Nature of the inquiry: My research inquiry investigated how qualities of personal interaction shape and affect the promotion of research utilisation for quality improvement in the US healthcare sector. The research investigated my own professional practice of consulting, teaching, and research regarding the improvement of healthcare practices and outcomes. Efforts to improve the quality of healthcare services are often difficult to realise and sustain. The quality improvement movement in the USA and elsewhere has not conducted much self-examination of its own processes for sources of these perennially problematic results. Relevance: The quality of healthcare services can be readily understood as having consequences of life or death, wellness or suffering. Healthcare expenditures in the USA are estimated at 16% of GDP and over 9% in the UK. Improving healthcare quality improvement efforts is a matter of profound human and social significance. Approach: The DMan research methodology is a reflexively aware process conducted as a cohort and as small learning groups of researchers during the three-year programme. The research inquiry used the complex responsive process of relating theory of learning as emergent changes of meaning or, equivalently, knowledge. As a social science of qualities, it uses the qualities of human interaction as the unit of analysis. The research utilised an interdisciplinary approach drawing upon: healthcare quality improvement literature; organizational discourse studies; research on strategy as practice; performance management; communications theories; the theory of mindful learning; interpersonal neurobiology; figurational sociology; and American pragmatist philosophy. The methodology employs a mindful reflexivity research strategy related to concepts from mindful learning and social neuroscience literature. Central methods included iterative peer and supervisor debriefing and iterative reflexive narrative practice. Findings: A contribution is made to the healthcare literature by describing how ordinary qualities of social coordination dynamics affect the promoters of healthcare research, not just potential users of research. A contribution is made to professional practice by providing a new perspective from which to analyse the sources of performance challenges prevalent in healthcare quality improvement efforts. The research findings indicate how applications of substantial organisational and social resources to promote research utilisation in the US health sector can be co-opted and dissipated away from ostensive substantive objectives. This occurs by research promoters‟ organizational discourse efforts to favourably shape power relating and other qualities of interaction of improvement initiatives. These efforts restrict the emergence of learning about the promoted changes.

The central goal of this thesis is to provide additional criteria towards implementing open-ended evolution in an artificial system. Methods inspired by biological evolution are frequently applied to generate autonomous agents too complex to design by hand. Despite substantial progress in the area of evolutionary computation, additional efforts are needed to identify a coherent set of requirements for a system capable of exhibiting open-ended evolutionary dynamics. The thesis provides an extensive discussion of existing models and of the major considerations for designing a computational model of evolution by natural selection. Thus, the work in this thesis constitutes a further step towards determining the requirements for such a system and introduces a concrete implementation of an artificial evolution system to evaluate the developed suggestions. The proposed system improves upon existing models with respect to easy interpretability of agent behaviour, high structural freedom, and a low-level sensor and effector model to allow numerous long-term evolutionary gradients. In a series of experiments, the evolutionary dynamics of the system are examined against the set objectives and, where appropriate, compared with existing systems. Typical agent behaviours are introduced to convey a general overview of the system dynamics. These behaviours are related to properties of the respective agent populations and their evolved morphologies. It is shown that an intuitive classification of observed behaviours coincides with a more formal classification based on morphology. The evolutionary dynamics of the system are evaluated and shown to be unbounded according to the classification provided by Bedau and Packard’s measures of evolutionary activity. Further, it is analysed how observed behavioural complexity relates to the complexity of the agent-side mechanisms subserving these behaviours. It is shown that for the concrete definition of complexity applied, the average complexity continually increases for extended periods of evolutionary time. In combination, these two findings show how the observed behaviours are the result of an ongoing and lasting adaptive evolutionary process as opposed to being artifacts of the seeding process. Finally, the effect of variation in the system on the diversity of evolved behaviour is investigated. It is shown that coupling individual survival and reproductive success can restrict the available evolutionary trajectories in more than the trivial sense of removing another dimension, and conversely, decoupling individual survival from reproductive success can increase the number of evolutionary trajectories. The effect of different reproductive mechanisms is contrasted with that of variation in environmental conditions. The diversity of evolved strategies turns out to be sensitive to the reproductive mechanism while being remarkably robust to the variation of environmental conditions. These findings emphasize the importance of being explicit about the abstractions and assumptions underlying an artificial evolution system, particularly if the system is intended to model aspects of biological evolution.

