CO2Y the intelligent green solution: minimising carbon emissions by maximising shared travel opportunity.

It is in the interests of everybody that the environment is protected. In view of the recent leaps in environmental awareness it would seem timely and sensible, therefore, for people to pool vehicle resources to minimise the damaging impact of emissions. However, this is often contrary to how complex social systems behave – local decisions made by self-interested individuals often have emergent effects that are in the interests of nobody. For software engineers a major challenge is to help facilitate individual decision-making such that individual preferences can be met, which, when accumulated, minimise adverse effects at the level of the transport system. We introduce this general problem through a concrete example based on vehicle-sharing. Firstly, we outline the kind of complex transportation problem that is directly addressed by our technology (CO2y™ - pronounced “cosy”), and also show how this differs from other more basic software solutions. The CO2y™ architecture is then briefly introduced. We outline the practical advantages of the advanced, intelligent software technology that is designed to satisfy a number of individual preference criteria and thereby find appropriate matches within a population of vehicle-share users. An example scenario of use is put forward, i.e., minimisation of grey-fleets within a medium-sized company. Here we comment on some of the underlying assumptions of the scenario, and how in a detailed real-world situation such assumptions might differ between different companies, and individual users. Finally, we summarise the paper, and conclude by outlining how the problem of pooled transportation is likely to benefit from the further application of emergent, nature-inspired computing technologies. These technologies allow systems-level behaviour to be optimised with explicit representation of individual actors. With these techniques we hope to make real progress in facing the complexity challenges that transportation problems produce.

The Development of a Holistic and Quantitative Tool for the Assessment and Improvement of Survey Quality.

There are a variety of guidelines and methods available to measure and assess survey quality. Most of these are based on qualitative descriptions. In practice, they are not easy to implement and it is very difficult to make comparisons between surveys. Hence there is a theoretical and pragmatic demand to develop a mainly quantitative based survey assessment tool. This research aimed to meet this need and make contributions to the evaluation and improvement of survey quality. Acknowledging the critical importance of measurement issues in survey research, this thesis starts with a comprehensive introduction to measurement theory and identifies the types of measurement errors associated with measurement procedures through three experiments. Then it moves on to describe concepts, guidelines and methods available for measuring and assessing survey quality. Combining these with measurement principles leads to the development of a quantitative based statistical holistic tool to measure and assess survey quality. The criteria, weights and subweights for the assessment tool are determined using Multi-Criteria Decision-Making (MCDM) and a survey questionnaire based on the Delphi method. Finally the model is applied to a database of surveys which was constructed to develop methods of classification, assessment and improvement of survey quality. The model developed in this thesis enables survey researchers and/or commissioners to make a holistic assessment of the value of the particular survey(s). This model is an Excel based audit which takes a holistic approach, following all stages of the survey from inception, to design, construction, execution, analysis and dissemination. At each stage a set of criteria are applied to assess quality. Scores attained against these assessments are weighted by the importance of the criteria and summed to give an overall assessment of the stage. The total score for a survey can be obtained by a combination of the scores for every stage weighted again by the importance of each stage. The advantage of this is to construct a means of survey assessment which can be used in a diagnostic manner to assess and improve survey quality.

It's not interaction, it's make believe.

A principal, but largely unexplored, use of our cognition when using interacting technology involves pretending. To pretend is to believe that which is not the case, for example, when we use the desktop on our personal computer we are pretending, that is, we are pretending that the screen is a desktop upon which windows reside. But, of course, the screen really isn't a desktop. Similarly when we engage in scenario- or persona-based design we are pretending about the settings, narrative, contexts and agents involved. Although there are exceptions, the overwhelming majority of the contents of these different kinds of stories are not the case. We also often pretend when we engage in the evaluation of these technologies (e.g. in the Wizard of Oz technique we "ignore the man behind the curtain"). We are pretending when we ascribe human-like qualities to digital technology. In each we temporarily believe something to be the case which is not. If we add the experience of tele- and social-presence to this, and the diverse experiences which can arise from using digital technology which too are predicted on pretending, then we are prompted to propose that human computer interaction and cognitive ergonomics are largely built on pretending and make believe. If this premise is accepted (and if not, please pretend for a moment), there are a number of interesting consequences.

