The dissertation contends that an instrument developed through using a model of complex adaptive systems as a generative metaphor will assist members of an organisation to better understand their organisation. Using an action research methodology, six Air Force Management Services Teams were exposed to six overlapping attributes of complex adaptive systems through focus group workshops with an aim to determine whether they, as experienced management consulting practitioners, saw value to themselves and their Air Force clients of using aspects of complex adaptive systems for organisational understanding. The overlapping attributes of complex adaptive systems were distilled from the literature reviewed. Whereas the focus group workshop participants found the attributes valuable in understanding the dynamics of organisational behaviour, they found the new way of thinking challenging on a number of different perspectives. Some aspects of the Air Force organisation, like its high levels of organisational experience, will make the introduction to and use of complex adaptive systems thinking simpler, while other aspects of the Air Force organisation, like its sensitivity to complex adaptive systems terminology, will make the introduction and use of complex adaptive systems more challenging. Notwithstanding the challenges, both the complex adaptive systems model, and the use of action research were found to be useful ways of introducing organisations to complex adaptive systems thinking.

Doctor of Philosophy (PhD) / The overarching objective of this thesis is to investigate and examine several contemporary IC theories and how they are utilised in practice so that understandings of the IC concept can be developed, in order to answer in part the main research question of “How does IC in action influence organisations?” The content of the thesis is based on a review of IC from both a theory and practice perspective and four empirical papers that examines IC theory as it is implemented in practice. In combining these papers into a coherent piece of work, a critical research perspective, as outlined by Alvesson and Deetz (2000), has been utilised as the theoretical framework. The term ‘critical’ is used in this thesis not to find fault with contemporary theory and practice of IC but rather to examine and question the application of IC theory into practice. The end result of doing so is the narrowing of an identified gap between IC theory and practice. A ‘critical’ analysis of IC in action is justified because the development of the concept of IC parallels that of ‘critical’ theory in that both have evolved from changing conditions in society as technology and the proliferation of knowledge that have fundamentally altered the conditions under which organisations operate. The overarching findings of the thesis are based on three outcomes of critical research being insight, critique and transformative re-definitions. Insight into IC is developed by examining contemporary IC frameworks as they have been applied. Critique is developed by putting to the test the implications for organisations as a result of implementing these contemporary IC frameworks. Last, transformative re-definition is achieved by opening a discourse on the impact of implementing IC practices so that academics and practitioners can develop critical, relevant and practical understandings that begins the process of change and develops practical managerial skills. More importantly this thesis identifies how the development of tools to reduce ‘causal ambiguity’ about how intangible resource help create (or destroy) value has the potential to raise the profile of IC as a strategic management technology. But from the wider view of the critical perspective, it is not the intention of this thesis to prescribe specific formulae for the measuring, management and reporting of IC, nor does it intend to further develop theory. So while the individual papers may proffer that certain avenues proved productive in developing insights, critique and transformative re-definition, these avenues are not offered as the preferred way of investigating IC. More specifically the goal of a critical perspective is to open a discourse. The opprurtinity for academics and practitioners to engage in discourse is enabled by the thesis’ focus on the issues identified by highlighting the gap between IC theory and practice. Furthermore, each of the included papers offers the opportunity for further discourse by way of the opportunities that remain for future research. Additionally, the thesis achieves exemplifies a number of different approaches to conducting research into IC practice that puts to the test particular aspects of IC theory in order to develop insights and understandings of IC in practice. As the empirical material only examines a fraction of contemporary IC theory there is scope for further research and thus discourse into the implementation of IC theory into IC practice. This future research should not be constrained by a particular method of research as exemplified in the variety of methods employed to gather the empirical material for the papers which stretches along the continuum of qualitative and quantitative research. This too provides an avenue of for future discourse.