My research focuses on the experience of policy development and implementation. It draws on my involvement in a government policy taskforce, the development of an organisation’s strategy to the taskforce’s recommendations and the commissioning of frontline services. The research material is my personal experience contained in a number of narrative accounts of important happenings. These are then used as a basis to engage with literature and conversation with practitioners, academics and fellow researchers. It is from this iterative process that the argument develops. The approach is therefore qualitative and reflexive in nature. I have argued against the traditional separation between the content of research and methodology. This is on the basis that human experience does not distinguish between the two as we make sense of new emerging situations. The research has been heavily influenced by analogies drawn from complexity sciences as a way of increasing our understanding of ongoing human interaction, namely complex responsive processes of relating (Stacey et al, 2000). By paying careful attention to the experience of policy development and implementation over an extended period of time I am illuminating that the development of policy can often be seen in literature and in the techniques people use as an activity that is isolated from the work of frontline staff. For example, a policy group is formed, policy or a strategy is drafted and the work is then seen to be done. This can be demonstrated by paying attention to the modus operandi of how policy and strategy groups work and how performance criteria are established. When it comes to frontline practice, policy is often silent to the multitude of unfolding interconnected possibilities that present themselves to practitioners as they seek to go about their activities. The way that policy is often presented implies that there is linearity from policy to implementation. Drawing on Elias’s notion of Involvement and Detachment (1987) I am highlighting a paradoxical relationship between policy and implementation. In introducing the notion of paradox, there is a “vitality” that is required to prevent a collapse to one of the two ends of a continuum; for example a conscious or unconscious rejection of policy in favour of embracing frontline practice, or an over reliance on policy to blindly drive through organisational change. In spending three years looking at the policy and implementation I argue that it is more helpful to consider policy and implementation as a “flow”, rather than a series of discrete activities that are seen to be completed before moving to the next policy area. In looking at policy as something that occurs over a span of time (as opposed to an isolated bounded activity) there is an opportunity to prevent the collapse of the paradox outlined above. By accepting the concept of paradox and considering policy from a temporal perspective, rather than one that is a spatially bound system, the issue of policymaking practice can be considered. There are books and management experts that recommend that managers should “walk the walk”, and get closer to frontline activity. My research has sought to add clarity here, arguing for an experiential and temporal form of reflexivity of practice (as opposed to reflective practice). In this context working and being present with frontline practitioners, paying very careful attention to the experience of the unfolding contingent nature of activity influences the practice of policy making. This is a different experience from simply being present, and being seen to be present. It would be ironic for my research to be converted into a policy document with key elements extracted and condensed into bullet points to be applied like a rule. Instead my research is best kept alive in evoking stories and reminiscences between people as they make sense of their experience of policymaking and implementation together.

