Which factors drive firm survival within an industry boundary over time?:the UK onshore oil and gas production industry 1984-1999

This thesis looks at the UK onshore oil and gas production industry and follows the history of a population of firms over a fifteen-year period following the industry's renaissance. It examines the linkage between firm survival, selection pressures and adaptation responses at the firm level, especially the role of discretionary adaptation, specifically exploration and exploitation strategies.Taking a Realist approach and using quantitative and qualitative methods for triangulation on a new data base derived from archival data, as well as informant interviews, it tests seven hypotheses' about post-entry survival of firms. The quantitative findings suggest that firm survival within this industry is linked to discretionary adaptation, when measured at the firm level, and to a mixture of selection and adaptation forces when measured for each firm for each individual year. The qualitative research suggests that selection factors dominate. This difference in views is unresolved. However the small, sparse population and the nature of the oil and gas industry compared with other common research contexts such as manufacturing or service firms suggests the results be treated with caution as befits a preliminary investigation. The major findings include limited support for the theory that the external environment is the major determinant of firm survival, though environment components affect firms differentially; resolution of apparent literature differences relating to the sequencing of exploration and exploitation and potential tangible evidence of coevolution. The research also finds that, though selection may be considered important by industry players, discretionary adaptation appears to play the key role, and that the key survival drivers for thispopulation are intra-industry ties, exploitation experience and a learning/experience component. Selection has a place, however, in determining the life-cycle of the firm returning to be a key survival driver at certain ages of the firm inside the industry boundary.

Resource allocation in decentralised computational systems:an evolutionary market-based approach

We present a novel market-based method, inspired by retail markets, for resource allocation in fully decentralised systems where agents are self-interested. Our market mechanism requires no coordinating node or complex negotiation. The stability of outcome allocations, those at equilibrium, is analysed and compared for three buyer behaviour models. In order to capture the interaction between self-interested agents, we propose the use of competitive coevolution. Our approach is both highly scalable and may be tuned to achieve specified outcome resource allocations. We demonstrate the behaviour of our approach in simulation, where evolutionary market agents act on behalf of service providing nodes to adaptively price their resources over time, in response to market conditions. We show that this leads the system to the predicted outcome resource allocation. Furthermore, the system remains stable in the presence of small changes in price, when buyers' decision functions degrade gracefully. © 2009 The Author(s).