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This research suggests that to model the complex dynamics of the organisational change in a firm evolving as it implements internet technologies requires capturing diverse independent and interdependent processes across multiple temporal and spatial context both within and external to the firm. This presents both an ontological and epistemological challenge as dominant research methods are either atemporal in nature and attribute action to disembodied variables or are simply storytelling. To provide explanatory legitimacy requires going deeper to capture the action of actors 'acting' within multiple levels of context and to pinpoint deeper 'rock-bottom' causal mechanisms that drive the higher order processes that give rise to the 'organisational life' we observe. To accomplish explanatory legitimacy I develop an analytical method that makes processuality fundamental and allows for the examination and theorising about mechanisms. The first essential element of this method is a framework that guides the researcher in the systematic gathering together of what we already know from the multidisciplinary and eclectic research in e-business, and in the intensive work of gathering empirical evidence. I apply a new methodology I call narrative sequence analysis, that combines process tracing and sequence analyses to make processes intelligible and help illustrate how mechanisms drive these processes. I use this method to develop an explanatory account of the process of e-business development covering three episodes of change within the Commonwealth Bank of Australia from 1995 to 2006. The research finds that the firm evolves over time as it develops new capabilities and identifies and pursues development opportunities by assembling and committing resources to e-business though both technology development and business application. It draws on past experience and gradually learns to develop, integrate and implement technology into existing business operations, discovers new innovative opportunities in which to apply the technology or is drawn into new areas by others who identify opportunities in which to apply the firm's knowledge, resources and technology. The path to development depends on the firms starting position and the timing of the sequence of events encountered along the way. It is a coevolutionary process where the firm interacts, cooperates, adapts and responds to the actions and interactions of other actors, balanced by the uncertainty of e-business and business operation risk.

This research suggests that to model the complex dynamics of the organisational change in a firm evolving as it implements internet technologies requires capturing diverse independent and interdependent processes across multiple temporal and spatial context both within and external to the firm. This presents both an ontological and epistemological challenge as dominant research methods are either atemporal in nature and attribute action to disembodied variables or are simply storytelling. To provide explanatory legitimacy requires going deeper to capture the action of actors 'acting' within multiple levels of context and to pinpoint deeper 'rock-bottom' causal mechanisms that drive the higher order processes that give rise to the 'organisational life' we observe. To accomplish explanatory legitimacy I develop an analytical method that makes processuality fundamental and allows for the examination and theorising about mechanisms. The first essential element of this method is a framework that guides the researcher in the systematic gathering together of what we already know from the multidisciplinary and eclectic research in e-business, and in the intensive work of gathering empirical evidence. I apply a new methodology I call narrative sequence analysis, that combines process tracing and sequence analyses to make processes intelligible and help illustrate how mechanisms drive these processes. I use this method to develop an explanatory account of the process of e-business development covering three episodes of change within the Commonwealth Bank of Australia from 1995 to 2006. The research finds that the firm evolves over time as it develops new capabilities and identifies and pursues development opportunities by assembling and committing resources to e-business though both technology development and business application. It draws on past experience and gradually learns to develop, integrate and implement technology into existing business operations, discovers new innovative opportunities in which to apply the technology or is drawn into new areas by others who identify opportunities in which to apply the firm's knowledge, resources and technology. The path to development depends on the firms starting position and the timing of the sequence of events encountered along the way. It is a coevolutionary process where the firm interacts, cooperates, adapts and responds to the actions and interactions of other actors, balanced by the uncertainty of e-business and business operation risk.

<p> </p><p>The international maritime industry is growing fast due to an increasing number of transportations over sea. In pace with this development, the maritime surveillance capacity must be expanded as well, in order to be able to handle the increasing numbers of hazardous cargo transports, attacks, piracy etc. In order to detect such events, anomaly detection methods and techniques can be used. Moreover, since surveillance systems process huge amounts of sensor data, anomaly detection techniques can be used to filter out or highlight interesting objects or situations to an operator. Making decisions upon large amounts of sensor data can be a challenging and demanding activity for the operator, not only due to the quantity of the data, but factors such as time pressure, high stress and uncertain information further aggravate the task. Bayesian networks can be used in order to detect anomalies in data and have, in contrast to many other opaque machine learning techniques, some important advantages. One of these advantages is the fact that it is possible for a user to understand and interpret the model, due to its graphical nature.</p><p>This thesis aims to investigate how the output from a Bayesian network can be explained to a user by first reviewing and presenting which methods exist and second, by making experiments. The experiments aim to investigate if two explanation methods can be used in order to give an explanation to the inferences made by a Bayesian network in order to support the operator’s situation awareness and decision making process when deployed in an anomaly detection problem in the maritime domain.</p><p> </p>

The international maritime industry is growing fast due to an increasing number of transportations over sea. In pace with this development, the maritime surveillance capacity must be expanded as well, in order to be able to handle the increasing numbers of hazardous cargo transports, attacks, piracy etc. In order to detect such events, anomaly detection methods and techniques can be used. Moreover, since surveillance systems process huge amounts of sensor data, anomaly detection techniques can be used to filter out or highlight interesting objects or situations to an operator. Making decisions upon large amounts of sensor data can be a challenging and demanding activity for the operator, not only due to the quantity of the data, but factors such as time pressure, high stress and uncertain information further aggravate the task. Bayesian networks can be used in order to detect anomalies in data and have, in contrast to many other opaque machine learning techniques, some important advantages. One of these advantages is the fact that it is possible for a user to understand and interpret the model, due to its graphical nature. This thesis aims to investigate how the output from a Bayesian network can be explained to a user by first reviewing and presenting which methods exist and second, by making experiments. The experiments aim to investigate if two explanation methods can be used in order to give an explanation to the inferences made by a Bayesian network in order to support the operator’s situation awareness and decision making process when deployed in an anomaly detection problem in the maritime domain.

This thesis has been carried out as there has been a need to expand research in men's violence against women in close relationships. This by a historical comparison to discover causal explanation and conceptions with a focus on change and continuity over time. Men's violence against women needs more research, although new interventions such as laws have been put into place, the problem still remains in society. The thesis will focus on finding change and continuity over time. Analyzing the area through a historical perspective can further contribute to a greater insight into the problem today, to reduce the risk of repetition of the past, regarding conceptions on gender and violence and not make the problem invisible. The material that has been used in the thesis is based on news articles from Dagens Nyheter and Svenska Dagbladet, based on four selected time periods during the 1900–2020s. The analysis focus on the public's perceptions and causal explanations of men's violence against women in close relationships. The result of the analysis concluded, among other things, that research and news articles do not always correspond and that society's perceptions and causal explanations have both altered and continued. A finding  in the thesis is that jealousy and men's feelings are two relatively unexplored areas.