Mega construction projects are complex undertakings. The complexity is increased during a construction boom in a city such as Dubai where more than 80% of material and labour resources are imported. The complexities inherent in mega construction projects include uncertainty and interdependencies, which affect project management performance at the operational level where most of the problems occur. Understanding these processes, how they interrelate and how to overcome the complexities is crucial for increasing the chances of project management success. This research contributed to construction project management theory and practice by using a highly inductive exploratory qualitative approach for capturing formal and informal processes in mega construction projects in Dubai. A dynamic model depicting the complementary formal and informal processes is developed showing formal and informal processes and how they interrelate to reduce complexity. Guidelines on how and when to use specific processes are provided as a framework for the model. This framework may be used to help develop communication processes in future complex projects to increase chances of project management success. The research was conducted by exploring two case study projects fitting the characteristics of mega construction projects. Both case study projects were of values above 1.5 Billion US Dollars and were similar in scope with elements including amusement parks, retail areas, hotels, extensive infrastructure and large landscape areas. Both case study projects were of an experimental character, considered an engineering achievement, complex, and thereby, difficult to control. The research data were collected through semi-structured interviews with 83 project staff from both case study projects. Rich picture diagrams of the organization and processes were made from data collected during the interviews and case study project documents. The analysis was performed in three phases where the results from each phase were built upon cumulatively. The first phase examined what the most crucial critical success factors (CSFs) were in the case study projects. These were revealed to be communication, top management support and effective change management. In the second phase each CSF was analyzed where it was found it that the majority of important communication modes were informal and were was most effective in reducing complexity. Furthermore, it was found that the characteristics of the client were crucial in both case study projects. The third phase involved development of the dynamic hybrid model from the rich picture diagrams created showing the interplay between formal and informal processes. It was found that informal processes are ad-hoc and chaotic in nature and controlled by individuals in the project. Development of guidelines for the positive use of informal processes was required. From the analysis it was found that the characteristics of client staff and individuals in the case study projects provided the main guidelines for effective use of the hybrid model. The research provides insights into the formal and informal processes and the reduction and management of complexity inherent in mega construction projects. Current research in managing complexity is from the perspective of the formal process where the informal processes are neglected, despite research and practice indicating their importance in construction projects. The research presents a systemic dynamic model of the processes for mega construction projects revealing that formal and informal processes are required and are complementary. Guidelines for the successful use of the model provide a framework for its application in practice. This shows how it can be used to inform understanding of processes in the context of the research. The model and guidelines were validated via discussions with practitioners experienced in construction of mega projects. Future work should expand the findings to applications of the model in practice for management of complex projects. The model may be used by practitioners to act as a guide in how to manage construction processes to consciously overcome the inherent complexities to achieve project management objectives. This tool may also be used to inform clients of the inherent complexities and the level of informality required to overcome them. IT/IS practitioners may use the model and framework to understand the complexities in construction, and thereby, develop systems that are practically applied in construction projects. Researchers in the field may build upon the model and findings to increase knowledge regarding construction processes, particularly informal processes.

Additive Manufacturing (AM) refers to the use of a group of technologies capable of combining material layer-by-layer to manufacture geometrically complex products in a single digitally controlled process step, entirely without moulds, dies or other tooling. AM is a parallel manufacturing approach, allowing the contemporaneous production of multiple, potentially unrelated, components or products. This thesis contributes to the understanding of the economic aspects of additive technology usage through an analysis of the effect of AM s parallel nature on economic and environmental performance measurement. Further, this work assesses AM s ability to efficiently create complex components or products. To do so, this thesis applies a methodology for the quantitative analysis of the shape complexity of AM output. Moreover, this thesis develops and applies a methodology for the combined estimation of build time, process energy flows and financial costs. A key challenge met by this estimation technique is that results are derived on the basis of technically efficient AM operation. Results indicate that, at least for the technology variant Electron Beam Melting, shape complexity may be realised at zero marginal energy consumption and cost. Further, the combined estimator of build time, energy consumption and cost suggests t AM process efficiency is independent of production volume. Rather, this thesis argues that the key to efficient AM operation lies in the user s ability to exhaust the available build space.

