The merging of business and information technology (IT) strategies, effectively becoming a Digital Business Strategy (DBS), is changing the way that organisations have to leverage resources to create differential value. Due to the DBS being such a novice idea, there is no clear understanding of what the DBS is, what its characteristics and boundaries are, how it impacts alignment between business and IT, and how it impacts organisational performance. Without this understanding, organisations leveraging a DBS run the risk of launching technological initiatives or making organisational changes that are disjointed from their strategic direction. These misaligned efforts may result in unrealised strategy and unsatisfactory organisational performance. The purpose of this study was to define the boundaries and characteristics of the DBS, provide a definition of a DBS and to establish if the DBS has a positive effect on organisational performance. To examine the DBS, it was observed in its natural habitat, through a single case study approach, focusing on an organisation that has been leveraging a DBS as part of their digital journey. The organisation is a South African based financial services provider and is a subsidiary of a larger financial services provider. In this study, the DBS was observed from an intellectual, operational, social and cultural alignment perspective, using a combination of the Strategic Alignment Model (SAM) and the Complex Adaptive System (CAS) frameworks. This study subscribed to a mixed-method approach which included both qualitative and quantitative research techniques. Staff providing input into this study included senior, middle, junior and non-management employees. The study was conducted over a period of thirteen months. The findings from both the qualitative and quantitative data suggest that to leverage a DBS the organisation must be concerned with more than just leveraging digital resources. For instance, organisations must focus on customer and staff empowerment, use customer and industry-related information to create opportunistic and competitive decision-making opportunities, and create a change-ready culture where bold experimentation and failing forward is embraced. Researchers and practitioners alike can use the findings of this case study as lessons on how to leverage organisational resources in the context of the DBS.

Simulation has been used to model combat for a long time. Recently, it has been accepted that combat is a complex adaptive system (CAS). Multi-agent systems (MAS) are also considered as a powerful modelling and development environment to simulate combat. Agent-based distillations (ABD) - proposed by the US Marine Corp - are a type of MAS used mainly by the military for exploring large scenario spaces. ABDs that facilitated the analysis and understanding of combat include: ISAAC, EINSTein, MANA, CROCADILE and BactoWars. With new concepts such as networked forces, previous ABDs can implicitly simulate a networked force. However, the architectures of these systems limit the potential advantages gained from the use of networks. In this thesis, a novel network centric multi-agent architecture (NCMAA) is pro-posed, based purely on network theory and CAS. In NCMAA, each relationship and interaction is modelled as a network, with the entities or agents as the nodes. NCMAA offers the following advantages: 1. An explicit model of interactions/relationships: it facilitates the analysis of the role of interactions/relationships in simulations; 2. A mechanism to capture the interaction or influence between networks; 3. A formal real-time reasoning framework at the network level in ABDs: it interprets the emergent behaviours online. For a long time, it has been believed that it is hard in CAS to reason about emerging phenomena. In this thesis, I show that despite being almost impossible to reason about the behaviour of the system by looking at the components alone because of high nonlinearity, it is possible to reason about emerging phenomena by looking at the network level. This is undertaken through analysing network dynamics, where I provide an English-like reasoning log to explain the simulation. Two implementations of a new land-combat system called the Warfare Intelligent System for Dynamic Optimization of Missions (WISDOM) are presented. WISDOM-I is built based on the same principles as those in existing ABDs while WISDOM-II is built based on NCMAA. The unique features of WISDOM-II include: 1. A real-time network analysis toolbox: it captures patterns while interaction is evolving during the simulation; 2. Flexible C3 (command, control and communication) models; I 3. Integration of tactics with strategies: the tactical decisions are guided by the strategic planning; 4. A model of recovery: it allows users to study the role of recovery capability and resources; 5. Real-time visualization of all possible information: it allows users to intervene during the simulation to steer it differently in human-in-the-loop simulations. A comparison between the fitness landscapes of WISDOM-I and II reveals similarities and differences, which emphasise the importance and role of the networked architecture and the addition of strategic planning. Lastly but not least, WISDOM-II is used in an experiment with two setups, with and without strategic planning in different urban terrains. When the strategic planning was removed, conclusions were similar to traditional ABDs but were very different when the system ran with strategic planning. As such, I show that results obtained from traditional ABDs - where rational group planning is not considered - can be misleading. Finally, the thesis tests and demonstrates the role of communication in urban ter-rains. As future warfighting concepts tend to focus on asymmetric warfare in urban environments, it was vital to test the role of networked forces in these environments. I demonstrate that there is a phase transition in a number of situations where highly dense urban terrains may lead to similar outcomes as open terrains, while medium to light dense urban terrains have different dynamics