Doctor of Philosophy (PhD) / The aim of this thesis is to understand what drives the evolution of industrial networks and how such understanding can be used to stimulate sustainable development. A complex adaptive systems perspective has been adopted to analyse the complex interaction between organisational behaviour and industrial network evolution. This analysis has formed the basis for the development of a modelling approach that allows for quantitative exploration of how different organisational perceptions about current and future uncertainty affect their behaviour and therefore the network evolution. This analysis results in a set of potential evolutionary pathways for an industrial network and their associated performance in terms of sustainable development. Subsequently, this modelling approach has been used to explore the consequences of interventions in the network evolution and to identify robust interventions for stimulating sustainable development of industrial networks. The analysis, modelling approach and development of interventions has been developed in the context of a bioenergy network in the region of KwaZulu-Natal in South Africa. Industrial networks are an important aspect of today’s life and provide many goods and services to households and individuals all over the world. They consist of a large number of autonomous organisations, where some organisations contribute by transforming or transacting natural resources, such as oil, agricultural products or water, while other organisations contribute to networks by providing information or setting regulation or subsidies (local or national governments) or by influencing decision making processes of other organisations in networks (advocacy groups). Throughout the process from natural resource to product or service, industrial networks have important economic, environmental and social impacts on the socio-economic and biophysical systems in which they operate. The sum of complex interactions between organisations affects the rate in which natural resources are used, environmental impacts associated with transformation and transaction of resources and social impacts on local communities, regions or countries as a whole. The aim of this thesis is to understand how industrial networks evolve and how they can be stimulated towards sustainable development. The first question that has been addressed in this thesis is how to understand the complex interaction between organisational behaviour and industrial network evolution. Organisational behaviour is affected by many functional and implicit characteristics within the environment in which the organisation operates, while simultaneously the environment is a function of non-linear relationships between individual organisational actions and their consequences for both the function and structure of the network. This thesis has identified four different characteristics of industrial networks that affect organisational behaviour: 1) Functional characteristics 2) Implicit behavioural characteristics 3) Implicit relational characteristics 4) Implicit network characteristics. Functional characteristics are those characteristics that are formally recognised by all organisations within an industrial network and which affect their position within the network. Examples of functional characteristics are the price and quantity of resources available, the location and distance of organisations within a network, infrastructure availability or regulation. Implicit characteristics, on the other hand, are those characteristics that impact the decision making process of organisations, but which are not formally part of the network. From an organisational perspective, implicit characteristics are the rules, heuristics, norms and values that an organisation uses to determine its objectives, position and potential actions. Implicit relational characteristics, most importantly trust and loyalty, affect an organisations choice between potential partners and implicit network characteristics are those social norms and values that emerge through social embeddedness. Collectively, these functional and implicit characteristics and their interactions determine the outcome of organisational decisions and therefore the direction of the industrial network evolution. The complex interaction between these large numbers of characteristics requires quantitative models to explore how different network characteristics and different interactions result in different network evolutions. This thesis has developed an agent-based simulation model to explore industrial network evolutions. To represent the multi-scale complexity of industrial networks, the model consists of four scales. Each scale represents different processes that connect the functional and implicit characteristics of an industrial network to each other. The two basic scales represent the strategic actions of the organisations on the one hand and the industrial network function and structure on the other. The third scale represents the processes that take place within the mental models of organisations describing how they make sense of their environment and inform their strategic decision making process. The fourth scale represents the social embeddedness of organisations and how social processes create and destroy social institutions. The model has been developed such that it allows for exploring how changes in different network characteristics or processes affect the evolution of the network as a whole. The second question that has been addressed in this thesis is how to evaluate sustainable development of different evolutionary pathways of industrial networks. First of all, a systems approach has been adopted to explore the consequences of an industrial network to the larger socio-economic and biophysical system in which the network operates. Subsequently, a set of structural indicators has been proposed to evaluate the dynamic performance of industrial networks. These four structural indicators reflect the efficiency, effectiveness, resilience and adaptiveness of industrial networks. Efficiency and effectiveness relate to the operational features by which industrial networks provides a particular contribution to society. Resilience and adaptiveness relate to the system’s capacity to maintain or adapt its contribution to society while under stress of temporary shocks or permanent shifts, respectively. Finally, different