The field of computational complexity theory--which chiefly aims to quantify the difficulty encountered when performing calculations--is, in the case of conventional computers, correctly practised and well understood (some important and fundamental open questions notwithstanding); however, such understanding is, we argue, lacking when unconventional paradigms are considered. As an illustration, we present here an analogue computer that performs the task of natural-number factorization using only polynomial time and space; the system's true, exponential complexity, which arises from requirements concerning precision, is overlooked by a traditional, `time-and-space' approach to complexity theory. Hence, we formulate the thesis that unconventional computers warrant unconventional complexity analysis; the crucial omission from traditional analysis, we suggest, is consideration of relevant resources, these being not only time and space, but also precision, energy, etc. In the presence of this multitude of resources, however, the task of comparing computers' efficiency (formerly a case merely of comparing time complexity) becomes difficult. We resolve this by introducing a notion of overall complexity, though this transpires to be incompatible with an unrestricted formulation of resource; accordingly, we define normality of resource, and stipulate that considered resources be normal, so as to rectify certain undesirable complexity behaviour. Our concept of overall complexity induces corresponding complexity classes, and we prove theorems concerning, for example, the inclusions therebetween. Our notions of resource, overall complexity, normality, etc. form a model-independent framework of computational complexity theory, which allows: insightful complexity analysis of unconventional computers; comparison of large, model-heterogeneous sets of computers, and correspondingly improved bounds upon the complexity of problems; assessment of novel, unconventional systems against existing, Turing-machine benchmarks; increased confidence in the difficulty of problems; etc. We apply notions of the framework to existing disputes in the literature, and consider in the context of the framework various fundamental questions concerning the nature of computation.

This thesis considers possible criteria for the selection of example sentences for difficult or unknown words in reading texts for students of German as a Second Language (GSL). The examples are intended to be provided within the context of an Intelligent Computer-Aided Language Learning (ICALL) Vocabulary Learning System, where students can choose among several explanation options for difficult words. Some of these options (e.g. glosses) have received a good deal of attention in the ICALL/Second Language (L2) Acquisition literature; in contrast, literature on examples has been the near exclusive province of lexicographers. The selection of examples is explored from an educational, L2 teaching point of view: the thesis is intended as a first exploration of the question of what makes an example helpful to the L2 student from the perspective of L2 teachers. An important motivation for this work is that selecting examples from a dictionary or randomly from a corpus has several drawbacks: first, the number of available dictionary examples is limited; second, the examples fail to take into account the context in which the word was encountered; and third, the rationale and precise principles behind the selection of dictionary examples is usually less than clear. Central to this thesis is the hypothesis that a random selection of example sentences from a suitable corpus can be improved by a guided selection process that takes into account characteristics of helpful examples. This is investigated by an empirical study conducted with teachers of L2 German. The teacher data show that four dimensions are significant criteria amenable to analysis: (a) reduced syntactic complexity, (b) sentence similarity, provision of (c) significant co-occurrences and (d) semantically related words. Models based on these dimensions are developed using logistic regression analysis, and evaluated through two further empirical studies with teachers and students of L2 German. The results of the teacher evaluation are encouraging: for the teacher evaluation, they indicate that, for one of the models, the top-ranked selections perform on the same level as dictionary examples. In addition, the model provides a ranking of potential examples that roughly corresponds to that of experienced teachers of L2 German. The student evaluation confirms and notably improves on the teacher evaluation in that the best-performing model of the teacher evaluation significantly outperforms both random corpus selections and dictionary examples (when a penalty for missing entries is included).