Understanding nurses’ decision-making when managing weaning from mechanical ventilation: a study of novice and experienced critical care nurses in Scotland and Greece.

Aim and objectives To examine how nurses collect and use cues from respiratory assessment to inform their decisions as they wean patients from ventilatory support. Background Prompt and accurate identification of the patient's ability to sustain reduction of ventilatory support has the potential to increase the likelihood of successful weaning. Nurses' information processing during the weaning from mechanical ventilation has not been well-described. Design A descriptive ethnographic study exploring critical care nurses' decision-making processes when weaning mechanically ventilated patients from ventilatory support in the real setting. Methods Novice and expert Scottish and Greek nurses from two tertiary intensive care units were observed in real practice of weaning mechanical ventilation and were invited to participate in reflective interviews near the end of their shift. Data were analysed thematically using concept maps based on information processing theory. Ethics approval and informed consent were obtained. Results Scottish and Greek critical care nurses acquired patient-centred objective physiological and subjective information from respiratory assessment and previous knowledge of the patient, which they clustered around seven concepts descriptive of the patient's ability to wean. Less experienced nurses required more encounters of cues to attain the concepts with certainty. Subjective criteria were intuitively derived from previous knowledge of patients' responses to changes of ventilatory support. All nurses used focusing decision-making strategies to select and group cues in order to categorise information with certainty and reduce the mental strain of the decision task. Conclusions Nurses used patient-centred information to make a judgment about the patients' ability to wean. Decision-making strategies that involve categorisation of patient-centred information can be taught in bespoke educational programmes for mechanical ventilation and weaning. Relevance to clinical practice Advanced clinical reasoning skills and accurate detection of cues in respiratory assessment by critical care nurses will ensure optimum patient management in weaning mechanical ventilation

Exploring the relationship between impulsivity and decision-making on mobile devices.

Mobile devices offer a common platform for both leisure and work-related tasks but this has resulted in a blurred boundary between home and work. In this paper we explore the security implications of this blurred boundary, both for the worker and the employer. Mobile workers may not always make optimum security-related choices when ‘on the go’ and more impulsive individuals may be particularly affected as they are considered more vulnerable to distraction. In this study we used a task scenario, in which 104 users were asked to choose a wireless network when responding to work demands while out of the office. Eye-tracking data was obtained from a subsample of 40 of these participants in order to explore the effects of impulsivity on attention. Our results suggest that impulsive people are more frequent users of public devices and networks in their day-to-day interactions and are more likely to access their social networks on a regular basis. However they are also likely to make risky decisions when working on-the-go, processing fewer features before making those decisions. These results suggest that those with high impulsivity may make more use of the mobile Internet options for both work and private purposes but they also show attentional behavior patterns that suggest they make less considered security-sensitive decisions. The findings are discussed in terms of designs that might support enhanced deliberation, both in the moment and also in relation to longer term behaviors that would contribute to a better work-life balance.

Interactive support effects on career agency and occupational engagement among young adults.

The PIC model by Gati and Asher describes three career decision making stages: pre-screening, in-depth exploration, and choice of career options. We consider the role that three different forms of support (general career support by parents, emotional/instrumental support, and informational support) may play for young adults in each of these three decision-making stages. The authors further propose that different forms of support may predict career agency and occupational engagement, which are important career decision precedents. In addition, we consider the role of personality traits and perceptions (decision-making window) on these two outcomes. Using an online survey sample (N = 281), we found that general career support was important for career agency and occupational engagement. However, it was the combination of higher general career support with either emotional/instrumental support or informational support that was found to lead to both greater career agency and higher occupational engagement. Personality also played a role: Greater proactivity also led to greater occupational engagement, even when there was little urgency for participants to make decisions (window of decision-making was wide open and not restricted). In practical terms, the findings suggest that the learning required in each of the three PIC processes (pre-screening, in-depth exploration, choice of career options may benefit when the learner has access to the three support measures.