results of the chapter hint that fine-grained rating scales best suit signalling reputation systems while coarse-grained scales should be preferred for sanctioning mechanisms.

In this thesis we study decentralized dynamics for non-cooperative and cooperative games. The dynamics are behaviorally motivated and assume that very little information is available about other players' preferences, actions, or payoffs. For example, this is the case in markets where exchanges are frequent and the sheer size of the market hinders participants from learning about others' preferences. We consider learning dynamics that are based on trial-and-error and aspiration-based heuristics. Players occasionally try to increase their performance given their current payoffs. If successful they stick to the new action, otherwise they revert to their old action. We also study a dynamic model of social influence based on findings in sociology and psychology that people have a propensity to conform to others' behavior irrespective of the payoff consequences. We analyze the dynamics with a particular focus on two questions: How long does it take to reach equilibrium and what are the stability and welfare properties of the equilibria that the process selects? These questions are at the core of understanding which equilibrium concepts are robust in environments where players have little information about the game and the high rationality assumptions of standard game theory are not very realistic. Methodologically, this thesis builds on game theoretic techniques and prominent solution concepts such as the Nash equilibrium for non-cooperative games and the core for cooperative games, as well as refinement concepts like stochastic stability. The proofs rely on mathematical techniques from random walk theory and integer programming.

This thesis presents a new integrated tool and decision support framework to approach complex problems resulting from the interaction of many multi-criteria issues. The framework is embedded in an integrated tool called OUTDO (Oxford University Tool for Decision Organisation). OUTDO integrates Multi-Criteria Decision Analysis (MCDA), decision rationale management with a modified Issue-Based Information Systems (IBIS) representation, and probabilistic forecasting to effectively capture the essential reasons why decisions are made and to dynamically re-use the rationale. In doing so, it allows exploration of how changes in external parameters affect complicated and uncertain decision making processes in the present and in the future. Once the decision maker constructs his or her own decision process, OUTDO checks if the decision process is consistent and coherent and looks for possible ways to improve it using three new semantic-based decision support approaches. For this reason, two ontologies (the Decision Ontology and the Energy Ontology) were integrated into OUTDO to provide it with these semantic capabilities. The Decision Ontology keeps a record of the decision rationale extracted from OUTDO and the Energy Ontology describes the energy generation domain, focusing on the water requirement in thermoelectric power plants. A case study, with the objective of recommending electricity generation and steam condensation technologies for ten different regions in the UK, is used to verify OUTDO’s features and reach conclusions about the overall work.

Social theorists have long argued that literacy is one of the principal causes and hallmark features of complex society. However, the relationship between literacy and social complexity remains poorly understood because the relevant data have not been assembled in a way that would allow competing hypotheses to be adjudicated. The project set out in this thesis provides a novel account of the multiple origins of literate behaviour around the globe, the principal mechanisms of its cultural transmission, and its relationship with the cultural evolution of large-group human cooperation and complex forms of socio-political organisation. A multi-method large-scale cross-cultural approach provided the data necessary to achieve these objectives. Evidence from the societies within which literate behaviour first emerged, and from a representative sample of ethnographically-attested societies worldwide (n=74), indicates that literate behaviour emerged through the routinization of rituals and pre-literate sign systems, eventually spreading more widely through classical religions. Cross-cultural evidence also suggests that literacy assumed a wide variety of forms and socio-political functions, particularly in large, complex groups, extending evolved psychological mechanisms for cooperation, which include reciprocity, reputation formation and maintenance systems, social norms and norm enforcement systems, and group identification. Finally, the results of a cross-cultural historical survey of first-generation states (n=10) reveal that simple models assuming single cause-and-effect relationships between literacy and complex forms of socio-political organisation must be rejected. Instead, literacy and first-generation state-level polities appear to have interacted in a complex positive feedback loop. This thesis contributes to the wider goal of transforming social and cultural anthropology into a cumulative and rapid-discovery science.