According to conventional wisdom, the petroleum industry is classified as a ‘resource based’ and ‘mature’ industry. It is subject to the ‘resource curse’ thesis, exhausted of ‘technological opportunities’ with limited capacity for knowledge based economic growth. This study questions the adequacy of this line of reasoning. Exploring the technological complexity of the sector, a complementary argument is presented. We show that the sector has recently experienced a surge in ‘technological opportunities’. However the ‘systemic complexity of the knowledge base’ has constrained many oil producing countries’ enjoyment of these opportunities. This view highlights the role of dynamics of knowledge base complexity as an important ‘cognitive’ barrier for building innovation capabilities in endowed countries. This study is based on the extension of a ‘Sectoral Innovation Systems’ approach, highlighting the role of technological regimes in catch-up possibilities and strategies. Knowledge base complexity is explored as an under-researched element of technological regimes. The research contributes in three ways. First, it introduces a dynamic and three-dimensional view of knowledge base complexity at the conceptual level, and hypothesizes its implication for patterns of innovation and catch-up processes. Second, a quantitative methodology is developed to examine the proposed hypotheses. Third, the conceptual and methodological suggestions are empirically examined in the context of upstream petroleum industry. The findings propose that the sector has gone through phases of transformation and reconfiguration. The sector’s technological regime over the most recent period experienced high opportunities combined with rising systemic complexity of the knowledge base. We show that this trend in technological regimes is associated with shift of the sector from Schumpeter Mark I to II and with the emergence of major Integrated Service Companies as new system integrators coping with rising systemic complexity. We also observe that rising systemic complexity is associated with slow down and halt of geographical dispersion of innovation. The sector-wide cumulativeness stemming from systemic complexity creates high cognitive barriers to entry for latecomers. The very scarce examples of catch-up in a few advanced oil producing countries suggest that high innovation opportunities in complex industries are open mostly to countries with both advanced national innovation systems and accumulated production experience. For latecomer countries to benefit, their industrial policy needs to cope with increasing systemic complexity, mitigating its coordination costs and facilitating the integration of distributed catch-up processes. This highlights the key role of ‘late comer systems integrators’ for successful catch-up.

This thesis explores a small number of TEFL teachers’ collective responses to an extended change process in their Mexican university context from 1989-2003. The nature of the emergent knowledge arising from this inquiry hinges on the analysis and interpretation by the researcher who is also a complete participant in this educational context of her informants’ perceptions from their retrospection, and a reconstruction of the past, in present time. The methodology I adopted broadly follows interpretative qualitative research principles, including aspects of life history inquiry. The data generation process employed to explore our perceptions of ourselves, as well as our working context, before and during the 1990s, as we ourselves narrate them, comprised of: ‘conversations with a purpose’, critical incident and repertory grid interviews, as well as the concurrent analysis of the data, based on aspects of Grounded Theory. As a result, numerous categories and concepts emerged. These not only helped me to discover the issues that were both instrumental and influential regarding our positive receptivity to change, but also how being involved in a change process changed us, not only as individuals, but also as a culture. Based on these findings that have led to my deeper understanding of the nature of educational change, I conclude this thesis by positing that instead of adopting a mechanistic paradigm for viewing change, it is necessary, and more useful, to view it through the lens of complexity theory. Finally, this thesis ends by examining the implications that this position and the findings have for change policy makers, managers and change leaders, as well as suggestions for future research.

In this thesis I examine a number of topics that bear on explanation and understanding in molecular and cell biology, in order to shed new light on explanatory practice in those areas and to find novel angles from which to approach relevant philosophical debates. The topics I look at include mechanism, emergence, cellular complexity, and the informational role of the genome. I develop a perspective that stresses the intimacy of the relations between ontology and epistemology. Whether a phenomenon looks mechanistic, or complex, or indeed emergent, is largely an epistemic matter, yet has an objective basis in features of the world. After reviewing several concepts of mechanism I consider the influential recent account of Machamer, Darden and Craver (MDC). That account makes interesting proposals concerning the relationship between mechanistic explanation and intelligibility, which are consistent with the results of the investigation I undertake into the science surrounding protein folding. In relation to a number of other issues pertaining to biological systems I conclude that the MDC account is insufficiently nuanced, however, leading me to outline an alternative approach to mechanism. This emphasizes the importance of structure—function relations and addresses issues raised by reflection on the nature of cellular complexity. These include the distinction between structure and process and the different possible bases on which system organization may be maintained. The account I give of emergence construes the phenomenon in terms of psychological deficit: phenomena are emergent when we lack the capacity to trace through and model their causal structures using our cognitive schemas. I conclude by developing these ideas into a preliminary and partial account of explanation and understanding. This aspires to cover the significant fraction of work in molecular and cell biology that correlates biological structures, processes and functions by visualizing phenomena and making them imaginable.