The thesis develops themes around eight published works and as such the thesis encompasses a coherent caucus of work within the petrochemicals industry in the UK. The thesis provides evidence which confirms the widespread use of a strategy of flexibility but challenges the conception of strategy as a deliberate formal plan, and the rational economism of Transaction Cost Economics. It also casts doubt on the existence of distinct strategic levels. The multinationals in the industry have been exposed as not using a sophisticated rationale to underpin their strategy, relying instead on institutional ideologies or mimetic isomorphism. The thesis also challenges exiting conceptions of the role of Human Resources in the pursuit of strategy by showing the importance of the generic HR function in line management as opposed to an HR department.

The impact of uncertainty in the commercialization lifecycle of new technologies is a complex phenomenon. Technologies are research intensive and exposed to uncertainty regarding their successful development and functionality. Further these technologies have to be absorbed by volatile markets in order to be commercialized. These different forms of uncertainty are of primary importance for decision makers but have not been thoroughly studied in previous technology commercialization research and put under one theoretical framework. The main focus of this thesis is to comprehend the recently growing trend among universities and public research organizations to commercialize their research activities from an empirical and theoretical perspective. More particularly the thesis focuses on the life cycle of two main commercialization streams namely the entry and exit of university spinouts, which are companies that evolve from intellectual property developed within academic institutions as well as the licensing and licensing termination of inventions. The main focus of the thesis therefore analysesmarket and technological uncertainty and explains the conditions under which spinout formation, spinout failure, licensing and licensing failure occur by putting them under the theoretical framework of real option theory.

Variation in the manufactured geometry of engineering components is perpetually present in production. Random variation can arise due to slight differences in material properties, machines and tools, processes and even climatic conditions in the factory. To guarantee the functionality or quality of individual components, features are inspected to verify they conform to the tolerance limits imposed. It is undesirable to produce nonconforming features, due to the cost of reworking features or scrapping components. In practice, it is not always feasible to improve manufacturing capability (reduce variation), or design components to be less susceptible to variation; in such a situation the cost of non-conformance should be minimised. Optimal Mean Setting, a methodology to maximise profit from a production system where the manufacturing variation is often greater than a feature's tolerance limits, can be applied in these circumstances. Although the principle of Optimal Mean Setting dates back over 60 years, its application to engineering design is relatively undeveloped. A major part of this thesis was devoted to developing a robust, reliable and generalised framework to practice Optimal Mean Setting in engineering design. Errors were uncovered in previous attempts in the literature relating to Optimal Mean Setting of simple systems. Improvements to the maximum obtainable profit were also realised by implementing a new optimisation strategy to that developed in the literature. Another innovation developed in this thesis was the the application of copula function modelling to Optimal Mean Setting. Copulas allowed joint distributions to be created from non-parametric (or non family specific) feature variation distributions. This permitted Optimal Mean Setting to be applied to components with several quality characteristics where different distributions modelled the manufacturing variation. It also allowed the final geometry of a component to be modelled to access the distribution of performance of a batch of components. Numerical examples and the applications to real components are given.

The fundamental structures that underpin business activities must evolve and change in order to equip companies to thrive in a market whose characteristics are increasing competition and instability. The incremental advances in applied computing technology and business methodologies which focus on improving one aspect of company operations ignore the need for an underlying structure and model through which to engage any and all functions in a consistent and integrated fashion. Indeed, many exacerbate the problem through closed architectures, isolationist views of entity data storage and rigid methodologies imposed on the company that employs them. The Product Model proposed fulfils that role. It is a model of the processes and entities that a company uses to conduct its business, at all levels and across all departments. Two other concepts are exposed: product model data and the design history record. Product model data are the values of instances of product model entities and relations, created to represent a particular design, artefact or object. The design history record captures the data and functions used in a transaction and the order and context in which they are used. To exercise these concepts, a software suite was written, the Glasgow Utility for Integrated Design, Guide. It supports the definition of a proud model and its subsequent use in the creation of product model data. Each interaction with the system is recorded, thus capturing the design history record, which can subsequently be processes to various advantageous ends. The major such uses are for re-use of part information in other designs and the extraction of design best practice with which to augment the company's design methodology. It is a comprehensive record, since all business processes are supported by, and can be transacted through Guide. Guide has been used to validate the adequacy of the product model and has established many benefits through its use. Applications in many spheres are possible; engineering has been the primary focus for exemplars and case studies. The development was carried out under the scrutiny of constant validation and testing in live situations with several industrial partners. Guide is built on industry standard tools and uses relational database technology to store frame-based representations of entities, methods and relationships. The design of project plans is carried out on the same platform used to support the project itself; the design data are not dissociated from the project controlling mechanism. Resources, including staff, are engaged according to requirements and audit mechanisms allow for constant re-evaluation of the project development. Control and communication mechanisms support applications in an extended enterprise environment and the distribution of resources that this entails.