multi-criteria decision analysis (MCDA) tools have been applied to provide a holistic evaluation of sustainable development of industrial networks. The third important question that is addressed in this thesis is how to systematically explore the potential evolutionary pathways of an industrial network, which has led to the development of agent-based scenario analysis. Agent-based scenario analysis systematically explores how industrial network evolutions might evolve depending on the perceptions of organisations towards the inherent uncertainty associated with strategic decision making in networks. The agent-based scenario analysis consists of two steps. Firstly, analysts develop a set of coherent context scenarios, which represents their view on the context in which an industrial network will operate within the future. For a bioenergy network, for example, this step results in a set of scenarios that each represent a coherent future of the socio-economic system in which the network might evolve. The second step is the development of a set of ‘agent scenarios’. Each agent-based scenario is based on a different ‘mental model’ employed by organisations within the network about how to deal with the inherent ambiguity of the future. The organisational perspective towards uncertainty is of major importance for the evolution of industrial networks, because it determines the innovative behaviour of organisations, the structure of the network and the direction in which the network evolves. One the one hand, organisations can ignore future ambiguity and base their actions on the environment that they can observe in their present state. On the other extreme, organisations can adopt a view that the future is inherently uncertain and in which they view social norms and values more important than functional characteristics to make sense of their environment. The mental models are differentiated according to two dimensions: 1) different mental representation of the world and 2) different cognitive processes that can be employed to inform strategic actions. Along these dimensions, different processes can be employed to make sense of the environment and to inform decision making. The thesis has shown that by systematically exploring the different perceptions possible, an adequate understanding of the different evolutionary pathways can be gained to inform the evaluation and development of interventions to stimulate sustainable development. The final part of this thesis has applied the analysis and methodology developed throughout this thesis to a bioenergy network in the province of Kwazulu-Natal in South Africa. The bioenergy network consists of a set of existing sugar mills with large quantities of bagasse, a biomass waste product, available. Bagasse is currently burned inefficiently to produce steam for the sugar mills, but can potentially be used for the production of green electricity, biodiesel, bioethanol or gelfuel. All of these products have important consequences for the region in terms of associated reductions in CO2 emissions, electrification of and/or energy provision for rural households and local economic development of the region. This thesis has modelled strategic decisions of the sugar mills, the existing electricity generator, potential independent energy producers, local and national governments and how their actions and interactions can lead to different evolutionary pathways of the bioenergy network. The agent-based scenario analysis has been used to explore how different perceptions of organisations can lead to different network evolutions. Finally, the model has been used to explore the consequences of two categories of interventions on stimulating sustainable development. The conclusions are that both categories of interventions, financial interventions by national government and the introduction of multi-criteria decision analysis (MCDA) tools to aid strategic decision making, can have both positive and negative effects on the network evolutions, depending on what ‘mental models’ are employed by organisations. Furthermore, there is no single intervention that outperforms the others in terms of stimulating both functional and structural features of sustainable development. The final conclusion is that instead of focusing on individual or collective targets, emphasis should be placed on the development of interventions that focus on evolutionary aspects of industrial networks rather than functional performance criteria. This thesis has also highlighted interesting research questions for future investigation. The methodology developed in this thesis is applied to a single case study, but there are still many questions concerning how different industrial networks might benefit from different organisational perceptions towards uncertainty. Furthermore, the role between the mental models and sustainable development requires further investigation, especially in the light of globalisation and the interconnectiveness of industrial networks in different countries and continents. Finally, this methodology has provided a platform for investigating how new technologies might be developed that anticipate needs of future generations. This thesis has provided a first and important step in developing a methodology that addresses the complex issues associated with sustainable development, benefiting both academics and practitioners that aim to stimulate sustainable development.

Thesis (M.S.)--California Polytechnic State University, 2008. / Major professor: David Janzen, Ph.D. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Computer Science." "June 2008." Includes bibliographical references (leaves 57-62). Also available online. Also available on microfiche (1 sheet).

Originally issued as author's Ph. D. thesis, University of Canterbury, 2002. / Includes bibliographical references (p. 215-222). Thesis available online from Univ. of Canterbury.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (p. 106-117).

Thesis (Ph. D.)--University of Texas at Austin, 2004. / Supervisors: James W. Fredrickson and Gautam Ahuja. Vita. Includes bibliographical references.

Thesis (Ph. D. (Investec Business School))--Rhodes University, 2004.

Thesis (Ph.D.)--Victoria University of Wellington, 2009. / Includes bibliographical references.

Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Computer Science, 2009. / Includes bibliographical references.